Customer expectations have never been higher. Today’s customers want more than quick answers; they’re looking for genuine, empathetic interactions that leave a lasting impression. When service falls short of that, loyalty wavers. This isn’t just about handling requests efficiently—agents are on the front lines of creating memorable experiences that can turn a routine call into a reason to keep coming back.

To achieve this, customer service agents need to go beyond problem-solving. They’re positioned to be advocates for the brand, building trust and fostering loyalty. But to unlock that potential, companies must shift their approach to agent support. Traditional scripts and policies aren’t enough; agents need the empowerment, insights, and autonomy to reshape challenging conversations into positive, relationship-building moments.

This is where performance excellence tools like MaestroQA play a vital role. MaestroQA’s QA software provides a structured, data-driven foundation for agent empowerment, making it easier for companies to monitor performance, analyze trends, and deliver coaching that truly makes a difference. By integrating actionable data into everyday interactions, MaestroQA helps companies consistently improve their customer service strategy and build loyalty in ways that standard customer service metrics alone can’t capture.

Why Empowerment Matters in Customer Service

Empowering agents is more than a strategy; it’s essential to delivering customer service that resonates. Agents who feel supported and confident handle interactions more smoothly, even under pressure. This empowerment is about giving agents the tools and autonomy to go beyond simply solving problems. When agents can approach each interaction with empathy and flexibility, they turn potentially negative experiences into ones that build trust and satisfaction.

Empowered agents feel pride and ownership in their roles, and this sense of agency reflects directly in their interactions. Customers sense when an agent is genuinely engaged and motivated, which builds a stronger, more authentic connection. Studies show that customers are more loyal to brands when they feel genuinely valued—and an empowered agent makes that happen. Instead of sticking to a script, these agents can listen, adapt, and respond in ways that show the customer they’re more than just a case number.

This isn’t just theory—metrics back it up. When companies invest in agent empowerment, improvements in customer satisfaction (CSAT), first contact resolution (FCR), and net promoter score (NPS) often follow. Tools like MaestroQA make it possible to track these metrics at the individual agent level, showing where improvements are happening and where further support might be needed. By providing real-time agent performance insights, quality assurance software helps companies turn empowerment into measurable results, reinforcing the value of investing in their teams.

The Core Pillars of Agent Empowerment

Empowering agents isn’t just about handing them a script and a set of policies. It’s about giving them the skills and confidence to handle any interaction with purpose and empathy, turning even tough conversations into opportunities to build customer loyalty. Three core pillars—training, thoughtful support strategies, and targeted coaching—lay the groundwork for this transformation.

1. Training Agents to Recognize, React, and Reshape Interactions

Customer interactions are full of nuances, and agents need more than a one-size-fits-all approach to manage them effectively. Empowering agents starts with training that focuses on recognizing, reacting to, and reshaping challenging situations.

• Recognize Points of Friction Early: Every customer service team encounters friction points—common triggers that lead to escalations. Training agents to recognize these points quickly allows them to take action before issues snowball. QA tools like MaestroQA help by tracking these friction points, analyzing patterns across conversations, and highlighting areas where agents may need extra guidance.
• React with Empathy and Precision: Customer interactions are dynamic. Training programs should prepare agents to respond thoughtfully based on customer cues, using scripts as a guide rather than a rigid template. Recognizing a customer’s emotional state, reading tone, and adjusting responses can make all the difference in turning a neutral interaction into a positive experience. Empathy and precision are powerful tools for de-escalation, showing customers they’re understood and respected.
• Reshape Interactions for Loyalty-Building Moments: When agents are trained to think beyond issue resolution, they can turn challenges into loyalty-building moments. Successfully calming a frustrated customer, offering an extra solution, or taking a moment to personalize an interaction are all ways to foster loyalty. With the right training, agents learn to spot these opportunities and seize them, transforming potentially negative experiences into reasons for customers to return.

2. The Fanatic Formula: Crafting Support That Delights and Builds Trust

Customer service that goes beyond satisfaction doesn’t just solve problems; it strengthens the customer relationship. By focusing on delighting customers and building trust, companies can create a deeper, more emotional connection that fosters loyalty.

• Moving Beyond Satisfaction: Satisfaction is just the baseline. Today’s customers are loyal to brands that surprise them, that go out of their way to meet unspoken needs or offer unexpected solutions. QA software plays a vital role here, capturing moments when agents delight customers so managers can see what worked and reinforce those behaviors. This not only keeps agents engaged but also creates a positive feedback loop where delightful customer service becomes the norm.
• Build Emotional Connections: An empowered agent is one who feels confident enough to connect with customers on a personal level. Training and QA tools help managers identify these loyalty-building behaviors, such as listening carefully, showing empathy, and responding to customers as individuals. Regular coaching and positive feedback reinforce these skills, encouraging agents to build genuine connections that make customers feel valued.

3. Coaching for Confidence: Equipping Agents with Problem-Solving Tools

Even the best-trained agents encounter tough situations. Structured, data-driven coaching ensures that agents have the support they need to face complex interactions with confidence and resilience.

• Structured Coaching Programs: Effective coaching addresses each agent’s unique strengths and areas for growth. QA software helps managers track performance data and identify specific coaching opportunities, enabling structured, targeted feedback. Instead of generalized feedback, managers can offer precise, actionable advice based on real examples, helping agents apply what they’ve learned directly to their roles.
• Building Resilience for Difficult Situations: Agents need tools to handle challenging customers and complex problems calmly and professionally. Coaching programs should prepare agents with role-playing scenarios, guided by insights from QA software that capture past difficult interactions. Analyzing these cases together helps agents understand what worked, what didn’t, and how to manage similar situations in the future. The goal is to help agents feel equipped for anything, fostering a calm, problem-solving mindset that benefits both customers and the team.

Implementing Targeted Evaluations for Maximum Impact

Effective agent empowerment depends on targeted evaluations that focus on the specific areas where each agent can improve or excel. By using data-driven insights and tailored performance metrics, companies can provide feedback that goes beyond general observations, helping agents to continually refine their skills and deliver exceptional customer service.

• Setting Performance Metrics: Metrics provide a clear picture of each agent’s strengths and areas for growth. Tailored performance metrics, such as specific QA scores, productivity measures, and call resolution rates, allow managers to see where an individual agent may need additional support or recognition. With a quality assurance platform like MaestroQA, managers can track these metrics at a granular level, ensuring that agents are evaluated on criteria that are directly relevant to their roles and goals. This level of specificity helps agents focus on meaningful improvements that align with both team objectives and customer satisfaction.
• Personalized Feedback Based on Data: Feedback is most impactful when it’s specific and actionable. Rather than offering broad comments, managers can use data-driven insights from QA tools to give agents targeted, context-specific advice. For instance, if an agent struggles with handling escalations, a manager can review past interactions flagged by QA software to pinpoint exactly where they could adjust their approach. This kind of personalized feedback is not only more effective but also builds agents’ confidence by showing them precisely how they can improve in real-world situations.
• Data Analytics for Consistent Improvement: A data-driven approach to evaluations does more than just highlight individual performance; it helps managers spot patterns across the team and identify common areas where agents might struggle. For example, customer service analytics in QA software can reveal trends such as recurring customer pain points or frequent issues with particular types of interactions. These insights allow managers to make informed decisions about where to focus team training, improving the quality of customer service as a whole. By continuously analyzing these patterns, companies can address systemic issues proactively and support agents in developing the skills they need to succeed.

Targeted evaluations powered by data analytics not only give agents clear goals and actionable feedback but also enable managers to build a culture of continuous improvement. This approach reinforces the idea that quality assurance is more than a monitoring tool—it’s an essential resource for developing agents and elevating the overall customer experience.

Feedback and Adaptation: Building a Culture of Continuous Improvement

A culture of continuous improvement transforms customer service from a reactive function into a proactive, growth-oriented area of the business. By providing real-time feedback, adaptive coaching, and a focus on personal development, companies can ensure that their agents are always learning, evolving, and delivering better service.

• Real-Time Feedback Mechanisms: The most effective quality assurance tools provide agents with real-time feedback on their interactions. Instead of waiting for scheduled reviews, agents receive immediate insights on what went well and where they can improve. This quick feedback loop helps agents make adjustments right away, which is especially valuable in fast-paced environments. Real-time feedback isn’t just about catching errors—it’s about empowering agents to learn from each interaction and become more skilled in responding to customer needs.
• Adapting Coaching Based on Performance Data: As agents develop, their strengths and areas for improvement evolve. QA software allows managers to track these changes over time and adjust coaching methods accordingly. When performance data shows an agent mastering a particular skill, coaching can shift focus to other areas that need attention. This data-driven approach to coaching ensures that each session is relevant, targeted, and beneficial, helping agents build a well-rounded skill set and adapt to the demands of their role.
• Fostering a Growth Mindset: Continuous improvement isn’t a one-time goal—it’s a mindset that should be embedded in company culture. QA software supports this by enabling regular assessments, allowing for friendly competition, and providing a structure for agents to learn and grow. When agents see that their progress is being measured thoughtfully and that improvement is celebrated, they’re more likely to take ownership of their development. This creates an environment where agents feel supported and motivated, reinforcing a cycle of growth that benefits both the team and the customer experience.

By prioritizing real-time feedback, adaptive coaching, and a growth mindset, companies can create a dynamic support environment where agents are continually improving and delivering exceptional service. This approach doesn’t just boost individual performance; it fosters a culture of excellence that keeps customers coming back.

Real-Life Impact: Industry-Wide Trends in Empowered Service Teams

Organizations that prioritize agent empowerment consistently see improvements in key metrics like customer satisfaction (CSAT), net promoter score (NPS), and overall customer loyalty. Research from customer experience studies shows that agents who feel supported and well-trained are more effective in managing customer needs and defusing challenging situations, which leads to better customer retention and higher satisfaction rates.

• The Link Between Empowerment and CSAT – Studies indicate that companies investing in agent training and real-time feedback tools often see a direct improvement in CSAT. Empowered agents are able to respond faster and more thoughtfully to customer needs, creating positive experiences even in challenging interactions.
• The “Friction to Fulfillment” Approach – Companies using data-driven quality assurance tools and targeted coaching report more consistent customer interactions and a reduction in escalation rates. With QA tools providing actionable insights, managers can focus on training agents to handle complex scenarios, leading to smoother interactions and improved customer loyalty.

These industry-wide insights show the measurable impact of empowering customer service agents through QA software, adaptive coaching, and data-backed feedback. Investing in these tools not only strengthens agent performance but also creates a customer experience that drives long-term brand loyalty.

The Role of Tools and Technology in Empowering Agents

Empowering agents requires more than just training; it demands the right tools to track, analyze, and support their performance effectively. Quality assurance platforms like MaestroQA provide a structured foundation for this empowerment by giving managers access to data that drives impactful coaching and improvement.

• QA Platforms as the Foundation of Empowerment: QA platforms are essential for managers who want to support agents with precise, actionable feedback. Tools like MaestroQA offer conversation analytics and real-time feedback capabilities, making it easier to identify strengths and areas for improvement. With these insights, managers can coach agents based on real data, helping them deliver high-quality service consistently. The result is a team that’s equipped to handle complex customer needs with confidence and precision.
• AI-Powered Insights for Targeted Coaching: AI-enhanced QA tools take coaching to the next level by surfacing trends and patterns across interactions. By analyzing call data and identifying common issues, AI helps managers focus their coaching efforts where they’ll have the most impact. For example, if AI highlights a recurring customer pain point, managers can prioritize training sessions to address it. This targeted approach not only makes coaching more effective but also ensures that agents are better prepared for the situations they encounter most frequently.
• Customizable Dashboards for Performance Monitoring: Customizable dashboards provide a clear view of individual and team performance metrics, trends, and patterns. Managers can tailor these dashboards to track specific goals, allowing both agents and managers to monitor progress over time. This alignment around key metrics keeps everyone focused on continuous improvement, helping teams stay engaged and committed to achieving their goals.

With the right QA tools, managers can turn raw data into actionable insights, enabling agents to grow in their roles and improve customer interactions. Investing in these technologies creates a support environment that benefits both agents and customers, ultimately strengthening brand loyalty and customer satisfaction.

Conclusion: Building Loyalty Through Empowered Customer Service

Empowering agents to go beyond simple problem-solving transforms customer service into a strategic advantage. By implementing targeted training, real-time feedback, adaptive coaching, and data-driven evaluations, companies can shift from a reactive approach to a proactive one, building loyalty at every touchpoint.

With tools like MaestroQA, managers can continuously support agent growth, turning everyday interactions into opportunities for creating memorable, loyalty-building moments. As agents gain confidence and skill, their interactions become more effective and engaging, generating a positive feedback loop that reinforces customer loyalty and strengthens the brand.

For a deeper dive into how agent empowerment transforms customer service, you can also check out our recent webinar, "From Friction to Fan: Empowering Agents to Overcome Customer Service Challenges and Drive Brand Loyalty." The session explores actionable strategies for elevating customer interactions and showcases real-world insights on agent empowerment.

Ready to see how quality assurance software can elevate your customer service strategy? 

Schedule a demo to learn more or request a demo to see how data-driven QA can empower your agents and enhance customer satisfaction.

As AI technology becomes increasingly embedded in employee performance management, HR processes, and customer support, companies encounter both transformative opportunities and emerging risks. In a recent webinar, legal expert Stacey Chiu, Senior Associate at Michelman & Robinson, joined Vasu Prathipati, CEO of MaestroQA, to explore these risks and opportunities. Together, they offered insights into how companies can maximize AI’s potential while protecting themselves against compliance and legal risks.

In this blog, we’ll unpack their discussion and share actionable strategies for adopting AI responsibly in employee evaluations and recruiting.

AI Bias, ADA Compliance, and Legal Risks

AI tools bring undeniable speed and efficiency to employee evaluations, but they also come with significant risks. Chief among these is a lack of contextual understanding, especially when it comes to meeting ADA (Americans with Disabilities Act) compliance standards. In Stacey’s words, while AI might speed up certain processes, it doesn’t inherently know when to adjust its calculations for employees who need special accommodations.

ADA Compliance and Bias Risks in AI Evaluations
One of the biggest risks of using AI in performance assessments is that it can overlook accommodations and nuance, leading to unintentional discrimination. For instance, an AI system might evaluate productivity by looking at keystrokes or task completion rates. But without human oversight, the system might penalize an employee with arthritis who needs regular breaks or an employee with ADHD who requires flexible working hours.

This unintentional bias can expose companies to serious legal repercussions. Stacey explained, “For someone with arthritis or ADHD, an AI system might penalize them for reduced performance without considering these factors. Without human oversight, you’re opening yourself up to significant legal risks.” This points to a clear and pressing need for companies to balance AI’s power with human review, especially in performance evaluations where ADA compliance is crucial.

Steps for Ensuring Fair and Compliant AI Evaluations
Preventing these pitfalls doesn’t require a complete overhaul—just a few straightforward actions can help companies ensure fairness and avoid bias in AI-driven assessments. Regular audits of AI performance evaluations, particularly for ADA compliance, are a good start. Companies should also ensure they have a human “check” on AI outcomes, especially in any assessment that may impact an employee’s job security, compensation, or progression.

Another key step is documentation. By keeping thorough records of how performance evaluations are conducted, companies can not only track for compliance but also provide a defensible process if discrimination claims arise. These simple practices make a significant difference in keeping AI-driven evaluations both accurate and legally sound.

Safeguarding with a "Human in the Loop" Approach

AI can be a powerful tool for identifying performance trends and flagging areas for improvement. However, leaving the final judgment to AI alone, especially in evaluations that impact real people, risks missing the context that only a human can bring. Without the perspective of a manager or team lead, AI might misinterpret performance data, leading to potential inaccuracies and, in some cases, unintentional biases.

Why Human Oversight Matters in AI Evaluations
In many cases, AI might pick up on surface-level metrics—like call completion times or task efficiency—without understanding the factors behind them. For example, an AI might flag an agent for not meeting productivity benchmarks, missing the fact that the agent was handling particularly complex cases or dealing with customer escalations. This is where “Human in the Loop” (HITL) comes into play. HITL combines the speed and scale of AI with the insight and judgment that only humans can provide. This model means AI provides the preliminary insights, while human reviewers add context, ensuring that evaluations are fair and meaningful.

A Practical Approach: MaestroQA’s Copilot Tool

To support this balance of technology and human insight, MaestroQA developed a platform for AI calibration, the Copilot feature. Copilot allows AI to highlight potential issues in employee performance while leaving the final decision to trained human reviewers. This setup not only supports compliance but also ensures that performance reviews account for individual circumstances. For instance, while Copilot can point to patterns or trends across calls or cases, it’s the human review that adds the crucial context and final validation.

As MaestroQA’s CEO, Vasu, puts it, “Use AI to tell you where to look, but let humans make the final judgment to ensure fairness.” This combination of AI-driven insights with human oversight helps organizations get the most out of AI without sidelining the human element—keeping evaluations accurate, fair, and legally sound.

For companies adopting AI in performance management, a “human in the loop” approach offers a practical solution. By involving people in the final evaluation stage, businesses can benefit from AI’s efficiency while making sure assessments align with organizational values and legal requirements.

Emerging Legal Trends in AI Use

As AI continues to play a bigger role in hiring and performance management, states are beginning to take action, implementing regulations to manage the risks AI can pose. These early moves offer a preview of the stricter oversight likely on the horizon.

Current Regulations and the Path Forward
In New York, the Bias Audit Law requires companies using AI in recruiting to conduct annual bias audits, ensuring that their AI tools aren’t discriminating against protected groups. This law applies to automated tools used to evaluate job candidates and mandates audits and transparency in the tool's selection criteria. Illinois has followed with a similar rule: companies must notify candidates when AI tools are used to evaluate video interviews. While these laws are relatively new, they’re a clear signal that AI in HR is on the radar for regulators.

‘These regulations are just the beginning. Similar laws will likely emerge across the U.S. in the coming years,’ Stacey noted, indicating that regulatory momentum is building.

The NYC Bias Audit Law is especially noteworthy as it mandates that employers not only conduct independent audits for bias but also publicly report their findings. This level of transparency may soon be the standard, urging companies nationwide to adopt similar safeguards preemptively.

The Need for Proactive Compliance
Staying on top of these evolving requirements is crucial. Even if a company isn’t directly impacted by these laws today, preparing for future compliance can save time and resources down the road. Companies that are proactive—reviewing AI implementations, working with legal advisors, and conducting internal bias audits—will be better positioned when regulations expand. A structured review process now can help companies avoid disruptions if and when nationwide regulations take effect. Companies using software for AI compliance in HR can establish these proactive checks to stay ahead of regulations.

The Role of QA Teams in AI Monitoring
QA teams play a key role in monitoring and auditing AI processes to ensure compliance. By actively reviewing AI outputs for fairness and accuracy, QA teams can prevent unintended biases before they become compliance issues. This ongoing review process not only safeguards companies from legal exposure but also builds a culture of accountability and fairness.

As AI regulation tightens, companies that take these proactive steps will be better prepared for the future, creating a strong foundation for AI adoption that respects both legal standards and ethical practices.

Proactive Compliance: Why Early Action Matters

When it comes to compliance, waiting until regulations force action is a risky approach. AI in HR and employee evaluations brings with it the potential for discrimination and privacy issues, and regulators are already starting to set their sights on these areas. Acting now—before regulations become stricter—can help companies avoid legal exposure and costly adjustments.

The Risks of Delaying Compliance
One of the key takeaways from Stacey’s insights is that waiting until something goes wrong can be disastrous. As she put it, “The legal system usually catches up when something catastrophic happens. By then, it’s too late.” Companies that delay compliance may find themselves scrambling to address regulatory demands after the fact, often at a high cost and with limited options.

Benefits of Early Compliance Initiatives
Companies can take a few practical steps today to build a defensible compliance framework. Regular bias audits, human oversight, and clear documentation are essential. By documenting AI processes, tracking how decisions are made, and having a clear audit trail, companies create a system that’s both defensible and fair.

Documentation, Stacey noted, isn’t just about having records on hand. It’s also about being ready for a possible regulatory future where companies may need to show exactly how AI systems function, especially in cases involving protected classes or accommodations. Companies can also avoid sudden disruptions by adopting a system of bias checks and audits now, making compliance more manageable if new laws come into effect.

Actionable Compliance Steps
For companies looking to stay ahead of the curve, the steps are straightforward but impactful:

1. Regularly Review and Update AI Models: Keep AI algorithms current, and test them periodically to ensure they align with compliance standards.
2. Train Employees on AI Use: Make sure employees understand how AI supports (not replaces) human judgment in evaluations.
3. Document AI-Assisted Performance Reviews: Maintain detailed records for every AI-influenced decision. This not only supports compliance but also provides transparency if questions arise.
4. Establish a structured QA process for AI compliance: Regularly review outputs and address any discrepancies early.

Staying proactive about compliance isn’t just a matter of avoiding penalties—it’s an investment in sustainable, responsible AI use that safeguards both companies and employees. By taking steps now, organizations position themselves for success in an increasingly regulated AI landscape.

AI’s Role in Performance Evaluations and Legal Compliance

AI can support HR teams in identifying performance trends, surfacing potential areas for growth, and standardizing certain elements of evaluations. However, when it comes to the final assessment, human judgment is essential to ensuring evaluations are both fair and legally compliant. AI works best as a guide—helping managers spot issues and focus their efforts on areas that may need attention—rather than as the final decision-maker in employee evaluations.

AI as a Supplement, Not a Replacement
The goal in using AI for performance evaluations should be to help HR teams make more informed decisions without replacing the human touch. For example, AI might highlight a dip in productivity, but a manager is still needed to interpret why that dip occurred—perhaps the employee was tackling a particularly complex project or had recently returned from leave. AI tools lack this kind of situational awareness, which is crucial for understanding an employee’s full performance context.

“AI’s power lies in its ability to support human judgment, not replace it. This proactive approach can prevent bias and ensure fair evaluations,” Stacey explained in the webinar, emphasizing AI’s role as a supplemental resource rather than a standalone judge.

Handling AI-Reviewed Data Responsibly
Data from AI assessments should be handled with care to avoid potential bias or misinterpretation. AI can be helpful in backing up a manager’s perspective with data, but HR teams should treat AI evaluations as just one part of the overall assessment. For instance, using AI to track call metrics in customer support can provide objective data on performance trends. However, without human oversight, these metrics alone can overlook factors like call difficulty, client satisfaction, or special accommodations for employees who may work at different paces due to health needs.

Best Practices for Ethical AI in Evaluations
Implementing AI in performance reviews with an ethical approach involves a few best practices. First, establish clear criteria for when and how AI will be used in evaluations. This includes creating guidelines for human oversight, ensuring that every AI-assisted assessment is reviewed by a manager or HR specialist before it informs any final decisions. Transparency with employees is also critical—make sure they understand that AI is a supportive tool, not a replacement for human assessment, and provide clarity around how AI data contributes to their reviews.

By implementing these best practices, companies can avoid common pitfalls associated with AI, such as unintentional bias or a lack of contextual accuracy. Done right, AI becomes a valuable tool that enhances performance management while upholding fairness and compliance with employment standards.

Want to learn more?
If you missed the live webinar, the recording is now available! Watch it here.

To explore how MaestroQA’s Copilot feature can help your team adopt AI responsibly, schedule a demo with us.

Quality Assurance (QA) has traditionally been associated with customer service, ensuring that agents provide consistent support and meet quality standards. However, as sales teams look to refine their strategies and performance, QA is emerging as a valuable tool in sales as well. Sales, like customer service, involves more than just numbers. Metrics like call volume and close rates are important, but they don’t fully explain the dynamics at play. Real success in sales comes from understanding the underlying drivers—what’s moving deals forward or stalling them, how well reps are engaging with prospects, and where opportunities for improvement lie.

Many sales teams fall into the trap of focusing solely on productivity metrics, assuming that more calls or emails automatically lead to better results. But this approach overlooks critical factors like well-timed questions, personalized pitches, or the ability to handle objections skillfully. By applying QA principles to sales, companies can dig deeper into these interactions, moving beyond surface-level metrics to gain a more comprehensive understanding of what’s happening. This helps optimize not just outcomes but the entire sales process.

In a recent webinar, Ana Heredia from Gorgias discussed how they incorporate QA into their B2B Software sales process. By analyzing sales interactions and reviewing call data, companies can gain a clearer picture of what’s working and what needs improvement. This approach not only enhances sales performance but also serves as a roadmap for other organizations looking to do the same. In this blog, we’ll explore how QA in sales helps teams rethink their approach, sharpen their techniques, and make more informed, data-driven decisions about their strategies.

The Role of QA in Sales

Sales teams often rely on surface metrics—how many calls were made, how many emails were sent, how many deals were closed—to gauge performance. While these numbers provide a snapshot of activity, they don’t explain why certain deals are won or lost, why some reps consistently outperform others, or why certain stages of the sales process stall. What truly drives success in sales goes deeper than raw activity; it's about understanding the underlying factors that influence these outcomes.

This is where QA comes in. Traditionally associated with customer service, QA is now finding a place in a variety of industries, like sales, not just to evaluate the quality of conversations but to dig into the metrics and workflows that reveal the "why" behind the numbers. QA enables sales teams to dissect their processes, uncover hidden issues, and gain insights into how reps engage with prospects, how they handle objections, and where in the sales funnel things tend to break down.

As an example, a sales team may incorporate QA into their sales operations not just to ensure high-quality interactions but to identify patterns in their workflows. By analyzing sales calls, they can pinpoint areas where deals are getting stuck, uncover inefficiencies, and adjust their overall strategy based on these insights. A team may discover that some reps are losing deals because they aren’t addressing key customer concerns early enough in the process. QA allowed them to see beyond metrics like call volume and close rates to understand the underlying reasons why certain deals fell through, leading to a strategic overhaul that improved both rep performance and overall results.

Without QA, sales teams may miss these deeper issues, relying solely on traditional performance metrics that don’t explain the "why" behind poor outcomes. QA gives teams the tools to dig into processes, uncover root causes, and make targeted adjustments that improve not only performance metrics but overall effectiveness.

Structuring a QA Program for Sales Teams

Building a QA program for sales requires a clear framework. The foundation of this process starts with defining the specific criteria that will be evaluated. Sales interactions are varied, so your evaluation criteria should reflect the different stages of the process, from discovery calls to negotiations. For example, when reviewing a discovery call, you might evaluate how well the sales rep uncovers the prospect's pain points and how effectively they tailor the conversation to those needs. On a negotiation call, the focus may shift to how well the rep positions the product’s value and handles pricing objections.

A leading B2B software company developed specific criteria for their sales teams, evaluating reps on elements like asking insightful questions, steering conversations toward solutions, and maintaining a natural flow. These criteria ensure that reps aren’t just meeting activity quotas—they’re meaningfully connecting with prospects. Applying these standards helped the company identify where deals were stalling and what changes needed to be made to keep conversations on track.

Cross-Departmental QA

A successful QA program for sales shouldn’t operate in a silo. To get a full picture of what’s happening across the sales cycle, multiple roles need to be involved in the evaluation process. Account Executives (AEs) are on the front lines, but Customer Success Managers (CSMs), Sales Enablement, and Product Managers also have valuable insights into how customers are engaging with the product and where potential gaps may exist.

Many companies are seeing the benefits of cross-departmental collaboration in their QA processes. By involving different teams in the review and analysis of calls, businesses can gain a more holistic view of the customer journey. This collaborative approach helps ensure consistent messaging and allows for early identification of opportunities for improvement across the entire sales funnel.

Key Metrics and Criteria

In any sales QA program, the metrics and criteria used to evaluate interactions should be practical and actionable. Sales teams may leverage tools like Gong to review call recordings and assess a range of criteria. These include the depth of questions asked during a discovery call, the rep’s ability to adapt to the conversation, and how effectively they identify opportunities for upselling or cross-selling.

For example, a rep might be evaluated on their ability to move the conversation forward by asking insightful, open-ended questions rather than relying on a pre-scripted pitch. Or, in a demo, the focus might be on how well the rep anticipates and addresses the prospect’s objections, keeping the conversation dynamic and customer-focused. These evaluations help pinpoint specific behaviors that can be improved, ensuring that reps are always working toward delivering the best possible experience for the prospect.

Structuring a QA program for sales is about setting clear standards for what great interactions look like and making sure every part of the sales process is aligned with these standards. The result? A more consistent, effective sales approach that goes beyond meeting activity goals and focuses on quality outcomes.

Beyond the Numbers – How QA Reveals Hidden Sales Insights

Sales metrics like call volume or close rates can tell you what is happening in your pipeline, but they don’t explain why. This is where QA proves its value, moving beyond surface-level data to uncover the deeper insights that traditional KPIs often miss. QA isn't just about tracking activity; it’s about analyzing the quality of those activities to understand why certain calls succeed while others fall short.

By listening to calls and reviewing interactions, QA programs help sales teams pinpoint the talk tracks, objections, and behaviors that make the difference between a closed deal and a missed opportunity. For instance, a rep might consistently schedule meetings but struggle to move them to the next stage. Traditional metrics would flag this as a problem, but without QA, the reasons remain unclear. Is the issue a weak pitch, poor timing, or a lack of follow-through? QA gives you the answers by providing context around each conversation.

For example, one sales team used QA to uncover why some reps consistently struggled to move deals past the initial stages. By analyzing call recordings, the team discovered that key objections were not being addressed early enough in conversations, leading to stalled deals. Armed with this insight, the team revamped their approach, ensuring that reps were better prepared to surface and address objections head-on, ultimately improving conversion rates and streamlining the sales cycle.

QA also provides actionable insights that go beyond diagnosing problems. It can reveal which phrases build trust, how the best reps pivot when a prospect starts to disengage, and what tactics work best at different stages of the sales process. For example, you might discover that certain talk tracks resonate more with decision-makers in particular industries, or that specific questions consistently lead to deeper engagement during demos.

These insights help teams refine their sales strategies. Instead of relying on guesswork or general advice, reps get feedback rooted in real interactions. They can adjust their approach based on what’s proven to work, leading to more successful outcomes. QA bridges the gap between what the metrics show and what actually drives sales success, giving teams a clear path to improvement.

Integrating QA into Sales Training and Enablement

Effective sales training isn’t one-size-fits-all, but many companies still rely on generic programs that miss the mark. Every rep faces different challenges, and what works for one might not work for another. This is where QA comes into play, transforming training from a broad, one-time event into something much more targeted and dynamic.

By providing a direct look into rep performance through real conversations, QA enables Sales Enablement teams to tailor their coaching. Instead of guessing what each rep needs to work on, they can focus on the specific areas where reps struggle. For example, if a rep consistently fails to handle objections effectively, the training can focus on objection handling rather than revisiting basic sales tactics.

This approach can reshape how sales teams are trained. After diving into sales calls through QA, for example, you may notice common patterns—like reps not positioning the product effectively during key moments in the conversation or letting customer concerns linger without properly addressing them. Armed with this data, training programs can be adjusted to focus on these exact issues, leading to better outcomes and more confident reps. These targeted sessions have a far greater impact than generic training ever could, helping the sales team fix specific weaknesses and apply real improvements to their day-to-day conversations.

But QA’s value doesn’t stop at the initial training. It creates a loop of continuous improvement. As reps go through their calls, QA offers real-time feedback that they can immediately apply. This iterative model means reps aren’t stuck with static training—they can adjust their approach, see how those changes play out in real interactions, and refine their techniques further. Over time, this feedback loop turns into sustained performance enhancement, with reps constantly evolving and getting better at their craft.

By integrating QA into sales training, sales teams are ensuring that their reps aren’t just trained—they're continuously coached, corrected, and pushed to improve in specific, meaningful ways. The result is a sales team that’s always learning, always adapting, and always ready to handle whatever comes their way.

How QA Drives Strategic Decisions

Quality Assurance doesn’t just improve individual sales performance; it serves as a valuable tool for sales leaders making strategic decisions. QA offers insights that go beyond rep-level performance, helping to shape broader decisions about product positioning, messaging, and overall sales tactics. By analyzing the patterns and trends that emerge from sales interactions, leaders can make data-driven adjustments that resonate more effectively with customers.

For example, QA data often reveals common themes in customer objections. When you see the same concerns popping up in multiple conversations, you know there’s a gap that needs addressing—either in the sales pitch or perhaps even in the product itself. Leaders can use this information to refine messaging and train reps to tackle objections head-on. Additionally, QA highlights which features customers respond to most positively, allowing sales teams to emphasize those aspects during pitches.

QA also aids in refining forecasting and strategy adjustments. By understanding why deals are won or lost, sales leaders can predict future performance with greater accuracy. If QA shows that certain objections are derailing deals at a particular stage, the team can pivot to address those concerns earlier in the process. Similarly, if certain product features consistently drive conversions, those insights can guide mid-cycle adjustments, keeping sales strategies aligned with real-time data.

Incorporating QA into strategic planning ensures that decisions are grounded in actual customer interactions, rather than assumptions or gut feelings. This makes sales teams more agile and better equipped to respond to changes in the market.

The Future of QA in Sales: AI and Automation

As sales teams grow and scale, reviewing every interaction manually becomes nearly impossible. This is where AI and automation come in, making it easier to analyze a much larger volume of sales conversations without overwhelming the QA team. In the past, QA programs had to rely on human reviewers to assess a limited sample of calls, often missing key insights. Now, AI-driven tools allow companies to analyze 100% of their interactions, uncovering patterns and trends that might otherwise go unnoticed, while allowing human auditors to focus on more complex, nuanced issues. However, to ensure AI's effectiveness, it’s crucial to continuously evaluate and calibrate its performance.

AI strengthens QA by analyzing sentiment, tracking behavior trends, and spotting red flags, such as negative tone or overly scripted pitches. Instead of manually combing through hours of call recordings, sales teams can prioritize which interactions need the most attention. AI can flag conversations with longer than average monologues, moments where prospects sound disengaged, or points where customer objections aren’t adequately addressed. This helps sales managers direct their coaching efforts more efficiently, focusing on the calls that really need improvement.

The Real Value of QA in Sales

Quality Assurance in sales goes beyond simply evaluating interactions—it’s about uncovering the insights that drive real improvements in performance. By focusing on the quality of conversations, rather than just the volume of activity, QA helps sales teams refine their strategies, provide better training, and make smarter decisions that directly impact outcomes.

As we’ve seen, QA allows teams to dive deeper into what makes some calls succeed and others fall short. It helps pinpoint areas where reps can improve, informs training programs that target specific weaknesses, and even guides broader strategic decisions about product positioning and messaging. QA is not a one-time fix but a continuous process of improvement, ensuring that sales tactics evolve and adapt over time.

For sales teams looking to elevate their performance, adopting a QA program is essential. It provides a clearer understanding of what works, what doesn’t, and why. When integrated with AI, QA becomes even more powerful, offering the scalability needed to analyze large volumes of interactions and providing deeper insights that can transform sales efforts.

If you’re ready to take your sales team to the next level, request a demo with MaestroQA for robust Sales QA software. By focusing on quality, you’ll build a more effective and agile sales team that’s better equipped to connect with customers and close more deals.

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We are excited to announce that MaestroQA has achieved PCI DSS 4.0 Level 1 Service Provider compliance. PCI DSS 4.0 Level 1 is the highest and most modern standard in payment card industry data security. This accomplishment highlights our commitment to protecting our customers' sensitive information and staying ahead in data security.

Importance for Regulated Industries

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This new compliance standard allows customers in industries like fintech, insurance, and ecommerce to expand their usage of MaestroQA to additional teams and workflows that touch their most sensitive data. This means that teams can safely use one tool to ensure quality across all their customer facing and back office workflows - enabling better compliance and higher efficiency than a fragmented approach.

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A Quality & Support Director from a leading fintech company shared their experience:

"Before MaestroQA achieved PCI compliance, there was no QA tool that met both our modern user experience needs and compliance standards for all our teams. Now, we're rethinking our quality management process across support, risk, and compliance teams. The tool's flexibility and security are unmatched."

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The Importance of PCI DSS

PCI DSS is a set of security requirements designed to ensure organizations handling credit card information implement effective security measures. Developed by the PCI Security Standards Council (PCI SSC), including Visa, MasterCard, and American Express, PCI DSS is the industry's gold standard for safeguarding cardholder data.

Our CTO and Co-Founder, Harrison Hunter, emphasizes: "At MaestroQA, we are committed to providing a safe and trusted environment for our customers. Achieving PCI DSS 4.0 Level 1 compliance reinforces our dedication to protecting customer information and supporting our financial and commerce customers in maintaining the highest possible security standards."

PCI DSS aims to enhance cardholder data security and ensure safe handling during payment transactions. Organizations that process, store, or transmit credit card information must follow these requirements to reduce data breach risks and protect against financial fraud.

A Level 1 service provider must submit an annual Report on Compliance (ROC) by a Qualified Security Assessor (QSA), verifying all requirements are met. They must also undergo quarterly network scans, penetration tests, and submit an Attestation of Compliance (AOC) form.

Commitment to Customer Data Security

MaestroQA's adherence to PCI security standards is crucial for safeguarding cardholder data. Our security measures include:

• Robust Encryption: Ensuring all sensitive data is encrypted both in transit and at rest.
• Penetration Testing: Conducting regular penetration tests to identify and address vulnerabilities.
• Quarterly Network Scans: Performing quarterly network scans to detect and mitigate potential threats.
• Internal Controls and Procedures: Maintaining rigorous internal controls and procedures to uphold data security.
• Regular Audits and Compliance Checks: Engaging in continuous audits and compliance checks to verify adherence to security standards.

These practices assure our customers that MaestroQA is dedicated to maintaining the highest levels of security and compliance.

Expanding Our Compliance Portfolio

PCI DSS compliance adds to MaestroQA's robust compliance practice, which includes ISO 27001, SOC 2 Type 2 (Security, Privacy, and Confidentiality), and HIPAA certifications. We also comply with GDPR and CCPA requirements, ensuring comprehensive data protection. Additionally, MaestroQA supports upstream redaction and advanced redaction abilities for audio, video, and case fields.

For more information on MaestroQA's compliance certifications and how we can support your organization's security needs, please visit: https://trust.maestroqa.com/

The Crucial Role of QA in Revolutionizing Chatbot Interactions

In today’s digital-first world, chatbots have become a ubiquitous presence across various industries, streamlining interactions and redefining customer engagement. But as their roles grow, so does the complexity of their tasks and the potential for errors. The effectiveness of chatbots hinges on more than just their ability to respond quickly. Quality Assurance (QA) plays a pivotal role in elevating these interactions from functional to exceptional. 

At our recent CX summit, insights gathered from over 100 customer-focused leaders underscored the transformative impact of QA on chatbot optimization. These discussions didn't just skim the surface; they delved deep into the challenges and triumphs of integrating QA into chatbot deployments. This gathering of experts provided a well-rounded view of the landscape, setting the stage for a comprehensive exploration of how QA can be a game-changer in the world of automated customer interactions.

Rigorous QA Processes are Essential for Chatbot Performance

Chatbots are essential components of modern digital customer service strategies, typically categorized into two types: scripted and generative. Scripted chatbots offer consistency with a predefined set of responses suitable for routine queries. Generative chatbots, however, use advanced AI to generate responses dynamically based on the context of the interaction, introducing a higher level of complexity in both deployment and ongoing management.

Inadequate quality assurance for both types of chatbots can lead to significant issues. Scripted bots might fail to respond accurately to unexpected queries, while generative bots are prone to more complex errors. As noted by a summit participant, generative models, despite their intelligence in mimicking tone and making educated guesses, also come with considerable risks: "They can hallucinate, they can make up information. There's a lot to consider, especially when sensitive information is involved."

The need for rigorous chatbot QA is crucial to prevent the risk of AI 'hallucinations'—where bots generate incorrect or misleading information. Ensuring chatbots accurately interpret and respond to customer inquiries is essential for maintaining their reliability and effectiveness. Implementing robust QA processes helps mitigate potential missteps that could impact customer satisfaction. 

A participant at the summit expressed, "Naturally, we anticipate some quality differences between humans and AI or chatbots. However, our goal is to minimize this quality gap as much as possible, ensuring that our chatbots approach human-like interactions."

Implementing Effective QA Processes

Effective chatbot quality assurance involves several key processes:

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• Automated Testing: Regular automated testing is crucial to prepare chatbots for a wide variety of customer interactions, helping to identify and correct errors before they affect the customer.
• Manual Oversight: Periodic manual reviews are essential to ensure that generative chatbots handle complex queries appropriately and maintain conversation accuracy.
• Continuous Feedback Loops: Mechanisms that capture real-time interactions and user responses allow for the continuous refinement of chatbot performance. This adaptive approach is supported by MaestroQA's systematic review capabilities, as mentioned by a participant: "Maestro was a really integral part of that saying, okay, well, we are going to have a systematic way to review these conversations and that's not just going to be for launch like that's also going to be ongoing so long as the chatbot is in existence."

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By adhering to these rigorous chatbot QA best practices, companies can ensure that their chatbots not only meet but exceed customer expectations, providing reliable and effective customer service while also respecting the regulatory requirements inherent in deploying such advanced technologies.

Balancing Automation with Human Oversight

Chatbots are revolutionizing customer service by efficiently managing routine tasks. These automated assistants are integral in handling inquiries such as FAQs and basic customer interactions around the clock, freeing human agents for more complex duties. This shift not only optimizes operational efficiency but also ensures that immediate customer needs are consistently met without delay.

Despite the strides in artificial intelligence, there remain distinct limits to what chatbots can achieve, especially in scenarios requiring empathy and nuanced understanding. Complex customer issues, emotional nuances, and sensitive concerns still demand the irreplaceable human touch. These situations underline the critical balance between automated efficiency and human empathy, ensuring that customer care goes beyond transactional interactions to build real connections and trust.

From the insights gathered during our summit, it's clear that the integration of human oversight significantly enhances customer satisfaction. Effective chatbot deployment isn't just about having AI handle all interactions but knowing when to bring a human into the conversation. This blend ensures that while routine questions are swiftly handled by bots, more intricate or sensitive issues are escalated to human agents who can provide the needed care and attention.

Guidelines for Seamless Escalation Processes

To optimize the collaboration between chatbots and human agents, businesses should implement structured escalation processes:

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• Trigger Identification: Establish clear criteria for when an interaction should be escalated to a human agent. This could be based on specific keywords, sentiment analysis indicating customer frustration, or complexity signals that the query exceeds the chatbot’s capabilities.
• Smooth Handoffs: Ensure chatbots are programmed to pass all relevant interaction history to the human agent. This transition should be seamless, with the agent fully briefed on the customer’s issue, avoiding any need for customers to repeat themselves.
• Training and Feedback: Continuously train both chatbots and human agents to handle transitions smoothly. Use real-time data and customer feedback to refine escalation triggers and enhance the overall interaction process.

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By adhering to these guidelines, companies can ensure that their customer service is not only efficient but also genuinely responsive to the needs of their customers. This strategic integration of chatbots and human agents is pivotal in delivering a customer experience that is both technologically advanced and deeply human-centric.

Data-Driven Improvements Lead to Better Chatbot Performance

Data is instrumental in transforming chatbots from basic automated responders to sophisticated systems capable of delivering personalized customer experiences. Through continuous analysis of user interactions, chatbots learn and adapt to meet customer expectations more effectively.

Key data types essential for optimizing chatbot functionality include user queries and responses, direct customer feedback, and analysis of conversation outcomes. These insights help identify both successful interactions and areas needing improvement. By analyzing trends and sentiment, businesses can refine chatbot responses to be more empathetic and contextually appropriate, while regular reviews of performance metrics like resolution rates and customer satisfaction scores gauge effectiveness.

Setting clear metrics and KPIs is crucial for systematic improvement. Tailoring these to organizational goals allows businesses to gain deep insights into chatbot performance, driving strategic enhancements. Metrics such as the Customer Satisfaction Score (CSAT), Containment Rate, and Error Rate are vital for assessing how well chatbots manage conversations and maintain accuracy.

Incorporating A/B testing enables teams to experiment with different configurations, determining the most effective approaches based on empirical data. This ensures that modifications are data-driven and targeted for maximum impact.

As highlighted by a summit participant, MaestroQA simplifies the process of compiling and sharing evidence of chatbot performance issues, making it easier to diagnose and correct errors. This capability supports continuous learning and adaptation, ensuring chatbots evolve in response to new information and changing customer interactions, thereby enhancing the user experience.

By committing to rigorous data analysis and continuous learning, businesses ensure their chatbots remain valuable assets in their customer service arsenals, consistently improving to better serve users.

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How MaestroQA Helps Optimize Chatbot Performance

MaestroQA is pivotal in optimizing chatbot interactions, serving as a crucial bridge between automation and quality assurance. By integrating seamlessly with existing chatbot technologies, MaestroQA enables businesses to monitor and enhance the effectiveness of their chatbots, ensuring that quality is a fundamental component of the customer interaction process.

By offering robust QA tools and actionable insights, MaestroQA ensures that chatbots are not just functional but are significant assets in the customer support landscape. The continuous improvement driven by detailed analytics and real-time data allows companies to elevate their customer experience, ensuring that every chatbot interaction adds substantial value to their customer journey.

Some of these chatbot QA tools include:

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• Real-Time Monitoring and Performance Dashboards: MaestroQA provides advanced tools that refine the quality assurance process for chatbots. Real-time monitoring allows businesses to observe chatbot conversations as they occur, enabling immediate identification and correction of deviations from expected performance standards. Performance dashboards provide a comprehensive view of chatbot metrics, such as response accuracy and customer satisfaction, helping teams quickly assess how well chatbots are meeting predefined KPIs and identify areas for improvement.
• Detailed Analytics: MaestroQA's analytics tools offer a deep dive into the data collected from chatbot interactions, crucial for pinpointing trends, forecasting potential issues, and tailoring responses based on real user feedback. One of the standout features of MaestroQA reporting is the ability to drill down into specific markdowns across all areas of performance, such as accuracy, completeness, and clarity. Within these key areas, teams can view sub-sections to assess whether the chatbot was marked down and why. Further, teams can drill down to the ticket level to see exactly what happened within each interaction. This detailed view not only allows for precise diagnosis of issues but also informs targeted training efforts to improve the chatbot's performance.
• Advanced Ticketing Insights: MaestroQA provides the capability to drill into specific ticket attributes within performance dashboards. This functionality allows teams to examine tickets based on tags from their helpdesk systems, enabling a detailed analysis of how the bot performs across different product areas and interaction types.
• AutoQA: AutoQA revolutionizes how businesses monitor and analyze chatbot performance. This tool enables the setup of custom AI Classifiers to analyze 100% of chatbot tickets, using custom metrics tailored to specific business needs. Metrics such as bot-to-agent escalation can be meticulously tracked and analyzed, providing teams with actionable insights that drive significant improvements in chatbot functionality and customer interaction quality.
• Coaching: Not only useful for human agents, MaestroQA’s coaching features are also beneficial for chatbot training. When issues are identified within the performance dashboard, Maestro's omnipresent coaching feature can be used to create a to-do list for the chatbot. This allows teams to have a list of improvements to reference when training the bot. As one summit speaker noted, "I can review the tickets where there is that knowledge gap, and then it helps inform my future trainings and what I’ve actually found most helpful in the Maestro interface is using maestro coaching for the bot to create a to-do list within Maestro, so when I’m training the bot, I have my list of things I need to do easily accessible.”

Real Client Experiences with Chatbot QA

At our recent CX summit, the transformative impact of MaestroQA on chatbot operations took center stage. Discussions highlighted how the platform has been instrumental in deepening the understanding of chatbot functionality and fostering targeted improvements across various industries. Here’s how participants detailed their experiences and successes:

Identifying and Addressing Training Gaps: A participant highlighted the precision with which MaestroQA pinpoints deficiencies in chatbot training: "When a generative bot makes an incorrect assumption, it often indicates a gap in its training on the subject at hand. With MaestroQA, I can easily access and review specific tickets to identify these gaps, which significantly informs and enhances future training efforts." This capability allows teams to efficiently diagnose issues and refine chatbot responses, ensuring they are more aligned with user expectations.

Streamlining Chatbot Training and Improvements: MaestroQA's analytics tools are instrumental in streamlining the training process for chatbots. By providing detailed insights into chatbot interactions, MaestroQA helps teams focus their efforts more effectively, ensuring that improvements are both strategic and impactful. Teams can analyze patterns in chatbot failures and successes, which guides the training modules to target specific areas needing attention.

Facilitating Continuous Learning and Adaptation: The ability to continuously learn and adapt is crucial for the evolution of chatbot functionalities. MaestroQA supports this ongoing learning process by integrating real-time data into the training cycle. This ensures that chatbots evolve in response to new information and changing customer interactions, maintaining their relevance and effectiveness over time.

Enhancing Diagnostic Capabilities: With MaestroQA, organizations benefit from enhanced diagnostic capabilities that allow them to delve deeper into the root causes of chatbot errors. This not only improves the immediate response but also informs long-term strategies for chatbot development.

Commitment to Quality and Regulatory Compliance

MaestroQA significantly enhances chatbot interactions by ensuring compliance with regulatory standards, crucial for industries where both performance and adherence to regulations are paramount. MaestroQA helps organizations swiftly enhance chatbot functionality and reliability.

MaestroQA transforms chatbots into powerful assets for customer support, providing actionable insights to refine their operations. Detailed analytics and real-time data enable continuous improvement, allowing chatbots to adapt to evolving customer needs and uphold high interaction standards.

By utilizing MaestroQA for chatbot QA, companies ensure their chatbots are effective and compliant, enhancing both customer satisfaction and operational excellence.

Next Steps?

As we've explored, integrating rigorous QA in chatbot strategies isn't just beneficial—it's essential. Chatbot QA elevates the effectiveness of chatbots, transforming them from simple automated responders into sophisticated tools capable of delivering truly personalized and satisfying customer interactions. Ensuring that every chatbot interaction is guided by strong QA practices means fewer errors, more accurate responses, and a generally smoother customer journey.

Are you ready to redefine your chatbot strategy with leading-edge QA solutions?

Explore how MaestroQA can transform your chatbot interactions with our advanced suite of QA tools. Experience the synergy of cutting-edge technology and human expertise in enhancing chatbot accuracy, effectiveness, and reliability. With MaestroQA, embrace the full potential of your chatbot technologies, ensure that your chatbot delivers not just answers, but accurate, efficient, and meaningful communication.

Explore Our Solutions

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In the bustling world of customer support, artificial intelligence (AI) has emerged as a transformative force. Call centers, often the first line of defense in customer service, are increasingly turning to AI in quality assurance to enhance the customer experience (CX). While the potential benefits are immense, including increased efficiency and personalized service, the road to AI integration is fraught with challenges. In a recent webinar, experts discussed how businesses can effectively leverage AI call center software technologies in call centers, navigate the common pitfalls of proprietary language models, and ultimately transform their customer interactions for the better.

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This blog explores how businesses can strategically approach contact center AI solutions and avoid the traps that could hinder their progress. By adopting this strategic approach, companies can not only avoid common mistakes but also set the stage for a future where technology and human ingenuity combine to create exceptional customer experiences.

AI Trends & Impacts of Rapid Advancement on CX

Artificial intelligence, particularly in the realm of large language models (LLMs) like OpenAI's GPT series, is evolving at an unprecedented pace. Each new version brings substantial enhancements in performance, demonstrating a remarkable ability to understand and respond to complex customer queries. The shift from GPT-3.5 to the more recent GPT-4, for example, represents a significant leap forward, offering refined capabilities that are becoming indispensable in customer service.

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As these technologies advance, the cost to implement them is dramatically decreasing. This change is making powerful AI tools accessible to a broader range of businesses, transforming customer service landscapes. Small to mid-sized enterprises can now leverage sophisticated AI solutions that were once only feasible for large corporations, leveling the playing field and expanding opportunities for innovation in customer engagement.

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While the integration of AI into customer service channels promises enhanced efficiency and improved customer experiences, it also brings challenges. Rapid adoption without adequate safeguards can lead to errors that may tarnish a brand's reputation. For example, inaccuracies from chatbots—due to insufficient testing or calibration—have sometimes led to customer dissatisfaction, highlighting the importance of cautious and thoughtful AI deployment.

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With the increasing complexity of AI-driven interactions, ensuring the accuracy of AI outputs is more crucial than ever. Implementing rigorous testing protocols and maintaining oversight are essential to prevent potential errors from affecting customer interactions. Companies must prioritize these practices to safeguard the integrity of their customer service operations, ensuring that AI tools enhance rather than compromise their service quality.

Don’t Be Fooled by the Allure of Proprietary Models

For many organizations, developing proprietary AI models in-house is an attractive idea, especially when they possess unique data specific to their domain. The allure lies in the promise of specialized solutions tailored to address distinct challenges. However, significant challenges come with developing these models that often outweigh the potential benefits.

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Firstly, proprietary models require substantial investment, not just in financial resources but also in terms of time, infrastructure, and technical expertise. Building such a system is a lengthy process, often spanning many months, with continuous retraining needed to ensure it remains up-to-date. Furthermore, because these models are built for niche applications, they tend to lack the versatility and adaptability required to tackle new challenges, limiting their long-term utility.

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General-purpose models, like OpenAI's GPT-4, have evolved rapidly, often surpassing proprietary models in both adaptability and performance. The speed of development in general AI is making it increasingly difficult for specialized models to keep pace.

Real World Example

Bloomberg’s financial-specific Large Language Model (LLM), Bloomberg GPT, serves as a poignant example of the limitations of proprietary AI. Developed at a cost of $10 million and trained on Bloomberg's unique financial data, the model initially outperformed GPT-3.5, demonstrating the potential of domain-specific models. However, within just six months, OpenAI released GPT-4, which comfortably outperformed Bloomberg GPT across all financial tasks. Bloomberg's considerable investment quickly became obsolete, highlighting the unpredictability of advancements in the AI field.

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In a recent webinar, MaestroQA’s CEO Vasu Prathpati discussed the Bloomberg case. Vasu elaborated on the inherent risks associated with investing heavily in proprietary AI models. He suggests that such ventures can often feel like stepping into an inevitable defeat. Reflecting on the Bloomberg case, he points out that despite their substantial $10 million investment to develop a specialized financial model, the rapid advancement of general-purpose models like GPT-4 quickly overshadowed their efforts. This rapid obsolescence not only undermined the initial success but also rendered the significant financial investment ineffective, illustrating a broader industry trend where the speed of AI development can nullify even the most focused and well-funded proprietary projects.

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His point clearly illustrates the risks organizations face when relying solely on proprietary models. As AI technology continues to evolve rapidly, the unpredictability of these advancements makes investing in proprietary systems a challenging strategy that often leaves organizations walking into a losing battle.

Pitfalls of Proprietary Models

While proprietary models can seem appealing for organizations with domain-specific data, they come with notable challenges that hinder their widespread utility. From their limited adaptability to the significant investment required and data demands, these models can struggle to deliver accurate results despite substantial investments. Let's explore these pitfalls in detail.

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• Narrow vs. Broad Capabilities: Proprietary models are often highly specialized and designed for specific tasks. This limits their versatility, hindering their ability to adapt to emerging challenges. Due to their reliance on limited training data, these models often require extensive time to adjust to new scenarios, hindering their flexibility and broader utility. In contrast, general-purpose models like GPT-4 have broader applicability and can be fine-tuned to different use cases.
• Significant Investment Requirements: Developing proprietary models demands considerable financial resources, time, and technical expertise. The training process for these models is inherently time-consuming, often spanning several months and necessitating multiple iterations for refinement. Prospective customers deploying competitors' proprietary models often struggle to achieve accurate results due to insufficient training data and the extended time needed for training. These models also require ongoing maintenance to stay current with the latest domain-specific data, adding to the operational overhead.
• Data Requirements: Proprietary models require vast amounts of high-quality domain-specific data. Gathering and annotating this data is a labor-intensive process. Even with such data, the models can still fall short in accuracy.
• Lack of Accuracy: Despite heavy investments in their development, proprietary models frequently struggle with accuracy. Their performance is often hindered by the limited scope and quantity of training data available. For instance, in a notable case, Air Canada's chatbot provided incorrect information to a traveler, leading to a legal ruling that held the airline accountable for the chatbot's advice. This incident underscores the importance of accuracy and the potential consequences of errors in proprietary AI systems.

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In contrast, general-purpose models like GPT-4, supported by vast datasets and significant funding, typically offer more robust and accurate performances. Their extensive training across a wide range of data not only enhances their accuracy but also their adaptability to various tasks, making them more reliable and versatile than many proprietary alternatives.

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The pitfalls of proprietary models highlight their significant limitations in comparison to general-purpose AI systems. Their narrow capabilities, high investment requirements, demanding data needs, and accuracy challenges make them less adaptable and effective. By recognizing these challenges, organizations can make more informed decisions and lean toward solutions that better align with their strategic goals and customer service needs. 

MaestroQA’s Approach

In the evolving landscape of AI for customer experience, MaestroQA offers a solution that balances precision, adaptability, and compliance. By combining general-purpose AI models with domain-specific data, prompt engineering, and human oversight, MaestroQA provides a robust framework that meets diverse organizational needs while minimizing risks. Let's delve into how MaestroQA’s Playground Approach harnesses these elements for optimal performance.

The Playground Approach

MaestroQA’s Playground Approach is grounded in the principle that prompt engineering and retrieval-augmented generation (RAG) are key to maximizing the potential of general-purpose AI models. Instead of constructing an LLM from the ground up, this approach leverages existing models while incorporating specific prompts and domain-specific data to provide accurate, context-aware answers.

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Sophisticated prompt engineering is used to guide foundational models with detailed contextual examples. For instance, in customer service, the model is fed unique, customer-specific scenarios and user queries to tailor responses effectively. Retrieval-augmented generation (RAG) takes this a step further by querying internal databases to find relevant data and augmenting it with general-purpose models to generate informed answers. The result is more precise, personalized, and relevant information for customers.

Flexibility and Experimentation

MaestroQA thrives on flexibility and experimentation, empowering organizations to explore and experiment with leading AI models to identify trends, compliance gaps, and coaching opportunities specific to their needs. By keeping up with the latest AI advancements, 

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MaestroQA remains adaptable, transparent, and future-proof, ensuring clients access the best tools while staying cost-efficient.

Human-in-the-Loop Framework

A robust Human-in-the-Loop framework serves as a safety net to validate responses generated by AI. This human oversight ensures alignment with the organization’s objectives, mitigating potential legal liabilities. By incorporating internal teams or external experts for validation, MaestroQA reduces the risks of AI hallucinations, enabling trustworthy, accurate responses while maintaining compliance.

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In short, MaestroQA’s unique approach combines the strengths of general-purpose models with the adaptability of prompt engineering and retrieval-augmented generation to deliver reliable, scalable, and transparent AI solutions that align perfectly with organizational goals.

AI-Driven Insights in Action

During our recent webinar demonstration, we highlighted the transformative potential of MaestroQA’s AI-driven tools. Our approach leverages cutting-edge GPT AI technology to deliver unparalleled insights and streamline operational efficiency.

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The journey begins with our robust Performance Dashboard, seamlessly integrating advanced AI models like ChatGPT, Claude, and others. This dashboard serves as the first step in identifying hotspots related to metrics tailored to business needs. In this demo, that metric was DSAT.

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From this starting point, customer service teams can drill down into specific subsets of related tickets to conduct root cause analysis (RCA). Here, you can then use MaestroQA's sophisticated GPT-powered prompting to generate detailed trends and insights that might otherwise remain obscured. These prompts allow teams to conduct nuanced analysis, transforming broad performance metrics into actionable intelligence that enhances both compliance and coaching opportunities.

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For instance, in the demo, we demonstrated how identifying DSAT hotspots through our dashboard allows teams to zero in on underlying issues and utilize AI-enhanced prompts to uncover the root causes of dissatisfaction. This information is invaluable in refining customer service strategies and delivering tailored solutions that improve customer interactions.

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Our playground-style approach empowers users to combine their proprietary data with leading AI models to create highly adaptive, transparent solutions. Retrieval-augmented generation enables organizations to leverage their internal databases alongside large language models, providing accurate and context-rich answers. This methodology enhances the quality of customer responses, ensuring seamless integration between MaestroQA’s data analysis tools and user interactions.

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MaestroQA’s platform transforms the way organizations manage AI in customer support, offering sophisticated AI-powered insights that help teams move from surface-level observations to strategic, actionable plans.

Bringing AI Innovation to Customer Service

MaestroQA’s platform demonstrates how cutting-edge AI technology can transform customer service by offering comprehensive, data-driven insights. With GPT-powered analysis and adaptable AI models, customer service teams can explore customer interactions in-depth, identify improvement opportunities, and develop strategies that align with their objectives.

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The platform's seamless integration with advanced models like GPT-4 and Claude ensures adaptability to evolving customer needs. MaestroQA empowers teams to analyze customer sentiment, spot DSAT trends, and validate results with human expertise, ensuring accurate and valuable insights. 

Next Steps?

Are you ready to transform your customer service approach with MaestroQA's AI-driven insights? Dive into our comprehensive suite of tools and experience how integrating state-of-the-art models like GPT-4 can uncover new dimensions of customer satisfaction, root cause analysis, and team performance.

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See how MaestroQA’s prompt engineering, flexible AI models, and human-in-the-loop validation can deliver deeper customer insights while enhancing your operational efficiency. Empower your team to excel with data-backed strategies tailored to your organization's specific needs.

Explore Our Solutions

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In the dynamic realm of customer support, traditional Voice of the Customer (VoC) strategies alone fall short in delivering the insights needed for exceptional service. As customer engagement channels multiply and the volume of interactions grows, the limitations of traditional VoC become increasingly apparent. This evolution in customer support reflects a broader shift in the digital landscape, where customers expect not only responsiveness but also proactive and personalized service across multiple touchpoints.

To meet these expectations, the field of customer support must evolve beyond the siloed analysis of direct feedback. Enter conversation intelligence—a groundbreaking advancement designed to harness and synthesize data across all communication platforms. Conversation intelligence leverages sophisticated analytics to dive deeper into the nuances of customer interactions, offering a comprehensive view of sentiments, trends, and behavioral patterns. 

This technology is not just about listening; it's about understanding the context and emotions behind each customer interaction, making it an indispensable tool for modern customer support strategies. By integrating conversation intelligence, businesses can transform their customer support from reactive to predictive, ensuring every customer interaction is both insightful and impactful.

Why Now - Traditional VOC Solutions Are Falling Short

Traditional Voice of the Customer solutions have been pivotal in gathering customer feedback. However, they now face limitations due to the increasingly complex nature of customer interactions across multiple platforms. As customer engagement channels proliferate, the need for more comprehensive VoC analytics solutions becomes evident.

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Traditional methodologies struggle to capture the expansive and multifaceted nature of modern customer dialogues. This gap in capturing a full spectrum of customer feedback results in fragmented insights, diminishing the overall effectiveness of VoC analytics.

Risks of Fragmented Customer Data Systems

In environments such as call centers, disconnected customer data streams pose significant operational risks. Traditional call center VoC methods often treat feedback channels in isolation, failing to provide a unified view of customer experiences.

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This approach can lead to critical oversights, where the comprehensive narrative of a customer's experience is lost. Such gaps increase the likelihood of unresolved issues and customer dissatisfaction, underlining the need for advanced solutions in these settings.

Urgency for Integrated VoC Solutions

The necessity for integrated VoC solutions is increasingly critical. Often, essential data for customer experience quality assurance is scattered across various platforms—from telephony and help desks to direct customer feedback mechanisms like surveys and comments.

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The challenge lies in aligning this disparate data with operational metrics, a task that traditional VoC software are ill-equipped to handle. This fragmentation often leads businesses to make decisions that are poorly informed and potentially detrimental.

Advancing to Conversation Intelligence

The solution to these challenges lies in the adoption of sophisticated conversation intelligence software. This technology serves as a critical bridge between disparate data sources and actionable insights.

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Conversation intelligence not only aggregates data across all customer touchpoints but also applies advanced analytics to decode the nuances of each interaction. By integrating conversation intelligence into VoC strategies, companies can transform raw data into predictive insights. This shift enables proactive customer engagement strategies and significantly enhances service delivery.

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Embracing conversation intelligence within VoC strategies marks a pivotal advancement for businesses aiming to deepen their understanding of customer needs. This evolution not only improves service quality but also provides a competitive edge in the rapidly changing market landscape.

Customer Example - The Challenge

In today’s competitive market, delivering outstanding customer service is more than a goal—it's a crucial element of brand identity. One company sought to differentiate itself by promising what they dubbed "The Cinderella Experience." This initiative was not just about providing service but ensuring that every customer felt uniquely valued and engaged in a magical, transformative interaction.

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For customer service agents, "The Cinderella Experience" pushed them to exceed typical service expectations. This initiative was designed to instill a deep sense of purpose and pride, motivating agents to create moments that left customers feeling delighted and cherished. It aimed to transform every support interaction into a memorable experience, reflecting the fairy tale's magic.

Identifying the Challenge

Despite the noble intentions, the journey to delivering this exceptional level of customer service faced significant obstacles. The company's initial approach was marred by a strict adherence to rigid policies that led to impersonal and robotic interactions. Agents, confined by stringent guidelines, often left customers feeling disconnected and undervalued—an outcome starkly at odds with the enchanting experience they intended to provide.

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Growing Dissatisfaction Among Customers

Customer feedback soon highlighted a growing dissatisfaction, which became impossible to ignore. The most common complaints centered around the unhelpful and mechanical nature of the interactions. These were not isolated incidents but a pattern that was reflected in steadily declining Customer Satisfaction (CSAT) scores. Such feedback underscored a critical and urgent need for a paradigm shift in how customer interactions were managed. The disparity between the intended "Cinderella Experience" and the actual customer experience signaled a profound disconnect that needed immediate attention to realign with the company’s ambitious customer service goals.

Customer Example - The Solution

In response to the challenges previously identified, the company initiated a transformative update to their quality scorecards and support structure. This segment outlines how adapting quality assessment techniques and empowering agents with enhanced tools and autonomy has revolutionized their approach to customer service, fostering a more responsive and empathetic environment. The changes implemented are instrumental in shaping a culture that values flexibility, continuous improvement, and deep customer engagement

Enhanced Quality Scorecard Design

As part of their commitment to refining customer interactions, the company undertook a significant transformation of their quality scorecards. They shifted from a strict policy adherence model to a more flexible framework, granting agents the autonomy to tailor their responses to the unique needs of each customer. This strategic shift cultivated a culture of trust, which is essential for forging authentic customer connections.

The organization revamped its coaching programs to emphasize empathy and effective problem-solving, equipping agents to address not only the immediate issues but also any underlying concerns. This holistic approach to customer service not only enhances the immediate interaction but also strengthens long-term customer relationships.

To further drive excellence, the company introduced a rewards system with leaderboards featuring partial and bonus points for agents who surpass service expectations, motivating them to consistently create standout customer experiences.

Empowering Agents with Autonomy and Tools

To ensure the success of the newly implemented quality scorecard changes, the organization has focused on empowering its agents with tools and autonomy that foster innovation and responsibility in their daily interactions.

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• Building Trust Through Autonomy: The restructured scorecard system has been instrumental in empowering agents, giving them the confidence to make impactful decisions. This trust has led to a more motivated workforce, keen on using their creativity to positively influence customer interactions.

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• Continuous Skill Development: Central to the transformation are ongoing coaching and development programs designed to equip agents with the necessary skills to excel in a customer-centric environment. Continuous feedback loops ensure that agents receive the support needed to refine their abilities and adapt to evolving customer expectations.

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• Agent Dashboards and Analytics: Leveraging MaestroQA’s AutoQA capabilities, the organization now analyzes 100% of customer conversations. This comprehensive insight allows for real-time monitoring of agent performance and customer sentiment on the Performance Dashboard. Agents have access to personalized dashboards displaying performance metrics, including grades, feedback, and coaching history, fostering a proactive approach to personal development.

Cultivating a Culture of Continuous Improvement

The commitment to enhancing the customer service experience is reflected in the ongoing efforts to refine processes and tools. The introduction of continuous, personalized coaching has set a new standard in feedback utilization, making it actionable and specific to each agent's needs. This strategy not only improves individual performance but also elevates the overall service quality, directly contributing to the company's success and reputation.

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By embracing a flexible, empathetic approach and integrating advanced analytics, this organization has transformed the way it interacts with customers. This strategic shift has not only resolved the initial challenges but has also set a new benchmark in customer service excellence. Their journey from rigid adherence to dynamic interaction underscores their dedication to delivering exceptional service and fostering lasting customer relationships.

MaestroQA’s Unique Analytics Approach

MaestroQA’s unique analytics capabilities stand out by turning complex data into actionable insights. This section delves into how our advanced analytics tools—ranging from holistic sentiment scoring to real-time DSAT analysis and sophisticated data aggregation—empower organizations to not only meet but exceed customer expectations. Here’s how each component of our analytics approach works to optimize your customer interaction strategies:

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• Holistic Sentiment Scoring: At the heart of MaestroQA's analytics capabilities lies our holistic sentiment scoring system. This sophisticated technology allows us to capture and analyze the full spectrum of customer emotions across multiple channels—from phone calls to chatbots and emails. By understanding the subtle tones and context of each interaction, we can offer precise feedback that enhances the quality of customer engagements.

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• Real-Time DSAT Analysis: Another cornerstone of our approach is the real-time DisSatisfaction (DSAT) analysis. This powerful feature swiftly identifies points of customer dissatisfaction, enabling immediate corrective action to prevent further customer churn. By focusing on these critical areas, MaestroQA helps ensure that every customer interaction contributes positively to long-term loyalty and satisfaction.

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• Advanced Data Aggregation: Through advanced data aggregation methods, MaestroQA integrates data from diverse sources such as help desks, telephony systems, workforce management tools, and CSAT surveys. This comprehensive view not only highlights efficiency and performance metrics but also aligns them with customer satisfaction indicators, providing a 360° view of the operational landscape.

MaestroQA’s Operational Impact

As the demands of customer service continue to evolve, MaestroQA’s cutting-edge operational technologies are crucial in transforming everyday customer support operations. This section explores how our innovative solutions, such as GPT-powered automation and comprehensive data analytics, not only streamline workflows but also bolster decision-making processes. We'll see how these advancements enable support teams to operate more efficiently and with a greater focus on delivering exceptional customer experiences.

• GPT-Powered Automation and Auto-Tagging: MaestroQA leverages the latest in AI technology, including GPT-powered automation, to enhance the operational efficiency of customer support teams. This AI-driven approach enables automatic tagging of conversations, categorizing them by sentiment, contact reason, and feedback quality without human intervention. Such automation speeds up the analysis process and frees up agents to focus on higher-value tasks.

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• Streamlining Customer Support Processes: Our tools are designed not just to gather data but to transform it into actionable insights that can be operationalized within customer support frameworks. By automating routine tasks, agents and managers can dedicate more time to strategic decision-making and personalized customer interaction. This shift not only boosts operational efficiency but also improves overall job satisfaction among team members.

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• Enhancing Decision-Making: With MaestroQA's Performance Dashboard, leaders in customer service can quickly access and interpret performance and call center QA metrics across all touchpoints. This capability ensures that decision-making is informed by comprehensive, real-time data, enabling managers to swiftly identify trends, allocate resources effectively, and implement strategic changes that enhance customer satisfaction and operational performance.

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• Continuous Improvement and Strategic Impact: Our platform is built on the principle of continuous improvement, driven by data, and refined through actionable insights. By consistently analyzing and responding to customer and agent feedback, MaestroQA empowers organizations to elevate their customer experience, thereby improving key business outcomes and solidifying their market position.

The Transformative Power of Advanced Conversation Intelligence

As we have explored throughout this blog, the landscape of customer service is rapidly evolving beyond traditional VoC approaches. With the advent of sophisticated tools like MaestroQA, businesses are now equipped to delve deeper into the nuances of customer interactions and agent performance. This transition from basic VoC to advanced conversation intelligence represents a crucial shift toward a more dynamic, insightful, and responsive customer service paradigm.

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MaestroQA's innovative analytics and operational solutions offer a holistic view of both customer sentiment and agent effectiveness, ensuring that every interaction is not just heard, but fully understood. By leveraging real-time DSAT analysis, holistic sentiment scoring, and comprehensive data aggregation, companies can identify and act on areas of dissatisfaction swiftly, transforming potential negatives into opportunities for customer loyalty and retention.

Strategic Advantages for Business Outcomes

The strategic advantages of integrating MaestroQA are clear. Organizations that adopt its cutting-edge conversation intelligence are better positioned to make informed decisions that drive customer satisfaction and operational excellence. The detailed insights provided by MaestroQA allow businesses to not only meet customer expectations but exceed them, securing a competitive edge in an increasingly customer-centric market.

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In conclusion, the shift to advanced conversation intelligence with MaestroQA is not just an upgrade—it's a transformation. It's about turning every customer interaction into a strategic opportunity to enhance service delivery and achieve remarkable business outcomes.

Next Steps?

Are you prepared to revolutionize your Voice of the Customer strategies using MaestroQA? Engage with our integrated suite of tools and embark on a path to unparalleled customer insight and service optimization. Learn how our advanced conversation intelligence, holistic sentiment analysis, and seamless data integration can elevate your understanding of customer needs and boost your operational efficiency.

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Discover MaestroQA's innovative solutions today and start transforming your customer interaction approach to achieve superior outcomes.

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In today’s customer experience landscape, adeptly managing difficult interactions is crucial, transcending mere necessity to become a strategic asset that significantly enhances customer loyalty and organizational success. As customer expectations rise, the complexities of customer support evolve, shaping customer perceptions and loyalty in critical ways. Modern support teams are tasked with transforming potentially negative experiences into positive outcomes that reinforce customer trust and satisfaction.

A transformative workshop, developed through a unique collaboration between MaestroQA, a leader in quality assurance solutions, and Courtney Orsinelli, an acclaimed executive coach specializing in CX dynamics, addresses these challenges. This partnership has produced practical strategies designed to empower customer support professionals, utilizing MaestroQA’s innovative tools and Orsinelli's extensive coaching insights. The workshop offers actionable techniques that can be immediately applied in daily customer interactions.

This blog post aims to distill the essential teachings from the workshop, equipping customer support directors, quality assurance managers, and frontline agents with the necessary tools to effectively manage and enhance customer interactions. Readers will gain a comprehensive understanding of the strategies discussed and learn how to implement them to build a more resilient and customer-centric support environment.

The Power of Emotional Intelligence in Customer Service

Emotional Intelligence (EI) is an invaluable asset in the arsenal of customer service professionals. Defined as the ability to understand, use, and manage one's own emotions in positive ways to relieve stress, communicate effectively, empathize with others, and overcome challenges, EI is particularly crucial in customer service settings. In environments where every interaction can significantly impact customer perceptions and loyalty, such as call centers, the role of EI becomes even more critical.

Understanding Emotional Intelligence

Emotional intelligence plays a pivotal role in managing customer interactions effectively. An example of one such scenario involves a customer support agent who, by recognizing early signs of frustration in a customer’s tone and choice of words, was able to respond empathetically and de-escalate a potentially volatile situation. This ability to read emotional cues and respond appropriately is a core component of EI that directly contributes to more effective communication and conflict resolution.

Enhancing EI in Customer Service

The benefits of enhancing EI among customer service agents are manifold. Firstly, agents equipped with strong EI skills are better at de-escalating tense situations, which is a critical competency in DSAT (Dissatisfaction Analysis) in call centers. They can identify and address the underlying emotional currents of customer interactions, which often go unnoticed but can significantly influence the outcome of support calls. Secondly, emotional intelligence training helps agents develop a more empathetic approach, aligning closely with the goals of customer-centric businesses to improve overall satisfaction and loyalty.

Leveraging EI with DSAT Training

Integrating EI into DSAT call center training programs can transform standard customer service protocols into more adaptive, sensitive customer interactions. With the support of DSAT software that provides real-time feedback and analytics, agents can refine their emotional responsiveness based on actual customer engagement data, leading to a noticeable improvement in customer service quality.

To truly leverage the power of emotional intelligence in customer service, ongoing coaching and support are essential. Programs that coach customer support teams not only in technical skills but also in emotional intelligence can create environments where both customers and agents feel understood and valued. This not only improves immediate customer service outcomes but also fosters a culture of empathy and continuous improvement, ultimately enhancing both employee satisfaction and customer loyalty.

The First Step to Effective De-Escalation

Identifying and mitigating customer dissatisfaction early is critical in maintaining high customer service standards and ensuring customer loyalty. Effective early detection and prevention strategies not only help resolve issues before they escalate but also enhance the overall customer experience, leading to higher satisfaction rates and reduced churn.

Recognizing the Signs of Customer Dissatisfaction

In customer support, recognizing the early signs of dissatisfaction is key to effective service. These signs can often be subtle and easy to miss. For instance, changes in a customer's tone or specific word choices during interactions can indicate underlying frustrations. An agent's ability to pick up on these nuances can make a significant difference in the outcome of an interaction.

Training customer support agents to detect these signs involves focusing on verbal cues like increases in speech tempo or shifts in tone. This sensitivity allows agents to adjust their approach promptly, addressing any concerns before they escalate. For example, if an agent notices a customer's voice becoming strained or hears phrases that signal confusion or dissatisfaction, it would be prudent to slow down, express empathy, and ask clarifying questions.

Implementing Proactive Measures

Once early signs of dissatisfaction are detected, proactive measures are essential to prevent escalation. Immediate empathetic responses and effective communication strategies are fundamental in this phase. By acknowledging the customer's concerns and demonstrating a willingness to solve the problem, agents can defuse potential issues.

Moreover, practical steps such as summarizing the customer's points to confirm understanding and offering clear, concise solutions can help reassure the customer that their issues are being taken seriously and handled efficiently.

Leveraging Tools for Detection

MaestroQA's Auto QA technology, a pivotal tool in DSAT, is instrumental for enabling agents to promptly recognize and address customer dissatisfaction. By running on 100% of tickets, Auto QA analyzes interaction data to identify patterns or trends of dissatisfaction, allowing teams to proactively address recurring issues. The results are displayed on MaestroQA's performance dashboard, where managers can easily identify hotspots of DSAT and drill down into data, facilitating targeted QA to uncover root causes and refine customer interaction strategies effectively.

Incorporating these insights into daily operations empowers customer support teams not only to respond to immediate concerns but also to anticipate and mitigate potential problems before they escalate. This proactive approach builds trust and reinforces the customer's decision to choose your service, thereby enhancing both resolution efficiency and long-term customer satisfaction and loyalty. 

Empowering Agents with a Structured Engagement Strategy

Managing difficult customer interactions effectively is crucial for maintaining high service quality and customer satisfaction, especially in high-pressure call center environments. A structured three-step engagement strategy—Acknowledge, Discuss, and Resolve—empowers agents to handle challenging scenarios with confidence and proficiency, ensuring that each interaction is optimized to turn potential negatives into positive outcomes.

A Step-by-Step Approach to Customer Engagement

• Acknowledge: The first step involves agents recognizing and validating the customer’s concerns, crucial for building trust and defusing tension. For example, an agent might respond to a frustrated customer by saying, "I understand why that would be frustrating. Let's see how we can fix this," demonstrating empathy and taking the issue seriously.

• Discuss: Agents then delve deeper into the issue, asking targeted questions to fully grasp the problem and gather necessary information. This step ensures both the agent and the customer are aligned on the issue's specifics, aiding effective troubleshooting.

• Resolve: The final step is collaboratively finding a solution that leaves the customer satisfied, whether through a replacement, refund, or other agreed-upon remedies. If immediate resolution isn't possible, setting clear next steps and follow-up times is crucial to maintaining trust.

Evaluating the Strategy's Effectiveness

This structured engagement strategy is proven to significantly improve customer satisfaction. DSAT software feedback indicates that customer satisfaction ratings improve markedly when this approach is applied. Additionally, this strategy boosts agent confidence and competency, enhancing overall service quality.

By providing a clear roadmap for interactions, this approach aligns with DSAT training best practices, ensuring precise and empathetic customer service. Empowering agents with these tools and techniques helps create a more positive environment for both customers and agents, promoting better outcomes and fostering a culture of continuous improvement.

Leveraging DSAT Analysis for Continuous Improvement

In customer support, the intelligent use of technology to analyze dissatisfaction—known as DSAT analysis—is transformative. By harnessing automated quality metrics and employing strategic DSAT tools, customer service teams can gain profound insights into areas needing improvement and how to enhance overall customer interactions.

The Role of Technology in Enhancing Customer Service

Automated quality metrics and DSAT analysis play critical roles by providing quantifiable data that teams can analyze to understand customer dissatisfaction deeply. This technology enables support teams to pinpoint dissatisfaction trends and areas that significantly impact customer experience. For instance, if DSAT analysis identifies a recurring issue in customer interactions, such as delays in response times or unsatisfactory problem resolution, teams can implement targeted improvements.

Integration with MaestroQA Tools

MaestroQA's tools offer seamless integration into customer support systems, automating and simplifying the process of data gathering and analysis, thus enhancing the effectiveness of DSAT in call centers. Maestro offers tools for Auto QA, Performance Dashboard Reporting, Coaching, seamless integrations with tools you already use, and more. By leveraging these advanced tools, teams can efficiently assess the quality of customer interactions, identify areas for agent training, and implement changes that lead to improved service delivery. This integration ensures that every customer interaction is an opportunity for assessment and improvement.

By integrating these MaestroQA tools into their customer support operations, organizations can transform their approach to quality assurance, ensuring that every interaction contributes positively to customer satisfaction and agent development.

Practical Application and Outcomes

Potential Real-World Applications

Consider a potential scenario where a customer service team implements the Acknowledge, Discuss, and Resolve framework. An agent might handle a call from a customer upset about a service outage. By acknowledging the customer's frustration, discussing ongoing steps to resolve the issue, and setting clear expectations for resolution, the agent not only manages to defuse a potentially volatile situation but also significantly enhances the customer's perception of the company. This structured approach can lead to improved customer retention and increased satisfaction.

Expert Insights on the Benefits

Courtney Orsinelli emphasized the critical role of emotional intelligence in customer interactions during the webinar. She highlighted how understanding and managing both personal and customer emotions can dramatically enhance the quality of interactions. Orsinelli noted that agents equipped with emotional intelligence are more adept at turning potentially negative situations into positive outcomes.

These insights serve as foundational principles guiding customer support teams to refine their approach to handling difficult interactions, underscoring the benefits of structured strategies and emotional intelligence in fostering stronger customer relationships.

The Role of Effective Feedback

Effective coaching involves not just the occasional feedback session but a continuous cycle of evaluation, feedback, and improvement. Using DSAT data, coaches can provide specific, targeted advice to agents. MaestroQA offers coaching features that facilitate this continuous learning process, ensuring that every agent can achieve their best performance. 

The Importance of Coaching

Effective coaching provides agents with the necessary tools and knowledge to manage customer interactions proficiently. Regular, structured feedback helps agents recognize their strengths and pinpoint areas needing improvement. Focusing on key competencies such as emotional intelligence and conflict resolution, coaching builds confidence and equips agents with the skills crucial for navigating complex customer scenarios successfully.

Impact on Agent Performance

Agents who receive regular, constructive feedback are better equipped to meet customer needs and handle interactions effectively. This leads to higher customer satisfaction rates and boosts agent morale, fostering a positive work environment that benefits the entire organization.

MaestroQA's comprehensive coaching tools transform traditional coaching into a dynamic, ongoing process that continually drives performance improvement. By embracing these advanced tools, organizations can ensure their coaching strategies are not only effective but also impactful, leading to significant enhancements in service quality and team performance.

A Culture of Continuous Learning and Improvement

Embracing a culture of continuous learning and improvement is essential for any organization aiming to excel in customer experience. By integrating emotional intelligence, structured engagement strategies, and advanced DSAT analytics into their operations, customer support teams can not only handle difficult interactions more effectively but also transform them into opportunities for growth and customer loyalty. 

Summary of Key Points

• Emotional Intelligence: Recognizing and managing both personal and customer emotions can significantly enhance interaction quality.
• Structured Engagement: Employing a clear, structured approach to customer interactions helps systematically resolve issues and ensures customer satisfaction.
• Effective Coaching: Continuous, data-driven feedback provided through advanced tools like MaestroQA empowers agents to improve their interactions and problem-solving skills continuously.

By implementing these approaches, organizations can ensure that their customer support teams are not only equipped to handle today's challenges but are also evolving to meet future demands.

Next Steps?

Are you ready to elevate your customer support operations to new heights with MaestroQA? Dive into our comprehensive suite of tools and start your journey towards exceptional customer service excellence today. Discover how our advanced coaching features, real-time feedback capabilities, and structured engagement strategies can transform your approach to customer interactions and propel your team toward peak performance.

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Advancing Continuous Improvement: How Six Sigma and MaestroQA Transform Call Center Operations

With customer expectations soaring, businesses are turning to proven methodologies like Six Sigma to streamline their operations, drive efficiency, and enhance customer experience (CX). We recently hosted a CX + Six Sigma webinar focused on continuous improvement with Pete Pande, a renowned expert in Six Sigma and best selling author, he shed light on how integrating Six Sigma analytics into customer service and call center operations can be a game-changer.

During the webinar, a significant revelation we uncovered was the shift towards continuous improvement within companies and their call centers — moving away from outdated agent performance reviews towards timely, personalized feedback mechanisms. These insights foster incremental improvements that significantly boost call center productivity and performance. The key to success lies in centralized systems that consolidate all call center performance data and customer interactions into one actionable location, enabling a comprehensive KPI dashboard that facilitates trend analysis, performance benchmarking, and drives actionable improvements over time.

Why Six Sigma in Customer Experience? 

The implementation of Six Sigma in customer experience and call center performance management provides more than theoretical benefits—it evolves into a practical strategy for quality management and performance optimization. This approach effectively addresses the needs of modern customers and teams. As Pete Pande stated during the webinar, "Six Sigma and continuous improvement methodologies extend beyond the manufacturing floor. They are crucial in the evolving landscape of customer service, offering a systematic approach to problem-solving that significantly elevates the customer experience."

Consider the example of a leading bank that integrated Six Sigma methodologies to refine its customer service processes. By analyzing and reducing process variability, the bank not only boosted its first-call resolution rate by over 30% but also saw a significant increase in customer satisfaction scores. This achievement marked a notable improvement in how customers perceived and interacted with the bank, underscoring that the benefits extend beyond operational efficiency to genuinely enhancing customer relations.

Through a disciplined, data-driven approach to identify, analyze, and improve existing business processes, companies can achieve substantial improvements in service quality, operational efficiency, and ultimately, customer satisfaction. Six Sigma provides the tools and methodologies necessary to make these enhancements sustainable and impactful.

Building a Culture of Excellence in Customer Service

Creating a culture of excellence in customer service quality assurance goes beyond merely setting high standards. It requires nurturing a proactive, problem-solving mindset among team members. This shift is crucial for making continuous quality improvement an integral part of everyday operations rather than an occasional focus.

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A company's culture must prioritize openness, transparency, and a commitment to continuous learning. Such an environment not only fosters growth but also supports the development of solutions that respond dynamically to customer needs and operational challenges. To cultivate this culture effectively:

• Encourage Open Communication: Ensure that all team members feel comfortable sharing insights and feedback without fear of negative repercussions. Open communication leads to richer ideas and problem-solving strategies, enhancing the collective intelligence of the team.
• Seek Active Feedback: Transform feedback from a passive to an active process. Encourage employees at all levels to seek out constructive criticism, not just receive it. This approach helps to create a continuous loop of improvement where every interaction is an opportunity to learn and adapt.
• Reframe Failure as Opportunity: Shift the perspective on failures from setbacks to learning opportunities. When mistakes are treated as critical learning points, employees are more likely to take innovative risks and explore new solutions without the fear of repercussion.
• Promote Continuous Learning: Offer ongoing training and development opportunities that allow employees to stay current with industry trends and improve their skills. This investment in your team not only boosts morale but also drives innovation and efficiency.

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By embedding these principles into the core of a company’s culture, customer service organizations can achieve higher levels of customer satisfaction and operational excellence. It’s not just about responding to issues as they arise but proactively improving processes to prevent problems before they occur.

MaestroQA: Spearheading Continuous Improvement in Call Centers & Quality Management

Supporting and enhancing this culture of excellence, MaestroQA’s suite of tools is specifically designed to foster the necessary transformation within customer service settings. By integrating customer service QA data with all help desk and telephony system data, MaestroQA provides a comprehensive, 360-degree view of customer support performance. This fusion of data establishes a reliable metric baseline, empowering teams to not only pinpoint areas for improvement but also actively contribute to the culture of continuous enhancement and problem-solving.

360-Degree Customer Support Performance Insights
Centralizing all CX data, MaestroQA facilitates unprecedented insights into the customer service process, ensuring that no aspect of the customer journey—from initial contact to resolution—is overlooked. This holistic approach is crucial for teams committed to upholding a culture of excellence where every interaction is an opportunity for improvement.

Unified Performance Dashboard and Coaching Features
Further driving this culture, MaestroQA’s unified performance dashboard and coaching features transform how teams interact with and learn from every customer engagement. By analyzing 100% of customer tickets and conversations, not only does the platform identify crucial performance gaps, but it also provides actionable insights for addressing them. This comprehensive visibility into customer support operations is not just a tool—it's an essential component in the continuous cycle of feedback and improvement that epitomizes a culture of excellence, offering a clear pathway to enhance service quality and customer satisfaction.

Data-Driven Decision Making
Building on the foundation of a data-enriched customer service environment, the essence of Six Sigma in enhancing customer experience is deeply rooted in data-driven decision-making. This methodology underscores the critical importance of data in identifying, analyzing, and addressing service challenges effectively. During the webinar, Pete Pande highlighted the foundational role of data in Six Sigma, emphasizing its capacity to eliminate guesswork and assumptions in the process improvement journey: "Six Sigma is fundamentally about understanding your processes to such an extent that you can improve them in meaningful ways," Pete noted. "And you can't get to that understanding without diving deep into the data, without really analyzing what your data is telling you about the effectiveness of your processes."

Auto QA and Conversation Analytics
Incorporating advanced tools like Auto QA and Conversation Analytics into MaestroQA’s platform, organizations gain the ability to dive even deeper into the data. These tools automate the analysis of every customer interaction, providing precise and actionable insights that drive decision-making. This capability aligns seamlessly with the Six Sigma emphasis on data-driven insights, enhancing the ability of businesses to pinpoint and rectify areas of inefficiency and customer dissatisfaction more effectively.

Pete further elaborated on the importance of converting data into actionable insights: "It's not just collecting data for the sake of it. It's about using that data to make better decisions, to see where your bottlenecks are, where your opportunities for improvement lie. That's where the real power of Six Sigma comes into play."

Leveraging MaestroQA’s sophisticated data analysis tools, organizations can maintain a continuous feedback loop where data informs actions, leading to significant enhancements in customer service quality. The integration of MaestroQA’s technology with Six Sigma principles exemplifies the modern approach to achieving operational excellence, proving that meticulous analysis and informed decision-making are key to elevating the customer service experience.

The Rise of Real-Time Actionable Feedback

In customer service, the move toward a model of continuous feedback and improvement marks a significant departure from traditional, often criticized annual performance reviews. This shift, highlighted in a prominent Wall Street Journal article, underscores that real-time, actionable feedback is far more effective in fostering professional growth and operational excellence.

Pete Pande, during our webinar, emphasized the vital role of continuous improvement: "The journey towards excellence is continuous. It doesn't end with a single training session or a yearly review. It's about creating an environment where feedback is immediate, learning is ongoing, and every interaction is an opportunity to improve." This reflects the necessity for ongoing coaching and development as fundamental elements of performance improvement, reinforcing the move toward more dynamic and responsive models of employee engagement.

Leveraging MaestroQA for Enhanced Feedback and Insights
MaestroQA’s data-driven agent coaching platform stands at the forefront of this paradigm shift within the customer service sector. The platform's sophisticated analysis capabilities allow supervisors to provide specific, actionable feedback that addresses the nuances of each customer interaction directly. This method not only enhances the quality of customer service but also cultivates a culture of continuous improvement where feedback loops are short, relevant, and deeply integrated into the daily workflow of customer service representatives.

Unique Approach to QA Scorecards and AI-Driven Insights

MaestroQA's innovative approach to QA scorecards and AI-enabled dashboards leverages the latest GPT AI models to surface actionable insights, driving highly precise and actionable decisions. This advanced technology allows teams to effectively 'converse' with their data, going beyond traditional data analytics to uncover deeper, more nuanced trends in agent performance and customer interactions.

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By utilizing GPT prompts, such as asking "What were the common issues in these tickets?", teams can interact with their data in a more intuitive and dynamic way. This method facilitates a deeper analysis of qualitative data, converting it into quantitative insights that are easy to understand and act upon.

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Beyond QA Scores: A 360-Degree View of Customer Service Excellence

MaestroQA's platform extends beyond traditional QA scores, advocating for a holistic management approach that encompasses people, process analytics, and policy. "It's not just about scoring an interaction but understanding the why behind the score," encapsulates the philosophy that quality management is a continuous journey toward excellence.

This comprehensive approach, deeply rooted in Six Sigma principles, transforms raw data into practical, actionable insights. Thus, MaestroQA does not just facilitate quality assurance; it fosters a culture of continuous improvement and excellence. The platform’s ability to provide an extensive analysis across different layers of customer service operations exemplifies the real-world application and value of Six Sigma’s data-driven methodology, ensuring that every decision, every improvement, is backed by solid evidence and geared towards enhancing the customer experience.

Conclusion: Setting New Benchmarks in Customer Service
In the rapidly evolving landscape of customer service, the integration of advanced technologies like MaestroQA with foundational principles of Six Sigma is essential, not just advantageous. This synergy paves the way for businesses to not only meet but exceed customer expectations, setting new benchmarks for quality service and performance excellence in the industry.

Next Steps? Eager to transform your customer service operations with Six Sigma and MaestroQA? Explore our solutions and take the first step towards unparalleled service excellence today.

The Imperative of Proactive Chatbot Quality Assurance

The Rising Stakes of Chatbot Interactions

In an era where speed and efficiency often dictate the parameters of customer satisfaction, chatbots have emerged as vital tools in the arsenal of modern customer service. These AI-driven assistants provide rapid responses to customer inquiries, handle large volumes of requests simultaneously, and offer support outside of traditional business hours. However, the convenience they offer comes with inherent risks. If not properly monitored and managed, chatbots can misinterpret customer intent, provide inaccurate information, or fail to escalate issues when necessary, leading directly to customer dissatisfaction.

Why Quality Assurance is Crucial for Chatbots

Quality Assurance (QA) for chatbots goes beyond routine checks. It is an essential practice designed to ensure that all digital interactions facilitated by chatbots align with customer expectations and company standards. Without robust QA processes, businesses risk the bot’s potential to mismanage interactions, which can erode trust and deter customers from using digital channels in the future. Effective chatbot QA must therefore be seen not just as a backend operation but as a front-line defense of customer satisfaction and brand integrity.

Leading Brands and the Commitment to Chatbot QA

Recognizing the importance of delivering consistently high-quality automated interactions, leading brands like Bombas have invested heavily in chatbot QA. These companies understand that the quality of these interactions can significantly impact customer loyalty and overall brand perception. By prioritizing chatbot QA, Bombas and similar companies ensure that their chatbots are not only efficient but also accurate, empathetic, and aligned with the brand's values, thus sustaining high-quality chatbot services that support their reputation for exceptional customer care.

Through rigorous and continuous chatbot QA, businesses can mitigate risks associated with automated customer service interactions. This commitment not only enhances the effectiveness of customer service chatbots, but also reinforces a brand’s dedication to maintaining high customer service standards, illustrating a proactive approach to customer experience management.

The Continuous Cycle of Chatbot QA

Understanding the Dynamic Nature of Chatbots

Customer support chatbot interactions are not fixed; they are dynamic elements within the customer service ecosystem, capable of evolving based on new data, customer feedback, and changes in business strategy. This fluid nature necessitates an ongoing process of monitoring and evaluation. Each interaction a chatbot engages in can yield valuable insights into both its operational efficacy and areas needing improvement. Therefore, constant vigilance is essential to ensure that chatbots remain aligned with the company’s service standards and customer expectations.

Risks of Neglecting Chatbot Quality Assurance

The repercussions of overlooking chatbot QA can be far-reaching. Primary risks include:

• Customer Frustration: If a chatbot fails to understand or appropriately respond to customer queries, it can lead to frustration and dissatisfaction. This is particularly critical in complex customer service scenarios where a misstep could escalate a customer’s issue rather than resolve it.
• Increased Service Tickets: Inadequately managed chatbots often result in increased service tickets. Customers unable to resolve their issues via chatbot interactions will likely turn to more traditional customer service channels, increasing the workload for human agents and driving up operational costs.
• Brand Reputation Damage: Consistently poor chatbot interactions can tarnish a brand’s reputation. In the digital age, a single bad experience can be shared widely on social media and review platforms, potentially deterring new customers and eroding the trust of existing ones.

Continuous QA as a Strategic Approach for Chatbot best Practices

Beyond the immediate corrective actions, continuous QA is fundamentally a strategic approach that enhances overall customer experience. It involves:

• Proactive Improvement: Continuous QA enables businesses to proactively improve chatbot interactions before they become a customer service failure. By analyzing interactions regularly, companies can refine chatbot responses, adjust their conversational flows, and ensure they are contextually relevant to the customer’s needs.
• Adaptation to Customer Needs: As customer preferences and behaviors evolve, so too must chatbots. Continuous QA processes allow businesses to keep pace with these changes, adapting chatbot functionalities to meet and exceed customer expectations. This is crucial in maintaining customer satisfaction and loyalty.
• Enhancing Customer Engagement: Well-maintained chatbots can do more than solve problems; they can enhance engagement by providing personalized experiences. For instance, by analyzing past interactions, a chatbot can offer tailored recommendations, celebrate customer milestones, or provide timely promotions, thereby enriching the customer relationship.

Through a dedicated commitment to continuous QA, businesses not only mitigate risks but also leverage chatbot technology as a strategic asset in enhancing customer engagement and satisfaction. This ongoing process of refinement ensures that chatbots remain a valuable touchpoint in the customer journey, reflecting the brand’s commitment to quality and innovation in customer service.

Revolutionizing Chatbot QA with Auto QA Technologies

Comprehensive Analysis with Auto QA

Auto QA is transforming the landscape of chatbot quality assurance by scrutinizing 100% of ai chatbot' interactions. Auto QA provides an exhaustive analysis, ensuring no customer interaction goes unchecked. Every dialogue,and every exchange is evaluated, providing a complete overview of the chatbot's performance across various metrics. This level of analysis is crucial for maintaining an error-free, customer-friendly chatbot service that operates smoothly and efficiently under all circumstances.

Visualizing Success and Challenges: The Role of Heat Maps and Performance Dashboards

Heat maps on the Performance Dashboard in MaestroQA pair with Auto QA, revolutionizing how businesses monitor chatbot interactions. A chatbot analytics dashboard provides actionable insights, allowing teams to visualize data effectively, making it easier to spot trends, identify anomalies, and note areas of success or concern. By mapping out chatbot interactions on these dashboards, QA teams can quickly pinpoint patterns of unwanted behaviors or highlight successful interactions that can serve as models for further chatbot training and development. This immediate, clear visual feedback is invaluable for maintaining an effective chatbot deployment.

Enhancing Operational Efficiency Through Auto QA

One of the most significant impacts of Auto QA is the considerable time savings it offers. Though traditional manual reviews of chatbot interactions are still valuable, they can be more labor-intensive and time-consuming, often requiring substantial human resources to sift through each interaction. Auto QA automates this process, freeing up staff to focus on more strategic tasks that cannot be automated. Additionally, the ability to quickly adapt chatbot responses to meet emerging customer needs is greatly enhanced. If a particular type of query is being mishandled, or if there is a sudden change in customer inquiry patterns, Auto QA can flag these issues in real-time, allowing for swift modifications to chatbot protocols.

Immediate Feedback Loops: Empowering Real-Time Adjustments

The immediate feedback loops provided by Auto QA are among its most valuable features. This rapid feedback system enables customer support teams to make informed adjustments to chatbot behavior without delay, ensuring that the chatbot continues to evolve and improve continuously. Whether it's refining answers, adjusting tone, or addressing new types of customer inquiries, the immediacy of this feedback ensures that chatbots remain a dynamic and responsive tool in the arsenal of customer service technologies.

By harnessing the power of Auto QA, businesses can ensure that their chatbots not only meet but exceed the evolving expectations of their customers. This technology not only safeguards the quality of customer interactions but also enhances operational efficiencies, making it an indispensable tool in the age of digital customer service.

Bombas’ Chatbot QA Journey

Leveraging Gladly for Enhanced Customer Interactions

Bombas, renowned for its commitment to customer comfort and satisfaction, has strategically utilized Gladly's chatbot as part of its helpdesk solution to streamline customer interactions. This integration is a testament to Bombas' forward-thinking approach to customer support, ensuring that every digital conversation reflects the brand’s high standards of service. The partnership between MaestroQA and Gladly further enriches this setup, providing Bombas with the sophisticated tools necessary for meticulous chatbot quality assurance. In a recent webinar, Eric at Bombas mentioned their process of QAing their chatbot.

Addressing Initial Chatbot Challenges

Upon integrating the Gladly chatbot, Bombas faced initial hurdles typical to digital customer service solutions. The chatbot, while efficient, initially struggled with generic responses and occasionally failed to grasp the complexity of user intents. Such challenges are common in AI-driven solutions, where the nuances of human communication must be translated into data the technology can process and learn from. Recognizing these issues was the first step in refining their chatbot's capabilities. These early issues highlighted the need for a nuanced understanding of customer interactions—a challenge Bombas was eager to address to maintain its reputation for exemplary customer service processes.

Implementing a Robust QA Framework with MaestroQA

Recognizing the need for precision in their chatbot interactions, Bombas collaborated with MaestroQA to develop a comprehensive quality assurance framework. This initiative focused on identifying 'hotspots'—key areas within the chatbot interactions where errors were most prevalent or where customer dissatisfaction tended to arise. Through MaestroQA’s advanced analytics and quality management tools, Bombas was able to dissect these interactions at a granular level, pinpointing specific issues and refining the chatbot’s responses accordingly.

Measurable Outcomes of QA Efforts

The rigorous QA processes implemented by Bombas led to significant improvements in the functionality of the Gladly chatbot. Notably, there was an enhancement in customer satisfaction scores, reflecting the chatbot's improved ability to handle inquiries with the nuanced understanding expected by Bombas’ customers. Furthermore, the successful refinement of the chatbot’s responses resulted in a reduction in the need for manual intervention by the support team and staff, allowing them to concentrate on more complex and high-value customer interactions. These improvements not only optimized operational efficiency but also reinforced Bombas' commitment to providing exceptional customer service across all platforms.

Bombas' journey underscores the critical role of targeted quality assurance in optimizing chatbot interactions. By leveraging Gladly’s chatbot integrated with MaestroQA's expert solutions, Bombas has set a benchmark in digital customer service, showcasing how strategic tools and partnerships can transform customer support into a seamless, efficient, and highly satisfying experience for users.

The Crucial Role of QAing Your Chatbot

Ensuring Personal and Engaging Interactions

Regular Quality Assurance (QA) of chatbots is essential not merely for correcting errors but for ensuring that every automated interaction is personal, engaging, and reflective of the brand's voice. This rigorous approach to chatbot management is crucial to prevent the erosion of customer trust and satisfaction, ensuring that these digital assistants are capable of offering more than just automated replies—they become a cornerstone of the customer experience.

The Impact of Chatbot Interactions on Customer Satisfaction

Recent insights into customer behavior highlight a significant shift towards digital interactions, especially in how customers manage their relationships with brands. Paul Jarman, CEO of NICE CXone, notes the high expectations customers have for digital services, stating, "Customers are tired...patience for friction is at an all-time low while digital interactions are reaching record heights" (Forbes, 2021). This observation underscores the importance of ensuring that chatbot interactions are seamless and efficient. If a chatbot fails to meet these high expectations, it can lead to customer churn and negatively impact the brand's reputation.

Example of Transforming Chatbot Service

Imagine a scenario where a financial services company introduces a chatbot to handle routine inquiries about account balances and recent transactions. Initially, the chatbot struggles with accurately recognizing specific customer requests, leading to repeated interactions and customer frustration. Recognizing the critical gaps in their chatbot's capabilities, the company initiates a comprehensive QA process. This process involves refining the chatbot’s language processing abilities and enhancing its contextual understanding.

Post-QA, the chatbot not only responds accurately but also begins to offer personalized financial advice based on the customer's transaction history, such as alerting them to unusual spending patterns or recommending savings strategies. This shift not only improves customer satisfaction but also positions the chatbot as a valuable advisor in the customer's financial health—a transformation fueled by meticulous QA.

In essence, regular QA of chatbots ensures these technologies not only respond accurately but also enhance customer relationships through personalized and context-aware interactions. As digital interactions become ai chatbots become more predominant, ensuring these automated systems are both effective and reflective of the brand's commitment to quality service is not just beneficial but essential for maintaining competitive advantage and customer loyalty.

Implementing Effective Chatbot QA Strategies for Your Business

Setting Up Benchmarks for Chatbot Performance

For businesses looking to optimize chatbot interactions, the first step is establishing clear, measurable benchmarks. These benchmarks should reflect both the technical performance of the chatbot—such as accuracy in understanding and responding to queries—and the quality of the interaction from the customer's perspective, including satisfaction and resolution rate. To effectively track these benchmarks over time, businesses should implement regular assessment cycles using tools that gather comprehensive analytics. This data not only measures performance against initial benchmarks but also highlights trends and patterns that can guide further improvements.

Integrating QA Insights into Broader Strategies

The insights gained from regular chatbot QA are invaluable for more than just improving chatbot interactions—they can also inform broader customer support and engagement strategies. For example, if QA data shows that customers frequently ask certain questions that the chatbot handles well, these queries can be leveraged to create FAQ sections or help guides. Conversely, if certain queries consistently lead to escalations to human agents, this might indicate a need for more complex decision-making support or training materials for the chatbot, ensuring it can handle similar future interactions more effectively.

Balancing Automation with the Human Touch

While automation can significantly enhance efficiency and consistency in customer service, maintaining a balance with the human touch is crucial. Here are a few best practices for achieving this balance:

• Escalation Protocols: Ensure your chatbot is designed with clear escalation paths to human agents when it encounters queries beyond its processing capabilities. This helps in maintaining customer trust and satisfaction by not leaving complex issues solely to automated responses.
• Personalization Techniques: Utilize chatbot interactions to gather insights about customer preferences and behaviors. This information can be used to personalize customer interactions across all platforms, not just via the chatbot. For instance, knowing a customer’s past concerns can help human agents provide more tailored advice or solutions.
• Human Oversight: Regularly review chatbot interactions from a human perspective, not just through automated reports. This can involve random sampling of chat logs by human agents to understand the customer experience better and to ensure the chatbot’s tone and responses are appropriately aligned with the brand’s voice.

By implementing these strategies, businesses can ensure their chatbots do not just serve as standalone tools but as integral components of a cohesive customer service ecosystem. This integration not only enhances the effectiveness of the chatbot but also enriches the overall customer experience, leveraging automation to improve human interactions rather than replace them.

Anticipating the Future: Chatbot QA Evolution

Emerging Trends in Chatbot Technology and QA

As technology continues to advance, the capabilities of chatbots are expected to grow exponentially, particularly through developments in predictive analytics and advanced natural language processing (NLP). Predictive analytics are set to refine how chatbots anticipate user needs by analyzing past interactions and deriving insights that can predict future customer behavior. This means chatbots could proactively offer solutions before the customer even identifies a need, thereby enhancing the customer experience.

Furthermore, advancements in NLP will allow chatbots to understand and interpret human language with greater nuance and accuracy. This will enable chatbots to handle more complex conversations, recognize a wider range of emotional cues, and respond in a manner that is more aligned with human conversational patterns. These developments will significantly improve the sophistication of chatbots, making them more reliable and effective in handling diverse customer service scenarios.

Integrating Chatbot QA Insights into Broader Customer Experience Strategies

The insights gained from chatbot interactions are invaluable for more than just improving individual chatbot responses. They can also inform broader customer experience strategies by providing a detailed understanding of customer needs, preferences, and frustrations. For instance, patterns identified in chatbot interactions can indicate broader trends in customer behavior or emerging issues with products or services. Businesses can use this information to preemptively address potential concerns on larger scales, such as adjusting product features or enhancing service offerings.

Balancing Automation and Human Interaction

While the efficiency and scalability of chatbots are undeniable, the importance of maintaining a balance with human interaction remains paramount. As chatbots become more integrated into customer service frameworks, it is crucial to ensure that they complement rather than replace the irreplaceable value of human touch. This involves designing chatbot interactions that seamlessly transition to human agents when necessary, ensuring that customers feel heard and valued at every stage of their journey.

Moreover, businesses must continuously evaluate the division of labor between chatbots and human agents, ensuring that chatbots handle routine inquiries and data gathering, while more complex, sensitive, or nuanced interactions are escalated to humans. This strategic division of tasks not only maximizes efficiency but also preserves the empathy and personal connection that customers often seek in their interactions with brands.

As we look to the future, the role of chatbots in customer service is poised to become more integral and sophisticated. By embracing emerging technologies and integrating chatbot QA insights into broader strategies, businesses can enhance both the efficiency and the quality of their customer service, ensuring that they meet evolving customer expectations while maintaining the essential human touch that defines brand loyalty and customer satisfaction.

Committing to Excellence in Chatbot Interactions

As we've explored, chatbot QA is not merely a routine check but a critical component of modern customer service strategy. The journey towards exceptional chatbot interactions involves continuous monitoring, precise tuning, and regular updates to ensure that every automated conversation accurately represents the brand and meets customer expectations. This commitment to excellence is what distinguishes leading companies in today’s digital marketplace.

Embracing Chatbot QA as a Path to Growth

For businesses, the process of implementing and refining chatbot QA should be viewed not just as a maintenance task but as an ongoing opportunity for significant growth and improvement. Effective QA processes enable chatbots to perform complex functions with greater accuracy and provide interactions that are not only satisfactory but delightful to customers. Moreover, the insights garnered from these QA activities can drive broader strategic decisions, influencing everything from customer service practices to product development.

Learning from Success Stories: The Bombas Example

Bombas serves as an exemplary case study in how dedicated QA efforts can dramatically improve chatbot interactions. By partnering with MaestroQA and leveraging Gladly's chatbot platform, Bombas was able to transform its customer service interactions. Through rigorous QA practices, Bombas identified key areas for improvement, optimized its chatbot's responses, and significantly enhanced overall customer satisfaction. The results speak for themselves, not only in improved efficiency but also in enhanced customer loyalty and brand perception.

By highlighting Bombas' success, we aim to inspire other businesses to recognize the potential benefits of robust chatbot QA. Like Bombas, businesses can achieve remarkable improvements in their customer interaction quality by adopting a proactive and dedicated approach to chatbot QA.

Forward-Looking Strategies

As we look forward, the evolution of chatbot technology and QA methodologies promises even greater integration of these tools into the customer service framework. Companies that commit to ongoing chatbot improvement and QA can expect not only to keep pace with technological advancements but to lead in delivering superior customer experiences.

In conclusion, by committing to rigorous chatbot QA, businesses can ensure their chatbots are powerful ambassadors of their brand, capable of delivering consistent, helpful, and enjoyable interactions. Let the success of companies like Bombas inspire you to elevate your chatbot services, turning every customer interaction into an opportunity to build trust and satisfaction.

Next Steps: Elevate Your Chatbot Interactions with MaestroQA

By prioritizing high-quality chatbot interactions, you're not just solving customer issues—you're enhancing the overall customer experience. This commitment to quality can distinguish your brand in a crowded marketplace and build lasting customer loyalty.

Are you ready to transform your chatbot services and set a new standard in digital customer interaction? Explore MaestroQA's solutions today and start your journey toward becoming a leader in customer service excellence. 

In the quest for operational excellence and superior customer interaction, businesses are increasingly turning to Artificial Intelligence (AI). By automating routine tasks and personalizing service delivery, AI technologies are transforming the landscape of customer experience, offering efficiencies previously unattainable. Emphasizing AI transparency is crucial in maintaining customer trust and brand integrity, as it ensures understanding and accountability in AI deployments. However, as discussed in our recent webinar, “Get Smart on AI for CX: Mastering Innovation While Protecting Customer and Employee Trust,” the rapid integration of AI also brings with it a spectrum of risks, particularly when deployments are not carefully managed. Missteps in implementation can lead to significant damage, eroding customer trust and tarnishing brand reputation.

Acknowledging both the transformative potential and the challenges of AI, it is essential for organizations to adopt a balanced approach. This blog post delves into the critical strategies for mitigating risks associated with AI in customer experience, highlights the importance of maintaining transparency in AI deployments, and discusses how aligning AI strategies with organizational ethics and values can safeguard against potential pitfalls. Join us as we explore these vital topics, aiming to harness the benefits of AI while upholding the trust and integrity of your brand.

Understanding the Risks of AI Technology in Customer Experience

Identifying Potential AI Risks

Artificial Intelligence, when optimally deployed, can revolutionize customer interactions, offering personalized experiences and streamlining processes. However, the integration of AI into customer experience (CX) isn’t without significant risks that need to be carefully managed. Key challenges include data privacy concerns, where mishandling of customer information can lead to breaches and legal repercussions. Additionally, AI systems might misinterpret customer emotions or nuances in communication, potentially resulting in responses that are inappropriate or frustrating for the user. Another critical risk is the potential for AI to perpetuate existing biases found in training data, leading to unfair or discriminatory outcomes. To address these challenges, organizations should consider adopting an AI risk management framework, which serves as a suite of tools and practices designed to protect organizations and end users from the distinctive risks of AI, ensuring the deployment aligns with responsible AI practices and values.

Case Study: The Air Canada Chatbot Incident

One poignant example of AI failure in the customer experience sector is the infamous incident involving the Air Canada chatbot. According to a report by Forbes, this automated system provided incorrect information regarding flight cancellations, leading not only to customer dissatisfaction but also to a high-profile legal challenge that ended unfavorably for the airline. 

The root causes of this failure included technical issues in how the AI interpreted data and significant shortcomings in how it was programmed to communicate under varying circumstances. This incident highlights the critical importance of accurate and reliable AI communications in customer interaction and the necessity for rigorous quality assurance of AI chatbots to ensure they convey correct and clear information.

Impact on Brand Reputation and Customer Trust

The consequences of such AI missteps can be severe for brands. Beyond the immediate legal or financial costs, the long-term damage to brand reputation can be considerable. Studies have shown that an AI failure can lead to a sharp decline in customer trust, which is often difficult and costly to rebuild. For instance, following the Air Canada incident, surveys indicated a notable decrease in customer confidence not only in the automated systems but in the brand's overall commitment to customer care.

By understanding these risks and implementing robust AI systems that prioritize accuracy, transparency, and fairness, organizations can avoid the pitfalls that have ensnared others in the pursuit of technological advancement in customer experience.

Case Studies of Potential AI Missteps

Exploring Potential AI Failures

While the following cases are not drawn from specific real-life incidents, they explore potential challenges that can arise with AI integration in the customer service industry. These examples are based on common types of AI difficulties to illustrate what might go wrong and how businesses can prepare. 

1. Financial Services Chatbot Challenges: Imagine a leading financial services firm implements an AI-driven chatbot to handle customer inquiries and transactions. If the chatbot is not thoroughly trained on complex financial queries and lacks adjustments for regional linguistic variations, it might frequently misinterpret customer intents. Such potential issues could lead to erroneous account actions and widespread customer dissatisfaction, demonstrating the critical need for context-specific training and linguistic diversity in AI systems.
2. E-commerce Customer Service Overload: Consider a scenario where a global e-commerce giant deploys an AI system aimed at preemptively addressing customer issues based on predictive analytics. If this AI system is not properly calibrated to manage the large volume and diversity of customer interactions, it could result in generic and often irrelevant responses. This potential scenario underscores the importance of scalability and the necessity of ongoing AI system refinements to maintain relevance and effectiveness. To prevent these potential failures, it is crucial to focus on building trustworthy AI systems that are explainable, interpretable, and transparent, ensuring trustworthiness and reliability in AI-driven customer service solutions.

Learning from Potential AI Implementation Errors

These potential examples underscore the importance of comprehensive testing in varied real-world conditions to fully understand AI limitations; continuous training with diverse and current data sets; and the essential role of human oversight in monitoring AI behavior and outcomes.

AI Regulations, Repercussions, and Shifting Public Perception

Even potential errors like these could lead to increased regulatory and public scrutiny. These scenarios illustrate the need for more stringent guidelines for AI deployments, especially those interacting directly with consumers, emphasizing transparency, accountability, and customer safety. The future of AI transparency will likely see the development of AI regulations focusing on ethical considerations of AI, addressing biases, fairness, and privacy concerns to ensure more responsible AI systems.

Strategies for AI Risk Management

Implementing Comprehensive AI Risk Assessment Frameworks

Effective management of AI risks in customer experience necessitates robust frameworks and methodologies tailored to identify potential threats, analyze impacts, and develop mitigation strategies. A comprehensive approach ensures that all potential issues are proactively addressed, safeguarding the integrity of customer interactions and the organization's reputation.

Strategic Preventive Measures

To maintain the integrity and effectiveness of AI systems, strategic preventive measures are essential. This includes the implementation of 'kill switches' for immediate intervention when AI systems malfunction, regular audits to ensure AI behaviors align with ethical standards and operational goals, and integrating human oversight to continuously refine AI decisions.

Enhancing Chatbot Quality Assurance with MaestroQA

Quality assurance of AI chatbots is critical in the digital era. MaestroQA provides powerful tools to scrutinize and enhance chatbot performance, ensuring every interaction positively influences customer experience. Through comprehensive tools like Auto QA, which analyzes 100% of chatbot interactions, organizations can systematically improve their chatbot services. These tools help pinpoint areas for improvement and monitor compliance with service standards, ultimately elevating customer satisfaction.

Emphasizing Real-Time Monitoring

Real-time monitoring of AI interactions is vital for immediate correction and adjustment, minimizing potential damage from AI missteps. MaestroQA's Performance Dashboard offers a dynamic platform for this purpose. With features like customizable dashboards that allow for detailed views of AI performance across different metrics and unique use cases, the dashboard is an essential tool for any organization looking to maintain high standards in AI-driven interactions. This platform facilitates the visualization of data at multiple levels—from teams down to individual tickets—providing all the necessary tools to foster a proactive, responsive customer service environment.

By adopting comprehensive risk assessments, implementing strategic preventive measures, and leveraging advanced tools like MaestroQA for real-time monitoring and AI quality assurance, organizations can effectively navigate the complexities of AI in customer experiences. These practices ensure that AI systems not only operate efficiently but also align with the company’s ethical standards and core values, thereby maintaining trust and enhancing customer relationships.

Aligning AI with Organizational Values and Ethics

Developing and Implementing Ethical AI Frameworks

To ensure that AI technologies enhance rather than compromise customer experience, organizations must develop and implement ethical AI frameworks that resonate with their core values and meet customer expectations. These frameworks should outline clear guidelines on how AI should behave, the ethical considerations it must adhere to, and the methods for addressing potential ethical dilemmas.

Dr. Kartik Hosanagar, a speaker from our webinar, emphasizes that ethical AI frameworks should not only focus on AI regulations and compliance but also on fostering trust and transparency. By integrating these ethical considerations from the outset, companies can build AI systems that not only perform efficiently but also operate in a manner that customers and employees deem fair and just. Additionally, these frameworks play a crucial role in relieving data scientists from the validation burden, as they are typically not experts in governance and compliance.

Involving Diverse Stakeholder Groups

The development and deployment of AI systems must actively involve a broad range of stakeholders to ensure that diverse perspectives and needs are considered. This includes not just technical teams but also customer support representatives, policy makers, and directly impacted customers. Involving these diverse groups helps in identifying potential unintended consequences of AI systems and in designing solutions that are inclusive and equitable. This multi-stakeholder approach was highlighted during our webinar as crucial for capturing the varied nuances of customer interactions and ensuring that AI solutions are well-rounded and robust against a wide array of real-world scenarios.

Establishing Robust Governance and Compliance

Governance of AI systems is critical to ensure they adhere to both internal ethical guidelines and external regulatory requirements. Best practices in governance include establishing a dedicated oversight committee that regularly reviews AI behaviors and outcomes against ethical benchmarks and compliance standards. Moreover, this committee should also be responsible for updating AI operational guidelines in response to new regulatory developments and ethical insights. Regular audits and assessments should be conducted to ensure ongoing compliance and to make adjustments as necessary, maintaining an alignment with both the company’s ethical standards and evolving external regulations.

By focusing on these areas—ethical frameworks, stakeholder involvement, and rigorous governance—organizations can align their AI strategies with their core values and ethical commitments, ensuring that their AI initiatives enhance customer experiences in a responsible and sustainable manner. This alignment not only protects the company from potential missteps but also reinforces its reputation as a trustworthy and customer-centric organization. The enforcement of the California Consumer Privacy Act has notably influenced privacy design and compliance programs, underscoring the Act's significant impact on privacy and data protection standards, practices, and processes among American companies.

Building and Maintaining Trust through AI Transparency Practices

Enhancing Transparency in AI Decisions

Transparency is a cornerstone of trust, especially when it comes to the deployment of AI technologies in customer experiences. Companies must strive to demystify AI operations for both customers and employees by making AI decision processes transparent. This can be achieved through detailed explanations or intuitive visualizations of how AI systems make decisions. For example, when a customer interacts with an AI-driven support tool, the tool could provide a simplified breakdown of how it arrived at its responses. Similarly, employees can benefit from interfaces that visually map out AI decision pathways, helping them understand and explain AI actions to customers.

Effective Communication Strategies

Clear and open communication about the role and benefits of AI is crucial in building trust. Companies should develop strategies that not only inform but also engage their audience. This involves regular training sessions for employees to ensure they are comfortable with AI tools and can confidently communicate about them to customers. Additionally, creating accessible content such as FAQs, videos, and interactive webinars can help demystify AI for customers. For instance, showing real-world scenarios where AI has improved service delivery can make the technology more relatable and less intimidating.

Illustrating the Benefits of Transparent AI Implementations

While real-world examples specific to transparent AI successes were not discussed in our webinar, envisioning the potential outcomes offers significant insights. For example, an online retailer that implements an AI system offering explanations for product recommendations could see increased customer engagement and trust. This transparency allows customers to understand the rationale behind suggestions, fostering a sense of control and appreciation for the personalized service.

Similarly, imagine a healthcare provider using AI to suggest treatments, providing patients with detailed explanations based on clinical data and individual histories. Such transparency could greatly enhance patient trust, reassuring them that their care is informed and personalized.

By implementing these strategies, companies can ensure that their AI systems are not just efficient but also trusted by those they serve. Transparent practices in AI foster a culture of openness and continuous learning, which not only enhances customer relationships but also empowers employees, ultimately leading to a more engaged and loyal customer base. Through transparency, companies can navigate the complexities of AI integration while maintaining and enhancing trust across all levels of their operations.

Conclusion

As we've explored throughout this discussion, the integration of Artificial Intelligence in customer experience represents a dynamic frontier with vast potential to enhance service delivery and operational efficiency. However, as underscored in our webinar with AI expert Dr. Kartik Hosanagar, it's crucial that this integration is approached with a balanced perspective. AI's capabilities can drive incredible advancements, yet its risks require careful management to avoid undermining the trust that businesses have worked hard to establish with their customers.

Ethical considerations, transparency, and the alignment of AI strategies with an organization's core values are not merely idealistic goals—they are essential practices that determine the success of AI in customer interactions. Ensuring that AI systems operate within these parameters helps safeguard sensitive customer data, respects privacy, and maintains fairness in automated decisions. By prioritizing these principles, companies can foster a relationship of trust and dependability with their users, turning new technological possibilities into enduring business value.

In conclusion, while AI offers transformative opportunities for businesses across sectors, the journey towards its adoption must be navigated with foresight and responsibility. Companies that successfully integrate these technologies in ways that respect ethical boundaries and align with their core values will not only avoid potential pitfalls but also strengthen their competitive edge in the marketplace. As we continue to embrace AI, let us do so with the commitment to uphold the highest standards of integrity and customer care.

Next Steps?

What to learn more about navigating the risks of AI implementation in your QA strategy? Connect with us!

In an era where customer experience (CX) can make or break a company, Bombas stands out as a beacon of innovation and dedication. Bombas has distinguished itself not just through its innovative apparel but also through its exemplary commitment to customer service. This brand's journey to the apex of CX excellence offers a compelling blueprint for integrating quality assurance (QA) and personalized coaching into the fabric of customer service operations. Through the insights of Eric Mead, Customer Experience Manager at Bombas, we get an exclusive look into how Bombas and MaestroQA synergize innovative QA practices with transformative call center coaching techniques, setting new standards for CX excellence.

Bombas’ Approach to Quality and Coaching

In a market where expectations are ever-evolving, Bombas has not only kept pace but set a new standard for customer experience (CX) excellence. At the core of this achievement is a sophisticated approach to quality assurance (QA) and coaching that focuses on the individual needs of each agent. This strategy embodies the essence of personalized and adaptive coaching, leveraging the power of MaestroQA's analytics to refine these practices into an art form.

Personalized Coaching

Bombas understands that the strength of its customer service lies in the hands of its agents. This realization led to the development of personalized coaching strategies, where each agent receives guidance tailored to their unique strengths and areas for improvement. Eric Mead, discussing the company's ethos, underscores the importance of this individualized attention, stating, "We ensure every agent feels supported and capable of delivering exceptional service." This approach not only boosts the agents' growth but also enhances the overall quality of customer interactions.

The Magic of Adaptive Coaching

Adaptive coaching methods are another pillar of Bombas' quality assurance strategy. Recognizing that the customer service landscape is dynamic, Bombas employs flexible tactics for coaching call center agents that evolve based on real-time data and insights. This adaptability allows Bombas to meet the shifting demands of customer service excellence, ensuring that their customer service agents are always at the forefront of call center quality assurance best practices.

Leveraging MaestroQA's Analytics for Insights

The partnership with MaestroQA introduces a powerful dimension to Bombas' approach. Utilizing MaestroQA's analytics, Bombas gains actionable insights into agent performance, customer satisfaction metrics, and the efficacy of their coaching methods. This data-driven approach not only ensures the continuous refinement of their coaching strategies but also strategically positions Bombas to improve CSAT scores through targeted interventions. The in-app coaching and targeted QA features of MaestroQA play a crucial role in fostering a culture of continuous improvement at Bombas.

How MaestroQA Fuels Bombas’ CX Innovation

MaestroQA's platform has been instrumental in enabling Bombas’ ability to implement these innovative practices. The in-app coaching functionality, for example, allows Bombas to deliver personalized feedback directly within the platform, making the coaching process seamless and more impactful. Similarly, the actionable insights derived from MaestroQA’s performance dashboard empower Bombas to make informed decisions about their QA and coaching strategies, continually enhancing the customer experience.

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A Testament to Customer-Centricity

Bombas' utilization of these advanced strategies, powered by the analytical might of MaestroQA, exemplifies their commitment to a customer-centric approach. The continuous loop of feedback and improvement ensures that Bombas not only meets but exceeds customer expectations, solidifying its position as a leader in CX excellence. This marriage of technology and personalized strategy showcases Bombas' innovative approach to QA and coaching, setting a benchmark for others in the industry.

Empowering Agents for Success

Bombas has charted a course in the realm of customer service that emphasizes not just the empowerment of its agents but their continuous evolution as cornerstones of customer satisfaction. This dedication to agent development is woven into the very fabric of their operations, underscoring a dynamic blend of personalized business development plans, robust training modules, and the strategic use of technology through a partnership with MaestroQA.

Fostering Continuous Improvement

At Bombas, every agent’s journey is marked by a commitment to continuous improvement, facilitated through personalized development plans. These plans are not static; they evolve, reflecting the individual growth trajectory of each agent and the shifting sands of customer service demands. Bombas recognizes that the empowerment of its agents is synonymous with providing them with tangible opportunities for growth. This philosophy is manifested in targeted training modules designed to equip agents with the skills needed to navigate and excel in complex customer interactions.

Training Agents to Receive Feedback

Key to the empowerment strategy is training agents not just to receive feedback but to actively engage with it. Bombas, in collaboration with MaestroQA, ensures that agents feel that feedback is not a one-way street but a dialogue. The platform allows agents to see their performance data and coaching sessions all in one place, fostering a transparent environment where feedback is not just delivered but discussed. This approach demystifies the feedback process, making it a tool for empowerment rather than a metric of judgment.

Revolutionizing Quality Management with MaestroQA

MaestroQA’s unified performance dashboard is a game-changer in the way Bombas approaches quality management. By analyzing 100% of customer tickets and conversations, MaestroQA provides Bombas with unprecedented visibility into its customer support operations. This comprehensive overview allows Bombas to identify performance gaps swiftly, pinpoint areas for coaching, and foster a culture of accountability and excellence. The dashboard serves as a mirror, reflecting the real-time impact of each agent’s interactions with customers, backed by data that guides their path to improvement.

Cultivating a Culture of Empowerment

The culture at Bombas is one that champions open feedback loops and readily provides resources for agent development. This ecosystem of support and accountability is pivotal in maintaining not just the quality of customer service but the morale of employees across the team. Agents at Bombas are not left to navigate the complexities of customer interactions alone; they are supported by a framework that values their growth as much as it does customer satisfaction.

The partnership with MaestroQA amplifies this culture, integrating technology with Bombas’ customer-centric approach to create a robust platform for agent development and agent empowerment. The use of MaestroQA’s insights and analytics has enabled Bombas to translate its vision for unparalleled customer service into actionable strategies.

In essence, Bombas’ successful strategy for empowering agents is a testament to its belief that the heart of exceptional customer service lies in the continuous growth and development of its agents. Through personalized development plans, comprehensive training, and the strategic use of technology, Bombas has set a new standard in the industry, proving that the empowerment of agents is the cornerstone of delivering outstanding customer experiences.

Performance Excellence Beyond Metrics

Bombas transcends the traditional boundaries of performance metrics in customer service, embracing a holistic approach that values not just quantitative scores but the qualitative essence of each interaction. This comprehensive view integrates Quality Assurance (QA) scores, Customer Satisfaction (CSAT), and other Key Performance Indicators (KPIs) to paint a full picture of the customer service landscape. By doing so, Bombas doesn't just measure performance; it nurtures and elevates it.

A Holistic Approach to Performance Metrics

Bombas' adoption of a holistic perspective on performance metrics is revolutionary. It acknowledges that true excellence in customer service cannot be captured by numbers alone. QA scores and CSAT metrics provide valuable insights, but Bombas digs deeper, considering factors like agent happiness and customer loyalty as essential components of operational success. This approach allows Bombas to identify not just where improvements are needed but also where success should be celebrated, fostering a culture of acknowledgment and continuous growth.

Celebrating Success and Identifying Improvements

By looking beyond the surface of traditional metrics, Bombas has cultivated an environment where successes are celebrated with as much enthusiasm as areas for improvement are identified. This balanced view encourages a positive feedback loop within the organization, where achievements bolster morale and areas of improvement are addressed with constructive strategies. It's a method that not only enhances operational excellence but also builds a resilient and motivated team, dedicated to upholding the highest standards of customer service.

Metrics Beyond Numbers

Bombas' focus on metrics beyond numbers is a testament to its understanding that the heart of customer service lies in the human experience. Agent happiness is not merely a nice-to-have; it's a crucial driver of customer satisfaction and brand loyalty. 

Happy agents are more engaged, empathetic, and effective in their interactions with customers, leading to experiences that not only resolve issues but also build stronger relationships with the brand. Similarly, customer loyalty is seen not just as a byproduct of effective service but as a key indicator of the health and effectiveness of the entire customer service operation.

Bombas' approach to performance excellence is a beacon for the industry, demonstrating how a holistic view of metrics can illuminate the path to true operational excellence. By valuing both the tangible and intangible aspects of customer service, Bombas not only achieves high standards of performance but also fosters an environment where continuous improvement is part of the DNA. This commitment to looking beyond the numbers to the very essence of customer service is what sets Bombas apart, ensuring that its reputation for excellence is as enduring as the relationships it builds with each customer.

Implementing Innovative QA and Coaching Strategies

Bombas has revolutionized its approach to customer service with a keen focus on quality assurance (QA) and personalized coaching for satisfied employees. Leveraging MaestroQA's technology, Bombas has crafted a dynamic framework that not only addresses the immediate needs of their team but also anticipates future challenges, ensuring a consistently excellent customer experience.

Deep Dive into Strategies

Bombas’ strategy centers on targeted QA to identify areas for improvement with precision. This approach, enhanced by MaestroQA's analytics, enables Bombas to tailor coaching sessions to the specific needs of each agent. The result? A team equipped to exceed expectations at every turn.

Challenges and Solutions

Facing the challenge of maintaining high-quality service across a growing team, Bombas employed MaestroQA's performance dashboard. This tool allowed for an in-depth analysis of customer interactions, revealing crucial insights that informed targeted coaching and development plans. The outcome was not only an uplift in customer satisfaction but also in agent morale and job satisfaction.

Role of QA in Strategy

The QA process at Bombas is integral, facilitating the continuous refinement of coaching strategies. Through the use of custom QA rubrics and the performance dashboard, Bombas delves into every customer interaction, ensuring that agents receive feedback that is both meaningful and actionable. This meticulous approach has fostered a culture of accountability and continuous improvement within the team.

Empowering Through Insights

At the core of Bombas' innovative approach is the empowerment of agents with data-driven insights. By analyzing 100% of tickets, Bombas has been able to pinpoint specific areas for agent training and development, leading to significant improvements in customer service quality and efficiency.

Bombas' implementation of these strategies showcases the power of a customer-centric approach, combined with the right technology, to transform customer service operations.

Leveraging Data for CX Insights

At the heart of Bombas' customer experience success is a keen understanding that data is more than just numbers—it's the voice of their customers and the blueprint for their service strategy. Bombas harnesses this wealth of information to continuously refine its support experience and enhance its approach to quality assurance (QA) and coaching, setting a benchmark in personalized customer service.

Transforming Data into Actionable Insights

Bombas dives deep into the data from each customer interaction, turning feedback, QA scores, and performance metrics into a strategic asset. This data-driven approach allows them to identify specific areas where coaching can have the most impact, tailoring sessions to address individual agent needs and broader team goals. It's a precision-guided method that ensures every piece of feedback is a stepping stone to greater customer satisfaction.

Optimizing Coaching Programs with Precision

Armed with insights from their comprehensive analysis, Bombas optimizes its coaching programs, ensuring they're not only relevant but also impactful. This isn't about blanket strategies; it's about understanding nuances and subtleties in agent performance and customer needs and adjusting coaching methods accordingly. The result? A team that's continuously improving, empowered by data-backed guidance.

A Culture Rooted in Continuous Improvement

The strategic use of data for enhancing CX underlines Bombas' commitment to a culture of continuous improvement. By effectively leveraging analytics tools and techniques, Bombas translates complex data sets into straightforward, actionable strategies that lead to improved overall experience, agent performance and higher, customer satisfaction scores.

Bombas' approach demonstrates the power and value of a data-informed strategy in crafting a customer experience that's not just satisfactory but remarkable. It's a testament to the belief that understanding and acting on customer feedback is paramount in the quest for service excellence. Through a meticulous analysis of data to provide insights and its translation into actionable coaching strategies, Bombas continues to lead the way in customer service innovation.

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A New Era of Customer Experience Innovation

Bombas' transformative approach to quality assurance and coaching marks a milestone in the realm of customer experience (CX), showcasing an unparalleled commitment to customer satisfaction and excellence. At the heart of their success lies a deep focus on tailored coaching, empowering agents, and harnessing the power of data to drive meaningful improvements. This strategy not only positions Bombas as a vanguard in the CX field but also serves as a blueprint for organizations striving to enhance their customer service. 

The story of Bombas illuminates the path to achieving superior customer interactions through innovation, personalized support, and an unwavering dedication to excellence. As the landscape of customer experience continues to evolve, Bombas shines brightly, demonstrating the profound impact that a commitment to high quality products, care, and continuous improvement can have on both customers and the broader industry.

Next Steps?

Embracing Bombas' trailblazing approach to QA and coaching, underscored by the strategic use of MaestroQA's analytics and coaching tools, is more than an aspiration—it's a reachable goal for any organization dedicated to elevating its customer experience. By prioritizing personalized coaching, empowering your team with actionable insights, creating and fostering a culture of continuous improvement, you can set a new standard in customer service excellence.

Ready to embark on your journey to outstanding CX, powered by MaestroQA? Explore our solutions and begin your transformation into a customer service leader today.

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In an era where digital platforms dominate, the importance of robust risk management and quality assurance in trust and safety cannot be overstated. TaskRabbit, a leader in the gig economy, exemplifies how integrating quality assurance and risk management can create a secure and reliable environment for both users and service providers. This post explores the sophisticated strategies employed by TaskRabbit to safeguard its platform and enhance customer experience (CX), drawing from the insights shared by Cody Summers, the Global Risk Operations Manager at TaskRabbit.

Setting the Standard for Trust and Safety

Unwavering Commitment to a Safe Platform

TaskRabbit’s mission to create a secure environment doesn’t just follow industry standards—it sets them. This commitment is deeply embedded in their business model and operational tactics, focusing intensely on ensuring a reliable platform for both users and service providers. By integrating thorough safety protocols and stringent quality controls, TaskRabbit enhances user trust and sets a high bar for the gig economy.

Advanced Risk Management and Quality Controls

TaskRabbit utilizes a proactive approach to risk management that includes a sophisticated suite of tools and protocols aimed at minimizing potential threats before they impact the platform. This forward-thinking strategy is supported by the use of advanced technologies, which analyze patterns that could indicate fraudulent activities. By employing data-driven strategies to preemptively address these fraud risks, TaskRabbit protects its platform’s integrity while ensuring that user interactions remain secure.

Fostering a Culture of Safety and Reliability

Beyond fraud prevention, TaskRabbit’s strategies for maintaining trust and safety permeate every user interaction on the platform. They enforce a robust set of community standards and performance metrics that all participants must adhere to. This not only helps in curtailing harmful interactions but also fosters a culture of accountability and transparency across the platform. Continuously refining these processes ensures that TaskRabbit remains adaptive and responsive to community needs, thereby upholding a stable and dependable marketplace.

Real-World Impact of Trust and Safety Measures

The impact of TaskRabbit’s trust and safety measures can be seen in the reliability and user satisfaction that characterize the platform. By maintaining strict oversight and continually enhancing safety protocols, TaskRabbit ensures that all transactions on the platform are conducted within a secure framework. This not only protects individuals but also builds a robust community where users can engage confidently and with peace of mind.

Through meticulous attention to creating a safe and reliable environment, TaskRabbit not only protects its users but also serves as a model for other platforms striving to enhance their operational strategies. This approach to trust and safety is what distinguishes TaskRabbit as a leader in the market, ensuring the platform remains a trusted space for all its users.

Proactive Strategies for Fraud Prevention

Harnessing Advanced Data Analytics

TaskRabbit leverages cutting-edge technology to spearhead its fraud prevention strategies. Utilizing advanced data analytics, the platform can detect and analyze patterns that might indicate fraudulent activities. These technologies are pivotal in preemptively identifying potential fraud, allowing TaskRabbit to maintain the integrity of transactions on the platform.

In his role as Global Risk Operations Manager, Cody Summers highlighted the use of data-driven strategies to streamline its risk control operations. By feeding transactional data through sophisticated rules models, TaskRabbit enhances the precision of its fraud detection mechanisms. This proactive approach minimizes the risk of fraud and builds a safer environment for both taskers and clients.

Balancing Automation with Human Expertise

While automation plays a crucial role in TaskRabbit's fraud prevention framework, human intervention remains vital. The balance between using automated systems and human oversight ensures that while the technology handles pattern recognition and data processing, the nuanced decisions are left to the trained professionals. This hybrid model enhances the accuracy of effective fraud prevention and detection without sacrificing the user experience.

For example, as Cody Summers pointed out, once the automated systems flag potential fraud activities, it's the responsibility of the risk operations specialists to step in and make the final assessment. This not only helps in confirming the validity of potential threats but also in understanding the context behind each suspicious activity, which might be overlooked by automated processes alone.

Ensuring High Accuracy in Fraud Detection

The dual approach of integrating both technology and human expertise to prevent fraud also ensures that TaskRabbit’s fraud detection mechanisms are not only efficient but also highly accurate. This strategy respects the user experience by reducing false positives — legitimate transactions mistakenly flagged as fraud — which can be disruptive and frustrating for users. TaskRabbit's commitment to maintaining a user-friendly platform while aggressively combating fraud showcases their dedication to operational excellence and customer satisfaction.

TaskRabbit's fraud prevention strategies exemplify their proactive stance on safeguarding the platform against potential risks and, ensuring a trustworthy and secure environment for all users. This thoughtful approach to integrating sophisticated technology with human judgment sets a high standard for risk management in the gig economy.

Accountability and Continuous Improvement

Comprehensive Training and Continuous Feedback

TaskRabbit places a strong emphasis on the empowerment of their customer service agents through rigorous training programs coupled with continuous feedback loops. This approach ensures that agents are well-equipped not only to handle the demands of the marketplace but also to excel in their roles by adhering to the highest standards of service quality.

The training at TaskRabbit isn't just about imparting knowledge; it's about embedding agents into a culture that values growth and accountability. This is reflected in their strategy to continuously update training materials to address the evolving challenges of the gig economy, ensuring that agents remain proficient and confident in their roles.

A Culture of Accountability

Feedback loops are integral to TaskRabbit's operational strategy, fostering a culture where accountability is paramount. This process involves not only regular performance reviews but also actionable insights that help agents improve over time. Cody Summers noted the importance of such frameworks in a discussion about operational excellence, emphasizing the impact of empowering agents through accountability. “When you give people the tools they need and get out of their way, they thrive,” Summers explained.

Agent Empowerment

The effectiveness of TaskRabbit's approach is evident in how they utilize performance metrics and dashboards to provide real-time, actionable feedback to their agents. These tools help pinpoint areas of excellence and those needing improvement, allowing for targeted interventions that boost performance and service quality.

Through structured training, ongoing feedback, and a commitment to accountability, TaskRabbit not only bolsters the capabilities of their agents but also ensures that these enhancements translate into superior customer service. This focus on empowering agents is a cornerstone of TaskRabbit's operational excellence, driving their success in the competitive gig economy landscape.

Advanced Performance Dashboards

Integrating Qualitative and Quantitative Data

TaskRabbit leverages MaestroQA’s performance dashboards that integrate both qualitative assessments and customer satisfaction metrics (CSAT) to enhance operational excellence. These dashboards are crucial in providing a holistic view of the service quality and operational efficiency across the platform. By combining quantitative data, such as completion rates and response times, with qualitative feedback on agent interactions, TaskRabbit ensures that all dimensions of customer service are meticulously monitored and optimized.

The use of this comprehensive tool enables TaskRabbit to maintain a high standard of service while continuously adapting to user needs and preferences. For instance, the inclusion of CSAT scores helps identify trends and areas for improvement directly related to customer experiences, ensuring that the services provided align closely with customer expectations.

Empowering Decision-Making

Maestro QA’s performance dashboards at TaskRabbit serve as vital tools for both managers and agents, facilitating informed decision-making that aligns with the company’s strategic goals and the immediate needs of customers. These dashboards provide a comprehensive understanding of real-time data that is accessible to all levels of the organization, fostering an environment where information is transparent and actionable.

Driving Operational Excellence

TaskRabbit’s Maestro QA dashboards do more than track performance; they are integral to the company’s commitment to operational excellence. By providing detailed and accessible analytics, these tools help TaskRabbit maintain an agile operational strategy that can quickly adapt to emerging challenges and opportunities. They allow for a level of granularity in performance analysis that is essential for continuous improvement and sustained success in the gig economy.

The specific mention of how these dashboards influence day-to-day management and strategic decisions underscores their value. For example, Cody Summers elaborated on how data from these dashboards could influence broader operational changes, suggesting, "This allows us to then fold in something like my performance review where all of a sudden we’re not just queuing high-risk fraud events but also ensuring consistency in risk assessments across the board."

By integrating both qualitative and quantitative data into their performance management systems, TaskRabbit not only fosters a data-driven culture but also ensures that every decision made is informed, strategic, and aligned with both customer needs and business objectives. These dashboards represent a critical tool in TaskRabbit's ongoing quest to refine their operations and deliver unmatched service quality.

Quality Rubrics in Action

Crafting and Refining Quality Rubrics

TaskRabbit’s commitment to operational excellence is exemplified through its meticulous development and ongoing refinement of quality rubrics. These rubrics are essential tools that guide the decision-making process across global teams, ensuring that every customer interaction adheres to the same high standards, regardless of geographical location. TaskRabbit regularly updates these rubrics to reflect the evolving nature of the gig economy and the diverse challenges faced by their service providers and users.

The process involves a detailed analysis of performance data and customer feedback, which informs the necessary adjustments to the rubrics. This dynamic approach allows TaskRabbit to maintain alignment with best practices in customer service and risk management, while also adapting to new insights or changes in the marketplace.

Ensuring Consistency Across Global Teams

The use of quality rubrics is crucial for maintaining consistency in how services are rendered across various regions. By standardizing the criteria for assessing agent performance and customer interactions, TaskRabbit ensures that every team member, no matter their location, has a clear understanding of the expectations and procedures they need to follow. This consistency is vital not only for maintaining service quality but also for fostering a unified corporate culture that values customer satisfaction and operational excellence.

Impact on Interaction Quality and Operational Efficiency

The implementation of quality rubrics has a profound impact on the overall quality of interactions on the TaskRabbit platform. These guidelines help agents understand precisely what is expected of them in every customer interaction, which in turn leads to more effective communication, enhanced problem-solving, and increased customer satisfaction. Furthermore, the rubrics provide a framework that supports efficient decision-making, reducing variability in responses and speeding up resolution times.

TaskRabbit’s commitment to refining these rubrics as part of their quality assurance strategy demonstrates their dedication to continuous improvement. The rubrics are not only about maintaining current standards but also about pushing the envelope on what excellent customer service should look like in the gig economy. This proactive approach to quality management ensures that TaskRabbit remains at the forefront of the industry, providing reliable and exemplary service to all its users.

Lessons from the Field

Building Effective Risk Management Frameworks

Cody Summers, as the Global Risk Operations Manager at TaskRabbit, brings a wealth of experience in managing complex risk operations that are integral to maintaining a secure and trusted platform. His approach combines a deep understanding of risk dynamics with a proactive stance on safeguarding the platform against potential threats. Key to his strategy is the blend of advanced technology and human oversight. Cody emphasizes the importance of integrating data-driven methodologies to anticipate and mitigate emerging risks, before they escalate.

Cody's insights into risk management are particularly valuable for enhancing trust and safety on a global scale. He discusses the necessity of adapting risk management strategies to different regional requirements and cultural contexts, ensuring that global operations maintain consistency in safety standards while being flexible enough to accommodate local nuances.

Adopting TaskRabbit's Strategies in CX Operations

CX professionals looking to implement similar practices in their operations can draw significant lessons from Cody's approach. One of the primary strategies is the use of technology to streamline risk detection and management. Tools that leverage data analytics can significantly enhance the ability to spot potential issues early, allowing CX teams to act swiftly and prevent harm.

Furthermore, Cody’s model of balancing automated systems with skilled human analysis can be particularly instructive. This hybrid approach ensures that while technology handles the bulk of data processing and pattern recognition, the nuanced decisions are still reviewed by human experts. This balance is crucial for maintaining the personal touch and understanding user intent, which is often necessary for complex customer interactions.

Practical Applications for CX Leaders

For leaders in customer support and CX, applying Cody's strategies involves several practical steps:

• Invest in Technology: Adopt tools and platforms that provide real-time analytics and can integrate seamlessly with customer interaction data.
• Train Teams Thoroughly: Ensure that all team members are not only familiar with the tools but are also trained in interpreting and acting on the insights these tools provide.
• Establish Clear Protocols: Develop and enforce clear protocols for handling risks, which should include steps for both automated and manual interventions.
• Continuous Learning and Adaptation: Encourage a culture of continuous learning and adaptation, where feedback from the risk management process is used to refine strategies and training programs.

Implementing these strategies can help CX professionals create safer and more reliable environments for their users, enhancing customer trust and building a reputation for safety and reliability. Cody Summers’ success in managing risk operations at TaskRabbit serves as a compelling blueprint for others in the industry looking to enhance their operational strategies in similar domains.

Elevate your Trust and Safety QA Strategy

As we've explored through TaskRabbit's exemplary practices, the integration of robust risk management and quality assurance into business operations is pivotal for enhancing customer experience (CX) in the gig economy. TaskRabbit's commitment to building trust and safety on a global scale, as demonstrated through the insights shared by Cody Summers, serves as a powerful model for operational excellence.

For organizations looking to elevate their own CX strategies, the lessons drawn from TaskRabbit’s approach offer valuable guidelines. Emphasizing proactive risk assessment and management, empowering agents through continuous training and feedback, and leveraging technology to ensure consistency and reliability are strategies that can significantly enhance trust and safety within any platform. These practices not only improve customer satisfaction but also foster a secure environment that users can trust.

We encourage CX professionals to consider how these strategies might be adapted and implemented within their own company's operations to achieve similar benefits. For those interested in deepening their understanding of CX improvement strategies and staying abreast of best practices, we offer a range of resources.

Next Steps?

Embracing TaskRabbit's innovative approach to risk management and quality assurance is an attainable goal for any organization committed to enhancing its customer experience. By prioritizing proactive fraud prevention, empowering your team with actionable insights, and fostering a culture of safety and reliability, you can achieve new heights in customer service excellence.

Ready to embark on your journey to outstanding CX, powered by MaestroQA? Explore our solutions and begin your transformation into a customer service leader today.

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Is your business fully leveraging the transformative power of Quality Assurance (QA) across all its operations? In an era where every efficiency counts, internal process improvements facilitated by QA can lead to a remarkable increase in overall business performance. This underscores the pivotal role of QA not just in direct customer interactions but as a crucial component in enhancing internal operations and strategic decision-making. 

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Today's business environment demands a broader application of QA principles. MaestroQA’s CEO, Vasu Prathipati, discusses the significant shift in the role of QA—from a focus solely on troubleshooting and error detection to a comprehensive tool that spans across the entire business landscape. This expanded role makes QA a strategic asset, capable of dissecting and improving the intricate processes behind the scenes that power companies, drive efficiency, and ensure compliance in increasingly complex regulatory landscapes.

Understanding the Strategic Role of QA in Business Operations

Traditionally, QA has been synonymous with end-product quality control, primarily seen as a final checkpoint before a product or service reaches the customer. This narrow view confined QA to a reactive role, focused on identifying defects after they had already occurred. However, modern business demands have transformed QA into a far more strategic tool. Today, QA is integrated into every facet of business operations, serving as a proactive force that shapes processes, enhances efficiency, and secures compliance.

Strategic QA Across Business Domains

Quality Assurance is critical not only at the point of final output but right from the initiation of various business processes. It significantly impacts domains that traditionally may not be the first thought of when it comes to quality control. Here are examples of how strategic QA is applied across different sectors of a business:

• Customer Success: QA plays a fundamental role in ensuring that interactions within customer success departments contribute positively to client relationships. By implementing QA strategies, businesses can ensure that their customer success teams are consistently delivering according to the company standards, tailoring interactions to meet customer needs and creating ongoing value. This approach helps in maintaining high customer satisfaction and loyalty.
• Trust & Safety: In areas concerning trust and safety, QA is indispensable for preventing fraudulent activities and ensuring the security of the platform. Through diligent QA practices, companies can proactively detect and mitigate risks associated with security breaches or fraudulent activities, thereby protecting users and maintaining a safe and trustworthy platform.
• Compliance: QA in compliance is crucial for organizations that need to adhere to regulatory and ethical standards. By integrating QA into their compliance processes, companies can continuously monitor and audit their operations to ensure they align with legal requirements. This rigorous approach minimizes risks and helps avoid potential fines and legal repercussions, ensuring the business operates within the bounds of regulatory frameworks.

Each of these domains benefits distinctively from the strategic application of QA, demonstrating its value beyond conventional applications and highlighting its role in supporting comprehensive business integrity and operational excellence.

Leveraging QA for Enhanced Operational Excellence

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In today's business climate, operational excellence is not just about efficiency; it's about combining technology with human insight to enhance process integrity and decision-making. QA plays a crucial role in this balanced approach, ensuring that while many processes can benefit from automation, the human element remains central to maintaining trust and handling complex analytics. Below, we explore strategies that effectively integrate both automated tools and human expertise to optimize operational excellence.

Enhancing Internal Processes through Collaborative QA

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To achieve a seamless blend of efficiency and insight, QA must employ a combination of automated audits and human oversight:

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• Hybrid Audits: Automating certain aspects of the QA process, such as data collection and initial analysis, with Auto QA allows for efficient monitoring of operations. However, it’s the human interpretation of these findings that often provides the nuances needed to make strategic improvements. Hybrid audits combine the speed and accuracy of automation with the critical, contextual analysis provided by human reviewers. This approach ensures comprehensive oversight, where machines handle volume and speed, and humans address complexity and subtlety.
• Regular Internal Reviews with Stakeholder Engagement: Incorporating regular reviews of processes and outcomes ensures that all operational facets are aligned with the company's strategic goals. These reviews should actively involve various stakeholders, including those who are directly impacted by the QA processes. This inclusive approach helps to validate the data provided by automated systems and fosters a culture of continuous improvement, grounded in real-world applications and team insights.
• Continuous Feedback Loops: Effective QA systems are distinguished by their robust feedback mechanisms that provide real-time insights, crucial for immediate operational adjustments. Tools like the MaestroQA Performance Dashboard are central to this process, showcasing easily visible information in heatmaps after AutoQA has analyzed 100% of tickets. This setup combines the depth of automated data visualization with the strategic input of human oversight, creating a dynamic environment where feedback is seamlessly integrated into the continuous improvement cycle. Such immediate visibility enhances operational adaptability, enabling teams to quickly identify and act on areas needing improvement through Coaching.

Utilizing QA Data for Data-Driven Decision Making

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Data from QA processes is invaluable for informing strategic decisions across the organization. To fully leverage this data, a combination of automated analysis and human expertise is essential.

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By ensuring that QA processes are a blend of automation and human expertise, organizations can achieve a higher standard of operational excellence. This balanced approach not only enhances efficiency and accuracy but also retains the critical human touch necessary for complex problem-solving and strategic decision-making.

Examples of Real-World Applications

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Implementing MaestroQA can significantly enhance various business functions by streamlining processes, ensuring compliance, and elevating overall efficiency. While there are many non-customer-support QA use cases, here, we delve deeper into three strategic areas where MaestroQA plays a pivotal role: Compliance, Fraud Prevention, and Onboarding.

Use Case Example #1: Compliance

Objective: Ensuring compliance with industry regulations and internal standards is crucial for businesses to mitigate risks and uphold ethical practices.

MaestroQA Solution: MaestroQA Auto QA automates the monitoring and auditing of compliance-related activities across an organization. By setting predefined standards and benchmarks within the system, MaestroQA can continuously review operations and flag deviations in real-time. This not only simplifies the compliance process but also enhances accuracy, allowing businesses to maintain impeccable standards and easily adapt to regulatory changes. Auditors are than able to focus their efforts and more thoroughly address complex issues. Regular reports generated by MaestroQA provide transparency and can be used to demonstrate compliance to regulatory bodies, significantly reducing the risk of penalties.

Use Case Example #2: Fraud Prevention

Objective: Accurately identifying and mitigating fraudulent activities is essential for protecting the financial interests of both the company and its customers.

MaestroQA Solution: MaestroQA offers robust tools to enhance the process of detection and prevention in fraud. By integrating with customer systems, MaestroQA can analyze patterns and flag irregularities or anomalies in fraud team interactions which can help minimize financial loss and protect customer relationships.

Use Case Example #3: Onboarding

Objective: Effective onboarding is critical for ensuring a positive initial experience for new customers, which can significantly impact customer retention and satisfaction.

MaestroQA Solution: MaestroQA standardizes and optimizes the onboarding process by ensuring all procedures are followed and quality thresholds met. Each step of the onboarding process can be checked for quality, ensuring consistency and thoroughness. Feedback collected during onboarding can be analyzed and addressed through Coaching to continually improve the process, enhancing the customer experience and increasing satisfaction from the outset.

MaestroQA’s integration into non-customer-facing areas such as compliance, fraud prevention, and onboarding exemplifies its versatility and impact. By automating critical processes and providing deep insights, MaestroQA not only enhances operational efficiency but also safeguards businesses against risks and ensures a superior customer experience from the first interaction.

Harnessing QA for Team Performance and Organizational Strategy

QA is not just about maintaining standards; it's a dynamic tool that can transform team dynamics and enhance overall performance within an organization. By incorporating regular QA evaluations and aligning them with strategic goals, companies can foster a culture of continuous improvement, heightened motivation, and increased accountability.

Enhancing Team Dynamics Through Regular QA Evaluations

Regular QA evaluations serve as a critical feedback mechanism for teams across an organization. By consistently measuring and analyzing performance against predefined standards, teams can identify both strengths and areas needing improvement. This process helps in tailoring coaching programs that address specific skills gaps or knowledge deficiencies, ensuring that all team members are equipped to perform at their best.

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For instance, in a customer service setting, regular targeted QA assessments can pinpoint exact moments where service could be enhanced, be it through better communication skills or more effective problem-solving strategies. This targeted feedback allows managers to customize coaching sessions that directly address these issues, which not only improves individual performance but also elevates the team's overall capability.

The Motivational Impact of QA Initiatives

QA provides a transparent framework for recognizing high performance and identifying leaders within teams. An exemplary tool for fostering this recognition is MaestroQA’s Leaderboards, which promote healthy competition and visibility of individual achievements. By clearly delineating performance standards and consistently applying them, team members know that their hard work and dedication are likely to be recognized and rewarded. This recognition not only boosts morale but also drives competition among team members to strive for excellence.

By integrating QA into the fabric of team operations, organizations can unleash the full potential of their teams. Regular QA evaluations refine and enhance team performance, while the alignment of these evaluations with organizational goals motivates and engages team members. This strategic use of QA not only drives performance improvements but also builds a robust, responsive, and motivated workforce ready to meet the challenges of today's business environment.

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QA’s Role in Shaping Organizational Strategy

QA data is a goldmine of information that offers more than just operational insights—it provides a strategic overview of organizational performance across various dimensions. By analyzing patterns and trends from QA evaluations, leadership can gain a deep understanding of underlying issues that may affect long-term success. These insights can drive strategic initiatives such as:

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• Resource Allocation: QA data can highlight areas that are underperforming or over-resourced, allowing organizations to optimize their investments by redirecting resources to areas that need attention or scaling back where necessary.
• Risk Management: QA helps identify potential risks before they become critical issues. This proactive risk management is crucial for strategic planning, enabling organizations to mitigate risks early and plan for contingencies.
• Policy Development: By providing a clear picture of compliance and performance gaps, QA data can be instrumental in shaping policies that enhance operational effectiveness and ensure regulatory compliance.

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For example, if QA processes identify a recurring issue in product returns due to a specific quality lapse, this insight can lead to strategic changes in manufacturing processes or supplier selections. This kind of strategic adaptation not only addresses the immediate quality issues but also aligns with broader business objectives such as cost management and customer satisfaction.

Integrating QA with Leadership

For QA to truly influence organizational strategy, it must be integrated into the decision-making processes at the highest levels. QA leaders can play a pivotal role in this integration by effectively communicating the strategic value of QA. Here are some strategies to help QA leaders advocate for QA within executive teams:

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• Translate QA Data into Business Insights: QA leaders should present QA data not just as metrics or KPIs but as actionable business insights. Demonstrating how QA influences customer satisfaction, compliance rates, or operational efficiency can help executives see the broader implications of QA investments.
• Demonstrate ROI: Quantify the return on investment (ROI) of QA activities by linking them to cost savings, revenue enhancement, or risk mitigation. For instance, show how improvements in QA processes have reduced waste, enhanced customer retention, or avoided regulatory fines.
• Align QA Goals with Business Objectives: Clearly align QA objectives with the organization's strategic goals. If the company is focusing on market expansion, illustrate how QA ensures product adaptability and compliance across new markets. If customer loyalty is a priority, demonstrate how QA enhances customer experience and satisfaction.

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There is a focus on how QA can transform perceptions within organizations, particularly through data-driven strategies that align with executive concerns. This approach not only elevates the profile of QA within the company but also ensures that QA initiatives receive the necessary support and resources.

Best Practices for Implementing Effective QA Strategies

Implementing an effective QA strategy is crucial for enhancing not only customer-facing operations but also internal business processes. MaestroQA provides sophisticated tools and functionalities that simplify the setup and management of QA processes, supporting continuous improvement and adaptability to changing business needs and technological advancements.

Implementation Strategies with MaestroQA

Selecting the Right Tools: MaestroQA offers a unified insights platform that consolidates all your metrics in one place, providing tailored insights for your organization’s critical workflows. This comprehensive visibility is crucial for managing both Auto QA and Manual QA processes effectively, integrating helpdesk and workforce management data to streamline coaching and development with a consolidated view.

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Training Staff: Effective QA implementation requires well-trained staff. MaestroQA enhances training and development through its agent development features. Non-agents gain a bird’s-eye view of rankings on the Performance Dashboard, facilitating direct coaching, grading, and feedback from the dashboard itself. This functionality allows for real-time coaching and immediate application of insights gathered from custom dashboards, helping identify training needs and proactively addressing underlying issues.

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Defining Clear Metrics for Success: Customization options in MaestroQA allow organizations to generate custom heat maps for trend spotting and design precise bespoke dashboards. These tools help in defining clear and measurable success metrics, tailored specifically to the needs of your teams. Gamified leaderboards transform tracking into an engaging experience, fostering friendly competition and providing holistic insights into agent rankings.

Fostering Continuous Improvement with MaestroQA

Routine Assessments and Refinements: MaestroQA’s Performance Dashboard enables effortless monitoring of multiple metrics, helping organizations keep a pulse on performance and swiftly identify areas for improvement. The dashboard’s shareable and customizable nature allows for team-specific views that target insights effectively, ensuring that continuous assessment is part of the daily workflow.

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Adapting to Changing Business Needs: MaestroQA’s AI-enhanced insights and workflow analytics adapt seamlessly to evolving business environments. Features like AI Classifiers analyze 100% of tickets through Auto QA, unlocking key insights for root cause analysis and trend identification. Beyond typical analytics, MaestroQA's Screen Capture feature provides deep insights into both customer-facing and backend workflows. With 'Moments', visualize key interactions within recordings to quickly identify crucial segments such as call holds and flagged tickets. This capability is further augmented by URL-based triggers and seamless integration with leading helpdesk platforms like Zendesk and Salesforce, enhancing workflow efficiency and operational adaptability without compromising privacy or agent autonomy. These features ensure that your QA processes remain aligned with both current and future business requirements.

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Technological Advancements: MaestroQA stays at the forefront of QA technology. Its integration capabilities with major platforms like Gladly and Salesforce streamline workflows and data accessibility, making it easier for teams to apply QA insights in real time. The platform’s continuous updates and enhancements in features like Screen Capture metrics and Omni-Present Coaching ensure that users have access to the most advanced tools available.

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By harnessing the power of MaestroQA’s comprehensive QA tools and strategies, organizations can enhance their QA processes to not only meet but exceed their operational and strategic goals. With MaestroQA, companies can effectively set up, manage, and continuously improve their QA strategies, ensuring that they remain competitive and responsive to both internal and external challenges.

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Conclusion: Elevating Organizational Success with Quality Assurance

As we have explored throughout this discussion, integrating Quality Assurance into non-customer-facing aspects of business operations is not merely a tactical decision but a strategic imperative. MaestroQA has been instrumental in redefining the scope and impact of QA across various domains, underscoring its pivotal role in driving business-wide performance excellence.

Future Outlook

Looking ahead, the role of QA in business strategy is set to become more critical than ever. As organizations navigate increasingly complex market conditions and regulatory environments, the demand for robust, adaptable QA systems like those provided by MaestroQA will grow.

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Expansion into New Domains: As businesses continue to evolve, QA will expand into new areas. MaestroQA is poised to lead this expansion, offering solutions that adapt to and meet the needs of these emerging challenges.

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Greater Strategic Influence: QA will increasingly influence strategic decision-making, moving beyond operational roles to shape high-level business strategies. With MaestroQA, businesses can harness the full potential of QA to not only mitigate risks but also identify new opportunities for growth and innovation.

Next Steps?

Integrating MaestroQA's cutting-edge Quality Assurance tools into your non-customer-facing operations is not just an innovation—it's a strategic necessity for any organization aiming to excel in operational efficiency and business performance. By embedding comprehensive QA processes, leveraging continuous improvement, and empowering decision-making with actionable insights, your organization can achieve new heights in operational excellence.

Are you ready to transform your internal operations and strategic planning with the power of MaestroQA? Explore our solutions and embark on your journey to becoming a leader in operational excellence today. Discover how our advanced analytics, customized dashboards, and continuous improvement tools can redefine your approach to quality assurance and drive your business forward.

Explore Our Solutions and Begin Your Transformation!

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Negative customer feedback can significantly impact a business's reputation, resulting in churn and lost revenue. To mitigate this risk, businesses are looking to ramp up their Quality Assurance workflows to detect and mitigate friction points in the customer journey before they impact business growth. 

Leveraging AI Classifiers and Sentiment Analysis with Novo’s Customer Service

In a recent Fireside Chat, we had the opportunity to speak with Novo, a leading mobile banking platform for small businesses, to learn more about the success their team is having using MaestroQA’s automated QA workflows, KPI dashboard and AI Classifiers to identify actionable insights that will have the greatest impact on customer satisfaction levels. 

In our discussion with Marcus Tatum, Quality Assurance Manager, he shared how his team uses MaestroQA's workflow automation and call center sentiment analysis to identify low-scoring DSAT tickets to perform targeted QA. While this automation has served Marcus and his team very well by not only identifying gaps in agent performance but also providing Voice of the Customer (VOC) insights into product and policy, it only captures feedback from customers who complete the CSAT survey, leaving out a potentially significant number of dissatisfied customers. 

In an effort to get a more accurate picture of what’s causing negative feedback from customers, Novo’s team is now leveraging MaestroQA’s automated transcription to analyze 100% of their customers' interactions to take their analysis of DSAT to the next level. They are even taking call center sentiment analysis one step further by revamping their approach to tracking negative sentiment by using MaestroQA’s AI classifiers and buildable logic to scan and surface the most meaningful tickets — enabling a new level of analysis and deeper quality metrics that didn’t exist before. 

How MaestroQA’s AI Classifiers Work

As an example, teams can build an AI classifier to scan tickets for signs of negative sentiment based on keywords specific to their business that indicate a negative customer experience. While the previous method of a blanket scan for negative sentiment was like a "black box," this new system is a “transparent box” and can be tailored to individual businesses.

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Using Transcriptions to Identify Customer Service Insights

Using MaestroQA, Novo was able to uncover an issue that was occurring with mobile check deposits, where specific checks from the California State Government were being repeatedly rejected by their banking software. With the use of AI Classifiers, Marcus will be able to build reports using keywords associated with the "check rejection" issue to determine its frequency, identify which agents are skilled at handling these situations, and assess the negative sentiment resulting from these customer interactions. MaestroQA's highly accurate transcriptions will even enable the Classifier to listen for key phrases such as "check rejected, California, or deposit error" to identify phone calls discussing this particular issue. Novo’s QA team can also pull in other metadata from his HelpDesk to identify tickets where a customer started the conversation upset but was satisfied with the agent's response or conversations where a customer initially felt fine but became upset due to the agent's service or policy.

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Benefits of Using AI Classifiers for Quality Metrics

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By using AI classifiers, businesses can gain a more comprehensive understanding of their customers' issues and needs. Instead of relying solely on Manual QA or feedback from NPS and CSAT surveys, they can leverage AI-driven sentiment analysis to capture feedback from all interactions and use it to make data-driven decisions. This can lead to more efficient and effective customer service, as well as improvements in product and process design. Furthermore, the customizable nature of the classifiers enables businesses to develop new Quality KPIs to help make decisions regarding agent coaching, outsourcing, processes, and even product decisions.

With MaestroQA's AI classifiers, Marcus's team will be able to grade 100% of their tickets, gaining insights into trends and sentiment that will help them make better decisions. Marcus says, "Being able to understand everything that's going on and its full context and how often it's happening and understand the trends that help us make better decisions for sure."

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Secure Handling of Sensitive Information with MaestroQA

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As a financial institution, Novo requires a tool that can meet its unique needs and accommodate the sensitive information shared by its customers. 

"Something I've loved about Maestro is how we're able to filter out tickets with automation. We realized that certain tickets are related to a potential policy break. Then there are tickets that just don't have any of that sensitive information. And so there's an opportunity to create an automation that’s specific to policy sensitive information or policy sensitive tickets or handling."

MaestroQA allows customer service teams to handle sensitive information securely, protecting their customers' data and privacy. Marcus emphasizes the importance of protecting their customers' data and privacy, saying, "Being a financial institution, it's super important that we're protecting our customers and their information." MaestroQA's redaction of account and debit card information provides an additional layer of security. Marcus and his team plan to use the AI Classifier tool to build out reporting on agent compliance, furthering their efforts to protect and support their customers.

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The Future of Quality Assurance and Customer Service with MaestroQA's AI Classifiers

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By automating and customizing the categorization of customer interactions, AI classifiers are revolutionizing how businesses approach quality metrics. As Marcus emphasizes, there's always an opportunity to use new tools to improve quality assurance and customer service. He notes, "I really think where MaestroQA goes, Novo goes. That's historically how it's been. Where we'll see new tools rolled out, and our mindset is we're going to use this platform to its fullest extent. We're looking to utilize every feature that Maestro offers." With MaestroQA, businesses can streamline their feedback analysis, protect their customers' data and privacy, and ultimately improve their bottom line.

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Check out the full recording of our chat with Novo, and if you would like to learn more about what MaestroQA can do for your business, please request a demo today.

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Empowering Agents: The Future of Customer Retention

In today's world, where customer loyalty is constantly shifting, customer retention is more important than ever. Businesses are stepping up with fresh strategies to leave a lasting mark with every interaction. The central theme? Empowering service agents. By examining strategies from industry titans such as Rent the Runway, Staples Canada, Gousto, ClassPass, and MaestroQA, we highlight a blueprint for businesses keen on redefining their customer service with agent empowerment as the foundation. In this blog, we explore five tactics championed by industry leaders, offering actionable insights for businesses to amplify their customer service and retain customers.

Tactic 1: Harness Partial Credit Scorecard Systems for Enhanced Empowerment 

Insights from Rent the Runway

Today's businesses thrive on strategies that boost customer satisfaction. A shining example of this comes from Rent the Runway, where instead of utilizing simplistic success metrics on their frontline agents, they leverage Partial Credit Scorecards. These scorecards delve into the intricate facets of agent-customer interactions. Instead of a black-and-white 'pass' or 'fail', agents are evaluated on a spectrum, highlighting their empathy, efficiency in resolution, and tailored service.

This nuanced system empowers agents, encouraging them to break free from rigid scripts and connect more genuinely with customers. In a recent conversation between MaestroQA and Rent the Runway's Michael Haefner, Manager of Quality Development, Michael emphasized the value of recognizing the varying degrees of an agent's performance. For instance, while an agent might show empathy, there's a distinction between generic empathy and a more tailored approach. By granting partial points, agents are motivated to uniquely tailor their responses to each customer, enhancing the overall experience.

The result? As demonstrated by Rent the Runway, this strategy not only offers agents better feedback but also strengthens customer retention and loyalty.

Takeaway: Move beyond binary feedback systems. Understand and appreciate the nuances in agent-customer interactions to foster deeper connections and improve loyalty.

Tactic 2: Empower Through Agent Appeals

Learning from Staples Canada's Approach

Staples Canada is a prime example of fostering a harmonious relationship between agents and quality teams. Their Agent Appeals process champions the idea that agents should have a voice, especially when they perceive evaluations differently.

MaestroQA sat down with Nicole Beepath-Singh, Training and QA Lead at Staples Canada to illustrate their process: Instead of viewing appeals as points of contention, Staples Canada interprets them as the agent's voice—a testament to the intricate and varied nature of customer service scenarios. Agents are encouraged to appeal evaluations they disagree with, shedding light on their reasoning and viewpoint. This isn’t merely a means of voicing disagreements; it acknowledges that agents sometimes need to think creatively to best serve customers.

But the benefits of this appeals process aren’t unilateral. It's also an internal feedback system for Staples Canada. Repeated agent concerns can hint at areas requiring training enhancements or policy tweaks. Nicole calls this feedback the "voice of the agent," a vital supplement to the voice of the customer. This circular feedback system ensures that the customer's input reaches the agent, which then informs the quality team through appeals.

Staples Canada's Agent Appeals process goes beyond addressing grievances—it’s an empowerment mechanism. By allowing agents to share their insights, especially when they diverge from standard evaluations, it boosts their morale and becomes a feedback conduit for organizational improvements.

Takeaway: Adopt an appeals process to show agents they're valued. Recognize their insights and use them as growth opportunities for the business.

Tactic 3: Empower Through Continuous Learning and Self-Service

Drawing from Gousto's Methodology

In an era where customers crave instant solutions, customer service must proactively evolve to meet those expectations. Gousto's strategy is a prime example of proactive agent empowerment that gets ahead of potential issues.

Michael Whittaker, Customer Care Training & Quality Manager at Gousto, spoke with MaestroQA’s CX community and emphasized Gousto’s commitment to consistent training and an up-to-date learning management system. Instead of only acting on customer feedback, Gousto promotes internal feedback, empowering agents to recognize their strengths and areas for growth.

More than just traditional training, Gousto encourages agents to spotlight instances where they excelled or faced challenges. These scenarios become focal points during coaching sessions, analyzed collaboratively to derive insights and applaud accomplishments.

Gousto's standout feature is the self-serve nature of its coaching and training modules. Agents are given access to their performance metrics, fostering a culture of self-evaluation and ownership. This autonomy not only uplifts agents but instills a heightened sense of responsibility, enhancing their interactions with customers. With an impressive 90% engagement rate on their grades, it's evident that agents are actively invested in this feedback process.

An informed agent is the bridge between a displeased customer and a brand advocate. Gousto recognizes that agents, when armed with the right knowledge and tools, can offer prompt solutions, elevating the overall customer experience. Their consistent training and integrated coaching platform and knowledge management system guarantee that agents are well-prepared for any customer encounter.

Gousto's emphasis on agent empowerment, characterized by perpetual learning and self-guided knowledge management, is more than just about refining agents—it’s about curating exceptional customer encounters. Ultimately, a well-equipped agent paves the way for a gratified customer—the endgame for any successful business aiming at robust customer retention.

Takeaway: Invest in ongoing training and equip agents with self-assessment tools. An informed agent is more confident, resulting in heightened customer satisfaction.

Tactic 4: Quality Benchmarks as Stepping Stones for Career Advancement

A Glimpse into ClassPass's Strategy

A recent conversation with Amy Fleming, Manager, Education and Quality Enablement at Classpass, shed light on the intricate balance between maintaining quality benchmarks and fostering agent motivation. 

ClassPass is a leading fitness and wellness membership platform, and their quality team seamlessly marries customer experience with agent growth. Amy highlighted that their strategy goes beyond just evaluating "customer-friendly language". It’s about leveraging quality benchmarks to both ensure top-tier customer experiences and chart a course for agents' professional development.

ClassPass champions the idea that enhancing an agent's experience directly uplifts the customer's journey. With transparent quality benchmarks, agents gain clarity on their areas for improvement and how their progress resonates with the company's broader goals. This perspective can be a game-changer, especially during challenging interactions, helping agents understand that both they and the customers share a common goal: an unparalleled experience.

ClassPass doesn’t stop at daily interactions. They intricately weave quality benchmarks with potential career advancements, providing agents with dual motivation: delivering stellar customer service and eyeing growth within the organization. Agents, thus, are not merely in avoidance of errors but are fervently exploring avenues to shine, innovate, and contribute to the company and their own growth.

The ripple effect of this approach is palpable to customers. Agents, powered by positive reinforcement and growth prospects, exude a distinct dedication in their interactions. This translates to more authentic, empathetic, and efficient service that drives customer retention.

In Amy's words, the essence is to “break away from silos,” recognizing that quality benchmarks resonate beyond just customer experience, creating a unified, goal-driven organization.

Takeaway: Align agents' professional growth with company quality benchmarks. This dual incentive approach can transform customer experiences.

Tactic 5: Embracing Data as a Guiding Light, Not a Restriction

Insights from MaestroQA

As technological advancements in CX give teams more and more access to data on agent performance, striking a balance between agent empowerment and the urge to micromanage is a challenge. Micromanagement, though rooted in the pursuit of quality, can inadvertently suppress innovation and lead to impersonal interactions. During a recent CX community discussion, led by MaestroQA’s CEO and Co-Founder Vasu Prathipati, he attempted to shed light on this delicate balance. 

While manual Quality Assurance (QA) programs can provide detailed insights into specific conversations, they often miss the bigger picture. Traditional QA systems usually review only 1-2% of interactions, leading managers to micromanage teams based on this limited perspective of their performance. With newer advanced AutoQA tools, it's feasible to examine up to 100% of customer conversations. And thus requires a paradigm shift, viewing QA as guiding guardrails rather than constraining barriers. This approach empowers agents, letting them navigate within defined boundaries while retaining the flexibility to innovate. Greater visibility into metrics like response times and personalization fosters trust. This clarity enables managers to grant agents more autonomy, leading to richer, more empathetic interactions with customers.

During the recent community discussion, Vasu likened QA to a canvas, setting the boundary but allowing the agent the artistic freedom within. By leveraging data as a guiding light rather than a restrictive leash, it cultivates creativity, paving the way for genuine, customer-focused conversations.

There is a transformative potential of data when used judiciously. In the evolving CX landscape, empowerment rooted in data-driven insights fosters innovation, trust, and customer-first interactions that drive customer retention.

Takeaway: Utilize data to inform and guide agents rather than restrict them. Trust in their abilities leads to enriched customer experiences.

Conclusion

In conclusion, the landscape of customer service is undergoing a transformative shift, pivoting towards an emphasis on agent empowerment and with customer retention at its core. As illustrated by industry leaders like Rent the Runway, Staples Canada, Gousto, ClassPass, and MaestroQA, the key to unparalleled customer loyalty and retention lies in the hands of service agents. The tactics outlined in this blog underscore a shared narrative—when agents are equipped, trusted, and motivated, they become the linchpin of authentic, effective, and resonant customer interactions. Businesses keen on fostering long-lasting customer relationships should view their agents not just as front-line workers, but as invaluable ambassadors of their brand. By integrating these practices, organizations can create a robust foundation for exemplary customer service, ensuring they stand out in today's ever-evolving marketplace.

Want to learn more?

If you would like to learn more about what MaestroQA can do for your business, please request a demo today.

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Rising to the Onboarding Challenge in Modern Customer Service

In today's dynamic digital landscape, agent onboarding isn't just a step—it's the foundation upon which exceptional customer service is built. Customer service leaders grapple with not only meeting ever-evolving customer demands but also ensuring every new agent is equipped to handle them from the outset. This places agent evaluation and an effective agent onboarding process at the forefront of achieving quality assurance. How does one navigate these complexities? The lessons from ClassPass, a prominent fitness subscription platform, offer invaluable insights. 

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Discover how ClassPass’s adept approach to agent onboarding, coupled with rigorous agent evaluation, provides a roadmap for embedding customer service quality assurance right from the start. Drawing from insights gained through an interview with Amy Fleming, Manager of Education and Quality Enablement at ClassPass, we will examine how their structured and condensed learning cycle between QA evaluations and feedback/education sessions during the first 60 days of an agent’s tenure has been a recipe for success for ClassPass, enabling new agents to hit the ground running to drive impact on the customer experience faster. 

Transforming Quality Assurance: A Catalyst for Agent Onboarding

The evolution of Quality Assurance (QA) from a simple role of monitoring to a strategic driver of business decisions is essential for scaling support teams successfully. Amy Fleming, in her journey with ClassPass, demonstrated how this transition could bolster the entire customer support framework. She accentuated, "Our vision wasn’t just about checking the quality boxes but making quality a pragmatic, invaluable asset." To illustrate its transformative power, Amy often collaborated with leadership by sharing customer insights, specifically focusing on feedback related to products and policies that the QA team was able to glean through its thoughtful QA scorecards and root cause workflows. 

A poignant example is the customer feedback the Quality Assurance team surfaced about ClassPass’s fee waivers. Customers were penalized for missing or canceling reservations at the eleventh hour. Although ClassPass empathized with life's unpredictability and occasionally waived these fees, the process required customers to engage in prolonged interactions with support agents. By spotlighting this customer pain point, Amy championed a process overhaul, simplifying the waiver experience for users.

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This triumphant revamp showcased to leadership the dual significance of both Support and Quality/Education. Their intertwined roles, when driven by insightful quality assurance, could amplify business outcomes substantially.

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ClassPass’s story underscores a pivotal lesson for QA leaders: Quality assurance isn't just about maintaining standards, but actively translating those insights into pivotal business decisions. This proactive approach to QA was foundational in shaping their agent onboarding process. For businesses aspiring for excellence, there’s no overlooking the profound influence of a QA-driven strategy, harmonizing customer satisfaction with business growth.

Fostering Agent Growth from the Get-go: The Power of Proactive  Evaluation

When focusing on agent growth, ClassPass realized a crucial strategy was to give priority to evaluating and grading new agents rather than focusing equally on more experienced ones. Amy emphasized that their aim was to "identify and correct bad habits from the start."

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To implement this, Amy and her team introduced ticket automations that directed a larger share of tickets assigned to new agents to the team’s graders on a weekly basis. By dedicating more attention to grading for these newer agents, they could focus on identifying and rectifying negative behaviors in their early stages. This approach allowed them to steer clear of overburdening their graders, as they didn't spend valuable time allocating an equal amount of effort to higher-tiered agents who had already met growth benchmarks. This proactive strategy is effective in preventing the development of undesirable habits that could become deeply ingrained over time.

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For leaders looking to drive excellence in their agent onboarding process, ClassPass offers a valuable lesson: integrate robust quality evaluations from the very beginning. By doing so, you set clear expectations, offer real-time feedback, and prevent the onset of poor habits. This not only ensures that agents are equipped with the right skills and mindset from the outset, but also translates to enhanced customer experiences and operational efficiency. As you map out or refine your agent onboarding strategies, prioritize a proactive approach to quality evaluation – the dividends, both immediate and long-term, are well worth the investment.

Clear Growth Paths and Achievement Recognition

In addition to more grading for newer agents, ClassPass also found that a clearly defined growth plan could play a vital role in motivating new agents and setting clear expectations for them. ClassPass put in place a growth plan that provided agents with set targets to aim for, outlines of these expectations, and offered distinct QA benchmarks as they progressed. This method not only brought clarity to agents’ individual goals but also fostered a sense of accomplishment when agents achieved these goals and were subsequently rewarded with added responsibilities and title changes.

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As agents move through their initial 60 days, they should have access to their own Quality Dashboard. This enables them to monitor their progress and feedback over time. Amy and her team pinpoint specific quality indicators at designated stages during the agent's onboarding process to gauge whether their quality level, in addition to other efficiency metrics, aligns with the standards needed for advancement to a higher support tier.

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Research by MaestroQA has demonstrated that granting agents insights into their performance fosters a stronger sense of ownership over their career paths. Comprehensive KPI leaderboards can also introduce an element of gamification or healthy competition among colleagues, leading to improved agent performance and a focus on personal growth.

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Amy's perspective underscores the connection between broadening skill sets and recognizing the significance of quality. “It's not just about maintaining the current state; rather, it involves actively seeking opportunities for growth that enhance both individual skills and overall quality standards.”

Agent Performance Metrics for Upskilling Success

ClassPass employs performance data as a yardstick to determine an agent's readiness for upskilling. This method guarantees that agents acquire necessary skills before progressing to the next level of their career advancement. Making decisions based on performance not only establishes tangible objectives for agents to strive toward but also boosts their engagement and motivation.

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According to Amy, "It's vital to concentrate on improvement within a specific timeframe." This focused approach to utilizing performance metrics for upskilling facilitates swift skill enhancement and immediate positive effects on customer interactions. If an agent isn't prepared to transition to the subsequent phase of their support growth plan, this data empowers their leadership to offer precise behaviors to focus on. With the available reporting, they can advise the agent to "prioritize this aspect over the next 30 or 60 days."

Collaboration Driving Agent Growth

To effectively support agent growth during their initial onboarding journey, the focus should extend beyond providing quality and efficiency KPIs. Feedback alone doesn't constitute coaching. In our discussion with Amy, she elaborated on how one significant factor in fostering agent growth was ClassPass's enhancement of collaboration between the quality and education teams. By integrating the roles of education and quality, the company nurtured a cooperative environment that capitalizes on the strengths of both teams. Whenever QA offered feedback to new agents, they concurrently developed team training and updated knowledge bases to enhance agents' QA performance. Drawing insights from Quality, the education team pinpointed where to concentrate their efforts when crafting learning materials. This collaborative approach has proven pivotal in implementing effective growth strategies.

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Fortunately, at ClassPass, this correlation was evident to the leadership. Amy's experience reveals that gaining support from team members and stakeholders wasn't a challenge. There was enthusiasm for embracing the evolving role of quality, underscoring its vital contribution to driving positive transformations across all aspects. In her words, "...it wasn't difficult to secure that support because as soon as I presented it, there was immediate agreement from both sides, and not just agreement, but also eagerness."

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The integration of quality assurance and education isn't just a collaboration; it's a partnership that can redefine agent onboarding success. Organizations seeking to amplify their agent growth strategies should prioritize this dual-focused approach, leveraging both feedback and instructional insights. The combined power of these teams can be the game-changer in crafting an unparalleled agent onboarding experience.

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ClassPass's innovative approach to agent development, fueled by collaboration between quality and education teams, serves as a powerful example for companies aiming to enhance their customer support strategies. By prioritizing QA performance during the crucial initial period and leveraging technology, businesses can achieve customer-centric growth that benefits both agents and customers alike. As the landscape of customer support continues to evolve, embracing the lessons from ClassPass can lead to improved customer experiences and business success.

Want to learn more?

For a deeper dive into these topics, we recommend watching the full recording of our webinar with Classpass or joining our upcoming webinars on the future of customer experience. Your participation is greatly appreciated, and we look forward to engaging in more insightful discussions in the future. If you're not already familiar with MaestroQA, don't hesitate to request a demo today!

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Sentiment analysis has emerged as a pivotal topic in the realm of customer support interactions, sparking intense conversations among industry professionals. As CX (Customer Experience) and QA (Quality Assurance) practitioners, it's crucial for us to approach this technology with a discerning eye, understanding both its potential benefits and challenges. We recently hosted a webinar discussion with CX leaders aiming to shed light on these important questions, fostering an environment of critical thinking and innovative problem-solving. In this blog, we delve into the key takeaways from this discussion, offering practical insights to effectively integrate sentiment analysis into QA practices.

"Sentiment analysis is something that's coming up so much in our conversations with customers & potential customers. It's the type of topic that is being thrown around so much on the internet and by different folks and it's a very sexy idea." - Vasu Prathipati, CEO & Co-Founder, MaestroQA

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Wide Adoption and Implicit Detection 

Sentiment analysis has gained popularity due to its ability to analyze sentiment across a high volume of conversations. Unlike traditional customer satisfaction (CSAT) surveys, sentiment analysis offers implicit detection of customer sentiment without the need for explicit surveys. This wide adoption provides valuable insights into customer interactions.

"Sentiment analysis could be on 100 percent of conversations and it's implicitly detecting what is the customer experience sentiment versus asking for an explicit survey." - Vasu Prathipati, CEO & Co-Founder, MaestroQA

Enhancing Quality Assurance Efforts 

One of the main motivations for exploring sentiment analysis is to augment QA programs without significant increases in individual grader headcount. By leveraging sentiment analysis, companies can gain deeper insights into customer support interactions, even when QA resources are limited. It offers the potential to scale QA efforts and derive valuable analytics from a larger volume of data.

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With MaestroQA, teams can comprehensively analyze 100% of interactions for negative sentiment using an omni-channel transcription tool. Through transcribing all voice interactions, teams can construct AI classifiers and Smart attributes based on keywords. These conversation analytics are completely customizable to accommodate the specific needs of the business.

"The biggest pushback that I hear from our customers is, 'Hey, we love Maestro. We plan on scaling the team, but we can't scale the QA program in terms of headcount proportionately. What kind of technology and AI and stuff can you use to help us get more in analytics without having to scale the QA teams headcount?'" - Vasu Prathipati, CEO & Co-Founder, MaestroQA

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Third-Party Tools and Open Source Solutions 

Many companies, (including MaestroQA, at the moment) utilize third-party tools to power their sentiment analysis capabilities. Industry giants like Amazon and Google offer pricey sentiment analysis APIs that leverage machine learning models. Additionally, open-source technologies have emerged as cost-effective and potentially improved options for sentiment analysis.

"Most people are using third party technologies to power their sentiment. We're evolving our sentiment analysis at MaestroQA. We use a hybrid of multiple tools to provide our sentiment analysis and we're working on transitioning towards an open-source model. The benefit of that is we can do it at a tenth of the cost, so we can make it a lot more affordable for our customers." - Vasu Prathipati, CEO & Co-Founder, MaestroQA

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Use Cases and Nuances 

Sentiment analysis can be applied to various use cases, such as measuring positive or negative sentiment in agent and customer emails, chats, or phone calls. Each use case has its own nuances, and sentiment analysis should be tailored accordingly. As every business is different, "positive sentiment" can mean one thing for one company and something completely different for another. Once you've determined what type of sentiment you are looking for, positive sentiment may be more relevant in evaluating agent performance, while negative sentiment can help identify areas for product improvement or potential process & policy adjustments.

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For example, using MaestroQA, Novo, a leading mobile banking platform for small businesses, was able to uncover an issue that was occurring with mobile check deposits, where specific checks from the California State Government were being repeatedly rejected by their banking software. With the use of AI Classifiers, Marcus will be able to build reports using keywords associated with the "check rejection" issue to determine its frequency, identify which agents are skilled at handling these situations, and assess the negative sentiment resulting from these customer interactions. MaestroQA's highly accurate transcriptions will even enable the Classifier to listen for key phrases such as "check rejected, California, or deposit error" to identify phone calls discussing this particular issue. Novo’s QA team can also pull in other metadata from his HelpDesk to identify tickets where a customer started the conversation upset but was satisfied with the agent's response or conversations where a customer initially felt fine but became upset due to the agent's service or policy.

"You have to think about your actual conversation flow and where does it make sense to actually try and detect it. When applied critically, sentiment analysis can uncover hidden trends you wouldn't see." - Vasu Prathipati, CEO & Co-Founder, MaestroQA

Accuracy and Actionability 

Ensuring the accuracy of sentiment detection is essential. If your sentiment analysis is yielding high overall positive sentiment scores, its actionable value should be questioned. Metrics that provide actionable insights should be prioritized, enabling targeted coaching and informed decision-making. 

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Our customers are harnessing the power of our AI-assisted sentiment analysis to develop more refined and actionable metrics, which in turn provide a detailed overview through a Targeted QA heatmap. For instance, one company identifies tickets with a "low empathy response," a customized Key Performance Indicator (KPI) established using MaestroQA's sentiment analysis and AI classification tool known as AI Classifiers. The concept of "low empathy response" involves detecting instances where a customer expresses negative sentiment and receives a poorly tailored macro-like response from the agent. When agents fail to provide personalized or appropriate reactions to customers' negative sentiments, they miss the opportunity to connect effectively with the customer, potentially exacerbating the negative experience.

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By unearthing this particular metric, the team managed to delve deep into targeted QA, uncovering valuable learning and coaching prospects for their agents. This proactive approach aims to mitigate such interactions in the future and enhance overall customer experiences.

"Did you get a new perspective that you can consider internally to have smarter discussions internally?" - Vasu Prathipati, CEO & Co-Founder, MaestroQA

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Machine Learning and Agent KPIs 

During the discussion, opinions were divided on using machine learning-based sentiment analysis as a key performance indicator (KPI) for measuring agent performance. While some participants (47% according to a poll) saw potential in leveraging machine learning for identifying lower-performing agents or areas of concern, others expressed concerns about the explainability and transparency of such metrics (41% said no and 11% were undecided).

“I think a really important consideration when we're talking about, ‘Hey, do we wanna use this as a way to measure agent performance?’ Well, it's machine learning. If someone on your team says, ‘Hey, why did I get this score? Why is this my score?’ How comfortable do you feel explaining this?” - Vasu Prathipati, CEO & Co-Founder, MaestroQA

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The Black Box vs the Transparent Box

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At MaestroQA, we adopt a cautious approach to Sentiment Analysis and AI implementation to maximize accuracy and reliability of results. Amidst the numerous claims of software offering 100% automated QA for customer interactions, a crucial detail often remains unaddressed. The source of this data remains ambiguous: Is it derived from an undisclosed black box of sentiment analysis or an internally developed Auto QA system that's uniformly applied across all QA clients?

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At MaestroQA, we are committed to dispelling this opacity. Through our MaestroQA AI Classifiers, QA teams gain the ability to establish tailored customer Auto QA KPI metrics (a transparent box). This empowers you and your team to precisely define positive and negative customer sentiment within the context of your unique business and outline benchmarks for superior agent performance that align with your customer expectations.

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The development of these AI classifiers occurs collaboratively with your designated MaestroQA Customer Success Manager. By deconstructing the specific customer pain points you intend to address, you and your representative collaboratively construct a logical framework within the MaestroQA tool. This framework facilitates the comprehensive scanning of 100% of support tickets to identify qualifying attributes. The outcome is then presented to you on a Performance Dashboard, displaying the percentage or total count of tickets that adhere to this established criteria.

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What sets our sentiment analysis and auto QA apart is its genuine relevance to your business. Through customization, it becomes a tool that resonates meaningfully within your unique operational context.

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Bridging the Divides 

In conclusion, sentiment analysis shows promise in enhancing customer support quality assurance efforts by providing deeper insights and analytics. However, it is crucial to carefully evaluate use cases, choose appropriate tools, and ensure the accuracy and actionability of sentiment analysis results. Additionally, using sentiment analysis as a key performance indicator (KPI) for agent performance should be approached cautiously, taking into consideration the transparency and explainability of machine learning-based metrics or the value of sentiment analysis as a tool for targeted manual quality assurance.

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The community discussion on sentiment analysis, as part of our bi-monthly CEO/CX: Strategy Chats, sparked valuable insights and discussions among participants, enabling them to consider new perspectives and challenges. As the field continues to evolve, staying informed about the latest developments, evaluating the suitability of sentiment analysis for individual businesses, and making informed decisions based on specific use cases and requirements are essential.

Want to learn more?

For a deeper dive into these topics, we recommend watching the full recording of our Strategy Chat with MaestroQA CEO & Co-Founder, Vasu Prathipati, or joining our upcoming webinars on the future of customer experience. Your participation is greatly appreciated, and we look forward to engaging in more insightful discussions in the future. If you're not already familiar with MaestroQA, don't hesitate to request a demo today!

Customer experience (CX) is at the heart of today’s competitive business landscape, shaping not only brand perception but influencing long-term loyalty and growth. MaestroQA’s recent CX Summit: The Art of Conversation brought together industry leaders, experts, and practitioners to explore the future of Quality Assurance (QA) within this critical domain. 

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From the role of AI in shaping customer interactions to the transformative impact of targeted QA approaches, the summit uncovered several trends that are redefining how businesses approach customer support, quality assurance, and agent performance optimization.

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In this blog, we will delve into the six biggest tech trends revealed through the CX Summit Workshops which featured win stories and challenges from 50+ companies and experts in QA and CX. These trends point to one overarching theme: businesses are looking for ways to unlock the goldmine of data and insights inside their customer conversations and interactions. They want to take their CX strategies to new heights and gain an edge over the competition. 

Trend 1: Targeted QA for Proactive Insights 

One trend that dominated discussions at the CX Summit was the growing use of Targeted QA. This practice takes QA beyond random sampling, aligning it with your business’s highest priority customer touchpoints, processes or policies to reveal deeper insights into specific business problems and opportunities. 

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Why is it so effective? It's all about precision and focus. With Targeted QA, companies can proactively address issues and optimize resources, ensuring the best possible customer experience. For example, one successful financial tech company shared their unique approach to Targeted QA. They utilize Targeted QA  “sprints” to quickly analyze the quality of their product launches. Instead of waiting for problems to arise, they align Targeted QA with their product launch schedule to ensure agents are well-prepared and equipped with the necessary resources and training to ensure the rollout goes smoothly. 

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“By concentrating on high-priority customer touchpoints and specific business problems, targeted QA gains deeper insights and uncovers timely and actionable opportunities for improvement.” - Group 6

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Another company shared how they wanted to reduce cost per contact and average handle time (AHT) was a major contributor to this. After implementing Targeted QA workflows to automatically surface and evaluate tickets with high AHT, they discovered that a long verification process was a primary driver in AHT so they were able to take actions to simplify this process, which effectively resulted in reduced AHT. 

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The shift towards targeted QA is not merely a trend, it’s an evolution in QA practices that is proving to be instrumental in optimizing resources, focusing on critical areas of improvement, and enhancing overall customer experiences.

Trend 2: Empower Agents with Direct & Actionable Feedback 

In the world of customer support, the role of Quality Assurance (QA) is undergoing a remarkable transformation. It's no longer just about evaluating agent performance; it's about nurturing growth and excellence. The discussions at the CX Summit highlighted this inspiring trend — with many leaders pointing out that they are reframing QA from being perceived as the "bad guy" to becoming a genuine partner in agent development.

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"Making sure the agents know we're here to help and not to criticize. The ultimate goal is to offer the best customer experience possible by enabling our agents to perform their best.” - Group 7

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This trend is creating a culture where feedback is not just seen as a critique but as a catalyst for improvement. The presentations among industry peers at the Summit demonstrated that the most effective QA teams were those that directly linked QA outputs to agent development and growth strategies.

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For example, one company shared that by implementing scorecards targeting new hires, QA helps catch, coach, and correct bad habits early on. This proactive approach nurtures a culture of high-quality customer interactions from the very outset of an agent's tenure.

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Another company shared how they use quality data and clear benchmarks to provide agents with a roadmap for career development. By setting expectations and using QA scores to verify readiness for promotion and upskill training, agents are empowered with a clear and motivating growth path.

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A company with a 100% remote support team also emphasized using QA to help agents feel supported and empowered. They shared how collaboration and trust was central to their success. By having team leads jointly shape the scorecard evaluation criteria with feedback from agents not only created more buy-in but paved the way for a more impactful coaching program. 

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What made this collaborative process even more effective is the utilization of tools like MaestroQA. With the ability to add examples to coaching sessions, agents are equipped with a laser-sharp focus on improvement areas and a better understanding of success criteria to implement feedback quickly and effectively. This targeted approach has led to increased engagement for both internal and BPO agents and team leads. 

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"Having a structured coaching program within MaestroQA has been a huge win for both internal and BPO agents and TLs. Increased engagement due to direct and targeted feedback." - Group 3

Trend 3: Data-Driven Insights to Enhance Agent Performance 

In the ever-evolving world of customer support, the saying “What gets measured gets managed" holds more relevance than ever. The CX Summit discussions spotlighted another trend that’s reshaping how companies approach agent performance measurement: the use of data-driven insights to propel agents and teams towards enhanced performance.

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Central to this trend is the transformation of agents into active participants in their own professional growth. We heard several people at the CX Summit share how providing agents with direct access to QA grades, feedback, and performance metrics from their own dashboard has ignited a sense of personal ownership over their growth journey. This not only boosts internal engagement, it also fosters a heightened sense of accountability. 

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Another person pointed out the impacts of using data and dashboards to spark a “healthy competition” internally. By providing visibility into performance metrics and benchmarks, agents and teams can track their progress, identify areas for improvement, and celebrate milestones. As a result, team members are more connected to their performance and are motivated to continually raise the bar, culminating in an environment of self-driven excellence.

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“We started comparing team and individual performance, it sparked healthy competition internally which drove up agent morale and engagement” 

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Lastly, we also saw an insightful example of how coaching data surfaced through QA can be a highly useful metric to track. One company discussed how they use MaestroQA’s platform to analyze the correlation between the number of coaching sessions led by managers and fluctuations in Customer Satisfaction (CSAT) scores. This correlation forms the basis of new metrics, opening doors to deeper insights into how training and coaching influence core metrics like CSAT and QA. It's not just about the numbers; it's about the impact. QA and CX leaders were most excited about the ways these insights gave them the datapoints they needed to create and propose an on-going roadmap for agent and call center training and coaching that actually accelerates customer satisfaction in a measurable way.

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Trend 4: Rise of AI-Assisted CX Solutions

CX technology is undergoing a huge transformation, largely driven by the rise of AI. As we delved deeper into discussions at the CX Summit, it became clear that AI's potential is immense, however, finding the right balance between AI and human intervention is crucial for achieving optimal results. 

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One sentiment shared broadly across people at the Summit was that AI should not be seen as a replacement for human agents but as a complementary tool that enhances efficiency and effectiveness.

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A prime example of this is the integration of AI in real-time assistance and chatbots. Rather than displacing human agents, AI is seen as a tool to ensure human intervention is concentrated where it's most valuable. A common strategy shared was leveraging AI-driven chatbots to “deflect volume”  by handling routine queries and straightforward tasks, freeing up skilled agents to tackle more complex and nuanced customer issues. Other ideas companies are looking at include the use of generative AI for suggested replies for agents and conversation summarization for escalations. 

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As one group aptly put it, "Don't expect AI to fully replace QA, but to complement it in a directional manner." The prevailing sentiment among customers was that while AI could provide insightful trends at scale, it still requires human intervention to make informed decisions and interpretations.

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"Don't expect AI to fully replace QA, but to complement it in a directional manner." 

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Research into AI's capabilities to identify trends at scale, whether in agent performance or policy adherence, emerged as a focal point. Customers expressed a desire for AI to guide their QA efforts, pointing out areas that demand attention and strategic intervention. While confidence in AI's ability varied, most attendees acknowledged the necessity of human oversight to ensure AI-generated insights align with the business's values and objectives. So many group presentations concluded that using QA to monitor AI accuracy was essential to avoid potential legal or reputational damage that could come from an AI chatbot responding to customer questions. 

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“QA on chatbots will be critical” - Group 6

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Trend 5: Emergence of Auto QA and "Hot Spots"

In the pursuit of enhancing quality assessment practices, the concept of Auto QA and the identification of "hot spots" emerged as a driving force. By marrying various metrics and harnessing AI capabilities, QA teams can proactively identify friction points and high-impact areas that warrant immediate attention, enabling businesses to swiftly adapt to evolving customer needs.

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The transformation brought automated quality metrics cannot be overstated. Shifting from random sample assessments to analyzing 100% of support interactions empowers QA teams to extract valuable insights from every customer interaction. 

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“We want the ability to see trends at scale to know where to target our QA efforts” - Group 6

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However, a recurring sentiment was the acknowledgment that not all AI-driven solutions are equal. As one group put it, "bad AI is worse than no AI." While automated solutions hold immense potential, their accuracy and reliability remain crucial. This stance underscores the importance of combining AI-driven insights with human expertise to ensure that the solutions' outputs align with the company's values and desired customer experience.

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An overarching theme within this trend was the desire to extract meaningful trends at scale, aiding in the strategic targeting of QA efforts. Whether it's identifying areas of improved agent performance or pinpointing policy-related concerns, customers expressed a need for AI to guide their QA strategies. This sentiment underlines the evolving role of QA teams from reactive evaluators to proactive enhancers of customer experience, facilitated by the insights generated from AI-assisted analytics.

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Trend 6: The Next Wave of CX Analytics: Blended & Tailored to Fit Business Priorities

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This exploration of AI-powered CX operations also shed light on another big trend discussed at the summit: the need for highly custom metrics and KPIs to deliver enhanced insights. 

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“Sometimes driving toward ‘Business level metrics’ is not in alignment with agent level experiences”

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Several companies pointed out that blending metrics is needed to bridge the gap between leadership's priorities and QA teams' coaching needs. It's about transforming data into actionable dialogue. One presentation acutely pointed out the need to “blend metrics” like NPS, CSAT, AHT with metrics that QA teams or CX management needs to coach to (FRT, hold times, sentiment, tone, empathy) in order to impact NPS, CSAT, etc. This approach ensures that data is not just numbers but a tool to enhance customer interactions. 

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One presentation noted that traditional productivity metrics like AHT and FCR lack the context needed to make actionable decisions. For example, they were seeing a spike in AHT and normally they would attribute this to an agent performance issue, but the customer was able to work with MaestroQA to use targeted QA and root cause analysis to get more contextual data points and insights to understand that the issue was actually due to an issue with their return policy. 

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The next wave of QA insights will bring a new dimension to CX analytics, going beyond standard KPIs metrics to gain a deeper understanding of the customer sentiment and root the cause behind adherence issues, agent performance problems, or policy/process issues. 

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Here are a couple notable examples of companies already moving in this direction: 

• Overall Advisor Score (OAC) - One customer is exploring the use of an Overall Advisor Score (OAC) to measure incorrect refunds, the score is calculated automatically by looking at attendance, CSAT, and AHT (Average Handle Time). Initially, calculating this metric posed a challenge and required the use of spreadsheets. However, the company has already witnessed some degree of success with this approach with their new automated approach. They have found that it enables them to compare vendors using a single score that incorporates multiple metrics.
• Triage Rate - Another company shared their implementation of a Triage Rate, a metric designed to evaluate the performance of AI during routing. This smart approach allows companies to measure how AI is performing and identify areas for improvement.

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Conclusion

The trends emerging from the Summit point to an industry that's not just responding to change but shaping it. From Targeted QA to AI's complementary role, from empowering agents to the emergence of custom metrics, the trends speak of a world where customer interaction is an evolving dialogue, rich in insights and opportunities.

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Businesses are no longer just serving customers; they are engaging with them, learning from them, and growing with them. The Summit was a reminder that in the world of CX, every voice matters, every interaction counts, and every insight is a step towards a more connected, responsive, and empathetic business landscape.

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Want to learn more?

Check out the full recording of the Art of Conversation: Keynote Address or sign up to attend our next CX Summit, and if you would like to learn more about what MaestroQA can do for your business, please request a demo today.

A Comprehensive Approach to Unleashing the Power of Targeted QA

Traditionally, QA has been conducted through random sampling, where agents' performance is evaluated against a set of indicators. However, a more focused approach called Targeted QA is gaining traction in the industry. While random QA has long been the norm, targeted QA is emerging as a powerful approach to address specific issues, identify root causes, and achieve tangible results. In this educational blog post, we will explore the concept of targeted QA, its benefits, and provide practical insights from an interview with Michelle Vanchieri, Director of Customer Success at MaestroQA. By following these guidelines, QA teams can enhance their practices and drive business impact.

Defining Targeted QA and Random QA

Random QA has been the primary method for evaluating agent performance for many years. It involves the random selection of tickets from various channels and the assessment of quality based on predetermined indicators. In contrast, Targeted QA goes beyond random sampling and focuses on addressing specific business problems or areas of improvement by delving deeper into particular situations or critical issues. Its aim is to understand the underlying causes of problems by analyzing tickets with specific criteria or metrics. For instance, it may involve surfacing tickets based on customer satisfaction (CSAT) scores or average handle time and grading them against more tailored rubrics. While random QA emphasizes agent performance, targeted QA seeks to obtain insights into specific areas of concern or improvement for the overall business. Michelle explains, "Targeted quality is more about proactively addressing a problem and conducting quality assessments to understand its root cause, as opposed to random quality, which mainly revolves around evaluating agent performance through random sampling."

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Implementing Targeted QA

QA teams often employ targeted QA when there is a problem that needs to be addressed or an opportunity for enhanced efficiency and cost savings. By aligning targeted QA with business-critical objectives and metrics, organizations can optimize their quality efforts. For instance, targeted QA can be utilized to address customer churn by providing insights into its underlying causes and strategies for reducing it. It can also be implemented in a positive context, such as analyzing successful customer win-backs to refine agent training and improve customer retention efforts. Michelle emphasizes, "It's often about identifying and fixing issues that are deemed business critical. Even if there isn't a problem, there are always ways we can enhance our performance."

Benefits of Targeted QA

Targeted QA offers numerous benefits to organizations. Firstly, it aligns quality initiatives with business objectives, ensuring relevance and maximizing impact. By focusing efforts on areas of concern, targeted QA drives meaningful changes that directly impact the bottom line. Secondly, targeted QA provides an opportunity for data gathering and insights generation. Michelle emphasizes, "When you start with a business problem and implement targeted quality measures, the information gathered becomes highly valuable." By delving deep into specific problems or opportunities, organizations can make informed decisions and drive continuous improvement, not only in agent performance but also in product, process, or policy changes. Lastly, targeted QA optimizes resource allocation by directing time and effort where they matter most, leading to improved efficiency and effectiveness within the CX team.

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Impact of Targeted QA

When considering the impact of targeted QA, it is crucial to assess its effects on three levels: the business, the agents, and the QA team. At the business level, targeted QA directly addresses critical issues, enabling organizations to improve key metrics, reduce costs, and enhance customer satisfaction. By leveraging insights from targeted QA, businesses can make informed decisions and take proactive measures to drive positive change.

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For agents, targeted QA presents an opportunity for growth and development. By focusing on specific aspects of their performance, agents receive feedback tailored to their strengths and areas for improvement. This personalized approach enhances agent training and empowers them to consistently deliver exceptional customer experiences. As Michelle wisely stated, "It can impact agent growth in a more holistic manner, not just focusing on individual agents, but as a team of agents. If we understand what drives our DSAT and we can change the way in which we interact with customers to create better experiences, then as a whole, our agent team is growing and learning. Similarly, we can make their jobs easier if we uncover what is driving up our efficiency that's within the agents' control and coach them on how to improve." 

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From the QA team's perspective, integrating targeted QA into the existing quality program requires careful consideration in terms of bandwidth. While random QA remains important, it is often recommended to adopt a hybrid approach that combines both random and targeted QA. This approach allows organizations to gain valuable insights into agent performance while also addressing specific business objectives. By strategically managing random QA, such as prioritizing low-performing agents, teams can create the necessary space to engage in targeted QA without overwhelming their resources. Michelle suggests starting with agile deployments of targeted QA, such as running focused sprints, which can provide valuable information without requiring a complete overhaul of the quality program. She emphasizes, "This doesn't need to be running targeted QA for a whole quarter. You can do a sprint on DSAT for two weeks and gather a statistically significant number of tickets to understand the drivers. So when it comes to greater bandwidth, I always try to caution that we don't have to reinvent our entire quality program. Can we be agile in the way we deploy it to gather a little bit of information?"

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Tips for Implementing Targeted QA

To embark on a successful targeted QA journey, starting with a clear focus is vital. Michelle advises, "Begin with something that is more business critical or holds importance for the leadership." Defining a specific objective, such as reducing customer churn or improving satisfaction rates, ensures that targeted QA efforts directly contribute to the organization's goals.

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It is then necessary to select relevant criteria. Michelle suggests developing customizable rubrics that capture key behaviors or metrics. She explains, "Tailor the evaluation criteria to the specific problem or area of improvement to gain more insights."

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Starting small, iterating, and improving are key aspects of the process. Michelle advises, "Implement targeted QA in short sprints to gather a little bit of information at a time." This iterative approach allows teams to collect data, analyze results, and continuously enhance their targeted QA process.

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Challenges may arise when implementing targeted QA. Michelle advises, "Review your selection criteria and refine your approach accordingly." By gathering feedback and making necessary adjustments, teams can optimize the impact of targeted QA and overcome any obstacles.

Utilizing Workflow Automations, Customizable Rubrics, and AI Classifiers in MaestroQA

MaestroQA provides valuable features to streamline and optimize targeted QA initiatives. Workflow automations enable teams to automate ticket selection based on specific criteria, ensuring efficient resource allocation. Customizable rubrics allow the creation of tailored evaluation criteria that align with the targeted areas or issues, ensuring that the evaluation process focuses on desired outcomes. AI Classifiers can be utilized to analyze data, identify patterns, and gain deeper insights within targeted QA evaluations.

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Setting up a targeted QA program in MaestroQA follows a structured approach. Michelle provides insights into the process, stating, "The first step is to identify the problem & the next step would be to build out the rubric." The rubric should focus on collecting specific data related to the targeted issue, such as the drivers of the problem or relevant categories. MaestroQA offers rubric options, including checkboxes, to effectively narrow down the root causes.

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Workflow automations play a crucial role in streamlining and optimizing the process. Michelle explains, "Typically, when we're doing targeted quality, we're focusing on specific types of tickets. In Maestro, you can use ticket attributes to specify which tickets to evaluate, such as DSAT tickets or tickets with specific tags, narrowing down the scope to the desired ticket types." By leveraging ticket attributes, teams can ensure that graders receive the appropriate tickets for evaluation, optimizing their efforts.

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Additionally, Michelle highlights the future impact of AI Classifiers in targeted QA. She explains, "Identifying the problem is where AICs or conversation analytics come in, and then deploying quality to address it by thoroughly examining those tickets." AI Classifiers enable teams to identify patterns and potential issues across 100% of conversations. This data-driven approach empowers organizations to proactively address issues, highlighting areas for targeted QA and improvements.

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As organizations adopt MaestroQA and its capabilities, they can efficiently structure and execute targeted QA programs. The tool's robust features enable teams to define rubrics, automate workflows, and leverage AICs for actionable insights. By utilizing MaestroQA's functionalities, QA teams can optimize their targeted QA initiatives and drive continuous improvement in their customer service operations.

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Drive Business Success through Targeted QA

Implementing targeted QA is a game-changer for businesses looking to address specific problems, drive improvement, and make quality a business-critical function. By following the insights and advice from Michelle Vanchieri, QA teams can define clear objectives, select relevant criteria, and align targeted QA efforts with organizational goals. With a focus on continuous improvement and agility, targeted QA can deliver tangible business benefits and enhance customer satisfaction.

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Want to learn more? 

To learn more about Targeted QA, listen to our recent webinar with luxury bedding brand, Brooklinen, where Senior Associate of Customer Experience, Corinne McClure, delves deeper into the practical implementation of targeted QA, shares her team’s best practices, and provides actionable tips to ensure success. By leveraging the capabilities of MaestroQA, QA teams can effectively structure and execute targeted QA programs, optimizing their quality assurance efforts and driving continuous improvement in their customer service operations. Request a demo today!

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Maintaining a 90% CSAT score sounds good, but what about the remaining 10% of dissatisfied customers?

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Analyzing customer DSAT (dissatisfaction) can provide a treasure trove of insights for improving the customer experience. However, knowing where to begin can be challenging when you’re dealing with hundreds or thousands of unhappy customers. MaestroQA is making DSAT analysis easier with our latest feature: DSAT Analysis Dashboard.

What is DSAT Analysis (& Why is it Important)?

DSAT analysis is the process of collecting, aggregating, and reviewing data from support tickets that contain low CSAT scores. What is a “low” CSAT score? On a five-star scale, anything other than a four or five-star rating could indicate dissatisfaction. Does this mean that all three-star reviews contain negative sentiment? Probably not, although it’s fair to say most CX managers aim for four or five-star experiences.

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As pointed out in our previous article about DSAT analysis, customers typically express dissatisfaction with one or more of the following:

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• Customer support issues (long wait times, poor communication, etc.)
• Product or service issues (defective packaging, missing parts, etc.)
• Policy issues (unreasonable return policies, pricing concerns, etc.)

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Why aren’t more CX leaders focused on their DSAT scores? For starters, analyzing tickets from unhappy customers isn’t the most pleasant way to spend your time. In addition, some customers are simply unreasonable, which presents credibility issues. And, since few ticketing systems offer prebuilt DSAT analytics, preparing the data can involve time-consuming data exports and spreadsheet manipulation. 

Automatically Identify DSAT Tickets from CSAT Surveys

Our DSAT Analysis Dashboard in MaestroQA provides an automated way to identify and aggregate tickets from unhappy customers—without manually exporting data from your helpdesk. CX leaders can gain access to multiple DSAT reports and charts from a single view, including the total number of:

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• Tickets available
• Tickets with CSAT
• Tickets with DSAT
• DSAT ticket trends by week

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Leverage DSAT to Learn from Your Least Satisfied Customers

Regularly reviewing DSAT tickets is a key step for ensuring a healthy QA program—especially when it comes to offering helpful feedback to agents. With the DSAT Analysis Dashboard from MaestroQA, managers can leverage DSAT data by using QA DSAT tickets to determine root cause and coach agents on areas to improve customer satisfaction. Since MaestroQA's DSAT Analysis Dashboard is integrated with QA and Coaching flows, leaders can identify areas of dissatisfaction and seamlessly review or coach to those tickets.

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Need to drill down into a specific ticket for a more in-depth view? MaestroQA makes it as simple as clicking a link to view the ticket in the MaestroQA dashboard. Then a user could grade the ticket using a rubric or coach an agent.

Refine the Customer Experience with DSAT Insights

MaestroQA slices your DSAT score by channel, tag, ticket form, and public comment buckets, which makes it easier to perform root cause analysis. Filter your data by agent, rubric, group, and other criteria to quickly identify your biggest opportunities for improvement.

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Start Tracking Your DSAT Scores with MaestroQA

Need an easier way to manage, track, and leverage DSAT data? The DSAT Analysis Dashboard from MaestroQA provides an intuitive, automated solution for turning dissatisfaction into a growth opportunity for your CX team.

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Learn more about the DSAT Analysis Dashboard or request a free demo of MaestroQA.

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In the world of customer service, delivering an outstanding customer experience is paramount. Quality assurance plays a crucial role in ensuring consistent service quality and adherence to company standards. Recently, MaestroQA had the opportunity to speak with Sydney, an experienced QA professional, to learn about her journey in QA and her role at Angi’s List, Handy, and Home Advisor (now Angi). Through our conversation, Sydney shared valuable insights on the transformative power of revamping QA processes from grading to growth.

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Sydney's journey in QA began at Patagonia, a company known for its robust QA program, where she developed a passion for delivering exceptional customer service. She then brought her expertise to Classpass, where she launched a QA program. Sydney's next challenge was at Angi, formerly Angi's List, where she faced skepticism about the efficacy of QA. Undeterred, Sydney reshaped the perception of QA within the company.

Reframing the Perception of QA: QA as a Training Tool 

Sydney encountered the misconception that QA served primarily as a training mechanism. She explained, "If we were seeing an issue with agent handling, the solution was to QA more. And I think the assumption was that because you're giving agents feedback through QA, that they would automatically know by getting more QA what they needed to fix in the interaction." However, Sydney recognized that merely providing feedback without guidance did not lead to improvement. To address this gap, she refined the QA rubrics to target knowledge gaps and areas for agent improvement and introduced greater transparency.

Transparency among graders became a catalyst for change in Sydney's QA journey. By implementing GraderQA, a tool that anonymously regrades QA’d tickets via a benchmark grader for alignment, Sydney eliminated the disconnect between feedback and coaching. This not only increased the transparency amongst the QA team itself, but also let agents know they could expect consistent grading/feedback across the board. She noted, "Instead of having a weekly calibration with our BPO graders, we got rid of calibrations and we started to implement the 'Grade the Grader' workflow." This transparency improved alignment and enabled analysts to understand why their grading differed from the expected standards. It avoided the temptation for graders to only "do it right" during standard calibration, which often led to neglecting these best practices in their day-to-day workflows.

Leveraging Technology: Maestro and Lessonly Integration 

Technology played a crucial role in Sydney's QA revolution. The integration of Maestro's QA platform provided valuable insights and data. Sydney explained, "Once we had data we trusted, we were then able to make an argument for needing to implement more training." To support targeted training, Sydney implemented Lessonly, a learning management system (LMS). This integration allowed the team to send out tailored trainings quickly and gauge agent understanding.

Sydney discovered that coaching was lacking for consistently underperforming agents, as agents only received coaching sessions when they completely failed a QA rubric. She emphasized the importance of coaching consistently, before an agent’s low performance got out of hand, stating, "Because those agents aren't getting zero percent, they're not being coached." To address this issue, Sydney established coaching parameters and introduced coaching forms within the Maestro platform. This increased visibility into coaching sessions ensured agents received the necessary support and feedback to improve.

Strengthening Partnerships with BPOs 

Working exclusively with outsourced BPO agents presented challenges, but Sydney fostered a collaborative partnership. She involved BPO agents in decision-making, addressed their feedback, and demonstrated the value of the "Grade the Grader" workflow. Sydney reflected, "I think they started to view me as a partner with them rather than just someone who was kinda talking down the pipeline, and that got some buy-in."

Sydney's efforts in revamping QA processes have had a tangible impact on Angi. By aligning BPO partners and focusing on QA scores and productivity, the company ensures a commitment to exceptional customer experiences throughout its operations. Sydney emphasized, "QA principles were adopted across all customer support departments, fostering a culture of continuous improvement."

A Testament to the Power of Revamped QA 

Sydney's journey at Angi exemplifies the transformative power of revamping QA processes. By shifting the perception of QA from being solely a training mechanism to a tool for continuous improvement, Sydney has propelled her organization towards delivering exceptional customer service. Through the integration of technology, transparency, and targeted trainings, the future of QA at Angi shines bright.

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Unlocking the full potential of QA requires a shift from mere grading to fostering growth and continuous improvement. Sydney's journey provides valuable lessons and actionable strategies for optimizing QA programs. By rebuilding trust in QA data, implementing targeted training, and emphasizing coaching and development, companies can unlock their QA potential and deliver exceptional customer service. 

Want to learn more?

Check out the full recording of our chat with Angi, and if you would like to learn more about what MaestroQA can do for your business, please request a demo today.

In this blog post, we delve into the world of outsourcing customer support and share valuable insights from industry leader Stitch Fix, an online personal style service with over 3.1 million active users. Our goal is to equip you with the best practices needed to effectively partner with an outsourcing company to scale your customer support. Additionally, we'll discuss the journey toward achieving optimal quality in customer service. Join us as we explore this crucial aspect of business growth.

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Partnering With a BPO: Igniting a Pilot Program to Test Before Committing

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When it comes to finding the right BPO (Business Process Outsourcing) partner for your call center or customer support, it's essential to understand what criteria (technical capabilities, cost, and company values, just to name a few) should be used to make the decision. Stitch Fix faced this challenge when looking for an outsourcing partner for their customer support team due to rapid growth. 

After evaluating a few potential partners, they initiated a pilot program with TaskUs (a leading BPO that provides “outsourced digital services and next-generation customer experience for the world’s most innovative companies”) that included an 8-week ramp-up period to assess the quality of their work and their ability to handle customer issues. 

During the pilot program, Stitch Fix conducted stress tests and early-on calibration sessions by selecting tickets that didn’t require an extensive amount of process knowledge; they were looking for the TaskUs team to exhibit a sense of curiosity, a willingness to learn, and an understanding of what it takes to provide a positive customer experience. Ultimately, they chose TaskUs due to their commitment to engagement and alignment with Stitch Fix's values. Going forward, Stitch Fix is committed to continuing to train and level up the TaskUs team and working with them to fully understand the Stitch Fix business.

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Partnering with a BPO in a Remote Environment: Strategies for Successful Management

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Two years into a successful BPO pilot with TaskUs, the challenge of remote onboarding and training due to the pandemic posed a unique set of issues. “To start,” explained Emily McKee, CX Quality Supervisor, Stitch Fix, “we couldn't have anyone from the internal team fly out and kickstart the training due to the pandemic. That made it extra challenging and caused a disconnect between our team and the BPO.” 

Stitch Fix faced a challenge with tribal knowledge since they didn't have subject matter experts on-site at TaskUs to assist. Initially, they approached the situation by attempting to replicate their internal program with TaskUS but soon realized that it was more about setting expectations and allowing TaskUS to bring their expertise to the table. One example of this was when TaskUS provided Stitch Fix with three graders. The Stitch Fix team tried to onboard them the same way as their internal graders but discovered that their internal graders had years of experience as agents, giving them a wealth of tribal knowledge that the BPO graders lacked. In summary, Stitch Fix learned that collaboration and setting clear guidelines while allowing for flexibility and adaptation were vital to success. 

“Communication was also a challenge; although we had a single point of contact, we needed to work as a team internally instead of silos to ensure we were all on the same page in supporting the BPO and treating them like a partner.” To ensure that they are always putting the customer first, the Stitch Fix team implemented a weekly business review that includes TaskUS, who acts as the voice of the customer. Additionally, Stitch Fix conducts monthly business reviews and calibrations using the MaestroQA platform. These sessions provide them with a platform to communicate and determine areas that require coaching, evaluate grading, and identify training needs for improvement.

Another challenge they confronted early on in the partnership was that their onboarding curriculum needed to be revised. As a result, Emily’s team developed an onboarding program, complete with training and resources, to empower agents to get up to speed quickly on Stitch Fix’s values, products, and processes. This personalized approach helped them promptly fill in any gaps, and the impacts were measurable! 

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Takeaway: Using coaching and resources like the MaestroQA app is an excellent way to empower BPO agents.

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In the end, Stitch Fix learned that they had to personalize their approach with the BPO and keep them top of mind when making business decisions to get the most out of the partnership.

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Partnering for Improvement: The Successful Journey to Quality

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During the initial launch with TaskUs, performance expectations simply included completing a certain amount of audits and participating in a calibration once a week. Stitch Fix saw that a more nuanced shift was needed to gain complete visibility into their BPO's performance and provide clear expectations around agent performance and quality. “When our contract was signed,” said McKee, “there was no quality target set for the TaskUs team, simply an expectation that they would perform well. We saw that we weren’t looking at their Grader efficiency, and we didn’t have goals in place, such as a 15-minute audit expectation.” To better manage Grader efficiency, Stitch Fix began to leverage more of MaestroQA’s key features. One is GraderQA, a workflow designed to provide qualitative feedback to individual graders on their grading performance while enhancing grader speed and efficiency.  

With GraderQA, a benchmark grader is selected; this is typically a member of the QA team that is the designated source of truth (an expert grader well-versed in your company's CX standards). The benchmark grader's key role is to grade the graders.

By utilizing MaestroQA, Stitch Fix not only has full visibility into the performance of their BPO through data-driven reporting, but they can establish efficiency goals for graders, alignment goals for team calibrations, and alignment goals for GraderQA. 

Speaking about data-driving reporting…

McKee shared that one of the key benefits of being able to dive deep into QA insights is that they can now look at quality and CSAT together with their BPO and go deep into their internal agent’s DSAT metrics vs. BPO DSAT metrics and make better-informed decisions on how to improve.

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“It’s great when you have a BPO that is willing to go on this journey with you,” stated McKee. “MaestroQA has helped us with this, and their tools have been instrumental in making our partnership a success.”

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To learn more about what MaestroQA can do for your business, please request a demo today.

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Unlocking the Potential of QA Scorecards for Optimal Agent Performance and Customer Satisfaction

Scorecards are indispensable tools in quality assurance (QA) processes, providing valuable insights into agent performance and driving improvements in customer service. However, to ensure their effectiveness and alignment with organizational goals, QA scorecards need to be regularly revamped and optimized. In this blog post, we'll dive into an enlightening interview with David Gunn, a Customer Success Manager at MaestroQA and an expert in scorecard revamping. David will share valuable insights and practical tips for maximizing the potential of scorecards and taking your QA processes to the next level.

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The Importance of QA Scorecards in Modern Customer Service

Quality Assurance (QA) scorecards are vital tools in modern customer service operations as they are detailed evaluation systems that define the specific criteria for evaluating customer interactions. By meticulously analyzing calls, chats, or emails against these criteria, businesses can ensure service quality, compliance, and exceptional customer experiences.

‍QA scores are also used to provide valuable insights, enabling companies to identify trends, train agents effectively, and enhance overall service efficiency. In the digital age, where customer satisfaction is paramount, QA scorecards serve as strategic assets, guaranteeing that customer interactions align with the brand's standards and leave a positive, lasting impression on clients.

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The Process of Building QA Scorecards from Scratch

When working with customers who are new to QA scorecards or need more defined goals, David emphasizes the importance of aligning objectives backward for maximum impact. According to him, "If you get the goals and work backward from there, it's more impactful. Some people might not have goals initially, so using a standardized scorecard can be beneficial in the beginning stages." This approach allows for initial grading and data analysis, identifying areas performing well, such as communication, that no longer require extensive questioning. 

From there, a tailored and refined scorecard can be formulated, addressing specific aspects and asking different questions that align with the customer's goals. David advises starting with simplicity and avoiding overly complex scorecards with numerous questions or unclear prompts that might overwhelm newcomers. "If it starts to be like 50 questions, that's too much," he advises. "Go and find areas where there's overlap or you're asking very like-minded questions and see where you can consolidate things into one or remove them."

‍Building scorecards based on goals and gradually refining them based on data-driven insights allows organizations to focus on relevant aspects and ensure that agents are evaluated on what truly matters.

Looking to build your first QA scorecard? Check out this comprehensive blog to learn how.

Key Components of an Effective QA Scorecard

Creating a powerful QA scorecard involves meticulous consideration of critical elements that define exceptional customer service. These can include:

1. Essential Components:

• Criteria Definition: Clearly outline evaluation criteria like agent professionalism, problem-solving skills, and adherence to policies.
• Scalability: Ensure the scorecard is flexible, adapting to evolving business needs and industry standards.
• Clarity: Make the scorecard user-friendly, enabling easy understanding for both evaluators and agents.

2. Metrics, KPIs, and Evaluation Categories:

• Metrics: Include response time, customer satisfaction ratings, and agent efficiency indicators.
• KPIs: Integrate first call resolution rates, customer feedback scores, and agent adherence to scripts.
• Evaluation Categories: Assess agent demeanor, problem resolution capabilities, adherence to company policies, and overall customer interaction quality.

By incorporating these aspects, businesses establish a comprehensive QA scorecard that not only measures performance effectively but also acts as a guiding beacon for continuous improvement, ensuring exceptional customer experiences and long-lasting customer loyalty.

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Streamlining and Enhancing QA Scorecards

To streamline QA scorecards and optimize efficiency without compromising accuracy, David recommends consolidating questions and addressing duplication. He suggests, "Utilize checkboxes or different levels of severity and specific criteria, so you don't need lengthy responses. Simplify the scoring process while still gathering valuable insights." By using section scores, it becomes possible to identify areas where questions can be removed, helping you optimize the scorecard over time. David explains, "After you've had a rubric for a while, use our reporting to look at the section scores. If three sections are consistently scoring 98 to 100, do I even need to ask those questions anymore? Is it worth my time? If somebody's constantly scoring high, do I still need to ask? Can I ask it in a different way to learn more?"

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By regularly analyzing section scores and eliminating redundant questions, organizations can streamline their QA scorecards, focusing on the most critical aspects that impact agent performance and customer satisfaction. This not only saves time but also ensures that evaluations are precise and aligned with the goals of the QA program.

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Customizing and Segmenting QA Scorecards for Improved Alignment and Insights

Scorecards should be tailored to different channels, query types, and agent roles to provide deeper insights into specific areas. David suggests breaking down channel-specific aspects and considering the different processes and ways of handling tickets. "You might ask a completely different set of questions because the skill set of somebody handling a technical troubleshooting question is different from someone addressing a billing question," he explains. Aligning QA scorecards with company and customer experience (CX) goals is crucial to ensure the questions asked are relevant and contribute to desired outcomes. David highlights the importance of splitting scorecards based on different agent roles and categories of tickets. "Asking the same questions isn't always fair because they're doing completely different types of work," he states. "Splitting them out in that way is really helpful."

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Segmenting QA scorecards based on channels, query types, or agent roles enhances clarity and efficiency, ensuring relevant evaluations for different scenarios. By aligning the questions in the scorecards with specific goals and objectives, organizations can ensure that the evaluations are meaningful and contribute to the desired outcomes. As David points out, "Sometimes people set up their rubrics, and they're asking questions for things that aren't actually important to what they're trying to accomplish. It's a really simple thing, but if decreasing a metric like First Response Time is really important to you, but the questions you're asking have to do with grammar or punctuation, you're not accomplishing that goal. If you have these goals from both a company perspective and a CX perspective, but then you're asking all these questions that have nothing to do with it, then what are you really accomplishing in your rubric?" The reporting derived from segmented scorecards offers detailed analytics and actionable insights, allowing organizations to make informed decisions and improvements that directly align with their goals.

For example, a telecommunications company may have different scorecards for voice calls and live chats, considering the unique aspects and skills required for each channel. By segmenting the scorecards, the company can gain insights into the strengths and weaknesses of agents in each channel, enabling targeted training and improvement strategies.

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Addressing Subjectivity and Calibration in QA Scorecard Evaluations

Subjectivity and calibration are common challenges in scorecard evaluations. To address subjectivity, it is important to set clear guidelines for scoring criteria to build trust among agents. David explains the significance of consistent feedback from multiple graders, stating, "If I'm an agent and I have five different people grading me and they're all giving me the same kind of feedback, then I would probably trust in that. But if I was an agent and you graded me, and you gave me a 95, but then Michelle graded me, and she gave me a 76, I'd be like, what is happening here? Haley thinks I'm great, but Michelle thinks I'm not, and they're grading the same types of tickets, so what happened?" Calibration exercises play a crucial role in aligning graders' perspectives, ensuring consistent evaluations across the team.

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Additionally, addressing ambiguity in the questions is vital for accurate assessments. David suggests using clear descriptions to define expectations, stating, "If you do have some level of ambiguity in your questions, using the description to lay out like, okay, this is what constitutes 'meets expectations.' This is what constitutes 'below expectations,' so on and so forth, and having that guideline set can help. By providing explicit guidelines, graders have a standardized framework to assess agent performance, reducing subjectivity. Evaluating the value of questions becomes crucial when managing high scores. Redundant questions can be eliminated if agents consistently score high, saving time without compromising accuracy. This strategic approach ensures efficient scorecard evaluations while maintaining the integrity of the QA process.

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Calibration exercises and clear guidelines empower organizations to overcome subjectivity challenges, establish consistency in evaluations, and ensure fair and accurate assessments of agent performance.

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Leveraging AI for Enhanced QA Scorecard Automation

Streamlining targeted QA with AI classifiers can significantly enhance efficiency and accuracy in the scoring process. By leveraging AI classifiers, specialized classifiers tailored to specific QA criteria can be created, such as identifying high-effort chat interactions based on key phrases and patterns. These classifiers can then be integrated into automated workflows alongside the scorecard, enabling a hyper-targeted QA approach.

Furthermore, AI classifiers can automate compliance-related questions by analyzing keywords and phrases within customer interactions. For instance, if the question pertains to agent verification, a classifier can be trained to identify specific macros or predetermined text that should be used. This eliminates the need for manual grading, as the classifier can flag instances where the verification requirements were not met, allowing QA teams to focus on more complex evaluations. The combination of AI classifiers and scorecards not only streamlines the QA process but also ensures consistent and reliable evaluations while reducing manual effort.

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By embracing AI technologies, organizations can automate repetitive tasks, enhance accuracy, and free up valuable time for QA teams to focus on strategic initiatives and high-impact evaluations.

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Common Mistakes to Avoid When Using QA Scorecards

Implementing QA scorecards demands precision to avoid common pitfalls. One mistake is underestimating the value of continuous feedback and adjustment. Over time, customer expectations shift; hence, static scorecard criteria may miss the mark. To mitigate this, foster a culture of adaptability. Regularly update scorecard parameters based on customer feedback and emerging trends. Additionally, ensure transparency in the evaluation process. Clear communication about scorecard expectations and providing actionable feedback can align agents' performance with company standards, fostering improvement and ensuring successful QA scorecard implementation.

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Elevate Your CX and Drive Conversions with Optimized QA Scorecards

Revamping scorecards is essential for efficient and effective QA processes. By following the insights and tips shared by David Gunn, organizations can optimize their QA scorecards, align them with company goals, address subjectivity challenges, and leverage AI technologies to enhance automation and personalization. Continually refining and adapting QA scorecards enables businesses to achieve better agent performance, improved customer experiences, and drive overall success in their operations. The result is increased customer loyalty, higher levels of efficiency, and a competitive edge in today's customer-centric landscape.

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Want to Learn More? 

Check out the full recording of our chat with Hims & Hers, and learn how they are De-Villainizing QA & Building a Scorecard That Agents Trust. If you would like to learn more about how MaestroQA can boost CSAT and improve agent retention for your business, please request a demo today.

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Rebuilding the Relationship: Transforming Quality Assurance from Adversary to Collaborator

As a customer service provider, Hims & Hers is dedicated to creating a human-inclusive and effortless customer experience. The company's values align with personalized support and building trust with customers, particularly in sensitive topics such as mental health and sexual health. To ensure that their agents provide exceptional customer service, the company relies on its Quality Assurance (QA) team, led by Salmeen Majid, CX Quality Assurance Supervisor, to ensure consistency, accuracy, and efficiency.

However, upon joining the QA team, Salmeen quickly discovered that front-line agents or "the floor" had a negative perception of the team, viewing them as the "villains" who harshly graded their performance using subjective scorecards and pointed out their mistakes. “Our agents' emotions are tied to their QA score, so it was critical that we remedy the situation,” she stated. She realized that the Quality Assurance team needed to rebuild the relationship with the floor and empower them to provide exceptional customer service.

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QA Scorecards for Call Centers

First, let’s get into the weeds on what QA scorecards actually do. QA scorecards are essential tools for call centers to assess agent performance systematically. These scorecards contain predefined evaluation criteria that align with desired customer service standards. By using scorecards, supervisors can consistently measure agent interactions, identify strengths, and pinpoint areas for improvement. This data-driven approach enhances customer experiences and ensures uniform quality assurance across the call center. Visit our Scorecard Builder to customize your own call center QA scorecards. 

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Standardizing the Grading System: Objectivity, Consistency, and Productive Feedback

To achieve this, Salmeen began standardizing the grading system with MaestroQA to make it more objective, ensuring consistent feedback, and building a positive and productive relationship with the floor. One of the ways Salmeen achieved this for the Hims & Hers customer service team was by having graders consistently grading the same agents week after week, which allowed her team to identify patterns in agents' performance and provide targeted and effective feedback. Salmeen and her team also held regular team calibrations, used data-driven insights to identify areas for improvement, and measured alignment in the way they approached scorecard questions. Salmeen also audited her analysts' audits every week using Maestro’s GraderQA tool to provide feedback and improve alignment over time.

In the quality assurance field, creating objective scorecards that accurately reflect customer experience while avoiding "double-dipping" and ensuring a clear distinction between criteria is a significant challenge. To address this, Salmeen's team is holding bi-weekly calibration sessions to fine-tune the scorecard's questions and interpretations. Furthermore, they are introducing a new "non-scoring" section to focus on internal processes and implementing "root-cause analysis" checkboxes to gather more data on agent coaching areas of opportunity. They are also preparing a knowledge resource with clear examples of positive customer interactions and tips and tricks for agents to tailor their solutions to each customer's unique situation.

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Empowering Agents for Exceptional Customer Service: Creating a Clear Path to Success with Objective Scorecards

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Salmeen emphasizes that the scorecard should be objective and clear to ensure that agents have a clear path to follow. Her Hims & Hers customer service team is working on creating distinct bullet points that are measurable and objective as possible. Additionally, they are contemplating separating categories like "internal processes" from "effortless experience" to make the scorecard more precise and eliminate any ambiguity.

Salmeen and her team are utilizing this new scorecard to highlight the significance of critical thinking and tailoring solutions to each customer's unique situation. They recognize that processes can be restrictive, and agents need to be able to navigate the gray areas and be inventive in finding solutions.

By focusing on continuous improvement and providing support to agents, Salmeen and her Hims & Hers customer service team are working to transform the perception of Quality Assurance from adversary to collaborator. They aim to establish a culture of collaboration and learning where agents feel empowered to provide the best possible customer experience.

Salmeen stated in the interview, "We're not here to criticize; we're here to support. We want to ensure that everyone is doing the best job they can, and we want to equip them with the tools to do so."

To make QA more approachable and effective, it's essential to involve agents in the process, standardize feedback, and celebrate successes. Quality teams play a critical role in improving customer experience, and their work should be perceived positively by agents. Utilizing tools like MaestroQA's AI classifiers can streamline the Quality Assurance process and provide agents with objective feedback.

In conclusion, QA doesn't have to be a negative or villainous aspect of customer service. By emphasizing its importance and creating a scorecard that agents and analysts alike can trust, Quality Assurance can transform into a positive and collaborative force that fosters growth and excellence within customer service teams. Salmeen and her team are dedicated to creating objective scorecards and empowering agents to enhance their own performance, working towards a more positive work environment where agents can provide exceptional service.

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‍Want to learn more? 

Check out the full recording of our chat with Hims & Hers, and if you would like to learn more about what MaestroQA can do for your business, please request a demo today.

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As the customer support industry evolves into an experience center, agents are no longer simply support representatives. They also serve as brand ambassadors and are critical to customer retention. However, the introduction of AI tools is once again transforming the CX landscape. This blog draws heavily on insights from a recent webinar with Vasu Prathipati, CEO & Co-Founder of MaestroQA. We will explore how an Automated Quality Assurance (Auto QA) program can speed up QA processes to revolutionize customer support, improve key performance indicators such as CSAT and AHT, and ultimately boost your bottom line. By sharing Vasu’s valuable frameworks, techniques, and tips, we aim to equip you with the knowledge needed to navigate this transformation and stay ahead of the competition. 

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So, read on to learn more about how to write your own Auto QA to transform your customer support experience and drive sustainable business growth.

What is Auto QA?

First, let’s define auto QA. 

Automated QA (Quality Assurance) for call centers provides automated quality metrics on 100% of your support interactions. 

By automating the QA process, companies can customize and run precise QA metrics to surface actionable insights from all your customer interactions -- voice, chat, text, and screen capture.

Shifting from Manual Call Scoring to Automated Scoring

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Today’s CX leaders want their quality assurance teams to execute a vision (see image above) that involves a gradual shift from manual QA to pairing Auto QA with targeted deep dives. “We’re seeing our customers come to us with this vision of how they want quality teams to operate going forward. Quality assurance teams want to do this. They see this as a huge opportunity to unleash their creativity. The reality, however, is that they come into this role of quality with the promise of being an analyst and coming up with insights, but they end up feeling and spending a lot of their time doing more data collection. The word auditor comes to mind.

"The hope is that there's a possibility with new technologies and new companies like MaestroQA that we can help quality teams transform into the promise that they've always set out for themselves, which is becoming a data analyst or a customer experience data analyst in particular.

"So, that’s the shift we’re working on with our customers, and that’s exciting because by allowing Auto QA workflows to handle tasks such as identifying low-scoring DSAT tickets to perform targeted QA or automated transcription to analyze 100% of interactions to get a more accurate picture of what’s causing negative feedback from customers, Quality Assurance teams can increase their strategic value to the organization significantly.” They can now shift their focus on “conducting targeted deep dives to determine where training gaps exist, uncover actionable insights, identify process and policy improvements, and enhance overall quality like never before.” With three simple steps, CX teams can elevate their Quality Assurance strategy to drive business success.

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Step 1: Map Out Support Organizational Structure

A customer service organizational structure refers to the hierarchical framework and arrangement of roles within a customer service department or team. It outlines how positions and responsibilities are organized, defining reporting lines and communication channels. 

This structure typically includes roles such as customer service representatives, team leads or supervisors, managers, and may extend to include specialized teams like technical support or escalation departments. The structure aims to streamline operations, facilitate efficient customer interactions and support, and ensure effective coordination and collaboration among team members. It helps distribute tasks, establish accountability, and promote smooth communication to deliver high-quality customer service consistently.

“When CX teams want to transition to this vision of shifting their QA teams to a more data analyst role,” shared Prathipati, “it’s important that they have a clear understanding of their current state. I recommend mapping out your support work structure. A support work structure is where there are not only just Tier 1, Tier 2, and Tier 3, but there are also different lines of business.” For instance, “an Airbnb may have a line of business for renters and another line of business for hosts. But they also may have a line of business for the people who host Airbnb experiences. Each of these lines of business has tiers like Tier 1, Tier 2, and Tier 3.”

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Step 2: List Current KPIs Used

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This next step is crucial in enabling you to identify and prioritize the metrics like CSAT, AHT (average handle time), or TTR (total time to resolution) that matter most to each line of business and within each tier. “You don’t want to include something about SLAs (service-level agreements) unrelated to agents here, but if it's an SLA related to agent performance, amazing. But if it's first response time, that's a reflection on volume and staffing; you don’t want to include that here,” detailed Prathipati. “We often see some metrics that are not relevant to all the groups, and that's an important thing to note.”

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Here’s an example: 

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Lyn Miller-Bright, Director of Workforce Management and Quality Assurance at Zendesk, agrees that not all metrics are of equal importance. “While some metrics, like FCR, may be crucial for Tier 1 because they handle a wide range of tasks, they may not be as critical for Tier 2, which deals with a narrower range of responsibilities.” In other words, different tiers prioritize different metrics based on their specific roles and objectives.

“For the sake of this exercise,” said Prathipati,  you want to focus on the metrics impacting your frontline agents (the people speaking to customers) so you can make better decisions about how you manage your teams, your BPOs and how you do root cause analysis on how you coach. This exercise is ideally something you can do if you have a data person on your team or a more data-savvy person, or a metrics-oriented person.”

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‍Step 3: Identifying Trusted Metrics vs. Misleading Metrics

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In our final step, you want to understand the trust level that your teams have in metrics such as CSAT since customer satisfaction scores are a combination of support, service, product, and/or other market feedback. And like any voluntary-response survey, they’re subject to problems like sampling and response bias. 

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Take this all too common, real-world example:

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A customer leaves a low CSAT score immediately after a lengthy call with a customer service agent. The reviewing manager looks at that low score, assumes the agent needs additional coaching, and sends them training resources to work on their soft skills.

The truth of the matter is, without additional context, that low CSAT score could have been the result of several things: an ineffective company appeasement policy, an outstanding product issue, or even prior service frustrations. In this case, CSAT didn’t reflect how (well) your agent handled the situation but reflected the customer’s larger company dissatisfaction that the agent would never be able to solve by themselves.

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Therefore, CSAT can be misleading.

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“We use the labeling term ‘misleading’ as an indication that the team feels that the metric doesn’t accurately reflect reality or that they have no trust in that metric.”

For example, furthered Prathipati, “When we complete this worksheet with our customers, we may discover that the total time to resolution metric may not be applicable to a particular tier. This is due to the fact that when an issue is escalated, it can often sit in the queue for an extended period of time, which can skew the average and make it an inaccurate measure of an agent's performance. Therefore, it may not be effective in coaching agents on what they need to improve.” 

Completing this exercise can bridge the gap between crucial decisions that leadership teams have to make, such as choosing “who to promote, reward, or let go, and the actual ground reality. By exposing the misleading indicators, you can make more informed decisions that can impact teams, culture, and customers positively,” said Prathipati. The ability to make better-informed decisions that align with the real-world situation ultimately leads to better outcomes for your organization.

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One-dimensional metrics often lead to misinterpretations, which can have a significant impact on customer experience. “MaestroQA aims to bridge this metrics gap in a new and innovative way that empowers quality teams to be more strategic and influential in their role. With MaestroQA, people-powered quality teams can become more impactful and make a meaningful difference in how customers perceive the quality of their experience.”

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The Two-Step Prioritization Technique: Shift the Vision into a Reality

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Now that you have identified the challenges that misleading metrics can bring by doing steps one through three and drilled down to identify your problem statement, “it’s important to remember,” said Prathipati, “that you can’t tackle all the challenges that you uncover at once.” He recommended that you follow a two-step prioritization technique:

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Prioritize #1:  Pick one team within a single tier to focus on

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This team might have the most misaligned metrics, or they represent the biggest areas of customer dissatisfaction and require immediate attention to improve customer experience.

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Prioritize #2: Within that team, determine which metrics are truly important

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During this step, the worksheet will help you identify your metric alignment process, which metrics should be kept, and which ones can be discarded. According to Prathipati, it's also a great opportunity to discuss your ideal scenario. For instance, your team may aspire to access metrics like customer request escalations, sentiment escalation in conversations, chat-to-email transfer rates, or the number of agents tickets are handed off to. These discussions not only provide insights into what's happening at the ground level but also open up a world of opportunities, such as identifying Auto QA partners like MaestroQA, that fit into this vision.

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This shift in vision and the ability to execute that vision has inspired some quality teams to resonate more with team names such as Performance Excellence Team or Quality as a Service Team.

“We’re not saying everyone needs to change their quality assurance team’s name,” said Prathipati, “but we're trying to highlight this real shift in mindset and how Auto QA from Maestro can create value for teams, companies, and customers, plus, help understand agent performance and manage BPOs. With MaestroQA, teams can see which BPOs are hitting performance expectations and which are not. Again, this type of real, actionable data helps make better decisions about people and their livelihood and, ultimately, customer experience.”

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Speaking about quality teams…

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The Role Of Team Leads And Quality Teams In Change Management

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It's crucial to factor in change management. This means taking into account the role of a quality person in the future, as well as the evolving responsibilities of the quality team. 

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Here's how a real-world example of how a MaestroQA customer has made adjustments in their change management.

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Team Leads use MaestroQA to monitor the performance of agents by analyzing aligned metrics and incorporating them into their coaching sessions. Using the MaestroQA dashboard, Team Leads can extensively review tickets based on these newly identified metrics and take a hands-on approach to coaching, providing personalized one-on-one sessions based on the metrics to ensure their team is meeting their targets.

The quality team, on the other hand, uses MaestroQA to look at things from a slightly higher level, such as how the BPOs are performing. They also look at how multiple teams are performing across a particular line of business. 

MaestroQA allows this team to look at patterns at the BPO level or across multiple BPOs to create ideas for training, new processes, or policies. “They can determine if they want metrics they don’t have today that allow them to monitor and inspect based on what they are seeing in customer interactions.,” said Prathipati. “The QA team shifts to a more targeted role where they can be hyper-focused on an insight level. “That’s why it’s important to flush through this and adjust your change management. Technology helps, but the way teams operate today is different.”

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Pick the Right Auto QA Partner 

In the previous sections; we've covered the essential steps needed to identify misaligned metrics, create a clear problem statement, and explore the benefits of redefining the roles of your QA teams. The ultimate objective is to develop an Auto QA playbook and put it into action. Now, the crucial question is, how can you choose a trusted partner to help you bring things to fruition and doesn’t overpromise on AI? 

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“This is such a massive shift, so finding a partner who is going to keep it real, who is an expert in the Auto QA space, and can help you execute the vision that you have defined, this is the type of partner you want to seek out,” said Prathipati. 

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If you would like to learn more about what MaestroQA can do for your business, please request a demo today.

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Consistently delivering quality customer interactions involves more than having the right support processes, training materials, and coaching. After all, it’s difficult to guarantee a smooth customer experience when you’re struggling to find enough agents to get the job done.

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As part of our MaestroQA community series, we recently discussed some best practices for working with call center BPOs. This blog post recaps key learnings shared by our customers and Mel Bilge, Director of Customer Success, Strategic at MaestroQA.

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What is a BPO Call Center?

The abbreviation “BPO” is short for “business process outsourcing,” which is a general term that refers to supplementing an organization’s business operations with outsourced talent. However, many people use the term “BPO” as a catch-all when speaking about one or more specific contractors.

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For example, you might hear someone say, “We brought on a BPO to help us solve a difficult problem” or “We struggled to be successful with BPOs.” (This article uses “BPO” interchangeably with the word “contractor” and “BPO call center.”)

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Organizations rely on BPOs to support several core business functions, ranging from back-office work to accounting and finance. Customer experience teams use BPO call centers to handle customer phone calls, respond to support tickets, answer live chat inquiries, and assist with quality assurance (QA).

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Why Do CX Teams Use BPO Call Centers?

CX teams use BPOs to achieve many important goals, including:

Increasing Capacity: 

New product launches and seasonal shifts in demand can lead to dramatic ticket volume fluctuations. A reliable BPO can help the organization ramp up while ensuring consistent customer experiences.

Expanding to New Time Zones: 

Asking existing team members to work nights and weekends may create unnecessary internal friction that ultimately erodes CSAT. Partnering with BPOs in a specific time zone can be a better approach.

Providing Multilingual Support: 

We live in an increasingly global marketplace. Bringing on BPOs from international markets can help an organization reduce miscommunication and elevate customer satisfaction. Although many international customers are at least proficient in English, providing native language support would be ideal.

Overcoming Staffing Issues: 

Recruiting and retaining experienced talent is challenging in today’s tight labor market. BPOs can help CX leaders mitigate risk and control costs by making it easier to quickly backfill roles and efficiently reshuffle talent.

Providing Breathing Room for In-House Staff: 

Working as a support agent can be incredibly fast-paced and mentally draining. Customers always seem to need assistance, but your agents are human beings who need to recharge, take time off, go on vacations, enjoy holidays, and generally enjoy life. BPOs can help CX leaders avoid overscheduling agents and, as a result, ensure a more sustainable work-life balance for everyone.

Types of BPO Call Center Services

BPO call centers encompass a range of specialized services to support businesses worldwide.

Inbound Call Centers 

Inbound call centers specialize in handling incoming calls from customers, addressing inquiries, resolving issues, and providing valuable information about products or services. 

By outsourcing their inbound call center operations to a BPO service provider, businesses can benefit from a range of services aimed at enhancing customer satisfaction and streamlining operations, including:

Answering Customer Support Questions

BPO call centers provide dedicated teams of contact center agents who are skilled in handling a wide range of customer inquiries, concerns, and complaints. They offer timely and personalized technical support, ensuring that customers' needs are met with professionalism and empathy.

Order Processing

BPO call centers assist businesses in managing their order processing tasks, including order placement, order tracking, and order status updates. This ensures a seamless and efficient order fulfillment process, leading to improved customer satisfaction and retention.

Appointment Scheduling

BPO call centers assist businesses in managing appointment scheduling tasks, ensuring accurate scheduling, reminders, and notifications. This streamlines the appointment booking process and enhances overall customer experience.

Dispatch Services

BPO call centers offer valuable assistance with inbound call center dispatch services, ensuring seamless routing of calls to the right departments or individuals. By optimizing communication and response times of dispatch calls, businesses can enhance customer satisfaction and deliver efficient service.

Outbound Call Centers

Outbound call centers play a pivotal role in sales, lead generation, telemarketing, and customer outreach. These call centers proactively reach out to customers to drive business growth and create meaningful connections. By partnering with a BPO call center, businesses can leverage a wide range of services to enhance their outbound campaigns and maximize results, including:

Sales and Upselling Through Telesales

BPO call centers employ skilled sales agents who excel in promoting products or services, identifying upselling opportunities, and closing deals. They are trained in persuasive communication techniques to drive sales and increase revenue.

Lead Generation Through Telemarketing

BPO call centers assist businesses in generating high-quality leads through targeted outreach campaigns. They conduct market research, gather prospect information, and qualify leads to support sales teams in converting prospects into customers.

Surveys and Market Research

BPO call centers conduct surveys to gather valuable customer insights and market research data. These insights help businesses refine their strategies, enhance products or services, and make informed business decisions.

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Overcoming Challenges of BPO Call Centers

Unlike employees, BPOs are independent companies with objectives, processes, and systems. Working with a BPO call center can come with its challenges. Here are a few common roadblocks to working with BPOs—and tips for overcoming them.

Cultural Differences

Bringing together two separate companies is bound to surface noticeable differences in how things are done—even among organizations in the same country. Mix in differences in language, time zone, and customs, and the complexity becomes even more significant. 

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Tip: Seek opportunities to align around shared CX processes rather than designing one method for the BPO and one for in-house staff. A deep dive into the BPO’s existing processes can help identify gaps and opportunities for alignment. Maintain a consistent brand voice by setting clear expectations for the BPO, offering plenty of training opportunities, and providing specific examples.

Creating a “Team” Mentality

Aligning around shared CX processes is a good start, but fostering camaraderie between in-house staff and BPO agents requires a proactive commitment to team building.

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Tip: Creating shared Slack channels and hosting on-site or virtual team-building events can be quick wins. It’s also essential to ensure that, at a minimum, the BPO’s managers go through your training program and understand the material. 

Selecting the Right BPO

An online search for “BPO call centers'' returns an infinite number of options. Understanding your actual needs, asking for referrals from trusted colleagues, and evaluating multiple vendors are essential, but it may still be hard to know if you’re selecting the right BPO.

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Tip: Don’t be afraid to ask tough questions of the BPO’s leadership team. Does the BPO treat its employees in a way that aligns with your organization’s values? Which tool(s) does the BPO use for coaching and QA? Are they willing to switch to the same tools used by your team? How will the BPO handle adjustments to process and performance expectations? For example, what if you increase your QA benchmark score from 70 to 85? You might even do an on-site visit to confirm your assumptions.

Motivating BPO Agents

The BPO, not your organization, compensates a BPO’s agents. This can cause motivational issues, especially if the BPO fails to develop the proper compensation structure for agents.

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Tip: Consider developing an incentive program that goes above and beyond the basic terms of your contract. An effective program would drive additional loyalty and productivity from BPO agents.

Managing BPO Vendor Relationships

CX teams often work with multiple BPOs—one to support a particular time zone and language, another to support a specific product line, and so on. Contract terms, documentation, and requirements will likely differ from one relationship to the next.

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Tip: Dedicate one person from your organization to serve as the “owner” of each BPO relationship. This will help reduce the likelihood of oversights and ensure that the BPO is meeting its obligations.

5 Steps for Integrating BPOs into Your QA Program

Quality assurance is another challenging aspect of working with a BPO service provider. How can you ensure customers receive high-quality interactions when the BPO manages its own QA? Trust but verify! 

At MaestroQA, we recommend integrating BPOs into your QA program to ensure they represent your brand correctly. BPO Management can be a method to ensure this happens smoothly. Here are five steps for doing that:

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Step 1. Know Your Contracts

Start deep diving into your BPO contract(s). What, if any, QA obligations have the BPO service provider committed to? For example, is there a specific number of tickets that must be QA’d weekly? Are there QA benchmarks or performance requirements that must be met? Is your QA team obligated to provide coaching, training, or QA support?

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Step 2. Appoint a CX Advocate for the BPO‍

Depending on your team’s size, this role could be filled by the person who manages the BPO relationship. The primary objective should be fostering open and consistent communication, answering questions, providing new training materials, and disseminating process changes to support the customer experience. 

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Step 3. Standardize QA Processes

Leveraging a tool like MaestroQA can make it easier to standardize internal and external QA processes. Our Team Calibrations and Grader QA features can prove valuable for helping BPO’s graders understand your brand voice and expectations for customer interactions.

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Step 4. Use Data to Evaluate BPO Performance‍

MaestroQA can make it easier to understand performance across multiple BPOs. For example, our DSAT Dashboard tracks DSAT by agent group, which could help identify coaching opportunities and evaluate BPO contract renewals.

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Step 5. Provide Useful Training & Enablement‍

Anyone tasked with grading interactions (including graders at the BPO) should be well-versed in your brand’s voice, processes, and products. That’s why it’s essential to ensure internal and external graders have access to the latest training and enablement resources.

Set Your BPOs Up for Success with MaestroQA

MaestroQA provides QA software that CX teams can use to ensure quality customer interactions. Quickly grade support tickets, track key performance metrics, and seamlessly provide coaching for in-house and BPO teams.

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Request a demo to learn more about using MaestroQA for BPO relationships.

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Today CSAT is a widely accepted metric used to determine if support teams and companies are keeping their customers happy. And brands have come to rely on these scores to manage their customer service operations. On its face, the reason for this seems obvious—customer satisfaction correlates with the outcomes brands care about the most: retention and revenue. Happy customers are loyal customers, who buy more and sing your company’s praises.  

But this logic can be dangerously flawed when it comes to relying on CSAT to make strategic and tactical customer service decisions to improve poor customer experience. 

While CSAT is a great aggregate measure of customer experience, its one-dimensional nature doesn’t provide brands with enough context or action items to address potential CX issues. Statistics 101 has taught us that correlation does not imply causation—it can only suggest where to look. Yes, customer satisfaction ratings are directionally helpful, but they’re not actionable on their own. 

93% of CX leaders reported using a survey-based metric (such as CSAT) as their primary means of measuring CX performance, but only 15% said they were fully satisfied with how their company was measuring CX—and only 6% were confident that their measurement system enabled both strategic and tactical decision making.

Source: McKinsey 2021

CSAT Scores Are a Mixed Bag of Feedback

The reality is that customer satisfaction scores are a combination of support, service, product, and/or other market feedback. And like any voluntary-response survey they’re subject to problems like sampling and response bias. Looking at these numbers alone, it’s impossible for brands to pinpoint the root cause of a CX problem, and more importantly, how to fix it.  

Take this all too common, real-world example:

A customer leaves a low CSAT score immediately after a lengthy call with a customer service agent. The reviewing manager looks at that low score, assumes the agent needs additional coaching, and sends them training resources to work on their soft skills.
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The truth of the matter is, without additional context that low CSAT score could have been the result of several things: an ineffective company appeasement policy, an outstanding product issue, or even prior service frustrations. In this case, CSAT didn’t reflect how (well) your agent handled the situation but reflected the customer’s larger company dissatisfaction that the agent would never be able to solve by themselves. 

Digging Deep into the 3 P’s

It’s important to remember that customers don’t know your product roadmap or internal processes. And realistically, not all CX issues can be solved immediately, or at all. Some negative feedback could be the result of something agents have no control over, or it could be a simple training fix. But being able to decipher the difference, and act accordingly (and timely), is imperative for brands to deliver an incredible customer experience. 

To uncover the root causes of poor CX, brands need to take a deeper dive into three main areas: 

1) People: Areas where an individual agent(s) could use additional training or coaching

2) Processes: Team-wide issues or other business functions impacting customers

3) Products & Services: Product gaps/glitches that are negatively impacting customers and causing significant support requests or complaints

At MaestroQA, we call these three P’s the CX Experience Blindspot: everything happening in your CX that doesn’t get captured by the traditional support metrics teams use to measure success (like CSAT). But todays’ CX leaders all have one thing in common—they’re aware of the Experience Blindspot and have taken steps to mitigate it. They’re moving beyond surface-level insights and assumptions to uncover and fix the root cause of poor customer experience.

Top 3 Ways Brands Can Address the Root Cause of Poor CX

1) Use CSAT to measure aggregate performance—not individual agent performance
‍CSAT alone isn’t a good indicator of agent performance. It was originally designed to provide an overall measure of how someone feels about their customer experience but is now often used as a measure of individual performance. 

But unhappy customers don’t always receive poor service. And customer satisfaction ratings can’t tell managers if more training is or isn’t necessary. So, you don’t have to ditch CSAT, but understand it’s not telling you the whole story.

‍2) Modernize your CX reporting stack 
To optimize customer experience, brands need specific insights on what's happening with their agents, customers, CX processes, and business. One-sided metrics like CSAT aren’t cutting it anymore, they need to see what’s behind those numbers.

So CX leaders are moving beyond one-sided metrics, to embrace more holistic measures of CX success like customer lifetime value (CLTV), net-promoter scores (NPS), and QA scorecards. Combining these new measurements of success with investments in new root cause analysis tech, brands can finally identify specific actions they can take to develop better support for their customers and drive CX initiatives internally. 

‍3) Use a data-drive approach when building agent skill sets
In the eyes of your customer, not all agent skill sets are equal. For instance, there are process-driven skills that help solve a customer’s problem (like accuracy), and then there’s skills that really only serve to help the company (like process). 

The same is true for soft skills. Some of the actions that many CX managers prioritize and push for (building rapport and personalizing messages), really don’t impact customer satisfaction as much as basic soft skills like showing empathy for the customer’s situation and addressing them properly.

At the end of the day, to be successful long term, CX professionals need to mirror their customers and exhibit behaviors that will help alleviate their pain points. Doing this will require digging into their customer interaction data to determine which skill sets their customers value most and prioritizing those when it comes to agent training. Updating your QA scorecard to then reinforce those behaviors can help your agents understand what they need to do to improve. In the case of MeUndies, they used non-graded feedback in their rubric to help agents focus without impacting their overall grade. Customers noticed the difference and their customer satisfaction surveys reflected the change. Through collaborating with the QA team, agents started performing better and were able to meaningfully increase CSAT.

‍Relying on customer satisfaction scores alone to drive a successful CX strategy can leave brands chasing after the wrong solution(s). When it comes to delivering a seamless customer experience, there’s so much more to consider than a single metric like CSAT. The brands that will succeed will be the ones who adopt a holistic approach to measuring customer satisfaction, rely on customer interaction data to empower internal teams and agents, and seek out new, innovative solutions for root cause analysis. 

To learn more about how to uncover the kinds of meaningful CX insights needed to drive customer loyalty, check out our Industry Report, eCommerce Essentials for CX: How to Create Customer Experiences that Set Your Brand Apart.

By leveraging Business Process Outsourcing (BPO) partners to scale customer support, CX leaders can mitigate risk and control costs. But how do you measure the success of your outsourced customer support to ensure you're getting the most out of the investment? 

In this blog, you'll learn how to craft a powerful KPI plan based on alignment scores, AHT, and FCR to measure the quality of your outsourced BPOs or Call Centers and ensure they perform to the highest standards. Drawing on insights from a discussion with Sydney McDowell, the Quality and Training Manager at Handy, an industry-leading online directory that connects consumers with local home service providers, we'll share how this trending organization, with over 150 million service requests, regularly assesses its outsourced customer support performance. Find out how you can use these key insights to set benchmarks and maximize success and customer satisfaction with your BPOs.

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Let’s jump right in.

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Maximize BPO Performance: Alignment is Key

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Onboarding a new BPO can be a daunting task, especially when a brand has multiple BPOs supporting different aspects of the business. Such was the case for Handy. The first step the company took was to get everyone on the same page and simplify the number of BPOs it used. The next step was to develop specific contractual obligations to ensure they had a strong way to manage each BPO to performance expectations. This meant creating explicit guidelines for performance (qualitative and quantitative), staffing, and training that the BPOs had to adhere to.

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Maximize BPO Performance: Establishing KPIs

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When setting BPO performance expectations, it's important to tie these expectations to your BPO KPI’s Quality Assurance (QA) scores. For example, “we required that each BPO ensure that graders had the necessary skills and qualifications to grade four tickets per week per agent with an alignment score of x% or higher. If the alignment score drops below the required level for more than two consecutive weeks, graders should be placed on a Performance Improvement Plan (PIP). Adherence to efficiency metrics such as AHT (average handle time), FCR (first call resolution), or tickets per hour (number of tickets an agent handles in one hour) was also critical. Establishing this level of specificity was key to providing our customers with the best service possible," said McDowell. “If the KPIs were not met, we had clawbacks in the contract, which meant that BPOs would be required to reimburse us for not meeting these KPIs.”

Standardizing quality assurance doesn't have to be a chore. With the right tools, such as Team Calibrations and Grader QA features, you can streamline internal and external QA processes to ensure that your BPOs are aligned with your brand’s voice and that customer interactions are in line with expectations.

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Since we’re on the subject of the right tools…

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Maximize BPO Performance: Provide the Right QA Tools

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Developing a powerful KPI plan requires having the right tools, plus support, to help manage and assess performance. “QA ensures agents are receiving the appropriate feedback and that the graders are performing their duties correctly. MaestroQA provides a reliable and robust way to ensure this process works efficiently and effectively,” said McDowell.

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With easy-to-use, one-click LMS integrations, MaestroQA allows Handy to seamlessly assign training to agents without leaving the MaestroQA platform. This provides the brand with the confidence that BPO agents are receiving the proper guidance and feedback to help them reach their goals. “Our Learning Management System (LMS) helps us to more accurately track what agents are reading updates, keeps everyone up to date on the latest information, and allows us to monitor agent performance. With an LMS, we can ensure that the right information is unpacked and easily accessible to the team leads at our BPOs, giving them more control and visibility into their team's conversations. This empowers team leads to make more informed decisions and better support their agents.

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Key Takeaway: Having an internal knowledge base and a QA program in place has helped Handy provide support to BPO agents that are struggling and improve customer satisfaction. 

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Maximize BPO Performance: Get BPO Buy-In Into a Data-Driven QA Program

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Optimizing BPO performance requires reliable quality assurance metrics to ensure that BPOs meet performance expectations. While some BPOs may have their own QA programs, it's important to scrutinize them to ensure that the BPO is not cherry-picking the calls they grade. This can inflate the QA scores and leave brands with inaccurate and unreliable performance data, which is why it is important to have a comprehensive and reliable Quality Assurance (QA) program in place. Getting the BPOs to understand and buy into the QA processes, however, can be a challenge. "At first, the BPOs we work with were apprehensive," explained McDowell. This is why collaboration is key; both sides need to be willing to provide and accept feedback, and communication is of the utmost importance. 

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Leveraging MaestroQA’s reporting platform, Handy was able to gain valuable insights into the performance of each BPO. This granular level of detail allowed them to make informed decisions on where to affect changes and optimize their processes.

Once the BPOs started to see how the data-driven metrics from the QA program uncovered the challenges the agents were facing, they were onboard. This enabled the two sides to work together to overcome the challenges, leading to a true partnership mindset.

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If you would like to learn more about how MaestroQA can help you gain insights into your BPOs' performance, request a demo today.

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MaestroQA has been named as one of Comparably’s 2023 Best Workplaces in New York for the second consecutive year. In 2022, Maestro was also awarded Best Company for Career Growth.

These annual awards are based on authentic, anonymous feedback from current employees within the last 12 months. The feedback is based on a series of 35+ structured and comprehensive workplace questions. The feedback collected measures how our employees rate their overall workplace experiences in several different spheres such as career growth, leadership, company outlook, co-workers, compensation, perks & benefits, and overall happiness at work. 

“At Maestro we strive to cultivate an environment that fosters growth, healthy debate, and high ownership of individual roles,” said Julie Pierce, VP of People at MaestroQA. “We are happy and honored to receive Comparably’s Best Place to Work Award, particularly because this award is based on the direct sentiments of our existing employees. It shows that the culture we’re building resonates with them and that, despite any challenges, we are steadily moving in the right direction each year.”

“Our culture shows up in how we challenge each other to be better.  Start-ups can be akin to a David vs. Goliath fight. Our people do not shy away from this type of culture. In fact, we embrace, welcome, respect, and expect it. We seek to attract people who get fired up about these types of environments and who have that fighter spirit." said Vasu Prathipati, CEO and Co-Founder of MaestroQA.

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‍ABOUT MAESTROQA

MaestroQA helps companies improve the quality of their customer support. MaestroQA's mission is to help transform customer service into a strategic partner when it comes to improving the company brand and CX. Learn more about MaestroQA at https://www.maestroqa.com/. 

MaestroQA would like to express gratitude to the Comparably team for this award that helps showcase our culture to the world and attract top talent. In 2023, MaestroQA will be hiring across several departments, so for anyone interested in learning more, please follow our careers page for updates: https://www.maestroqa.com/careers

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Interested in connecting with a member of the Maestro team? Please contact:

Lauren Alexander

Vice President of Marketing

lauren.alexander@maestroqa.com

OR

Julie Pierce

Vice President of People

julie.pierce@maestroqa.com

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Despite being one of the oldest forms of customer support, phone calls are still the most popular channel among customers. In fact, 76% of consumers prefer to contact a brand via phone, according to a study by CFI Group.

Offering phone support can reduce customer effort but also add costs you might be overlooking. If you want a clear idea of how your spending correlates with productivity in your call center, step one is calculating your cost per call.

Cost per call is a popular contact center KPI that measures how much money it costs a company to handle a single customer support call. This metric is essential to understanding your ROI on call center technology and the cost-effectiveness of your operations.

This article covers everything CX teams need to know about cost per call, including how to calculate it and reduce it (without sacrificing quality.)
5 Inputs You Need to Calculate Cost Per CallBefore you can calculate cost per call, you need to tally every expense for your call center. Here are five factors to consider:

1. Employee Wages and Benefits

Labor is usually the biggest expense for customer support teams. This includes the cost of employing agents, supervisors, quality assurance managers, and directors.

To ensure you don’t overlook anything like employment taxes, it’s best to work with your CFO or accountant to get this information.

2. HR Expenses

Factor in all expenses allocated to recruiting, hiring, training, and onboarding agents.

3. Call Center Overhead

The biggest chunk of overhead comes from the cost of real estate for your call center. But even if your team is fully remote, don’t forget to factor in one-time setup costs such as hardware and servers.

4. Software Subscriptions

This includes the fixed or per-agent license fees for customer relationship management (CRM) software, quality assurance software, learning management systems, helpdesk software, data warehousing, and phone systems.

5. Total Calls Answered by Agents

Determine how many customer support calls your agents handled during a given time period. You can break this number down into calls per week, month, year, etc.

How to Calculate Cost Per Call

Organizing your expenses may take a while, but calculating cost per call is simple. Here’s the formula:

Total Call Center Costs ÷ Total Calls Answered = Average Cost Per Call

So, if your company incurred $75,000 worth of call center expenses last quarter and answered 22,000 calls, your formula looks like this:

75,000 ÷ 22,000 = $3.40 average cost per call

What Is a Good Cost Per Call to Aim For?

According to an analysis of 18 large companies with call volumes between 900,000 and 9 million, the industry benchmark for cost per call is between $2.70 and $5.60. However, that benchmark fluctuates depending on your industry.

For example, a brand with a small but loyal customer base that hires highly specialized agents might have a cost per call that exceeds the average. On the other hand, a retail company that handles relatively simple support calls with less experienced agents could have a lower-than-average cost per call.

5 Ways to Reduce Call Center Cost Per Call

If your cost per call is higher than average (or higher than what your budget allows), the issue usually boils down to two factors:

• A lack of insight into what causes inefficiencies in your call center
• A lack of technology or resources to help agents perform up to their potential

Here are five strategies to tackle both of those issues (without cutting corners in terms of quality).

1. Implement a Quality Assurance (QA) Program

Cost per call tells you if your agent interactions are cost-efficient, but it doesn’t tell you why. That’s where a customer service quality assurance (QA) program comes in.

Customer service QA is the process of reviewing agent interactions to see how well they follow your approved internal processes to resolve customer issues. During QA reviews, a QA manager listens to customer support calls and grades the agent using a scorecard (also called a rubric).

The grader assigns points for questions on the scorecard, such as, “Did the agent follow the approved escalation process?” Here’s an example of what a QA scorecard looks like:

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Conducting regular QA audits helps you pinpoint what causes long call times or frustrated customers. In fact, when monday.com increased their volume of quality audits, their average ticket handle time dropped from 24 minutes to 16.9 minutes.

2. Use Artificial Intelligence (AI) to Predict Peak Call Volume Times

Overstaffing during slow times or understaffing during busy times can drive up cost per call. Call center staffing is normally left to guesswork. But machine learning uses historical data to forecast future call volumes.

For example, you might discover that February and March are your slowest months, so you can reduce your staffing and therefore reduce your cost per call during that time period.

3. Review Call and Screen Recordings with Agents

Sometimes QA data alone isn’t enough to help agents overcome roadblocks—you need to step into your agents’ shoes to see exactly what they see during customer interactions. That’s where screen capture technology comes in.  

Take tails.com, the pet food subscription company, for example. Their CX team noticed agents struggled to track down information to resolve support issues, leading to high Average Handle Times (AHT).

tails.com used MaestroQA’s Screen Capture feature to identify opportunities for improvement during phone calls, such as keyboard shortcuts, monitor configuration, and support ticket navigation. These small tweaks helped one agent reduce her AHT by 50%.

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“We’re able to see what goes on in a typical agent’s day in a big, new way,” said Daniel Jensen, quality and training team leader at tails.com. “Every second adds up when multiplied across the course of a day, week, month, and year...It could be the difference of thousands of tickets.”

4. Optimize Call Routing with IVR Technology

Routing calls to the agents with the right expertise keeps your call center operations as efficient as possible. For example, agents who specialize in product demos shouldn’t field questions about return policies. However, manually routing calls is time-consuming and prone to human error.

To streamline your call center workflow, implement Interactive Voice Response (IVR) technology. This allows customers to connect to a specific support department via voice prompts, e.g., “Press 2 for account services.”

Ideally, when customers call, they should only be one degree of separation away from the agent who can answer their questions.

5. Automate Low-Level Tasks

When agents are bogged down with tedious tasks, it creates a bottleneck in your support queue. Putting those tasks on autopilot gives agents more breathing room and reduces your cost per call.

For example, at the onset of the COVID-19 pandemic, ClassPass noticed their agents spent way too much time chatting with customers who wanted to cancel their subscriptions. ClassPass fully automated their cancellation process, saving them more than 6,000 days’ worth of chat time.

Cut Cost Per Call (Without Cutting Corners)

Cost per call is one of the oldest and most popular call center metrics, but don’t make it your CX team’s sole focus. Exceptional customer experiences require a balance of efficiency and high-touch service.

Think of it like a restaurant: rushing customers through their meals might get you more people in the door, but they won’t come back (or advocate for you) if the experience was sub-par.

Ready to get 360-degree insights into your call center’s interactions? Request your demo of MaestroQA today.

As the use of Artificial Intelligence tools continues to grow in the Quality Assurance world of CX; organizations wonder if all-in AI tools can provide greater customer satisfaction, deliver stronger measurable results, and maximize efficiency more so than manual QA programs. 

To determine if there is value in adding AI to your QA program, organizations must clearly understand the value of their manual QA program and use it as a benchmark to measure the effectiveness of an AI-based QA program. Rather than solely focusing on the cost factor, organizations should also compare the quality and accuracy of their manual QA program to the quality and accuracy of an AI-based QA program.

In this blog, we’ll reflect on three common patterns shared by Vasu Prathipati, CEO of MaestroQA, and uncover the critical role that manual QA programs play in streamlining processes, reducing costs, and improving customer satisfaction. By understanding these patterns, you can determine if manual QA programs are best utilized to improve customer satisfaction and deliver more actionable results.

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Manual QA Programs: Key to Understanding and Measuring Agent Performance

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“One of the common patterns that I noticed while researching why our customers come to us and what problems they were facing in their world was around understanding and measuring agent performance,” said Prathipati. "Our customers found that while productivity metrics can track how much work an agent does, they don't always capture the quality of that work, or they found that using productivity metrics to incentivize behavior could be problematic.

Furthermore, Customer Satisfaction (CSAT) surveys were not always reliable indicators of high-quality customer service or support performance because they didn’t always consider the process involved.” 

For example, “say you have 100 agents that support 40,000 customers per person, and you’re spending $4,000,000 on your support team; what would happen if a QA metric for agents didn't exist, or what would happen if you add one?”

Understanding and measuring agent performance accurately is mission-critical. We have heard stories of customers letting go of the highest-performing people because leadership was using metrics that didn’t reflect people’s work accurately!

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Manual QA Programs: Key to Managing and Measuring BPO Performance

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The second pattern that Prathipati noticed in his research on why customers come to MaestroQA is that they want a new way to manage their BPOs or outsourced call centers. “Sometimes customers don't have a quality program at all, but they want a QA program to manage their BPOs, or sometimes the BPO has their own quality program, but customers are finding that the BPOs quality scores are all at 97 to 98% score, but that’s not the real reality, so they want to take more control of the QA program internally so that they can hold their BPOs accountable to these quality metrics. Imagine that you have a BPO and they have 200 agents there that are paid $20K per year; that’s $4,000,000 per year to that BPO. What would happen if a QA program didn't exist to manage that BPO, or if you add one?” 

Prathipati suggested another way of looking at it: “What if your manager didn't have 1:1 meetings with you, or if you’re a manager and didn't have 1:1’s with your direct reports? How would that impact the productivity and work quality of the team? The same concept applies to managing and optimizing your BPO agents.

How are some of the world’s industry-leading companies leveraging MaestroQA to manage their BPOs?

One of the fastest-growing direct-to-consumer underwear and apparel companies has a fully outsourced support team but utilizes MaestroQA for its QA program. The result: a 99% CSAT and their BPO agents are bonused based on QA performance. 

Here’s another one– a leading food delivery app made training and development for outsourced agents a central part of their BPO partnership strategy. By leveraging MaestroQA, they created a detailed training and agent development plan that gives BPO agents the skills and support they need to provide excellent customer experiences. They even implemented a rigorous onboarding certification program required for all new BPO agents to complete. “We’ll guide teammates through to retrieve that certification,” said the company’s Quality Assurance Lead.

Manual QA Programs: Key to Root Cause Analysis With QA As Its Foundation

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Lastly, Prathipati revealed that people come to MaestroQA because they want to invest in a quality program that allows them to do deeper root cause analysis. “We hear from our customers that their CSAT metrics are down, but they don't know why. Or they notice that AHT is going up, and they don't know why, or they have a goal to reduce contact volume, but they don't know what's really driving an increase in these contact volumes, or they’re seeing a spike in escalations but don’t understand why they’re seeing this spike. Is it because they have new agents? If so, why do they have new agents? Are there retention issues?” Customers use manual QA programs to dive deep into these issues and complete a true root cause analysis. 

“A manual QA program and a good QA scorecard,” said Prathipati, “is a great way to do these deep dives.”

During another research call that Prathipati conducted with a top-tier on-demand provider, the Senior Customer Service Operations Manager said: “my QA analysts are in the MaestroQA tool all day. I get feedback that they don’t have to listen to a call more than once because they can go back and read a section they had a question about. So, I'd be pretty confident that's saving them time. I like that with MaestroQA, we're leveraging data from multiple sources to build rules showing insights about the business.”

In the end, Prathipati said, “we’ve talked about three common patterns and the challenges that manual QA programs help organizations overcome, so when you’re thinking about layering in AI, it’s important not to look at your QA program just as a cost, but to look at the current value that it’s delivering. So much so, “that when you invest in a technology such as AI, is it clearing that bar? It needs to be delivering more value than your current quality program. So it’s a one plus one equals three situation.”

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If you would like to learn more about MaestroQA, request a demo today.

Creating a quality monitoring scorecard for your customer service team or call center can be a scary task. Questions abound. How many items should it hold? What type of scoring method should we use? Which questions matter the most? And which are the ones that don’t? Will it lead to increased agent performance?!

What makes it even scarier is that the call center scorecard is the foundation of a great quality assurance program. A bad scorecard can lead to scores that don’t represent what a quality interaction actually means to your brand or worse still—result in inflated customer satisfaction metrics that your team can’t use to improve (GASP!). 

But as Jeremy Watkin, long-time QA professional, tells us, creating a quality management form doesn’t have to be scary. There are some tried and tested methods that companies can use to think through the process of creating a quality form that works really well for their unique business (and their unique customer base). 

These articles walk you through various methods of thinking about what should go into your agent scorecard, starting from your first, to your second, to your 30th quality assurance scorecard/rubric. Ultimately, these changes will lead to improved customer satisfaction, a better customer experience, and increased customer loyalty. But first, let's define what call center scorecards are and explain why they are so necessary for your call center.

What is a Call Center Monitoring Scorecard?

A call center monitoring scorecard is an evaluation tool used to gauge how well your contact center is performing. It can provide you with details on how to analyze agent performance, client responses, and compliance or noncompliance with your business' SOPs. A good call center scorecard is objective, allowing you to pinpoint the team's or an individual's strengths and weaknesses.

Scorecards are effective because they are agent-focused across all channels, including phone, email, chat, social media, etc. With this you can keep track of, inform, and improve customer experiences across your company.

Simply put,  call center monitoring scorecards serve as a framework for call center agents to improve, by providing measurable metrics that impact customer satisfaction and customer loyalty.

Key Metrics and KPIs Tracked in the Scorecard

Some of the key metrics that are tracked in a quality assurance scorecard include call resolution rate, call handling time, customer satisfaction score, first call resolution rate, and adherence to script or call flow. By tracking these metrics, call center managers can identify areas for improvement and make data-driven decisions to improve the overall quality of service provided by their agents.

Additionally, KPIs such as agent attendance, punctuality, and compliance with company policies and procedures are also tracked in the scorecard. These KPIs help ensure that agents are adhering to company standards and are performing their duties in a professional and timely manner.

Why You Need a Call Center Quality Monitoring Scorecard

In today's highly competitive business landscape, it's crucial for call centers to prioritize quality assurance. It can make the difference between a satisfied, loyal customer and a lost opportunity. Call center quality assurance is an investment that pays off in the form of happy customers, increased revenue, and a positive brand image. You’ll find more ways in which it can benefit your customers, call center agents, and overall business below. 

Benefits for Your Customers

Firstly, having a quality monitoring scorecard in place ensures that customer concerns are addressed and resolved quickly and effectively. This leads to improved customer satisfaction, loyalty, and retention. Additionally, a quality scorecard helps identify areas where agents may need additional training, leading to more competent and confident agents who can provide better customer service.

Benefits for Your Call Center Agents

In terms of benefits for agents, a quality scorecard helps to promote consistency and fairness in performance evaluations. Agents can see where they excel and where they need improvement, leading to more meaningful feedback and better opportunities for professional development.

Benefits for Your Business

Finally, having a quality monitoring scorecard in place can ultimately benefit the business as a whole. With improved customer satisfaction and agent performance, businesses can expect to see increased revenue, decreased customer churn, and a stronger reputation in their industry.

If you are ready to go really in-depth into building QA scorecards that will generate insights and trustworthy data for your Customer Experience (CX) team, look no further than our Ultimate Guide to CX QA Scorecards, or keep reading for more information on how to build your own!

How To Build Your First QA Scorecard

What does Roman urban planning have to do with building a QA Scorecard? Lots, as you’ll find in this article. There’s one key difference, though. Building your first QA Scorecard is going to be way easier than planning a whole city. 

With your training wheels firmly attached as you speed down the Via Maestro, you’ll learn:

👉 What is a QA Scorecard and why your CX team needs one

👉 The tools you can rely on to build that first Call Center Quality Monitoring scorecard

👉 Three examples of companies who’ve gone and built their scorecards from the ground up with our process.

👉 The essential CX software integrations you need to get up and running.

And while Rome wasn’t built in a day, your first call center QA scorecard certainly can be!

Read this article to learn how.

Choosing the Right Metrics

‍An effective call center quality monitoring scorecard is essential to ensuring that customers are receiving the best possible service, agents are performing at their highest level, and businesses are meeting their goals. To build an effective scorecard, it is important to choose the right metrics that are relevant to your business and goals. This could include metrics such as call handling time, first call resolution, customer satisfaction, and agent performance.

Setting Achievable Goals

When setting goals for your scorecard, it is important to make them achievable and measurable. Goals could include reducing call handling time by a certain percentage or increasing first call resolution rates. 

Measuring and Reporting Progress

Measuring progress is also critical in ensuring the effectiveness of your scorecard. Regularly reporting progress to stakeholders and making adjustments as needed can help ensure that your scorecard is effective in improving call center quality.

Training and Coaching Agents

Training and coaching should focus on areas identified by the scorecard as needing improvement. This can include topics such as communication skills, product knowledge, and problem-solving techniques.

Additionally, agents should be provided with feedback and coaching based on their individual performance metrics. By addressing specific areas of improvement, agents can make targeted changes and improve their overall performance.

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Kickstart your QA Scorecard Research Process

First scorecard done and dusted? The work doesn’t stop there. Unlike a foundation (yes I’m still hanging on to the Roman city analogy) that gets buried under feet of rubble and concrete, you can always pull out your call center scorecard, reassess if it’s carrying the weight that it should, and rebuild if you have to.

This article helps you to think critically about the many great examples that we feature here on the website. While every customer that we feature here is a successful example of how to build your own QA scorecard (and program!) from scratch, QA is not really one of those things where you can buy off-the-rack.

In this article, we feature 5 common questions that we’ve seen appear in many scorecards, and tear them down to expose the logic behind each question.

Through that process, you’ll be able to learn:

👉 how the pros are thinking about their call center quality monitoring scorecards

👉 how you can apply that to your own QA scorecards

Read the article here.

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Omnichannel Contact Center Assurance Scorecards - The Definitive Guide

So you’ve iterated on a few scorecards, you’re feeling fairly confident about your scorecard-building skills, and your QA program is working like a charm. CSAT and customer satisfaction is at an all-time high📈, and more importantly, your agents are motivated and doing better than ever 💪.

You lean back in your chair, thinking you’ve earned some rest when….

“Next quarter... let’s take our CX omnichannel.”

Drats. Bosses never take breaks, do they?

We’ve got your back. Building an omnichannel call center quality assurance scorecard doesn’t mean tearing up your old scorecard and rebuilding it from scratch. Think of it more like an upgrade, where you take a hard look at your existing parameters and figure out if they still make sense as you move to an omnichannel strategy, or as your brand evolves over time.

In this article, we apply Jeremy Watkin’s 4C framework to planning an omnichannel scorecard that will get your boss off your back - until next quarter, that is.

Catch a break here.

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‍Creating a Customer Service Quality Assurance Scorecard Doesn’t Have to Be Scary

Speaking of Jeremy Watkins, this article by him imparts 20 years of customer-facing experience to help guide you along the process of building out a call center quality assurance form on any medium, be it in a spreadsheet, or an omnichannel QA platform.

The first step is to consider your company’s brand, how you want to be perceived by your customers, and what good looks like for your specific company and customers. This includes: 

👉 What you call your customers (and what your greeting script is)

👉 What the philosophy or mission of your company is and (equally importantly) what the mission of your support team is 

👉 What good looks like for your company, and support team (is there a list of things that make up a “good” customer interaction for your team, etc) 

The next step is to think about quality in three separate areas: 

👉 Accuracy: Did you provide the right answer? In the right way? Were all internal processes followed?

👉 Compliance: Did the agent handle PII in the right way? Did you protect the log-in information of your customer? 

👉 Connection: THIS ONE IS LAST-BUT-DEFINITELY-NOT-LEAST, WOW! Did the agent have an authentic interaction with the customer that will differentiate your brand from the other companies that customer has talked with? Was it real? Was it human? Did the agent thank the customer for their time? And so on... 

Then, how do you think about the ways that you use this customer service quality assurance checklist to create different scorecards for each channel (or do you use the same form?), and what should you look for in a support tool to support your team goals? 

Read this article, and be not afraid!

(Another fun read – the only difference between fear and courage is the action that you take). 

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Creating an Omnichannel CX Quality Management Form

More from our guest blogger Jeremy Watkins here - use this to guide your omnichannel QA scorecard building process. There are two schools of thought about how many call center quality monitoring scorecards companies should have. Some believe that you should have a different form for each support channel. After all, each channel requires a very different set of communication skills. 

For instance – tone of voice matters over the phone, and doesn’t really exist for other channels. And grammar might be more important in an email than over SMS, where an agent could be a lot more casual with a customer. 

Others think that a single quality monitoring scorecard should be applicable for every customer interaction so that it better reflects the customer experience. After all, each channel should be aligning to a standard of excellence that applies to every interaction a customer has with your brand, right? 

For adherents of the second school, this article lays out a game plan to create scorecards that work across all your channels:

👉 Communication Skills – How well did the agent communicate the message?

👉 Customer Connection – Did the agent make a human connection with the customer?

👉 Compliance and Security – Did we follow all essential policies and procedures to keep the customer and the company safe?

👉 Correct and Complete Content – Did we give out correct AND complete answers and use our tools effectively to arrive at those answers?

...and covers the nuances of how these pillars can mean slightly different things on different communication platforms. 

It also goes into the benefits of omnichannel customer service scorecards, and considerations for creating this type of form. Including: 

• Keep your form relatively simple 
• Create a quality definitions guide 
• Use N/A for certain questions 
• Grade the entire interaction 
• Slice and dice by channel and question in your reporting 
  

Start livin’ la vida omnichannel! 

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Using Company Core Values to Build Your Quality Management Scorecard

FullStory has a simple mission – they believe that everyone benefits from a more perfect online experience. To help accomplish that mission, they have some watchwords (read: brand values) to guide them. These are: empathy, clarity and bionics. 

The watchwords give everyone at the company a framework from which to make decisions, and guide both their product decisions as well as how they operate their call center internally. 

Fullstory leaned heavily on their watchwords when building their quality monitoring scorecard, and it allowed the support team to align with the efforts from marketing, sales, and product.

Learn more about what they did here.

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Building a more Human Quality Assurance Scorecard

SeatGeek built a ticket search engine with the knowledge that scoring tickets to your favorite band, or ringside seats to a boxing game can be an intense affair.

Behind the tech, they also put together a personable, human CX team to ensure that their clients received the support that they needed.

When the time came to add a QA program, they wanted the same humanity and care to be shown to their agents as well.

Read about how SeatGeek built a more human QA process here‍

Customer Support is no longer just a cost center - it's been transformed into a powerful experience center where support agents act as brand ambassadors and drivers of customer retention. But the rise of Artificial Intelligence (AI) is changing the CX landscape yet again.

In this blog, we'll dive into how machine-learning models are impacting Quality Assurance and the role of support agents. We'll also explore whether AI is empowering agents or stifling their creativity and discuss the way AI is affecting CX and the part that support agents play in the customer experience journey. With this in mind, we'll share deep insights from a recent CEO/CX webinar featuring MaestroQA CEO Vasu Prathipati.

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This will be a good one, so let’s get started.

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Why the Push toward AI in a Quality Program

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As Quality Assurance Managers continue to be tasked with finding ways to elevate customer service, the question often arises: How can AI help impact quality assurance? 

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“When we ask customers why they are interested in using AI for their quality program, three responses are typically given,” shared Prathipati:

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1. We're only sampling 2% of our interactions – AI can help us to do 100% sampling, providing us with more insight. 

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2. AI can be used to do sentiment analysis on 100% of interactions, making sentiment analysis more efficient and thorough.

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3. Manual QA is expensive and filled with human errors, so AI can be the perfect solution to reduce costs and increase accuracy.

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Prathipati suggests taking a more discerning approach when evaluating the potential impacts of AI on QA to help ensure better decision-making. By examining each of the initial reactions mentioned above more thoughtfully, organizations can better understand the implications of their AI-related investments and make informed decisions that align with their long-term goals. 

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So, let’s start with the first one.

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Actionable Insights vs. UnActionable: Which is More Important

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“We're only sampling 2% of our interactions – AI can help us to do 100% sampling, providing us with more insight.”

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Of course, 100% sounds better because it means more insights. 

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“But let’s challenge that assumption,” said Prathipati. “Would you rather have actionable insight based on 2% of interactions or unactionable insight based on 100% of tickets?” 

The answer for many at this point might be to focus on the 2%, “but what happens when the 2% and the 100% are both actionable, but in different ways?” asked Prathipati. “What if the 2% of actionable insight results in more cost-savings than the 100% of actionable insight?” 

One would focus on the 2%, but is that the right choice? “All of a sudden, what matters more than 2% vs.100%, is the word actionable. We need to start spending more time thinking about what is actionable, whether it's through manual or AI-powered insight,” Prathipati pointed out.

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This leads us to a discussion on:

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AI and Sentiment Analysis: Hype vs. Reality

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“AI can be used to do sentiment analysis on 100% of interactions, making sentiment analysis more efficient and thorough.”

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In today’s fast-paced environment, the capabilities of AI in QA have high expectations. “We hear promises, said Prathipati, “that this technology can do the whole end-to-end process from detection to root cause analysis. That’s why when speaking with our customers, we ask a series of questions to get a more balanced point of view on what is a right fit and what are reasonable expectations: innovative but reasonable.”

Shifting back to our discussion on using AI to do sentiment analysis on 100% of interactions, Prathipati said, “we want actionable insights. If sentiment is low, how will you identify the ‘why’ it’s low to determine how to take action to improve it? The same rules in our current world still apply in this world of using AI in quality programs. What we hear from our customers is that CSAT is low, so what do we do? We build a DSAT process where we start to look at all the negative CSAT scores. With scorecards, we can do root cause analysis to determine if it’s a people issue, process issue, technical issue, or some other type of issue.”

When it comes to using AI, definitions matter too! Prathipati said, “how we want to define Sentiment. This is the key to actionability. For example, how do we account for customers coming in upset? How are we looking at sentiment where they're already upset? Or are we looking at customers that get upset later in the conversation?” 

Determining if it’s agent sentiment or customer sentiment leads to asking yourself: which one of these is even that actionable? If AI is just for Sentiment, will you be able to generate 4X the cost-savings or revenue gain to justify that to your CFO?

“We’ve heard from customers that dig into it, ones that have been burned in the past, that it’s already hard to measure a correlation between CSAT and retention or CSAT and churn or CSAT and growth.” This means that “first we might have to do the hard work to determine do we believe sentiment. Do we have data to show internally that sentiment and churn are really correlated before we can go and invest in AI?”

Critical thinking is needed, recommended Prathipati, so that a company doesn’t end up with something that “sounds good on the surface, but when you get into the details, it doesn’t fulfill your goals or promises.”

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Let’s move to the last reason why some push for AI in quality programs.

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Manual QA vs. AI: Is AI the Silver Bullet?

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“Manual QA is expensive and filled with human errors, so AI can be the perfect solution to reduce costs and increase accuracy.”

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One of the last common reasons for the shift to AI is the manual and expensive process of QA, which some feel can be filled with human bias. Hence, the perception that AI should be the perfect solution.

Today, “some feel that AI is the silver bullet, and they have this great vision for it, but pairing that vision with reality hasn't been fully thought through, “ shared Prathipati. “Some of the questions that we ask our customers after reviewing their current scorecards revolve around the sections of those scorecards; we want to know which are the hard skills and soft skills. 99% of our customers have hard and soft skills in their scorecards.” 

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"Whether they are looking at other QA software vendors or us, we ask: what are vendors showing you auto-scoring around, and what will you do about the parts they aren’t covering? Most typically, we see use cases that are soft skills based." What’s interesting in this finding, as Prathipati pointed out, is that troubleshooting or probing questions come from the hard skills section, but it’s this section where you can save time and impact metrics like first call resolution or reduce total time to resolution." That’s why it’s important to consider the coverage when considering AI for this. "There’s a role for AI, but it’s not the silver bullet for everything." The goal, said Prathipati, is to think about "how they should be coupled together" so you can "really create a dynamic and exciting quality program."

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What about using AI for auto-grading?

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“So many of our customers use quality programs where they're not only reviewing the conversation in a Zendesk or Salesforce in their case management system or listening to the call. There are a lot of back-end systems, so they must check to see if the case or issue was resolved properly. This requires going into your internal tooling. And that's a whole different beast,” said Prathipati, “How do you make sure you're accounting for that type of deep work when you're thinking about auto-grading? From our research, that's a whole different set of work. And so when we start to unpack this with customers, we can help our customers with this amazing vision that we still want to hold on to, but bringing it down so that we get the best of both worlds: the great work we're doing as people, paired with the great work of technology.”

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AI In Quality Assurance: The Wrap-Up

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In the end, Prathipati said, “we’ve talked about three common perceptions of AI and why people are thinking about AI in their quality program, but when you start to pull back the layers, we try to take the conversation to the next level, there’s a lot of hype for AI, but it’s really important not to look at your quality program just as a cost, but to look at the current value that it’s delivering. So much so, “that when you invest in a technology such as AI, is it clearing that bar? It needs to be delivering more value than your current quality program. So it’s a one plus one equals three situation.”

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If you would like to learn more about MaestroQA, request a demo today.

Grading your agents’ customer interactions can be an effective strategy for ensuring best-in-class customer experience. But, maintaining consistency gets complicated as you scale your operation and begin grading for subjective topics, such as empathy.

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That’s why many QA teams calibrate regularly. 

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What does it mean to “calibrate” your QA team? How do you do it? Continue reading to learn the basics about call calibration.

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What is Call Calibration & How Does it Work?

Call calibration is a process where call center agents and supervisors review and assess customer interactions together. The goal is to ensure consistency in evaluating agent performance, aligning standards, and enhancing the accuracy of quality assurance measures.

At a high level, QA teams calibrate to keep graders on the same page. Dan Rorke, Customer Success Manager at MaestroQA, points out, “The whole point is to make sure the QA team is aligned with how they’re interpreting the standards for the CX organization.”

Reviewing the Same Ticket

To get started with the call calibration process, each grader reviews the same support ticket. The ticket could be related to a phone call, email conversation, or live chat, although it’s essential to provide graders with the entire transcript regardless of the support channel. Graders review the ticket independently and then join a calibration session for a team-wide discussion. 

 When choosing a ticket for calibration, there are multiple approaches you can take:

• Target tickets with low QA scores or low Grader QA scores (Grade the Grader) 
• Find particularly challenging tickets or those tied to a problematic topic
• Tickets that are related to a process or part of the product that has recently changed

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Providing Clear Evaluation Criteria

During the call calibration process, offering clear and well-defined evaluation criteria is essential. This ensures that both agents and supervisors have a unified understanding of performance expectations. Clear criteria enable consistent assessment, reduce ambiguity, and promote accurate alignment of quality standards across the call center.

To establish clear evaluation criteria in the call calibration process, begin by outlining specific performance metrics, communication standards, and desired outcomes. Provide examples and reference materials that illustrate these criteria in action. Encourage open discussions among supervisors and agents to ensure a shared understanding. Regularly review and update criteria to reflect evolving customer needs and industry trends, fostering consistent and accurate evaluations.

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Running a Calibration Session

Calibration sessions can take many forms, but at MaestroQA, we see most customers take one of two approaches:

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1. Answer-by-answer review: The meeting organizer shares their screen to show how each grader graded each question in the scorecard. This approach allows graders to explain their processes, especially on varying grades.

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2. Benchmark alignment discussion: Before the calibration session, a “benchmark grader” (usually the QA manager or CX director) will score the customer interaction and prepare an analysis demonstrating the team’s alignment. Large QA teams with many graders may find this more efficient than the previous approach.

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Calibration sessions can include leadership, graders, and even the call center agents. We recommend regularly including different stakeholders outside of graders in the calibration process to ensure alignment across all levels of the organization and to tap into different perspectives of the grading quality standards. 

Spreadsheets vs. Software

QA teams often rely on spreadsheets to facilitate the call calibration process. For example, graders input their scores into spreadsheets. Benchmark graders use spreadsheets to run calculations and determine team alignment. This approach requires considerable administrative work for CX leaders and opens the door to unreliable QA data. “There’s so much data all over the place that it’s tough to track how things are progressing and trending,” Rorke said.

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At MaestroQA, we offer a comprehensive suite of QA features, including several that enhance the calibration workflow. Our team calibration workflow makes it easy to invite graders, collect their responses for a particular rubric, and run successful calibration meetings. Individual scores are organized automatically without copying and pasting from spreadsheets.

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MaestroQA also makes it easier for benchmark graders to perform final calibrations and confidentially share results with graders. When logging into MaestroQA, individual calibrators can see their scores along with the final calibration scores—but not the scores of other graders. 

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Reporting in MaestroQA simplifies analysis and helps QA leaders identify misalignment with graders, rubrics, and other criteria. Interactive heat maps provide a convenient way to drill down into problematic areas and identify opportunities for improvement. Calibration data can be easily exported for offline analysis.

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Continuous Feedback Loop

Creating a continuous feedback loop during call calibration involves regular communication between supervisors and agents. Schedule frequent calibration sessions to review interactions, share insights, and address questions. Encourage open dialogue and the exchange of perspectives to refine evaluation consistency. Emphasize the importance of ongoing improvement and collaborative learning to enhance agent performance and maintain alignment with quality standards.

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Call Calibration Benefits

Regularly calibrating can yield numerous benefits that ultimately support the CX team’s ability to deliver excellent customer service and a consistent customer experience. Here are a few examples:

Grader Alignment

Simply asking graders to participate in a quarterly, monthly, or bi-weekly calibration session might be enough to increase accountability and mitigate the potential for grading bias. Well-run calibration sessions help participants better understand the organization’s expectations, thereby increasing the likelihood of improved grading.

Coaching Opportunities

Analyzing calibration session data can help CX leaders identify graders who may need additional coaching. Grader QA from MaestroQA is a valuable tool for providing structured, one-on-one actionable feedback during coaching sessions.

Strengthening of Standards

Perfect alignment between the benchmark grader and the rest of the team is unlikely. That’s OK. Sometimes misalignment can help the CX organization identify unknown gaps in the customer experience. It’s an opportunity to teach and strengthen the performance standards, including important areas such as soft skills or technical behaviors.

Team Cohesion & Collaboration

Spending most (or all) of the day grading support tickets can cause even the most experienced grader to feel disconnected from the larger organization. Calibrating gives everyone a reason to reconnect, leading to increased motivation, productivity, and job satisfaction.

QA Data

Calibrating produces a new data set that QA leaders can use to measure grader performance. Centralizing calibration data in a system like MaestroQA helps ensure this data's reliability and usefulness. “You have all the data right there, and it makes the process of getting data into one spot easier,” Rorke said.

Capture Feedback for Rubric Improvements

More often than not, calibrations will surface areas of confusion or misunderstanding regarding the interpretation of rubrics and grading criteria. Because of this, calibrations are a great tool to use when launching new rubrics to ensure grading expectations are as straightforward as possible. 

Boost the Impact of Your Call Calibrations with MaestroQA

MaestroQA provides modern QA software that makes call calibrations faster, easier, and more productive. Streamline calibration preparation, grading, analysis, and follow-up with MaestroQA.

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Request a demo to learn more about our call calibration features. 

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As companies seek to thrive in today’s current competitive landscape, customer satisfaction remains a key factor in their success. Identifying and eliminating customer pain points and de-escalating issues quickly to prevent revenue loss is an essential part of this equation. 

That's why we wanted to take a closer look at how Gousto, a leading British meal kit retailer with over 150,000 customers a week, leverages reporting and coaching systems to quickly spot performance trends, uncover threats to customer satisfaction, and boost the performance of their blended team of in-house and BPO agents. 

To get exclusive insights into Gousto's strategy, we spoke with Michael Whittaker, Customer Care Training & Quality Manager. In this blog post, we'll share what we gleaned from Michael so you can learn how to implement these strategies to provide your in-house and BPO partners with the tools they need to elevate customer satisfaction.

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Let’s get started.

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Making the Internal Shift from Cost-Center to Value-Add

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For any business looking to create long-lasting relationships with its customers, having an in-house customer care team can be an invaluable asset when it comes to understanding and engaging with your customers and ultimately driving loyalty and growth. 

To stand out from the competition, however, brands must move beyond viewing their internal customer care as a cost center and embrace it as an opportunity to add value and strengthen their brand. As Whittaker put it: “It's all about delivering unique experiences to customers so that when they think about a brand, they think about choice, convenience, and—most importantly—care. We want to make every interaction of our customer care team a value-add moment in terms of our overall brand image in the market. When a customer calls because they have a problem with a box, we want them to have a warm, informative, and easy conversation with an agent. They should leave that conversation with the agent thinking: “Wow, I really trust that brand to do what's right for me as a customer.”

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Boost Agent Performance With a KPI Dashboard and Gamification

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For Whittaker's team, the MaestroQA KPI dashboard has become an invaluable tool, providing them with a single, centralized source for data. They can use it to review poor CSAT trends and monitor efficiency metrics such as average handle time (AHT) and first call resolution (FCR), as well as to generate ideas for gamification. As Whittaker stated: “The UI of the dashboard is designed like a leaderboard. That is a great inspiration for team leaders to build more gamification into what they do. It's a great visual cue to be like; I have the data now; let's create something from that. Let's create games, let's create competitions, and let's create prizes—all these things. And gamification, when done in a really cool way, is an amazing and positive thing for agents.”

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Leveraging BPO Partners While Maintaining An Internal Customer Support Team

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Creating positive customer experiences is essential to any successful business, but as customer demands increase, it can be difficult to maintain exceptional support experiences at scale without sacrificing quality. To help combat this challenge, many companies outsource their customer support to multiple BPO partners (offshore and onshore).

Gousto implemented this strategy and outsourced up to 70% of their customer support while maintaining a blended solution (internal support team and outsourced teams). “We've learned a lot in the last three to four years about integrating our two BPO partners into the wider Gousto ecosystem,” shared Whittaker. 

One key learning for Whittaker and his team comes from their BPO partners using their own internal QA grading systems. As Whittaker pointed out, “they did everything in Excel spreadsheets – scoring rubrics, and everything else. To this day, I still shudder at the thought, frankly. And over time, we very slowly brought them along that journey of building their own rubric in Maestro and explaining how these different things could work; they adopted it. And now they love it, and they would never go back to using their old methods because it's so much easier, it's so much more centralized. Yeah, again, it goes back to the point of letting BPOs be a BPO, but bring them along your vision.”

With the performance metrics from the MaestroQA BPO dashboard, “you can literally learn with your team leads from your in-house support team, and from your BPOs,” MaestroQA allows “us to get on the same journey with them,” said Whittaker. Each team can “craft their own coaching and performance management identity,” so Whittaker recommends bringing “your BPOs along with you from day one” of using MaestroQA.

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Speaking about coaching…

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The Difference Between Reductive Coaching and Coaching With MaestroQA

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Through data analysis, Whittaker and his team discovered that their high-value customers were churning but that the underlying cause was deeper than they first thought. By taking a closer look at customer-agent conversations, they realized that customers were dissatisfied and frustrated due to the poor quality of conversations. They had a general overview of the issue but realized they needed to look at how agents handled customer conversations.

This discovery led to a bigger challenge - Whittaker and his team were now faced with implementing a coaching system, so they turned to MaestroQA for a solution. MaestroQA's powerful coaching platform enabled them to foster meaningful conversations where all parties had a say, and agents could share their areas of need. The platform also provided a needed layer of accountability for coaches and agents and allowed easy integration with their learning management system. Together, these features enabled Whittaker and his team to move from a reductive coaching environment to one that was truly collaborative.

Now let’s break this all down by allowing Whittaker to share, in his own voice, a real-world example of how his team uses the MaestroQA dashboard for their coaching sessions.

“Before the coaching session, a team leader would use the performance dashboard, and they would maybe have a couple of metrics they want to focus on, potentially link to OKRs for the overall team. And they'd use the performance dashboard to dive deep into some tickets. They do some spot checks in that case. And they started to add to the coaching section a few tickets that really caught their attention, ones that they wanted to chat about in the conversation. 

“On the other hand, agents are also in the Maestro platform looking at their grades, looking at their CSAT tickets, and again, thinking about some things they want to chat about and start adding their notes on areas that they want to discuss within that conversation.

 “And then, the coaching session happens. We start it off with the agent talking us through the cases that they want to talk about—asking them questions like, what excited you about those tickets? What worried you, and what do you want to want to maybe work on? How can we support you with that? And really talk through those examples in detail, record coaching points, record to-dos, that sort of thing. And then we finish off with a big old smile on our faces because it's been a very productive session in that case.”

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Get a sneak peek of MaestroQA’s coaching platform. Watch the video below.

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If you would like to learn more about MaestroQA, request a demo today.

What is DSAT?

DSAT (Customer Dissatisfaction) is the reciprocal metric of CSAT (Customer Satisfaction). DSAT utilizes specific data points to assess whether customers are dissatisfied with an experience. Generally, contact centers tend to overlook DSAT, but it is an important metrics that can reveal useful insights that may be missed when only focusing on CSAT.

1. Identify and Tag DSAT Tickets in Your CRM
2. Conduct Quality Assurance Audits for DSAT Tickets
3. Perform a Root Cause Analysis
4. Apply DSAT Insights to Improve Future Experiences
5. Track the Impact of AdjustmentsDetractors Provide Valuable Data

Your least happy customers might be your most valuable customers—if you get the right data. Hear us out.

If you're in the customer experience industry, you know customer satisfaction (CSAT) data is one of the most popular KPIs. But you might overlook customer dissatisfaction (DSAT) data when you look at customer satisfaction levels.

Digging into negative customer experiences isn't the most fun exercise, but it pays dividends in the long run (and when it comes to customer retention). In this article, you'll learn five steps to turn negative customer experiences into a goldmine of data you can use to elevate your brand and maximize your support agents' potential.

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1. Identify and Tag DSAT Tickets in Your CRM

Customer dissatisfaction (DSAT) is derived from CSAT survey responses. Here's a quick refresher, in case you need it:

Brands send CSAT surveys after customer service interactions. They include one simple question: “On a scale of 1-5, how satisfied are you with the support you received today?” 1 means “extremely dissatisfied,” while 5 means “extremely satisfied.”

Any response labeled as 1 or 2 falls into the DSAT category.

If you don't already, include a free-form text box below your CSAT survey where customers can explain why they gave the score they did. This is crucial for a DSAT analysis (more on this soon).

Once the DSAT tickets are compiled, they can be tagged based on why the customer was dissatisfied. There are three main DSAT categories that often come up: 

Dissatisfaction with Customer Support

This refers to complaints about agent inefficiency, lack of product knowledge, escalation procedures, etc. It also includes frustration with long hold times or having to reach out multiple times to resolve an issue.

Dissatisfaction with the Product or Service

If a dissatisfied customer issue stems from a defect, bug, missing/broken part, etc., it falls into this category.

Customers might reflect a bad experience with a product or service in their CSAT response—no matter how friendly or efficient the agent is. These types of issues are rarely under the agent's control, but they still yield valuable feedback to pass along to other departments, such as the product team.

Dissatisfaction with Company Policies

It's common for customers to get frustrated with company-wide rules and regulations. This includes return, exchange, and refund policies, hours of operation, or other policies that fall outside the CX department's control.

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2. Conduct Quality Assurance Audits for DSAT Tickets

A round of Quality Assurance (QA) audits adds additional context to DSAT tickets, namely the ones that involve customer support processes.

A QA audit involves reviewing a customer-agent interaction to determine how well the agent performed and adhered to the brand's standards. Depending on your volume of DSAT tickets, a QA analyst or CX leader can audit every ticket or a sample. The more data you collect, the more accurate your insights will be.

Every QA audit starts with a QA scorecard. This is a rubric based on a company's values and standards for agent-customer interactions. QA scorecards are a roadmap for agents to sharpen their skills; they provide measurable metrics that impact customer satisfaction and customer loyalty.

Here's an example of what a QA scorecard looks like:

‍Put simply, DSAT data alone tells you if customers are unhappy. But QA audits tell you why.

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3. Perform a Root Cause Analysis

QA audits aren't the only way to identify the underlying cause(s) of dissatisfied customers. Let's look at two root cause analysis (RCA) methods that are beneficial for CX teams.

Fishbone Diagram

A fishbone diagram (also called a fishbone analysis) is a visual representation of cause and effect. The problem is listed at the “head of the fish,” and the potential causes are listed on the “bones” of the fish in varying categories or areas.

Here's a brief example in the context of CX:

• Problem: Multiple customers are complaining about long hold times with agents.
• Area: Staffing > Cause: Not enough agents to handle call volume during the holiday season.
• Area: Coaching > Cause: Coaches don't place enough emphasis on Average Handle Time (AHT) in 1:1 coaching sessions.

The main benefit of the fishbone diagram is that it keeps the focus on the causes of problems rather than symptoms.

5 Whys Technique

As the name implies, the 5 Whys Technique involves asking “Why?” five times when you encounter a problem. This might sound simplistic, but it can uncover unexpected insights.

Let's say a customer indicated they were “very unsatisfied” in their CSAT scores. Here's a 5 Whys sequence that might follow:

• Why? The customer had to reach out multiple times to resolve an issue
• Why? The agent didn't have adequate knowledge about the product/service
• Why? That specific detail wasn't covered in the onboarding process
• Why? The onboarding process hasn't been audited in 6 months
• Why? Leadership is stretched too thin

Just like the fishbone diagram, this technique keeps you focused on the essence of the problem instead of surface-level observations.

4. Apply DSAT Insights to Improve Future Experiences

Once you get a firm grasp of the support- and non-support-related issues leading to DSAT, put those key learnings to use. Here are four types of changes CX teams can implement with DSAT data:

Improve Your Agent Onboarding Experience

Get ahead of customer complaints by training new agents on red flags to look out for. Some teams have to learn lessons the hard way first, but documenting those experiences prevents newer agents from running into the same issues down the road.

This can range from product knowledge to specific language that resonates well with your audience.

Inform Customer Service Coaching Sessions

Let's say through QA audits you discover agents are asking customers for information that's already available in your CRM, leading to unnecessary customer effort. In this case, you'd tailor coaching sessions to teach agents how to track down past customer conversations in your CRM so they can get that information on their own moving forward.  

The more your coaching sessions are informed by fresh data, the more impactful they are.

Expand Your Internal Knowledge Base (IKB)

DSAT insights don't do any good sitting around collecting digital dust. This is an opportunity to create or expand a living, breathing resource for agents.

Consider the ride-sharing app Lyft, which struggled to formalize knowledge for its CX teams. For example, agents were unsure what types of vouchers they should offer to customers, which backed up their queue.

MaestroQA helped them implement a knowledge base in tandem with a QA program. The result? Lyft's senior agents were freed up to focus on the tickets in their queue, reducing their Average Handle Time and improving agent productivity.

Suggest Company-Wide Changes

If DSAT stems from an issue outside the CX team's control, don't ignore it. It's important to share your insights with other departments, especially since CX teams are on the front lines interacting with customers every day.

This includes suggestions for user experience (UX), product design, billing policies, shipping, and other ways to drive customer loyalty.

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5. Track the Impact of Adjustments

Ideally, the data-informed changes you make are reflected in the form of improved CSAT scores and QA scores—but there's only one way to find out. Prioritize monthly reports to measure the impact of those adjustments.

Dedicated customer service coaching platforms offer 360-degree insights and even correlated CSAT scores with QA scores, so you get the full story on agent performance.

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Detractors Provide Valuable Data

Learning about why customers are unhappy can be disheartening for customer support organizations to study. As a result, companies often ignore DSAT data, and only pay attention to CSAT data from satisfied customers. Or they collect it but don't act on it. But as you can see, digging into DSAT measures is an effective way to identify and improve your company's weakest links. By following the steps above, your DSAT analysis will pave the path for elevated agent performance, happier customers, and improved customer loyalty.

Want to start uncovering more actionable CX insights? Request a demo of MaestroQA today.

Remember Apple’s Genius Bar—dedicated spaces in Apple stores for friendly, technical support? When the program launched, it was lauded for its personalized customer service. 500 Apple stores later, customers can’t stop complaining about the terrible service they offer. Scaling customer service quality is hard, even for a giant like Apple.

Each growth spurt in a startup’s journey brings new customers and customer service requests. For most teams, this results in a decline in support quality: long wait times, impersonal service, and inefficient processes.

A customer service quality assurance program ensures your customer service doesn’t go from five-star to DMV-level like Apple’s did. It helps you standardize good customer service practices as you grow from 10 to 100 to 10,000 customer service agents.

What Is Customer Service Quality Assurance?

Customer service quality assurance (QA) is the process of reviewing customer service conversations with the goal of delivering high-quality support.

Quality customer support could mean different things to different businesses, but in general, it includes: using the right tone and language, following protocols, solving customer problems efficiently.  Quality assurance ensures these goals are achieved consistently and helps detect any inefficiencies in the process.

To conduct a customer service quality assurance review, a QA manager listens to or reads customer support conversations across channels like email, phone, live chat, and social media and checks if they meet accepted standards of quality support against a quality assurance scorecard. Findings from these reviews are then used to coach agents for improvement.

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3 Ways Customer Service Quality Assurance Helps Scaling Businesses

A customer service quality assurance program helps you standardize good support practices in your organization, irrespective of the size of your support team or the volume of tickets you receive.

Over time, quality assurance helps you:

Proactively improve agent performance

Agent unfriendliness, long wait times, and ill-trained agents are common causes of bad customer service. Customer service quality assurance helps prevent these by identifying where they occur in customer interactions, helping teams avoid the same mistakes again.

Deliver great customer service at scale

Delivering consistent, quality support should be a top priority for growing businesses, as it influences customer loyalty: 52% of customers go out of their way to buy from brands they love. Quality assurance helps you achieve consistency in service, no matter how large your support team grows.

Regular quality assurance reviews allow you to benchmark good support practices—the ideal tone agents should adopt, the fastest resolution times they can achieve without sacrificing quality, the tools they should use to be more productive. As you onboard new agents to meet growing support needs, you can use these as guidelines to train them. This ensures your support quality remains uniform and brand-focused.

Boost agent morale

Happy agents are more likely to feel empowered to solve customers’ issues. They’re also more likely to stay with your organization. Quality assurance is a good way to keep agents motivated.

Discussing quality assurance results with agents on a weekly or monthly basis helps them see the areas where they need improvement and areas where they’ve made progress.

What’s more, when managers conduct quality assurance reviews, they can identify instances of great customer service and reward agents. This improves agent morale and encourages them to do better.

All in all, a customer service quality assurance program is good for your team, customers, and, ultimately, your business.

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How to Create a Customer Service Quality Assurance Program for Your Team

An effective customer service quality assurance program is the result of clear customer service values, a QA scorecard to evaluate conversations, and an actionable plan for your support team to follow through on support reviews.

Define your customer support values

The first step in creating a customer service quality assurance program is to define your customer support values. Your support values are an extension of what quality support means to you—they help you prioritize areas of customer support when grading conversations.

Ideally, your support values should reflect customer expectations, your brand values, and your team’s interests. Thus, your business might emphasize speedy responses and ownership, while another may focus on empathy and injecting humor into support conversations. It helps to revisit your support values as customer expectations and your brand evolve.

Take a look at Intercom’s support values: “thriving under pressure,” “connecting personally with empathy,” “being an owner,” and “being resourceful.” When they conduct support conversation reviews, they look for these qualities in their agents.

Create a QA scorecard

A quality assurance scorecard (also known as a rubric) is the backbone of your customer service quality assurance program—it allows graders to check if agents meet your support quality requirements.  A QA scorecard consists of two components. The first is a questionnaire, the questions for which are based on your support values. The second component is a system to grade agents for each question.

Questions in a scorecard might include “Did the agent follow X process?” or “Did the agent identify the customer’s issue correctly?” Most scorecards organize questions under different aspects of support such as brand and tone, protocols, and efficiency.

As for the grading system, graders might assign points or a grade for each question, based on whether or not an agent completed a specific task correctly. In some cases, they may assign additional or negative points to important questions or assign scores for each question on a scale of 1–10.

Here’s a sample question from a QA scorecard:

In this case, a grader might assign 0, 1, or 2 points to an agent, based on whether they used the right tone and terminology.

If you haven’t created one yet, here’s an in-depth guide on creating your first QA scorecard. It covers everything from generating a list of questions to the best grading scale to use to measure your support team's performance.

Hire a specialist or set up a QA team

When support requests pile up, customer service quality assurance often falls by the wayside in favor of recruiting, onboarding, and reporting. An independent specialist or dedicated team for QA helps you avoid letting QA take a backseat.

For businesses with a large support team, it makes sense to hire a QA specialist for grading support conversations. A specialist may focus only on grading customer service conversations, as well as provide in-depth analysis and suggestions.

But if you’re a startup with a small support team, you may want to set up a quality assurance team consisting of senior support managers and team leaders. Such a team can funnel their expertise and knowledge into performing quality assurance reviews. You’ll want to ensure they can keep up with quality assurance in addition to other responsibilities.

Teams with an open and accessible culture can also do peer-to-peer quality reviews.

Choose the right conversations to review

Choosing the right number and type of support conversations you review ensures you’re not spending too much time on grading, getting an incomplete picture of customer support, or missing important customer service insights.

Most teams review between 1% and 5% of customer service conversations. Smaller teams with dedicated QA specialists may review at least 5%. The number of conversations you review depends on the resources you have at your disposal and the volume of support conversations you receive.

When it comes to the type of conversations to review, it’s best to keep it random so you’re getting a holistic picture across all channels. You’ll also want to keep an eye on problem tickets. For instance, the team at MeUndies makes it a point to grade tickets with low customer satisfaction (CSAT) scores, in addition to reviewing tickets randomly. This helps them delve deeper into why customers were unhappy with an interaction.

Make it scalable

Scalability makes your quality assurance program easy to manage, even when the number of agents on your team increases or support conversation ticket volume grows.  

Your QA program’s ability to scale depends on the processes and tools you choose to manage it. While small support teams often run their QA program on Google or Excel spreadsheets, such systems often fall apart when ticket volume increases. Graders end up spending more time navigating spreadsheets than on grading and analysis.

To make your QA program easy to scale, consider investing in a dedicated QA tool such as MaestroQA. A specialist QA tool provides graders with automated conversation review suggestions for different support channels, a simple way to log scores and feedback, and an organized dashboard to coach agents.  Ultimately, it helps graders review a large number of support conversations in a more efficient way.

MaestroQA also has a screen capture feature that allows QA mangers to look at a specific moment in the customer-agent conversation from the agent’s perspective. With this tool, QA managers can identity gaps in workflows and resources that are inhibiting their teams from performing at their best.

Use QA to coach your team  

For quality assurance to improve your support team’s performance, you need to use QA findings to actively coach your team.  

To keep your reps focused on improvement as their ultimate goal, Jeremy Watkin, director of customer support and CX at NumberBarn, recommends not giving agents their QA score until they’ve been coached. Coaching should focus on what the agent did well, where there’s room for improvement, and practicing desired behaviors together.  Then, at the end of the session or in a separate session, managers should provide QA scores.

Apart from using QA for individual coaching, you can also use it to spur team-wide improvement. For instance, Postmates runs a monthly team-wide “State of Quality” presentation to provide actionable insights from QA data. This helps their team learn from one another’s hits and misses.  

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3 Tips for Creating a Customer Service Quality Assurance Scorecard

The success of your QA program depends largely on your quality assurance scorecard—the better your QA scorecard, the more accurate your QA findings will be, and the more efficiently your graders can do their job.  

Here are some tips to make your QA scorecard more effective:

Keep it simple

You might be tempted to create a QA scorecard with hundreds of grading criteria and a complex grading scheme. But think of all the work it will create for graders and how difficult it will be for agents to interpret scores. A simple QA scorecard will save graders’ time and be easy to manage, even when demands increase.

Two cardinal rules for a simple QA scorecard: Keep it short and stick to a simple grading scheme.

Take a look at this simple quality assurance rubric from eero:

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It only has three grading criteria and a simple Pass, Fail, Coach system to grade agents.  

It also helps to better organize questions in your scorecard, either according to the areas of customer support they relate to or the order of a regular support conversation.

For example, questions related to tone, language, and brand voice could be grouped together. Or questions like, “Did the agent greet the customer in a friendly manner?” could be at the beginning of a scorecard, and “Did the agent thank the customer?” at the end.

Align your scorecard with customer expectations

The goal of a quality assurance program is to ultimately improve customer experiences by improving agent performance. Thus, you don’t want to create a QA scorecard without any real customer expectations or insights to guide you. If that happens, you’ll find your QA scores may be high, but your customer satisfaction scores still remain low.

To align your QA scorecard with customer expectations, keep an eye on metrics like CSAT, Net Promoter Scores (NPS), and first response time (FRT). You also want to track customer feedback in support tickets and on social media. This gives you a more holistic picture of the quality of support that customers expect from your brand.  Use those findings to tweak your scorecard.

For instance, it’s possible your customers care greatly about personalization and empathy, but your scorecard only prioritizes quick responses within a certain timeframe. In this case, it would make sense to assign equal weight to both of these aspects on your scorecard.

Clarify grading criteria

Clear grading criteria keep grading uniform and objective. As Intercom found in their peer reviews, a lack of clarity around “good tone” resulted in three different evaluations of the same conversations.

To bring more clarity to graders, break down subjective aspects of support such as tone of voice, empathy, and clarity into specific qualities graders can pinpoint. Share your scorecard with agents for transparency so they know what a good experience looks like, but make sure grading criteria are easy to remember and not complex.

For example, Intercom uses a  simple acronym, “PREACH,” to evaluate conversations. It stands for “proud, responsible, empathetic, articulate, concise, and human.” It’s easy to remember and helps graders check if agents use the right tone of voice in a conversation.

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Customer Service Quality Assurance Checklist for QA Managers

As you try to scale customer service quality, a customer service QA checklist can be a great resource. It ensures you don’t overlook an important aspect of quality customer support when creating a questionnaire for your QA scorecard.

In this checklist, we’ve organized various support criteria around the pillar framework, which defines quality customer support as being comprised of three main pillars: soft skills, issue resolution, and procedure.

Customer Service Soft skills

• Grammar and spelling: This includes correct punctuation, spelling, and construction of sentences.
• Tone: Good tone includes slow, thoughtful responses, use of positive language, and flourishes like thanking and welcoming the customer.
• Empathy: Empathy means using phrases like, “I understand your concern” or “I would’ve felt the same way.”

Customer Service Issue resolution

• Effectiveness: This includes a few different aspects: identifying the customer’s issue correctly, resolving the issue on the first try (first contact resolution), and reducing customer effort.
• Clarity: This means using simple language, free of jargon and complex sentences.
• Product knowledge: This refers to accuracy in product-related answers, knowledge of key product features, troubleshooting, and staying updated about product changes.

Customer Support Procedure

• Productivity: This means resolving issues swiftly without hurting support quality. It includes presence of mind and the ability to find the right information quickly.
• Compliance with processes: This refers to how well agents use internal support tools and resources such as a knowledge base and canned responses. It also includes tagging tickets correctly and routing or forwarding calls with care.
• Compliance with privacy policies: This consists of regulations your reps need to comply with, such as PII (personally identifiable information) or HIPAA (Health Insurance Portability and Accountability Act), and declaring that a call may be recorded.  

You don’t have to grade each conversation for each of these criteria, but it’s a good starting point for creating your own scorecard or adding questions to an  existing one. Note that it works for both written and oral customer service conversations.

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Takeaway: Customer Service Quality Assurance Lays the Foundation for Growth

As businesses scale, their customer service quality should, too, or it will become their weak link.

When mattress startup Amerisleep launched, they noticed how their competitors Mattress Firm and Sleepy’s had “grown so big, they’d forgotten to empathize with customers.” They decided to use it to their advantage. This scenario plays out a hundred times in the startup world. Companies grow quickly, but support quality doesn’t scale—it worsens. New startups use this shortcoming to fuel their growth.

Customer service QA allows businesses to grow without the fear of poor customer service bringing them down. Over time, it makes high-quality customer support their secret weapon against new players.

If you need help scaling your customer service processes with quality assurance, request a free demo with MaestroQA today.

“I talked to an agent yesterday, but I still need help…”

Your customers want to avoid contact center conversations that start like this. 

But, when they’re unable to achieve their goals, they’ll go to great lengths to get the answers they need. And, for your customer service team, that can mean countless conversations, chats, and emails that can artificially inflate your call volume numbers.

In your customer’s ideal world—and, yours too—every request would be solved on the first customer support interaction. We don’t live in a perfect world, but there are steps you can take to improve an important metric: first call resolution.

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What is First Call Resolution?

So, what exactly is first call resolution (or “FCR,” for short)?

First call resolution—sometimes referred to as “one call resolution” or “first contact resolution” on omnichannel customer experience teams—is the rate at which support tickets are resolved on the first call or contact (chat, email, etc.). First call resolution rates are typically expressed as a percentage of all calls a support team handles. 

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How to Measure First Call Resolution

To calculate the first call resolution rate for your company, divide the number of support tickets that were resolved on the first contact by the total tickets from the same period. (If your company routinely deals with complex or technical requests that cannot reasonably be solved on the first interaction, you may want to exclude those from the total number of tickets.) Expressed as a formula, your FCR rate looks like this:

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For example, let’s say that customers opened 1,200 tickets last month and 600 were resolved on the first contact. You guessed it—your first call resolution rate is 50%. Not bad, but you definitely have room for improvement!

Remember, FCR is concerned with one thing and one thing only: whether or not the customer’s issue is resolved on the first interaction. Note that FCR does not factor in the efficiency of the first call or contact. This means that improving FCR may come at the expense of other efficiency-based metrics, such as AHT (average handle time). Solving a customer’s problem on the first interaction means that your agents will need to spend more time clarifying questions, getting to the root cause of an issue, and checking for other problems. In the short term, FCR may actually lead to a slower support process—but one that’s much better for your customers, your agents, and your CSAT rating! ⭐⭐⭐⭐⭐

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Why Improving First Call Resolution is Important

If FCR has an inverse relationship with AHT and other efficiency-based metrics, why spend any time thinking about it? Good question! Here are three big reasons:

Improves Customer Satisfaction (CSAT)

Customers dread being placed on hold, getting transferred to other agents, and explaining their situations over and over again. Forcing customers to expend a lot of energy is not a good idea. And, doing so will only erode your CSAT (customer satisfaction) score in the long run. In fact, one support metric—the Customer Effort Score (CES)—actually measures customer satisfaction in terms of the ease or difficulty of the interaction. 

Key takeaway: Customers want easy—not difficult. They want one interaction with support, not a bunch. Give customers what they want, and you’re sure to see a boost in CSAT.

Increase Customer Loyalty

Highly satisfied customers become loyal customers. Frustrated customers, on the other hand, are far more likely to shop for alternatives and churn. Having customers jump through hoops to resolve their issues provides a poor experience, which is a big reason why people get frustrated and leave.

Key takeaway: Solving issues on the first call reduces friction and sets the stage for long-term relationships.

Enhance Agent Performance and Efficiency

Say what? Yes, you read that right. Improving FCR can actually have a positive impact on agent productivity. But, what about FCR’s inverse relationship with AHT and other efficiency-based metrics? It all comes down to perspective. Is your goal to “handle” customers in the least amount of time possible? (That’s what AHT basically measures.) Or, are you in the business of helping customers achieve their goals so that they become brand advocates? Pressuring agents to close out tickets as quickly as possible helps no one—including your agents. 

Your agents want to make a difference. They want to help customers become more successful and feel fully satisfied with the experience. Prioritizing first call resolution encourages agents to do exactly that. It also unleashes their creativity to identify opportunities to efficiently serve customers, which leads to process improvements and long-term value.

Key takeaway: Focusing on first call resolution increases support agent efficiency by aligning their actions with their desire to help your customers. It also leads to healthier internal conversations that elevate the team’s productivity.

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Industry Standards for First Contact Resolution: What’s a Good FCR Rate?

So, what’s a “good” FCR rate? Well, the answer could vary depending on your industry, business, and support model. Having said that, there are no first call resolution best practices that apply across the board.

According to research from MetricNet, a leading source of online benchmarking data, 74% is about average. That being said, MetricNet also noticed a wide variance in the data set. Some service desks scored in the low 40% range, while high performance teams scored up to 94%. The difference? The data shows that top support teams are highly skilled, well-trained, and possess the right tools to deal with almost any customer request.

Industry standards aside, experienced customer service leaders realize the importance of tracking FCR data for their specific companies and industries. Start by collecting reliable data from your support operations and compare it to industry-specific best practices. Let data guide your decision-making for improving FCR.

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How to Improve First Call Resolution

Speaking of improving FCR, here are a few approaches that have worked well for our clients:

✔ Diagnose the Root Cause of Bad FCR, Not the Symptoms

Customers don’t have perfect knowledge of your products and services. As a result, they often use words that describe the pain that they’re experiencing instead of the underlying problem. Your agents need to know how to ask the right questions to get to the root cause of the issue. Doing so reduces the chance that a customer will call back in the future, thus improving FCR.

✔ Preempt Customer Issues that Stem from A High First Call Resolution Rate

Sometimes, a customer engages in a repeat call because they simply forgot to ask a related question. That’s why it’s a good idea to send follow-up emails that contain helpful documentation. Many customers prefer a self-service support model, and online documentation aligns with that preference. Getting answers from a help site is much faster and more convenient for the customer—and eliminates unnecessary interactions with your support team.

✔ Provide Agents with the Right Tools

To thrive, your support agents need more than a basic online ticket management system. Smart customer service leaders empower agents by implementing a variety of tools that elevate productivity, streamline learning management, and encourage customer self-help. For example, WP Engine recently integrated their online knowledge management solution using QA data from MaestroQA to close knowledge gaps and increase agent performance. An appeasement chart is another excellent tool that helps agents provide resolutions and prevent further escalations.

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Why Trustworthy QA Data is Critical to Understanding First Call Resolution

Now that we understand what FCR is and how we should improve it, we need the last piece in the puzzle—data. 

Data helps answer these questions: What’s your next move? Should you scrap your current training program and start all over? (Answer: Not just yet!) Do you need a better knowledge management system? More workflows and better emails? Before you make any big changes, go back to your support data and check for (and eliminate) any experience blindspots.

Tracking FCR is a good idea, but it will not eliminate your experience blindspots. Here’s why:

If you’re like most support teams, you probably use CSAT and/or Net Promoter Score (NPS) to measure customer satisfaction. As we’ve already discussed, focusing too much on efficiency-metrics—like AHT—can actually detract from the customer experience. And, although FCR is arguably superior to AHT, at the end of the day it’s still an efficiency metric that can be manipulated. Not every ticket can be resolved on the first interaction. However, if agents are overly focused on first call resolution, they may take undesirable actions that artificially lower FCR at the expense of customer satisfaction. Keeping a customer on hold for 20 minutes to avoid a transfer defeats the purpose! ⏰

That’s where trustworthy QA data comes in handy: 

Agent Adherence: QA serves as a check to ensure that your agents are following your FCR best practices. So, as you start to implement programs aimed at boosting your FCR rate, you can have confidence that agents aren’t gaming the system just to make their stats look good. 

Maximizing FCR: QA data is key for surfacing new insights to further increase FCR. Check out how popular ridesharing service, Lyft, increased their FCR rates by using QA data to identify product and policy knowledge base enhancements.

360-Degree Insights: Last, but certainly not least, QA data enriches all of your other metrics and helps you get the full story behind agent performance. For example, QA data might surface new coaching opportunities for an agent with a high FCR rate but low CSAT score (read: the agent tends to rush through tickets without getting to the bottom of the problem).. 

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First Call Resolution Best Practices

Develop a knowledge base with common questions and problems

In the realm of customer service, developing a comprehensive knowledge base brimming with common questions and solutions stands as a pivotal best practice for achieving stellar First Call Resolution (FCR). This knowledge base of information empowers customer service agents by providing instant access to tried-and-true solutions, enabling swift issue resolution. By preemptively addressing frequently encountered problems, businesses can proactively serve their customers, leading to higher satisfaction rates and reinforcing brand loyalty. [h3] Use automated call routing

Answer support questions quickly

Rapid responses not only enhance customer satisfaction but also save time and resources. By addressing concerns promptly, businesses foster trust, improve customer loyalty, and elevate their brand reputation. Moreover, fast issue resolution significantly impacts customer retention, making it a cornerstone of exceptional customer service and positive online reviews.

Use active listening

Active listening is the linchpin of First Call Resolution. By genuinely engaging with customers, agents grasp concerns accurately, leading to precise solutions. This empathetic approach not only resolves issues promptly but also enhances customer satisfaction. Active listening fosters trustand elevates the overall customer experience to reinforce brand loyalty, making it a crucial FCR strategy.

Perform comprehensive agent coaching

In the pursuit of exceptional First Call Resolution, investing in comprehensive agent coaching is indispensable. Thoroughly trained agents can adeptly handle customer queries, ensuring swift issue resolution. Contact centers can use quality assurance (QA) procedures to validate the effectiveness of training, guaranteeing consistent service excellence. Empowered agents equipped with extensive knowledge not only enhance FCR rates but also foster lasting customer satisfaction and loyalty. This emphasis on training stands as a crucial element in elevating overall customer service standards within contact centers.

Use a CRM with customer history

Leveraging a CRM enriched with detailed customer history is paramount for achieving First Call Resolution. Equipped with this wealth of data, agents can swiftly access past interactions and preferences, facilitating tailored solutions that boost customer satisfaction. This strategic use of CRM insights not only enhances FCR rates but also strengthens customer loyalty by delivering efficient and personalized support.

Establish follow-up procedures

After the initial call, following up with customers ensures satisfaction and addresses any residual concerns. Proactive engagement not only resolves potential issues but also strengthens trust. This approach enhances FCR rates by guaranteeing comprehensive issue resolution and nurturing lasting customer relationships, vital for business success.

Conduct root cause analysis

By conducting meticulous root cause analysis of customer queries, agents can identify the core issues triggering concerns and businesses can implement targeted solutions that prevent recurrence. This proactive approach not only resolves problems swiftly during the initial call but also fortifies the system against future challenges. Addressing root causes ensures sustained FCR success, fostering trust and satisfaction among customers, and reinforcing a positive brand image in the competitive market landscape.

Regularly collect performance metrics and feedback

In order to identify agent strengths and areas for improvement, contact centers should regularly measure FCR rates and gather customer feedback. Analyzing these metrics provides valuable insights into agent performance and customer satisfaction levels. This data-driven approach enables businesses to make informed decisions, refine strategies, and ensure efficient issue resolution. Regular feedback loops not only enhance FCR rates but also foster continuous improvement for agents and contact centers alike.

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Foster a collaborative environment

When agents work cohesively, knowledge is shared, enabling swift issue resolution. In a collaborative environment, agents pool their expertise and insights, ensuring efficient problem-solving during customer interactions. This collective effort enhances FCR rates significantly. By encouraging teamwork, businesses not only resolve issues effectively but also cultivate a positive work culture.

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QA Data as a Catalyst for Improving First Call Resolution

Looking for reliable QA insights to help your support team elevate the customer experience and boost your FCR rates?

Take a tour of MaestroQA and request a free demo.

Customer service teams are facing a perfect storm: delivering exceptional support experiences at scale without sacrificing quality. As customer demands continue to rise, businesses are turning to multiple BPO partners (offshore and onshore) to create a seamless support experience. But how can you ensure that your outsourced customer service agents are performing at their peak? 

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In this blog, we'll uncover four essential strategies to help drive better BPO performance. Drawing on insights from a recent discussion with Justin Evans, Senior Strategist for Salesforce and CX expert with 15+ years of experience designing and delivering exceptional customer experiences for brands like Saks Fifth Avenue, HBC, and Hertz, we'll explore how the Champion-Challenger model can be leveraged to reward the best-performing BPOs with more support volume – the result is higher-performing agents and happier customers.

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Let’s get started. 

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Leverage the Champion-Challenger Model: Ensure Your BPO Partners Are Meeting the Highest Standards

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For companies looking to optimize their business process outsourcing (BPO) partnerships, the Champion-Challenger model is quickly becoming the go-to strategy. This model allows companies to ensure that their BPOs meet the highest standards.

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For Evans, the decision to outsource their contact center operations was driven by high attrition and turnover within their internal customer support call center. While outsourcing provided a cost-effective solution, Evans recognized the risk of relying on a single BPO. “If you have all of your volume with one vendor, that vendor controls you,” said Evans. To mitigate this risk, they adopted the Champion-Challenger model and leveraged multiple BPOs to ensure maximum efficiency and performance. This approach allowed Evans to benefit from the advantages of outsourcing while still protecting the organization from potential vulnerabilities, such as unforeseen technology issues or challenges with the weather.

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“Being able to space the volume out is really important, and it gives you a fighting chance; if that particular site goes down, the other sites can pick up that volume. You might not make service level that day, but you're not completely shut down,” said Evans.

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How the Champion-Challenger Model Works

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The Champion-Challenger model is based on creating a “competitive environment” between BPOs in terms of volume and quality. This ensures that companies are not simply measuring their BPOs against predetermined KPIs such as service level, average handle time, and first contact resolution but rather comparing the performance of one BPO against another. “It gave us that extra opportunity within the contract to say: It's not just good enough to hit the metrics,” said Evans.

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This form of competition pushes both BPOs to strive for excellence, as the “champion” BPO is the one with the highest performance. The “challenger” BPO must strive to be better than the champion to secure the volume.

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The Champion-Challenger model allows much more flexibility in choosing the best BPOs for the job, as well as allowing you to reassess the performance of your BPO partners continually.

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Furthermore, by providing the incentive of competition, the model encourages BPOs to go above and beyond what is expected. This, in turn, results in better value for money and greater customer satisfaction.

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How to Implement the Champion-Challenger Model

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To implement the Champion-Challenger Model, it is essential to engage in conversations with each BPO. The dynamic of these conversations should focus on how the Champion-Challenger model can be adjusted to benefit the team and improve customer experience. Evans suggested writing clauses into the contracts that give the team the ability to move volume, and that includes bonuses and penalties for hitting any agreed-upon KPIs. Additionally, Evans recommended including a clause that allows the team to move volume without justification up to a certain percentage. This clause should also focus on performance as well as cost.

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That being said, when it comes to workforce management teams, it is critical to be careful and strategic in order to ensure proper ramp-up. “Having a locked forecast is not enough; you also need to have a flash forecast in place and be able to communicate it,” said Evans. This will help you to be proactive and make changes in certain periods, such as the beginning of the quarter. By communicating the percentage of the volume that will be moved, the BPOs will understand the timeline (30 or 60-day advanced notice) and can have an opportunity to pursue the volume back. “When you create a little bit of a window, it gives hope and a reason to make an adjustment. And it is more collaborative when you have that mindset. And so that it's not a devastating blow when you give them an opportunity to improve, which is significantly more morale boosting,” said Vasu Prathipati, CEO and Co-Founder of MaestroQA. Therefore, Evans suggested having consistent conversations with the BPOs on a weekly or monthly basis. 

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Create a Collaborative Culture: Ensure Exceptional Customer Service in Your BPOs

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Creating a collaborative culture between your BPO partners can be challenging but far from impossible. Collaboration is essential to a successful partnership, and it all starts with a willingness to give and receive feedback between the two parties.

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Evans shared an excellent example of a customer that “had a whole day dedicated to bringing their BPO partners in and creating a “one team, one dream” mentality. This was a great way to foster collaboration and break down any competitive walls that may have been there. Once the two parties saw how their collaboration could help their customers and each other, it was a game-changer.

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So, what should a collaborative culture look like? The best way to know if you have a culture of collaboration in place is “when your BPO partners are quick to identify customer friction points and suggest process changes. When they come to you regularly with ideas on how to improve policies, such as those related to merchandise not received or shipping delays,” said Evans,  that’s when you know you have a successful collaborative culture.

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It’s also important to give your BPO partners the resources and autonomy they need to do their jobs effectively. This may mean giving them the freedom to make decisions and offering flexible working arrangements. By doing this, you’re showing your BPO partners that you trust them and respect their expertise.

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Finally, it’s important to keep communication lines open. Regular check-ins, feedback sessions, and clear goals and expectations can go a long way in maintaining a healthy collaboration. “I constantly reminded our BPOs that they represent our brand, so we have to work together as a team. That helps bring a lot of comradery amongst the BPOs,” said Evans.

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When a BPO becomes a part of your brand, your customers win.

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Achieve Optimal Performance: Leverage QA Metrics to Measure People, Processes, and Technology

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When optimizing BPO performance, quality assurance metrics are key. But what metrics do you use? As it turns out, the answer isn’t as simple as it may seem.

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“We were leaning heavily on our net promoter score. And what we noticed in our NPS scores was that when we looked at the detractors, we could break it down into three buckets: people, process, and technology. And so when we were going through the implementation with MaestroQA, our QA score form was into those three categories,” said Evans. 

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These three buckets allowed the company to evaluate its performance against each BPO and decide where to shift volume. This deep dive into QA metrics via the MaestroQA platform provided a valuable means of evaluating the performance and effectiveness of their BPOs. “We could rate interactions on a few people-related factors, like how well agents were greeting the customer, their sentiment and attitude, and whether they were following the process. We also looked at whether they understood the policies well and whether they could correctly use the technology we had put in place.”

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Evan and his team were also able to look at the number of customer escalations, customer satisfaction scores, customer retention rates, and other key indicators. These QA metrics are essential for companies to have in place to ensure their BPOs deliver optimal performance.

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Speaking about QA…

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Before using MaestroQA, the quality assurance process was largely manual for Evans and their team. They relied heavily on Excel spreadsheets, which made it difficult to track how their BPOs were adhering to their contractual agreement regarding the number of interactions an agent was to be scored on. As their business scaled, this lack of oversight caused further problems. “We really didn't have a good system in place that helped us better understand our agent population,” said Evans. For example, “Jason might be performing really well on what he was QA'd on, but he may not have the knowledge of post-purchase interactions. On the other hand, Mary might be a star at merchandise not received claims, but Jason might be failing at that, yet very good in product inquiry. We wanted to build this insight into a dashboard so that we could better understand how our agents were growing and where to focus our coaching opportunities, as well as build the right agent base for the contacts our company was receiving.”

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Leveraging MaestroQA’s reporting platform, Evans and his team were able to gain valuable insights into the performance of each BPO. This granular level of detail allowed them to make informed decisions on where to affect changes and optimize their processes.

Take your BPO Performance to the Next Level With a Fully Integrated Salesforce + MaestroQA Tech Stack.

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Customer service and support are critical components of any successful business. As customers become more demanding, companies increasingly turn to technology to provide a better customer experience. 

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Watch the video to learn more about utilizing a fully integrated Salesforce + MaestroQA tech stack to centrally manage and report on quality assurance to optimize the customer support experience.

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If you would like to learn more about MaestroQA, request a demo today.

Managing a customer support team without tracking key performance indicators (KPIs) is like taking a road trip in a foreign country without a GPS: confusing, stressful, and inefficient.

Monitoring customer service KPIs gives CX leaders a clear view of agent performance and the effectiveness of their coaching processes—both of which impact the company’s bottom line. You might be familiar with some foundational KPIs, such as CSAT. But did you know there’s another subset of advanced metrics you can track to level up your customers’ experience?

In this article, we’ll discuss two tiers of customer service KPIs:

1. KPIs for Agent Performance, which are foundational metrics every CX team needs to track
2. KPIs for CX Process Insights, which are for advanced CX teams

Let’s get started.

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Tier One: KPIs for Agent Performance

This first tier of KPIs gives customer service leaders and stakeholders a valuable look behind the scenes at how well agents interact with customers and where there are areas for improvement. These are standard metrics every team needs to monitor.

The first three KPIs measure agent performance directly, and the last two evaluate customers’ perceptions of an agent or the company in general.

1. Quality Assurance (QA) Score

QA scores offer a powerful snapshot of how agents perform relative to the company’s standards for quality interactions. This is almost always the most important customer service KPI because it provides actionable data.

In other words, it indicates why—not just if—agents perform up to par.

How to Calculate QA Scores
QA managers calculate scores with a QA scorecard, which can contain questions such as:

• Did the agent use a friendly tone?
• How well did they explain the solution to the customer?
• Did they use the right processes to solve the customer's problem?

QA managers assign points to agents for each question, and an agent’s score is the percentage of total available points they earn on their scorecard.

So, if an agent is consistently scoring low on a question about friendliness, a manager can focus future trainings on greeting techniques or using approved brand language.

QA scores usually fall between 75-90% based on four random conversation reviews per week.

2. Average Handle Time (AHT)

Average Handle Time indicates the average amount of time it takes for a support agent to close a ticket. That includes hold time, the duration of the interaction, and any necessary follow-ups.

Nearly 60% of people are frustrated with long hold times, according to RingCentral. Accordingly, you should keep tabs on agents’ AHT to better understand which agents need to improve their efficiency.

How to Calculate AHT

AHT = (total call time + total hold time + follow-up time) / total number of calls

3. First Contact Resolution Rate (FCR)

First Contact Resolution indicates the percentage of customer issues that are resolved on the first interaction.

To understand the importance of FCR, put yourself in the customer’s shoes: reaching out multiple times to customer support to get a question answered is a major pain. When agents resolve issues on the first contact, it reduces friction with the customer and may even help other KPIs, such as CSAT.

How to Calculate FCR

FCR = (number of tickets solved on first contact / total number of support tickets)

FCR varies by industry, but the average is 74%, according to research from MetricNet.

4. Customer Satisfaction Score (CSAT)

CSAT scores indicate how satisfied a customer is with a product or service. CSAT provides quick, easy-to-interpret data on customer sentiment. But the downside of this KPI is that it can’t tell you why a customer is satisfied or so furious they never want to do business with you again. In other words, it creates a CX blindspot.

How to Calculate CSAT
CSAT is measured through direct customer feedback with a question like:

On a scale of 1-5, how would you rate your overall experience with the product/service you received today?

To calculate your CSAT score, divide the number of positive responses (4 or 5, if you’re using a scale of 1-5) by the total number of responses, then multiply by 100. Here’s a quick example:

Let’s assume you have 60 total responses, and 45 of them are positive.

45 / 60 = 0.75 x 100 = 75

CSAT scores vary by industry, but 80 is a great benchmark to aim for.

5. Net Promoter Score (NPS)

Net Promoter Score gauges the likelihood of a customer recommending a company’s product or service. NPS isn’t the sole responsibility of customer support teams, but keeping track of NPS for individual agents can help CX teams draw a correlation between customer service and a customer’s willingness to promote the business to their family, friends, or co-workers.

How to Calculate NPS
NPS requires a bit more number-crunching than the previous metrics.

First, send customers the standard NPS question: “On a scale of 1-10, how likely are you to recommend us to a friend/family/colleague?”

Next, group respondents into three categories:

• Promoters: customers who respond with 9 or 10
• Passives: customers who respond with 7 or 8
• Detractors: customers who respond with 6 and under

Last, calculate the percentage of respondents in each category and subtract the percentage of Detractors from the percentage of Promoters. That number is your Net Promoter Score.

Here’s a quick example:

[60% Promoters] - [30% Detractors] = +30 NPS

NPS scores greater than 0 indicate that your audience is more loyal than not, while scores greater than 80 are considered world-class.

Now that we’ve covered the essential KPIs, let’s explore some metrics that advanced CX teams can track.

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Tier Two: KPIs for CX Process Insights

Once you have a firm grasp on the first tier of KPIs, you can take the next step to audit your processes and unlock insights to improve them. Team that track Tier Two KPIs are usually more established, have more agents, and have specialized roles such as a QA analyst or training lead.

The following KPIs are often overlooked, so teams that dig into them can get an edge over their competitors and take their customers’ experiences to new heights.

1. Support Ticket Review Volume

As its name implies, ticket review volume represents how many customer support tickets a CX team reviews over a certain period of time.

One of the main reasons CX teams track this KPI is that tells leadership how effective their QA process is and highlights areas for optimization. For example, Monday.com set a goal to increase their ticket review volume by 48% over the course of three months, and as a result of the increased insights they gleaned, reduced their AHT by 30%.

2. Alignment Score

An alignment score is a percentage that shows how QA managers’ scoring stacks up against an internal benchmark. This is known as “Grading the Grader.”

In this workflow, a random sample of graded tickets is sent to a Senior QA Grader (or Benchmark Grader) who sets the standard on how grading should be done.

The Benchmark Grader grades the ticket without seeing the original score to see how well-aligned the Original Grader was with the Benchmark Grader. If there’s a significant discrepancy, the two parties meet to resolve the issue instead of letting the agent get stuck in the middle.

Alignment scores are important to keep your graders consistent. It’s more than just checking if the grader has given the same final score as the Benchmark Grader—it zeroes in on individual parts of the scorecard to ensure alignment on every section.

How to Calculate Alignment Score

To calculate Alignment Score, a QA grader is assessed on how their grades stack up against the Benchmark Grader for every question (or criterion) on the QA scorecard.

Then, using the weight of each criterion on the rubric (if the criterion makes up 15% of the rubric, it’s given a weight of 15%), calculate the grader’s Alignment Score by adding the weighted scores of each criterion, up to a total of 100%. The closer to 100%, the better.

If that’s too much mental math, MaestroQA handles all the calculations for you—just run your Grade the Grader workflows every month to keep everyone aligned.

For a more detailed example of how to calculate Alignment Score, check out this spreadsheet.

3. Agent Engagement

High-performing CX teams track agent engagement, which is the percentage of graded customer support tickets reviewed by a particular agent.

Grading and compiling QA scores is helpful, but knowing how dialed in an agent is to their own development lets you know which ones are self-driven learners and which ones might need some prodding.

How to Calculate Agent Engagement
The equation is easy:

Agent Engagement = (Total Number of Graded Tickets / Number of Graded Tickets Reviewed by Agent)

4. Ticket Appeal Percentage

This KPI indicates how often an agent disagrees with the QA scores they receive. If agents continually appeal their scores, that can be a sign of a mismatch between the team's CX goals and how those goals (and the corresponding customer service training and policies) are perceived by the agent.

Once teams track this KPI, they can set a target (for example, 2-3%), and if the ticket appeal percentage exceeds that target, they know to review their CX or QA policies and scorecards with agents to understand why that gap exists and how to close it.

How to Calculate Ticket Appeal Percentage
To determine your ticket appeal percentage, simply divide the number of appealed tickets by the total number of graded tickets, then multiply by 100.

Take Data as Seriously as You Take Your Customers

Customer service is both an art and a science. It requires masterful people skills, as well as constant digging into the data behind interactions (and setting goals along the way) to turn bland customer experiences into remarkable ones.

Ready to see how data can level up your customer service? Get a free demo of MaestroQA today.

Strengths and Opportunities from MaestroQA Customer hims & hers

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Trust is important in every relationship– especially in customer support. An impending (or maybe already here, depending on the economist you talk to) recession has led companies to laser focus on happy customers and meet their demands by quickly scaling customer support teams. In order to make rapid changes, many companies have turned to Business Process Outsourcing (BPOs) to quickly increase agent count, accommodate 24/7 service, and provide assistance in multiple languages. These BPO teams often work relatively independently of the company that contracts them. This distance creates problems with visibility into Agent and Quality Assurance workflows, leading to inconsistencies in the customer experience. But integrating BPO Management into your QA program can make process a lot smoother.

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In this blog, we’ll discuss how implementing a strong Calibration workflow for your internal and outsourced Quality Assurance Graders, can establish trust and transparency in your relationship with your BPO. To inform this post, we’ll dive into how one of our customers, hims & hers– a fast-growing telehealth company– collaborates with their BPO today and how they plan to improve accuracy and reporting from these outsourced graders in the future. 

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Pitfalls of a BPO Led Calibration Exercise

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When Quality Assurance Supervisor, Salmeen Majid, started at hims & hers, they were already partnered with a Business Process Outsourcer (BPO). At prior companies, she remembers how selecting a partner–"was really about just aligning with similar values, brand tone, and voice, and making sure that they had the ability to coach to quality." 

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Salmeen meets with her approximately fifteen BPO supervisors weekly. During this time, she and one of her internal QA Analysts perform a calibration exercise. The outsourced team will share two of their agents’ tickets ahead of time & Salmeen and her analyst audit the agents’ performance based on a scorecard she and her internal team have created. During their meeting with the BPO supervisors, they will go over the tickets together and discuss where they landed in terms of scoring vs how the BPO supervisor scored. These discussions continue until both teams feel they are aligned. 

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This weekly meeting is also Salmeen’s opportunity to get a temperature read on how things are progressing at the BPO: if there are any pain points the team is experiencing in terms of quality if they need updates to the scorecard or any other process issues the BPO supervisors want to raise to the hims & hers headquarters. In between these weekly meetings, Salmeen tries her best to be available to her BPO supervisors to answer questions about the business and quality processes via Slack. 

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While Quality is Salmeen and her internal QA Analysts’ bread and butter, they tend to feel a hesitation from their BPO partner when it comes to having these discussions. Every week the BPO supervisors will have one person present and read the ticket while sharing the Google Sheet of their scores and feedback. To Salmeen’s chagrin, it’s– 

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"just one person's feedback. So based on that, once they've read their feedback from this Google Sheet, then my analysts and I will go over our feedback and where we kind of landed. We’ll ask them some questions to understand better where they landed & the reason for the score they chose, and then we'll open up the discussion to the rest of the group. People kind of slowly chime in here and there or will put it in the chat what score they landed on. In those meetings, there's a variety of camera on camera off."

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This worries Salmeen. Her internal team is only getting visibility into one person’s thought process per week and that one supervisor is the supervisor of the agent that they’re grading which tends to lead to some degree of bias. While some other supervisors (usually the same few week after week) chime in with thoughts, it's a heavy lift on Salmeen and her analyst to create a discussion and turn it into a conversation “the group is pretty quiet.”

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Needless to say, Salmeen is not a fan of this process. While she concedes it has a lot of opportunity, the manual process really has her and her teams down. The entire calibration process happens in GoogleDocs & GoogleSheets. With notes and thoughts being spread over multiple documents and hiding in various drives, it's hard for her and her BPO supervisors to keep track week to week on their overall process and progress. Salmeen says its– 

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 “a very unstructured discussion which I think lacks some benefit. It doesn’t feel very effective.” 

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Creating a Culture of Trust with Your Graders

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Salmeen’s internal support team at the hims & hers headquarters utilizes MaestroQA for their team calibrations. 

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“When you do a calibration in Maestro, you can see everyone's feedback written there. We can share screen and see it there and compare who landed where in terms of scoring, and then we also have the scorecard actually there to refer to." 

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She finds her internal calibrations lead to more in-depth discussions and free-flowing conversations among her team. This is a deep contrast to the hesitancy and disorganization of her weekly BPO meetings. Salmeen expressed that implementing a Quality tool like Maestro at their BPO could lead to better organization and visibility, allowing them to find their way to a better alignment that doesn’t feel so, in her words– “scrappy.”

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By implementing a service quality tool like MaestroQA, Salmeen has held her internal team to a level of expectation and excellence. When performing a Team Calibration using the tool, her analysts (and herself) are all expected to audit a ticket ahead of time– they read the entire customer interaction pulled from their helpdesk, add their feedback, and score based on the appropriately surfaced rubric. So when her teams are entering into the discussion, they already know what they want to say. 

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"We already know what we wanna talk about. We all feel really prepared. And that makes it a lot easier to have that active conversation.”

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Even with her small team of analysts (about five), Salmeen can tell from these traditional team calibrations that there is a wide spectrum in how they approach grading. Some team members go much easier on their agent groups, while others hold agents to a higher standard. In order to get her team fully aligned and standardize their grading process, Salmeen has taken advantage of MaestroQA’s grade-the-grader tool. 

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Grade-the-Grader (also known as GraderQA), is a workflow in which a random sample of already graded tickets are surfaced to a “benchmark grader” for review. The benchmark grader re-grades the ticket (without seeing the original score) and the system generates an alignment score between the original grader and the benchmark. 

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“The reason why I started doing that was not only to see how we can get more calibrated as a team and make sure we're all aligned in terms of how we actually grade these tickets, but also to see the quality of my analysts' work."

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Salmeen found that utilizing a tool to double-check grading quality, allowed her to uncover performance opportunities in her analysts– such as coaching analysts to be more efficient in their grading or spending more time personalizing their feedback rather than copying and pasting from previous tickets. By generating alignment through a grade-the-grader system, Salmeen was able to create trust in the QA data they were creating.

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BPOs Need Grader Management Tools 

Oftentimes, when a BPO is only engaging in some sort of team calibrations, they have the know-how to present a grading style the greater business wants to see. Because the Graders are aware that they are being tested, they can not only cherry-pick which customer inquiries to share (opting for higher-performing agents, or easier-to-resolve customer calls), but may even engage in grading practices completely different from their day-to-day grading. 

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Without true alignment between BPO graders and internal graders, a BPO can misrepresent its quality. We are constantly hearing the complaint that BPO teams report blanket QA scores in the high nineties (with little to no data to back this up), while the internal team working with those same customers and running a robust QA program on MaestroQA holds a QA score in the mid-eighties. When your QA scores internally and externally are not aligned and your CSAT scores don’t match your BPO’s reported QA scores, something is up. 

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While Salmeen is still working with her team internally to roll the MaestroQA tool out to their BPO, she is empowered with the structure and knowledge of how successful calibrations and oversight within her internal team have increased customer happiness. These systems allow her to notice the red flags in a BPO’s reporting and bubble up needed changes and expectations both to her own leadership teams and those of her outsourced partners. 

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If you want to learn more about MaestroQA, request a demo today.

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Today’s customer service landscape is tricky to navigate, especially when you need to outsource support to keep up with growing customer demands. Having a reliable BPO (Business Process Outsourcing) partner can help ease this burden – enabling you to scale up (or down) cost-efficiently. But it's not enough just to hire a BPO – having the right BPO agent training and development strategies in place with a BPO Management program is essential to delivering world-class customer experiences. 

In this blog, we’ll explore five strategies that are proven to establish and maintain successful BPO partnerships. To inform this post, we’ll lean on insights gathered from interviews with one of our customers, a leading food delivery app, and our very own Customer Success Director. 

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1. Empower Agents with Training & Certification

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In the food delivery app marketplace, ensuring a delightful customer experience is critical to gaining a competitive advantage and earning brand loyalty. This is why one food delivery app made training and development for outsourced agents a central part of their BPO partnership strategy. 

Signing a contract with a BPO is just the beginning of a successful, long-term partnership. According to the Quality Assurance Manager, “continuous management” is the next critical phase of every BPO partnership. During this phase, the company and the BPO work together to create a detailed training and agent development plan that gives BPO agents the skills and support they need to provide excellent customer experiences. They even implemented a rigorous onboarding certification program that is required for all new BPO agents to complete. “We’ll guide teammates through to retrieve that certification,” said the company’s Quality Assurance Lead.

Their training program typically takes three weeks to complete, and agents enter a period of “redshirting.” During this time, they practice what they have learned and become familiar with the company’s services. To help ensure that BPO agents are up-to-speed on the app's customer support quality standards and practices, they leverage MaestroQA to provide the agent with live QA insights. “Agents can work a case, and typically within an hour and a half, we'll go ahead and complete the audit and then send it back to get the agent fully ramped by the time they hit their 60 days.”

Through MaestroQA, companies have full visibility into quality metrics such as empathy scores, completed cases, audited cases, and calibration alignment scores. This helps brands measure the effectiveness of their training and ensures agents are aligned with the “high bar” of customer service expectations that brands have put in place.

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2. Leverage Feedback to Turn Good Behavior Into Habits

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Giving agents feedback is one way to ensure they provide the best customer experience possible. This feedback helps agents better understand how their actions impact customer experiences and allows them to make adjustments accordingly.

It was fascinating to hear how this leading food delivery company has taken this feedback approach to a new level. In order to provide agents with consistent and clear feedback during redshirting, they conduct three live audits of cases a day for six days. Providing agents with these layers of feedback over a condensed period helps them “immerse” themselves in the repeatable behaviors and practices that have a positive impact on customer experiences.

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3. Use Coaching & Empathy to Overcome Language Barriers and Improve Customer Experience

As customer expectations continue to grow, companies must find new ways to provide a better customer experience. Training and coaching agents on showing empathy are two great strategies companies can use to sharpen their BPO agents and develop good habits.

For example, when one of our customers saw a dip in CSAT ratings from one of their BPO partners, they were able to audit results to discover that their agent’s greeting lacked empathy. So how did they address this? They implemented a coaching initiative to help their offshore BPO partners move away from robotic and transactional greetings, instead focusing on providing empathy and a solution within 30 seconds. Now their agents have the necessary tools and training to understand the customer’s needs quickly and better respond to them.

While providing empathy and delivering clear feedback and coaching can help agents create better experiences for customers, it’s important to remember that these tools are just the start of creating a positive customer service experience. Companies need to invest in developing their agents on a continuous basis to help them provide the best customer experience possible. Through an app like MaestroQA, you can actually manage your coaching sessions with agents, linking QA scores and coaching points directly to your 1:1s to manage and track the proper follow-up. 

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4. Improve Culture Challenges with a Train-the-Trainer Strategy

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Offshore BPOs have their own set of unique cultural challenges, and train-the-trainer strategies are an invaluable necessity for improving these challenges. Train-the-trainer strategies work by having a team of certified trainers visit the BPO locations.

“By training the trainers, the BPO learns to be autonomous around training future new classes of agents, saves the internal team's time and resources — freeing them up to tackle other projects,” said MaestroQA’s Michelle (Lamerta) Vanchieri, Director of Customer Success. “This allows for a more customized approach to training that meets the specific needs of the BPO.”

Speaking of training, there’s an old saying; you can’t manage what you can’t measure. This is why using data and metrics to measure the success of your train-the-trainer strategy is vital. "By analyzing data trends through a quality rubric, you can identify ongoing training opportunities for each BPO to ensure they are well-enabled on customer service processes. Furthermore, as you roll out new processes, we recommend adding these topics into your Quality Scorecard to ensure you are tuned into any new training opportunities that may arise,” said Vanchieri. 

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5. Give Your BPO Partnership a Boost with a Little Latitude!

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The shift to a new model of freedom and autonomy in BPO partnerships can be a difficult one for many companies. The leading food delivery company mentioned earlier recently implemented this “new model,” and the results were impressive. Their BPO partners experienced a strengthened relationship, streamlined workflows, and an improved agent experience.

Before the shift to the new model, the delivery company took a more hands-on approach. “The old model was we told our partners how to jump, how high to jump, what to wear when they were jumping, and put them through a lot of hoops just to make sure that we were hitting all of these processes metrics,” said the Quality Assurance Lead.

So how did they make the shift to this new model of autonomy and freedom? They provided a clear set of guidelines and then let their BPO partners operate based on those guidelines, giving them the latitude to demonstrate their expertise. This was a significant shift, as it provided the BPO partners with the freedom they needed to execute.

This new model of autonomy and freedom allowed the BPO partners to take ownership of their tasks and be more efficient in their processes. This, in turn, provided a better experience for customers and agents.

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If you want to learn more about MaestroQA, request a demo today.

Expanding to new time zones, providing multilingual support, and scaling to keep pace with ticket volumes are a few reasons why call centers and customer support teams bring in a BPO (“business processing outsourcing”) organization. Regardless of the reason, outsourcing your customer support to a BPO can be a great way to maximize efficiency and provide excellent customer experiences. But how can you make sure you are set up for success? 

This blog will outline essential tips to get you up and running successfully with your BPO partnership, pulling heavily on industry insights we gathered from our customer Rubiko, a best-in-class, customer support provider (BPO) for the iGaming Industry.

Read on to discover how to get started with a customer support BPO, from selecting the right provider, aligning performance expectations, onboarding successfully, and optimizing performance long term. 

Selecting a BPO that’s Right for Your Business

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The ideal BPO will help you achieve your operational goals while enabling fantastic customer experiences. Finding a partner who can live up to such high standards doesn’t happen by chance. That’s why when selecting a BPO, it’s “not just about the experience; it’s also about the tools the BPO can provide to support the services the client needs,” said Francisco Parker, Head of Operations at Rubiko. “What’s key here is creating that relationship, so you can determine what the client wants.” 

Here are 5 key factors to have in place before selecting a BPO that’s right for your business:

‍1. Know your primary objectives: Start with an internal review. Have you been tasked with scaling in-house services, adding a multilingual customer support team, or does your business needs now require 24/7 customer support services? This analysis will help you determine the best time to reach out to a BPO, as Paulina Coronado, Human Resources, Head of Business Operations at Rubiko, said, “once you have determined that you could benefit from the expertise of a partner (BPO) to help you take your primary objectives to the next level,” that is the optimal time to reach out to a BPO.

‍2. Have a project owner: Appoint a team player who knows how to drive the project momentum forward, and knows when to bring in additional stakeholders or resources. 

3. Determine selection criteria: To select the right BPO for your business, it’s not only important to identify five to ten business needs that the BPO should meet, but Parker recommends getting the answers to three key interview questions:

1. What metrics does the BPO focus on?
2. What are the BPO’s values?
3. How will the BPO meet the client’s key metrics?

Of course, each BPO will share different insights when responding to these questions. “At Rubiko, we care about quality, but in general, when it comes to metrics (first call resolution, email response time, etc.), some BPO’s are going to just share what’s important for them. So already, you can start assessing what they value and what they are capable of offering,” said Parker. 

The answers from a potential BPO should really “be based on what the client needs and what the client wants,” added Parker. “In the end, it’s about pulling all the pieces together, so that you create a joint partnership in order to find success.” 

‍4. Define success criteria: Define the KPIs and performance standards you expect from a BPO partnership and use this criteria to determine which companies are the best fit for your business objectives and support teams’ needs. For example, you might set very clear performance expectations upfront with your BPO partners around quality standards for customer support. To take this a step further, you could include these performance expectations in your BPO service level agreements to hold the BPO accountable. 

‍5. Be prepared for speed bumps: Even the best partnerships face challenges. Coronado recommends interacting with the BPO for at least three weeks (requesting demos, more information, or follow ups) before making your final selection, so that you get a sense of the BPO’s communication style and how it may handle challenges.

It’s vital to remember that you are in a sense, selecting an “extension of your business,” said Coronado. “You are incorporating someone into your organization, into your operations. You're not outsourcing, I don't even think that outsourcing is the right word…it’s a partnership,” said Coronado.

Onboarding & Working with Your BPO

It is an exciting time for any business when they have finally selected a BPO partner and are ready to officially kick off their onboarding process. Coronado pointed out that many BPOs complete their onboarding process in 30 days, however, to her, onboarding isn’t a one-time activity, she takes a long-term view of this process. It should be thoughtfully planned and maintained over a period of 9 to 12 months and even beyond.

Onboarding is the process of integrating a partner into the business, and for Coronado, “it starts the moment you have that first conversation with the potential business partner.” 

Getting the Most from Your BPO Partnership

So, what are top brands doing to maximize their BPO relationships? Implementing BPO Management into their QA program is one important step. But the team at Rubiko believe their best partnerships have the following characteristics: 

‍1. Expect Positive Results

“The best ones challenge us, question us, and request results,” Coronado said. Don’t be shy to ask tough questions and change what isn’t working. After all, partnering with a BPO isn’t a set-it-and-forget-it proposition.

‍2. Look for Transparency & Collaboration

How do you handle a misalignment on performance standards by your BPO? “Teamwork and being as transparent as possible is important,” said Parker. He further recommends that if you see that the BPO is not achieving a metric that you as the client has set, then collaborate as a team to start changing that.

‍3. Ask for Meaningful Data & Insights

Most BPO providers will provide basic reporting back to the client, but for most businesses this isn’t enough. “Companies that partner with us,” said Coronado, “are expecting valuable insights. They expect us to meet specific specifications, and they expect us to go the extra mile. So those are the best ones, because they make us better.”

Meaningful data and insights from a Quality Program helps: 

1. Identify the knowledge level of your BPO’s agents and training gaps
2. Analyze customer interactions that drive low CSAT or churn
3. Standardize the BPO’s QA Processes (this is extremely important when using multiple BPOs)
4. Understand the BPO’s overall performance and evaluate contract renewals.

Unlike Rubiko, many BPO’s manage QA on their own without sharing meaningful data and insights. Unfortunately, this results in a lack of visibility into the data and limits a brands ability to uncover any meaningful trends or opportunities for improvement. In fact, more often, a lack of visibility leads to more disconnect and performance problems with the BPO due to the inability to see the full customer journey, unreliable reporting on quality scores vs NPS or CSAT (due to inflated QA scores), the inability to understand top/lowest performing individual agents (by QA score), and a misalignment on calibrations, just to name a few.

By leveraging MaestroQA’s platform, Rubiko is able to provide the brands they work with complete visibility into the QA workflow so they can spot trends, analyze results, and make smarter decisions that can lead to better customer interactions and even impact retention and business growth. From grader performance dashboards and coaching metrics, to an DSAT analysis dashboard, Rubiko’s “clients can see how we are doing and we can show them that,” said Parker. 

Here’s a good example of how Rubiko manages a broad range of teams using a MaestroQA Grader dashboard that allows them to keep up with the high volume of tickets that require grading each month. 

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With the Grader Performance dashboard, Rubiko is able to quickly compare average grading times vs the number of tickets graded. 

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The MaestroQA coaching dashboard also provides Rubiko with a centralized platform for 1:1 sessions and agent performance reviews.

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The DSAT Analysis Dashboard in MaestroQA provides Rubiko with an automated way to identify and aggregate tickets from unhappy customers—without manually exporting data from a helpdesk.

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Uncover a Better BPO Partnership with QA

MaestroQA provides QA software that CX teams can use to ensure quality customer interactions. Quickly grade support tickets, track key performance metrics, and seamlessly provide coaching for in-house and BPO teams.

See how leading brands use MaestroQA to better gauge their BPO’s performance.

Request a demo to uncover a better BPO partnership with QA.

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One of the biggest mistakes that businesses make with call center quality assurance (QA) programs is that they allow the mechanics to become far too complicated. At a certain point, you hit diminishing returns - meaning you're not getting nearly the level of insights that you'd hoped for despite collecting more data, or assigning out more tickets to grade.

Thankfully, there are a number of important features to look for in call center QA software that will help streamline - and improve - your program moving forward.

What is Call Center Quality Assurance?

The goal of any call center is to help an organization's customers. A call center quality assurance program is one that intends to make sure they're actually accomplishing that goal in the most efficient way possible by ensuring that customer interactions are on-point.

Obviously, team leaders want to make sure that all of their call center agents are operating at peak efficiency and that they're giving the right impression of the brand with each call that they take. But managers and business executives can benefit from a call center quality assurance process too.

Those organizational leaders can use quality assurance programs to keep track of the overall quality of their customer support interactions. They can use the data generated from them to make organizational improvements that increase customer loyalty and retention through a call center QA framework. They can even be important in terms of raising brand awareness - after all, a satisfied customer is likely to tell friends and family members about that business.

Regardless, the overall outcome desired from a call center quality assurance program is to improve the experience that an organization is able to offer its customers. That experience can and likely will form the basis of their own competitive advantage, which is why this is all so important to call center performance.

4 Features That Streamline Your QA Program

1. Automated Grading Assignments

Historically, grading has been the key action underlying call center QA programs - but it has always been time-consuming to sort assign out tickets to graders. Thankfully, technology has advanced to the point where a lot of these manual and repetitive tasks can be performed accurately and instantly, with tools such as Auto QA. This frees up the valuable time of QA specialists and managers so that they can focus on those matters that truly require their attention - like diving deep into improvements to CX.

Examples of this include things like automatic ticket assignments based on tags, ticket status, or other fields. 

2. Custom Scorecards

Custom scorecards are also an important way to improve the efficiency of your call center's QA program, as they better align the data that you're capturing with the organization's unique goals.

Agent performance of a customer service team is something that is crucial to monitor, but it's also a relative term. Depending on what your goals are, the definition of "quality performance" may change - meaning that what you're paying attention to needs to evolve just as quickly.

Thankfully, most modern QA tools allow you to customize your scorecards with a scorecard builder, according to your business' own goals and KPIs.

One important key performance indicator (KPI) is Average Handle Time or AHT. This helps you better understand how long it is taking to answer certain concerns that customers may have. Another might be Average Speed of Answering or ASA, for example. This helps make sure that call center agents are actually connecting with customers as quickly as possible. 

Another important quality metric is your customer satisfaction score (CSAT score), which measures how happy customers are with their current interaction with your company. Although this is just one factor to consider when evaluating call center performance, finding methods to improve your CSAT score can provide valuable insights to your customer journey. 

Improving quality metrics like these improves the quality of the user experience, which is really what this is all about.

3. Screen Capture

Screen capture is an important feature to look for when it comes to a solution that can streamline your call center's quality assurance process. This is especially true when it comes to evaluating and improving agent performance for future improvement down the road.

Screen capture helps team leaders better understand the exact journey that agents are having as they attempt to help customers. Ultimately, optimizations made from these insights speed up agents' response times and give customers a speedier experience.

4. A Centralized Platform

All of the above attributes are great - but ideally they all can function together to create a seamless QA program. Housing all of these capabilities in one centralized platform is key to saving time and money in your QA process - and to improving the customer experience! Call center quality assurance software is a solution that fills in that gap and provides a platform that includes tools for agent training, coaching sessions, and creating a strategic QA framework to improve call center performance.

Find a QA Platform That Drives CX and Agent Performance

Features like the ones outlined above are more than just an afterthought for your quality assurance program. They're ideal ways to mitigate a lot of the challenges that such programs face to begin with.

Oftentimes, ineffective quality assurance ultimately comes down to a lack of actionable information. You know you have an issue, but you don't know exactly what it is. These features allow you to see "the bigger picture," giving you as much data as possible so that you can make better and more accurate decisions moving forward.

Maestro's QA solution has all of these capabilities and more and is more than ready to take your call center to the next level. So to get additional information about how to streamline your call center's QA program, or to speak to someone about your own needs in a bit more detail, please feel free to contact us today.

Customer experience (CX) leaders place a big emphasis on communication between support agents and customers—rightfully so. However, if you want to deliver world-class experiences, solid communication between support agents and their coaches is equally important.

As a customer service coach, you’re responsible for delivering feedback (whether positive or negative), navigating interpersonal conflicts, and laying the foundation for professional development. There’s no blueprint for any of this. But with patience, empathy, and data, you’ll cultivate strong relationships with agents during your coaching sessions.

Let’s take a look at five ways you can foster better communication in your future coaching sessions.

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1. Got an Issue? Get to the Root Cause

Whether you run into a conflict with an agent over goal setting, performance expectations, or something else, it’s common to fixate on the symptoms of the issue rather than the underlying cause.

Let’s say you have a disagreement over how much control the agent should have when it comes to appeasing an upset customer who didn’t receive their order on time. The agent wants to offer some free swag as an apology, but this isn’t an approved tactic. Your gut reaction might be that the agent is going rogue and not adhering to the approved de-escalation process. But in reality, the agent is frustrated with a lack of autonomy and feels they deserve more trust.

In these situations, questions (not assumptions or accusations) are the best way to identify the root cause of the disagreement. Here are some examples of questions to ask:

• How do you feel about this situation?
• Why do you think you feel [frustrated/anxious/upset]?
• What do you feel is holding you back?

Once you both agree on the source of the issue, you can take steps toward a resolution.

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2. Build Feedback Around Data

Opinions alone shouldn’t be the foundation for successful communication—you need to support them with data.

Citing data reduces friction between coaches and agents because it grounds both parties in a single source of truth rather than raw opinions, which can be tainted by biases. Whether that data is a Quality Assurance (QA) score or a performance metric like Customer Satisfaction (CSAT) scores or Average Handle Time, it’s crucial to have a mutually accessible dashboard so that everyone has access to the same data at the same time.

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One example of emotionally charged, subjective feedback might be: “You were too slow resolving support tickets this month.” This doesn’t provide any value to the agent, and they might put their guard up—rightfully so.

Instead, weave in a statistic and make the feedback less personal. For instance: “Your First Call Resolution Rate is 12% lower compared to last quarter—let’s see how we can get that down.”

An alternative to citing numerical data is reviewing call recordings or screen recordings from customer interactions. For instance, Screen Capture illuminates all the steps that go into an agent’s interactions with customers, leading to more collaborative and transparent customer service coaching conversations.

“In 1:1 [coaching sessions], I can now say, 'I see you clicked back and forth, it seems like you struggled with this decision. Let's talk about your mindset in solving this ticket,'” says Kelly Moloney, Client Experience Lead at Stitch Fix.
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3. Understand the Agent’s Perspective

Every agent has unique strengths, weaknesses, needs, and opportunities for growth. Accordingly, coaches need to bring their full attention to every conversation with agents—not pass it off as “just another coaching session.”

“[Not listening] is something we’re all guilty of,” says Adrienne Isakovic, a lecturer for Northeastern University’s Master of Science in Corporate and Organizational Communication program. “As the other person is talking, we’re already preparing what we’re going to say in response. You need to actively listen, and even if it takes you 30 seconds after they have finished talking to respond, that’s fine.”

As a coach, you don’t have to agree with everything an agent says. That said, it’s crucial to step into their shoes and acknowledge that they have a different perspective. After all, they’re on the front lines interacting with customers every day.

If the agent’s point of view is unclear, follow up with questions and repeat their messages back to them to make sure you’re on the same page. For instance, if an agent appeals a QA score they receive from their grader (like the example below), ask them to elaborate so that you fully understand their rationale.

Acknowledging that you don’t have the full story and giving the agent an outlet to voice their opinion will increase their trust and foster a more authentic dialogue.

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4. Avoid Unilateral Decisions

Customer service coaching works best when agents are involved in making decisions, whether that’s setting goals, optimizing a process, or coming up with a plan to refine their skills.

Let’s say an agent’s CSAT scores are stagnating. You might assume the best path to improvement is assigning an online course on emotional intelligence. But before you jump the gun, encourage the agent to offer ideas of their own. They may be more inclined to active learning techniques, like a live workshop with other agents.

This same principle of collaboration applies to resolving conflicts.

“The goal of conflict resolution is not to decide which person is right or wrong; the goal is to reach a solution that everyone can live with,” note the authors of UC Berkeley’s Guide to Managing Human Resources.

Coaches and agents both need to articulate the desired outcome, then work backward to find a middle ground. Here’s a simple example scenario:

• Agent: I don’t want to feel micromanaged.
• Coach: I want you to have all the feedback you need to succeed.
• Compromise: We’ll use a learning management system where agents can learn and test valuable skills at their own pace in a low-stakes environment.

The more comfortable agents are with taking an active role in their growth, the better your relationship will be.

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5. Close the Feedback Loop with a Follow-Up Meeting

Customer service coaching sessions typically occur once a month or once a quarter. However, this might not be frequent enough if the agent is new to the team or struggling with a particularly complex issue.

Schedule a follow-up meeting after your initial meeting to tie any loose ends and reinforce the points you previously discussed.

If you’re trying to resolve a conflict with an agent and can’t seem to make any progress, use the follow-up meeting to determine the next steps, such as:

• Bring in a neutral third party as a buffer - this can be another coach, manager, or an experienced agent
• Get HR involved
• Assign the agent to a different coach or manager

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Get Ahead of Issues Before They Happen

We’ve discussed strategies to navigate sensitive situations with agents. But one of the most valuable things CX leaders can do is forecast conflicts by proactively seeking out questions, comments, and concerns.

This can be as casual as a monthly check-in with agents via email or as structured as a formal employee engagement survey. Conflicts often stem from communication issues (or no communication at all), so understanding the agent experience lets you address issues before they cause problems.

Human nature isn’t an exact science by any means. But practicing honest, open dialogue puts the odds of a mutually beneficial agent-coach relationship in your favor.

Ready to coach with confidence? Get your free demo of MaestroQA today.  

What is the foundation of a robust quality assurance program? It starts with well-defined CX standards for your organization. For a fantastic customer experience, well-defined CX standards represent the characteristics and process your customer-facing teams should adhere to and excel in. 

Two Key Workflows To Increase QA Grading Team’s Alignment

Quality assurance (QA) is crucial to ensure that your agents maintain this standard set out by the organization and give them opportunities to improve their performance. The CX scorecard is the cornerstone of any successful QA program, but one of the often overlooked aspects of QA is whether or not your QA team is aligned with how they interpret the standards in the scorecard. If your rubric is perfect, but your graders interpret it differently and have different scoring strategies, how much can you trust the results of your quality program? What insights can you draw if your graders are not using the same standards? 

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This article will provide the framework for two proven workflows that help measure and improve alignment amongst your grading team! 

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There are two widely accepted workflows for measuring and improving alignment:

1. Call Calibrations
2. Grade the Grader (in the MaestroQA platform, we call this GraderQA)

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Both of these workflows ensure your QA team or team leads are aligned with how they interpret the CX standards in the scorecard. As we dig deeper into these workflows, they also have stark differences intended to drive different results. Let’s define each process before deciding which workflow suits your team: 

What is Call Calibration? 

Call calibrations allow your QA team to grade agent performance and collaborate on the same ticket. The purpose of call calibrations is to have your team grade (or calibrate) the interaction individually while utilizing the same scorecard. 

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Performing Call Calibration Sessions for Quality Assurance

After each member of the QA team has submitted their scores, the team holds a call calibration session to discuss why they landed on the scores they did. Your team will probably disagree on what the “right” grade was - and that’s okay! The purpose is to have a constructive conversation to collectively decide how to grade. 

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Once the call calibration process has been completed, Maestro will generate an “alignment score” to showcase how aligned each QA team member is with the final calibration score. The higher the alignment score is, the more closely aligned they are to the agreed-upon CX standards. 

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Tips

• Designate one person to be the final calibrator. This person will be the final decision maker and will submit the Final Calibration. This is your source of truth to measure alignment against! There is a lot of back and forth when going through the call calibration process, so it’s important to designate someone as the decision-maker. 
• As you become more aligned, select harder, more complex, or more ambiguous tickets so you can continue to drive value from these conversations and raise the bar. 
• Consider recording the sessions to share within your CX organization to build a culture of transparency around how you think about and talk about quality.  

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Other benefits of Call Calibration sessions

In addition to improved team alignment, call calibration sessions can help refine training processes and identify issues, including soft skills and technical behaviors in customer interactions. Ensuring agents meet evaluation standards leads to a more consistent customer experience.

How often should my team do Call Calibrations?

If your quality program is new, we see teams go through the call calibration process as frequently as once a week! Once your call calibration process runs smoothly, and alignment is high, consider moving to once a month and focusing on more complex tickets. When you launch a new rubric, it’s a good idea to increase frequency again until all graders are comfortable and aligned with the new criteria. 

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MaestroQA Grade the Grader (aka GraderQA) 

The key difference with this workflow is that it’s designed to provide feedback to an individual grader on their grading performance rather than engaging in a team-wide discussion about the standards. Similarly, there will be a member of the team designated as the “source of truth” (in Maestro, we call this a Benchmark Grader. In your program, this should be your most experienced grader or perhaps your QA Manager. Whoever is an expert on your grading standards!) who grades a ticket that another grader already completed in AgentQA. 

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The goal is to provide feedback to the original grader on how they answered the questions and shared feedback with the agent. Ultimately, the work done by the Benchmark Grader is then shared back with the grader so they can review their feedback about how to grade more consistently with the CX standards set out. 

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Tips: 

• Graders want feedback as much as your agents do, as it helps them to perform at a higher level and ensure they’re keeping within your team's standards. If your team has the bandwidth, providing bi-monthly feedback on a few graded tickets should give them confidence moving forward that they are grading consistently to the team standard. 
• Focus on tickets where the grader left the agent with qualitative feedback (comments or selecting additional checkboxes). As the “Benchmark Grader,” this will give you ample opportunity to share feedback with the grader and see how they deliver feedback to your agents. 

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How often should my team run GraderQA?

Similarly to call calibrations, we typically see teams run GQA at least a few times a month to share regular feedback with your graders. Depending on internal bandwidth, it’s a good idea to include consistent feedback for your graders alongside the feedback shared for agents, so everyone can continue performing at the expected organizational standards. 

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Which workflow is right for me? 

Ultimately, it depends on your ideal end state! Let’s walk through a few scenarios to help demonstrate the use cases of each:

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1. Your agents benefit from QA feedback, and you want to provide that same level of feedback to your graders to improve their grading skills.  

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Our Suggestion: MaestroQA GraderQA! This gives you the tools to give qualitative feedback to individual graders. 

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2. You have a few graders that you think are underperforming. Their QA scores are high, or maybe they take a long time to grade a single ticket and are not completing their weekly assignments. Any of these are indicators that a grader may need some more help. 

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Our Suggestion: GraderQA! This gives you the tools to grade these graders’ tickets, uncover which criteria they are not grading correctly, and coach the grader toward success. 

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3. You just launched a new rubric. The scoring strategy changed, and a few questions were added that focused on customer satisfaction. 

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Our Suggestion: Definitely Call Calibrations! This will allow you to see what questions graders have, which areas of the rubric are unclear, and perhaps even make changes before launching. 

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4. You just hired a class of new graders. They are getting ramped on your rubric and processes. 

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Our Suggestion: Both Call Calibrations and GraderQA! Call Calibrations will be great to teach the new graders how you think about the rubric and work through customer problems. GraderQA will give you a specific alignment score, so you know how quickly your graders are ramping and what parts of the rubric they need coaching on. 

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Key Takeaway

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GraderQA and Call Calibration workflows are valuable tools in your QA toolkit to unlock additional insights and better align your grading team. Whether pursuing just one of these workflows or implementing both, the conversations and learnings that come from these are endless. They should help create a more robust experience for your customers and agents! 

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Interested in learning more about MaestroQA GraderQA?

Request a demo.

Delivering fantastic customer experiences involves more than keeping CSAT high and AHT low. Customers don’t just want you to solve their problems—they want you to do so in a genuinely empathetic way.

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At MaestroQA, we consider empathy as putting yourself in the customer’s shoes, which isn’t the easiest thing to quantify or track. 

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Let’s take a closer look at empathy in customer service and tips for leveraging QA to ensure better experiences.

Demonstrating Empathy in Customer Service

Customers can easily recognize (and appreciate!) empathy when they experience it. They can also detect when an agent is trying to seem empathetic—but, in reality, it’s all a show. 

Don’t Fall into These Traps

Much has been written online about empathy in customer service. Just do a quick search, and you’re bound to find all sorts of tricks, tips, and buzzwords. Unfortunately, many of these “best practices” fall short of helping the agent to demonstrate genuine empathy. 

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For example, you’ve probably heard that restating the issue back to the customer is a best practice. That’s only true, however, if you understand the customer’s issue. Changing your story later in the conversation can make you look silly and frustrate the customer. As Mel Bilge, Director of Customer Success, Strategic here at MaestroQA, points out, “Don’t just copy, paste, and repeat to make it seem like you understand. It should be about understanding exactly what the customer is asking.”

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Words that express empathy—such as “I’m sorry,” “I understand,” or “I’ve got your back”—can be appropriate in certain situations. Still, such phrases should not be empty statements to simply make the customer feel better. “Be careful about how you choose phrases that mirror empathy and make sure that your follow-through reflects that,” Bilge said.

Being Empathetic is about Being Genuine

The best path to empathy starts with treating customers like people—not support tickets. Seek to quickly understand the customer’s frame of mind and tailor the experience to his or her needs. As Bilge said, “Is the customer coming in hot, or are they approaching from a steadier state?” The efficiency of delivery along with the agent’s tone plays an especially important role when helping customers through time-sensitive, frustrating issues. 

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Empowering agents with additional flexibility to make judgment calls is another way to increase empathy. “Following processes to a fault might not be the best way to resolve the customer’s issue. Taking some liberties could help solve the customer’s problem and result in higher satisfaction levels,” Bilge said. 

Developing a Game Plan to Increase Empathy

Agents don’t magically become more empathetic overnight. Increasing empathy in customer service is a gradual process that requires ongoing commitment to change. That’s best achieved through training, coaching, and QA.

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Training: Start by evaluating your existing training program. Does empathy play an essential part in the training materials? Do you provide specific examples to help agents demonstrate empathy across all channels (phone, email, chat, etc.)? For example, encouraging agents to use emojis in written communication might help them “sound” more empathetic.

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Coaching: Setting clear expectations, reviewing productivity metrics, and assigning action items are all parts of an effective coaching session. Providing personalized feedback to agents is also part of the process, which is a great time to weave empathy into your coaching.

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QA: Of course, good coaching depends on good data. That’s why QA is especially important to empathy-focused CX teams. Regularly reviewing and grading agent interactions—specifically for empathy—establishes a baseline for measuring progress and informing coaching and training decisions.

Leveraging QA Insights to Become More Empathetic

MaestroQA can make tracking, coaching, and increasing empathy across your CX organization easier. For starters, creating an empathy-focused rubric in MaestroQA gives graders a tangible way to review interactions from the customer’s perspective. Flexible question types (multiple choice and linear scoring) and non-scoring options make it possible to design a rubric that captures relevant data.

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“We can create highly configurable and flexible rubrics, and you can create as many rubrics as you need,” Bilge said. “If you can dream it, there’s a good chance you can build it with MaestroQA.”

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Weighting certain sections of the rubric allow CX leaders to emphasize actions that directly impact empathy, such as the agent’s tone. “With weighting, you can value what matters most to your business and relate that to your higher-level CX goals,” Bilge said.

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As tickets are graded and data is tabulated in MaestroQA, you’ll see how your team performs from an empathy standpoint. Drill down by question, agent, or other criteria for an in-depth look into factors contributing to (or detracting from) the customer experience. 

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Use MaestroQA to Track (& Improve) Empathy in CX

With MaestroQA, CX leaders can finally achieve a data-driven approach to improving agent empathy. Interested in learning how to build an empathy rubric? 

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Request a demo of MaestroQA to get started. 

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Much has been written about the three Ps of business- people, process and product- as they amount to a fundamental foundation for every company. While data is critical for improvement and to enable leaders to make informed decisions for the betterment of the business, measuring the three Ps with quantitative data has historically been a challenge.

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With new tools embracing artificial intelligence and automation, it is now possible to progress from a qualitative view of the three Ps and transform them into quantitative, measurable areas. This allows business leaders to evaluate a brand’s quality, or even a customer experience agent’s performance, by taking a data-driven approach.

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Read on as we explore some of the measurable data available for the three Ps, and how organizations might exploit that data.

Product data

Swimming in a sea of product options, customers can afford to be selective. That’s why best-in-class companies focus on product quality to drive user satisfaction and business outcomes by understanding what their customers are saying. The Voice of the Customer is everywhere, from reviews in the App Store or on Google Play, incident response tickets in Jira, and social media interactions on Twitter or Reddit.

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With this feedback, organizations can understand what features customers enjoy, what they find hard to use, and what bugs should be prioritized or included in long-term roadmap strategies.

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However, parsing and tagging feedback is time consuming, as without automation or artificial intelligence teams are left to manually sift through siloed sources to try and identify trends, and at the end of the day are still lacking a 360° quantitative view that can be shared with the rest of the business.

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By incorporating supervised machine learning and artificial intelligence models, unitQ is able to take your user’s qualitative feedback and automatically consolidate, translate, and categorize it into real-time data that is actionable and more importantly, measurable – the unitQ Score.

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Incorporating a score into how your organization evaluates your product’s quality means a quantified, data-driven approach can be taken to evaluate improvements, strategize on future updates, and even visualize how you measure up against the competition, all in real-time. 

People and process data

Even with a top tier product, maintaining a process and customer experience via the people on the front lines is critical to brand loyalty. When consumers have a negative customer service experience, they not only tell others, but often switch to competitors, and may do so without telling the brand about the bad experience, leaving CX leadership in the dark.

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While CSAT and NPS tell part of the story, each lacks a key element of quantitative data – being actionable – as they do not offer sufficient clues for how to make measurable improvements.

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Much like a unitQ Score should be used to effectively and efficiently measure product quality, a Quality Assurance (QA) Score is used to measure agent performance, customer support effectiveness, and can help improve customer experiences.

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Having customized scorecards as part of your quality assurance program is crucial. Customized scorecards allow you to gain the information and strategic insights your agents need to perform. Relying on spreadsheets lacking scalability means time wasted on manual and repetitive tasks, which can lead to ineffective agent coaching sessions.

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A quality assurance platform like MaestroQA provides unfiltered visibility into what's happening with your agents, customers, CX processes, and business.

Combining the three Ps

Evaluating quality by leveraging quantifiable user feedback data from unitQ and customer experience data from MaestroQA gives CX and leadership a complete picture about how they are interacting with their customers, as well as what customers are saying about product capabilities, features, and performance. 

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This amounts to a goldmine of actionable insights about the quality of your people, process, and product to take your business to the next level.

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If you're looking for an easy way to run a quality assurance program and track and improve your QA scores, sign up for a demo of MaestroQA today!

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unitQ helps brands harness user feedback to improve product quality, increase app store ratings, reduce churn and enhance brand loyalty. Request a demo today!

CSAT is a go-to metric for most CX teams.

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But, as we’ve pointed out in previous articles, CSAT doesn’t tell the entire story. Only a fraction of customers takes the time to complete CSAT surveys. To complicate matters, CSAT only tells you about how a customer feels at the end—not at the beginning or midpoint—of an interaction, which makes it difficult to understand the full experience truly.

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Implementing a customer service QA program is a key step for overcoming the CSAT blindspot, but manually reviewing each ticket for sentiment insights is not feasible. Modern CX leaders are looking for a scalable, automated way to leverage customer sentiment data, which is why we’re excited to introduce a new solution from MaestroQA.

What is Customer Sentiment?

At MaestroQA, we consider customer sentiment as the emotion behind engagement. And, as any experienced support agent will tell you, customer emotions can quickly change—even during a single support interaction. 

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For example, an angry customer might cool off as he chats with a friendly, knowledgeable agent and receives his desired outcome. Conversely, what starts as a neutral conversation could rapidly turn negative if the customer is asked to re-explain her situation multiple times. Simply put, customer sentiment can evolve as the experience progresses. 

Understanding Customer Sentiment with MaestroQA

Our new Sentiment Analysis Dashboard in MaestroQA uses Artificial Intelligence (AI) to surface tickets containing negative customer sentiment—even tickets that do not have a CSAT score. Intuitive charts and graphs convert raw sentiment data into actionable insights for CX leaders. From a single view, users can instantly see:

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• Total number of tickets available and analyzed
• Number of tickets containing negative sentiment
• Negative sentiment trends over time

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MaestroQA pulls in the specific comments that contain negative sentiment into a scrollable experience, which makes it easy to review customer feedback and look for potential issues. Need to see the original support ticket? Just click on the ticket number to view it in your help desk software.

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Our Sentiment Analysis Dashboard lets you slice and dice your data by agent group, channel, tag, and other criteria. Are new agents more likely to contribute to negative sentiment? Is a poor chat experience causing customers to express their frustration? With MaestroQA, you’ll be able to answer difficult questions like these and make data-driven decisions about coaching, staffing, and technology.

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Applying filters to the Sentiment Analysis Dashboard provides an even more refined look at the data. Filter by tag, rubric and channel agent group to analyze customer sentiment from a new perspective.

Customer Sentiment Q&A

We’ve received positive feedback from customers since announcing the beta availability for the Sentiment Analysis Dashboard. In case you’re interested, here are a few answers to common questions:

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What does MaestroQA use as its basis for detecting customer sentiment?

Sentiment is based on the conversation itself, not CSAT. MaestroQA uses AI to automatically detect and flag negative sentiment within a sample of tickets.

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How quickly does sentiment analysis occur on a ticket?

MaestroQA customers can expect to see sentiment data within three hours of an interaction.

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Does sentiment analysis occur on open tickets, too?

Yes, MaestroQA can analyze both open and closed tickets.

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How can I learn more about the Sentiment Analysis Dashboard while it’s still in beta?

Feel free to request a demo of the Sentiment Analysis Dashboard or other MaestroQA features.

Turn Negative Sentiment into Positive Experiences

Listening to customer feedback—even when negative—is one of the best ways to improve your support operations and elevate the overall customer experience. The Sentiment Analysis Dashboard from MaestroQA is built to help you do that.

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Interested in learning more? Request a free demo of MaestroQA.

Customer satisfaction scores have been a popular metric for measuring customer experience (CX) for a long time. It’s easy to calculate and understand, but it doesn’t tell the whole story. 

Your CSAT scores only measure how happy customers are with their current interaction with your company. It doesn’t consider whether they’ll come back, recommend your product, or keep spending. You also miss customer feedback from the vast majority who don’t submit a customer satisfaction survey. 

To get the full picture of the customer's relationship with your business and increase satisfaction, you need more than a CSAT score. Analyze the numbers behind your CSAT rating to see what’s positively and negatively impacting your customer experience. 

Improving Your CSAT Score Means Using Key Insights to Inform Your CX Strategy

Understanding what’s impacting customer satisfaction can be difficult. There are plenty of factors to consider, and it’s easy to get lost in the data. You can segment your customer base by product, location, or other business-related criteria to see your most satisfied customers. You can also compare your CSAT data to your customer effort data, quality data, or conversational analytics to see which metrics correlate most closely to high CSAT scores.

See where agents excel at delivering high customer satisfaction and turn those learnings into best practices and training materials. Pull specific examples from your QA data to share with your team and help them better understand what great agent performance looks like.

How Customer Dissatisfaction (DSAT) Tickets Can Help Improve CSAT Scores

Understanding what’s negatively impacting customer satisfaction is crucial. Digging into your DSAT tickets isn’t the most fun exercise, but learning why customers are unhappy pays dividends in the long run when it comes to improving CSAT scores. 

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There are three main DSAT categories that often come up: dissatisfaction with customer support, with the product or service, or with company policies. A series of Quality Assurance (QA) audits gives additional context to DSAT tickets, namely ones that involve customer support processes.

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With a deeper root cause analysis, you make sure to address the underlying problem rather than get stuck on the symptoms. A well-known method that helps you look beyond surface-level issues is the 5 Whys Method. For each reason, dig into the sub-reason that can be surfaced from your customer support data.

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Fill CX Gaps to Help Improve Your CSAT Score 

To provide the best possible customer experience and improve your CSAT score, you need to understand your customer's journey. You can use data from customer surveys, customer service tickets, social media interactions, and more to generate a complete picture of the customer experience. 

Pull in sentiment analysis and conversational analytics to help pinpoint key events affecting your customer experience and fill gaps in your understanding of the customer experience to determine which areas to focus your resources on.

With MaestroQA Screen Capture, you can collect data from your support interactions and use it to generate insights that will help you improve and inform your CX strategy. 

Connecting Good CX and CSAT Scores 

Customers are looking for efficiency and ease. They don’t want to chat with support agents all day, but they also want their issues resolved with minimal effort on their part. There are several ways a customer support team can provide a better experience and improve customer satisfaction. Happy Customers = Better CSAT Scores!

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Minimize Your Customer Effort

Difficult customer service experiences erode loyalty and hurt overall customer satisfaction. One main driver behind excessive customer effort is reaching out to a company multiple times to fix a problem. It’s important to value your customers’ time, but sometimes agents can place too much focus on quickly resolving tickets when resolving a ticket the first time a customer reaches out is even more important. 

81% of customers will return if their issue is resolved on the first contact. But that number drops to just 13% if the problem isn't resolved until the customer's fifth contact.

Another driver of higher customer effort is asking customers for information that’s already available in the agent’s CRM. Make sure your agents have easy access to quickly grab any necessary information from your CRM to save your customers’ time.

Deliver with a Positive Attitude

Beyond having an efficient interaction, you also need to ensure your customers have a positive connection with your team. Authenticity, a friendly tone, and empathy are the three soft skills with the biggest impact on customer satisfaction.

Demonstrate that you care about your customers by acknowledging their concerns and doing your best to put them at ease. Use positive language to let customers know what you can do for them instead of what you can’t.

Move from Scripts to Conversations

Step away from boilerplate responses and empower your agents to personalize their responses and tailor their solutions to the specific situation.  

Make sure your agents actively listen to your customers, so they can more effectively resolve their problems. When customers share their concerns, paraphrasing what they've shared back to them ensures your agents understand the issue. Asking the right follow-up questions is also key to getting at the core of the problem and helping your customer feel heard.

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How to Take Action to Improve Your CSAT Scores 

Some of the key factors in great customer experience include agent performance, the ease of resolving an issue, as well as non-service-related aspects such as product experience or policies.

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Reduce Your Customer Effort Score (CES)

Make it easy for a customer to resolve an issue or find the information they need. Start by giving them multiple options for finding the answers they need. With a consistently updated Frequently Asked Questions section on your product, service, or policies, you can get ahead of common issues your customers face. 

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Similarly, an Internal Knowledge Base (IKB) can help agents quickly find and share information about policies, procedures, and best practices, so they can resolve customer issues faster. 

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When you share information in a variety of formats, you create a more effective self-service model for your customers. For example, monday.com’s support hub offers quick answers via a knowledge base, video tutorials, a community forum, webinars, and more. Then, if customers need personalized support, they have 24/7 support available.

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Better Trained Agents Can Help Improve CSAT Scores

When agents know what customers are looking for and how they can deliver on those expectations, they’re more likely to provide a great customer experience. Give them the skills and the data they need to better manage support interactions and delight your customer base.

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One major area where you can help agents become more effective is in identifying the root cause of a problem rather than addressing symptoms. Pull specific examples from tickets graded by the QA team and share guidance on possible follow-up questions they could use. 

How we can help:

With MaestroQA, you can implement personalized, structured, and data-driven coaching to help agents improve their skills, learn from mistakes, and fill in knowledge gaps relating to the company’s products and services. 

Within the coaching module, track 1:1 sessions with agents to discuss performance over a particular week, month, or quarter. Review an agent’s tickets or their recent KPIs using Coaching Points to discuss areas of strength and opportunities for growth. Standardize continuous learning for agents by assigning learning modules and tasks with To-Dos that link to learning modules or list follow-up tasks aligned to development goals. 

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Using QA Audits for Continuous Improvement and Better CSAT Scores

Your quality assurance (QA) audits can deliver a wealth of CX insights. The best customer support agent could receive a low customer satisfaction score if there’s a broader product issue or policy frustrations. But building a smooth QA audit process to track and surface these insights can be difficult and time-consuming. 

A custom QA scorecard allows you to tag and manage customer experience data that falls outside the influence of the customer support agent. You can also create separate tracking to pull more detailed insights around new initiatives like a product launch. Capture the voice of the customer data from your support interactions that you can share with your product team.

How we can help:

With MaestroQA, your organization gains deeper insights into how your customers think and feel straight from your support team. You can automate repetitive QA tasks, like ticket assignments, to ensure every negative CSAT score is always triggered and routed to the right people to review.

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Ready to Take the Next Step to Improve your CSAT scores? 

Get in touch today to see MaestroQA's modern customer experience platform in action and learn how you can uncover actionable insights from your entire customer experience and start moving the needle on customer satisfaction. 

Request Demo

One of the best parts about good restaurants is having the wait staff guide you through your meal at the perfect pace. A savvy waiter or waitress never rushes you, but they also don’t let you linger at your table when you’re clearly ready for the check.

Customer support teams can benefit from the same mindset: thoroughly resolving issues without wasting a caller’s precious time. In order to accomplish that, Quality Assurance (QA) managers need to get familiar with Average Handle Time (AHT).

AHT is a critical metric for QA teams to track in order to help agents resolve customer service requests efficiently without sacrificing the quality of the customer’s experience. If your goal is to reduce AHT, it’s important to organize your tools, customer service training, and tech before an agent answers a single call.

But before we talk about specific ways to cut down your AHT, let’s cover the basics.
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What Is Average Handle Time (AHT)?

Average Handle Time (AHT) is a customer service metric that indicates the average time it takes for a support agent to close a ticket, including hold time, call time, and necessary follow-ups. AHT is a common KPI for contact centers that want a tangible way to measure efficiency.

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Why Is Average Handle Time Important?

Any interaction—whether via phone, email, chat, or social media—that’s drawn out longer than necessary is a low-quality one. On the flip side, you can’t have a quality customer service interaction if the customer feels like an agent is rushing them or cutting corners for the sake of closing a ticket.

QA managers need to pay close attention to AHT because the stakes are high. Microsoft’s 2019 State of Global Customer Service Report notes that 61% of people have cut ties with a brand due to a poor customer service experience. And one of the most common causes of a poor customer experience is—you guessed it—sitting on hold. In fact, nearly 60% of people are frustrated with long hold times.

You can’t improve what you don’t measure, which is especially true when it comes to how efficiently agents resolve customers’ questions. That’s where the AHT calculation comes in.

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How Should QA Managers Calculate Average Handle Time?

Calculating AHT is simple:

AHT = (total call time + total hold time + follow-up time) / total number of calls

Here’s a quick example of calculating AHT:

Let’s say you have 100 calls that take 600 minutes with a total hold time of 200 minutes and 300 minutes of follow-up work.

(600 + 200 + 300) / 100 = 11

So, your AHT is 11 minutes.

What Is a Good Average Handle Time to Aim For?

This is like asking how long it should take to prepare a meal: are you serving instant ramen or a four-course dinner?

AHT benchmarks can vary depending on several factors, such as the industry you’re in, the complexity of your business, or how well-established your customer support team is.

That said, there are some ballpark figures for certain industries. According to data sourced by Call Centre Helper, a good AHT for telecommunications companies is about 8.5 minutes, while the benchmark for financial services is 4.75 minutes.

With a rough industry benchmark in mind, QA managers can take a sample of a month’s worth of customer support tickets, then evaluate the AHT for that sample period. Once that's done, ask these two questions:

1. How does your AHT stack up to your industry's average?
2. What was the average QA score on these tickets, and is that on par with your own QA standards?

It’s important to note that a low AHT shouldn’t be the sole indicator of customer support success. If agents are under constant pressure to close tickets faster than last time, they might make mistakes that cost more time in the long run. That’s like a server handing a guest their check before giving them a chance to order dessert.

However, if your team is consistently battling a backlog of support tickets, there are some strategies you can implement to boost efficiency.

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5 Ways QA Managers Can Help Agents Reduce Average Handle Time (Without Cutting Corners)

Reducing AHT isn’t about shortcuts or hacks—it requires QA managers to be proactive with their training and processes. This way, every moment a customer spends with an agent goes toward resolving their issue.

1. Increase Your Volume of Quality Audits

Quality audits help QA managers identify their team’s weak spots that can contribute to bloated AHT metrics.

“If you want to drive change in any metric, whether it’s First Call Resolution, AHT, or CSAT, you have to start with the quality of the experience,” says Justin Junious, Customer Experience Lead at monday.com.

One way to scale-up grading for customer experience (CX) teams is with advanced quality assurance scorecards. That’s how MaestroQA helped monday.com increase their volume of quality audits by 48% within three months.

By ramping up their monthly quality audits, monday.com cut down their AHT from 24.1 minutes to 16.9 minutes—nearly a 30% improvement. That’s the power of using data—not guesswork—to improve the customer experience.

2. Leverage QA Insights to Optimize Agent Training

Some companies might be tempted to throw new agents into the mix, especially if the support team is overwhelmed with incoming tickets. But under-trained agents can cause bottlenecks in your queue, thus increasing your AHT.

The most impactful agent training is informed by data—not legacy systems or cookie-cutter presentations. Take Zola, an online wedding planning service, for example. To identify training gaps, their QA team uses MaestroQA to score new agents’ support tickets on key criteria to share customized feedback during coaching sessions.

“Our goal is to get agents the lessons they need quickly and create a real-time feedback loop,” said Rachel Livingston, Senior Director of Operations at Zola. “Agents are expected to complete their lessons within a few days, and supervisors usually reconnect on the topic in future coaching sessions.”

Additionally, Zola syncs MaestroQA with Lessonly (a leading team training software) to expedite agent onboarding, identify training gaps, and collaborate on new opportunities. For example, based on the analysis of past interactions, Zola’s CX team identified the need to focus on training lessons for brand voice and call de-escalation.

By closing the feedback loop between QA and training, Zola cultivated more confident agents, productive coaching sessions, and happier customers.

3. Make QA Data the Foundation of Your Internal Knowledge Base (IKB)

Tracking down answers to recurring questions can quickly eat up the clock—especially if resources are unorganized. A digital, easy-to-navigate knowledge base can help with this. But knowing exactly what information to include and whether it’s actually helping agents can be confusing.

The ride-sharing app Lyft ran into these challenges while trying to codify internal knowledge for customer service training purposes. MaestroQA stepped in to help identify aspects of the business that were causing the most confusion for new agents by providing a steady drip of CX data.

These insights laid the foundation for a single source of truth that put product and policy knowledge at their fingertips, which ultimately improved Lyft’s first call resolution (FCR) rates.

Additionally, since senior agents gained more time to focus on the tickets in their queue, their AHT dropped significantly.

4. Automate Tedious Tasks

In 2019, 25% of interactions between brands and customers were automated by artificial intelligence (AI)—a number that’s expected to grow 40% by 2023—and for good reason. Without automation, manual, repetitive tasks drag agents (and the business as a whole) down.

For example, in 2019, the online fitness company ClassPass spent the equivalent of 6,250 days—that’s over 17 years—chatting with 1.5 million contacts to cancel their subscriptions. QA data revealed that ClassPass’ support team was spinning its wheels, leading to unrealized revenue and inaccurate forecasting, on top of a lot of wasted time.

"We decided to fully automate the process," said Sydney McDowell, CX enablement Lead at ClassPass. “Now we have zero cancellation chats handled by agents.”

Automation can’t(and shouldn’t) fully replace human interaction, but it can give customer support teams the breathing room they need to take on more tickets—and close them faster.

5. Test and Optimize Templated Responses

Responding to questions with “Let me check...” or “I think you should...” doesn’t just erode trust between support staff and customers; it wastes time as well.

These instances can be avoided with templated or “canned” responses, which are pre-written answers that ensure concise and consistent communication between agents and customers.

Let’s say a customer needs clarification about a refund policy. The agent can simply reference the approved response for that SKU rather than relying on a subjective interpretation, which could be lengthy or inaccurate—both of which extend AHT.

Taking this a step further, QA managers can create specific scorecards that track the effectiveness of templated responses, and identify those that need to be tweaked. These insights can also inform training, ensuring new agents avoid ineffective communication strategies.

QA managers can even A/B test templated responses to gauge how well they perform in specific scenarios.

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Efficiency Shouldn’t Hinder Experiences

AHT is one of the most commonly-tracked call center KPIs, and lowering it can be a great goal. That said, QA managers can’t afford to let speed become the priority over effective customer support.

AHT is just one piece of the CX puzzle that should be viewed within the context of other metrics such as First Contact Resolution and QA scores.

Of course, agents should strive for efficiency. But if they’re over-eager to close support tickets, that can backfire in the form of callbacks for unresolved issues. An interaction that takes longer than your normal AHT isn’t necessarily a bad thing, especially if a customer is responding well to the agent who’s guiding them towards a solution.

Remember to think of CX like the dining experience at your favorite restaurant: equal parts efficient and enjoyable.

QA managers hold the insights that separate average customer support teams from all-star customer support teams. Want to see how QA data can improve your AHT (and more)? Take a tour of MaestroQA and request a free demo.

Whether your mission is to generate leads, close sales, or retain customers, every communication is important. Your continued focus is on offering the best customer service experience. To ensure quality service and reliable connection, you must implement a streamlined way to measure quality with a rating scale that demonstrates an understanding of emotional intelligence.  

The easiest and most cost-effective way to do that is to use a Quality Assurance Scorecard as a grading or assessment rubric for your customer service teams. It’s also an effective guide or checklist for what your agents should keep in mind on every call. With a clear understanding of your expectations, your agent will be more successful and productive as they continue to deliver a high-quality level of service.  

What is a Quality Assurance Scorecard?  

A Quality Assurance Scorecard (or QA Scorecard) is a way to quantify the expectations you have for your call center agents. It’s a way for team managers to compare the standards you’ve set with the agent performance you’re seeing based on measurable results on a call, in an email, or even via a live chat and video chat.  

You’re constantly monitoring the quality of your communication with your customers. The best way to review interactions is by evaluating the skills and behavior of your call center agents as part of the customer experience and QA process. Your quality monitoring scorecard offers a quick checklist of what they should keep top-of-mind for every call. It’s also an important coaching tool.  

Why You Need a Quality Assurance Scorecard 

You need a Quality Assurance Scorecard because it’s the best way to determine the level of service you’re really providing. You could conduct customer experience surveys, but those are not always very effective in gauging customer loyalty. You don’t want the first warning signs of poor service to be when your customers stop using your service with no explanation or warning. That’s what happens with 52% of customers.  

When you use a call center quality scorecard, your goal is to improve customer service as part of your QA Program and to understand where gaps are in the customer experience. In one great example, Classpass streamlined its services by saving 6,250 days' worth of chat time. They retained more customers, with an 83% retention rate even during the pandemic.   

What’s The Difference Between Text and Voice Customer Interactions? 

Some 97% of smartphone owners text regularly. Studies show that 7.5 million Americans have trouble using their voices, but there are generational reasons a customer might want to use text instead of talking on the phone or the other way around. Each person you reach out to will probably have a different preference, and that’s not something you can change.

That’s why it’s so important that you offer a range of communication options, including text and voice interactions. You need to support and encourage communication in methods that feel right for every person, while still aligning with your company's values.  

Build Your Scorecard 

Step 1. Start with your values 

You should start by asking yourself and your team about your core values. These value statements will inform what you focus on as you build out your quality assurance scorecard.  

• What are your company values?  
• How do you apply those values to your customer interactions? 
• What are the values that drive your customer interactions? 

You and your team may have different answers for what you consider core values, but this is still an important exercise. This exercise comes down to figuring out why you do what you do. If it’s a core value, then it just makes sense that you will purvey a sense of those values when you communicate with your customer.  

Step 2. Outline your goals

You should know what you’d like the outcome of your interactions to be. You could look at operational goals and Key Performance Indicators (KPIs) to gauge the quality of your customer’s experience. You could look at these factors:  

• Average Abandonment Rate 
• Average Handle Time (AHT)
• Average Speed of Answering (ASA) 
• Average Time in Queue 
• Customer Satisfaction Tracks (CSAT)  
• First Call Resolution (FCR)
• Net Promoter Score (NPS) 

These metrics offer insight into how effective you and your team are, but you can also determine how your productivity levels are directly and indirectly affecting the quality of your service and your customer’s satisfaction.  

Step 3. Identify pain points 

As part of your process of building your call center scorecard, reach out to your customers and agents to find out more about their pain points. As you listen to them talk about challenges, you’ll gain insight into where you could make improvements. Here are a couple of questions.  

• What challenges are they facing?  
• What are some areas for improvement? 

When you see crossovers between what you’re hearing from your agents and your customers, you know that it’s an area you should include on your call center quality scorecard.  

Step 4. Create a framework 

As part of the QA process, you need to create a framework to build your scorecard around, but what is that exactly? You need overarching themes that each represent a section in your rubric. You can use your framework to build out questions for your scorecard. At the core of that framework is an exploration of these four items:  

Communication Skills  

You’re really looking at how effective the agent is at communicating the message and achieving the goal of the call.  

• Did the agent sound friendly?  
• Did they follow the procedures and protocols?  

Based on this framework, you may determine some areas where you can coach the agent on customer service skills.  

Customer Connection 

If the agent can’t connect with your customer, it doesn’t matter how skilled they are. So, that’s the next part.

• Did your agent connect with the customer?  

Correct and Complete Content 

Correct and complete content could overlap with communication skills because there are some of those skills needed as well. Your agent must provide accurate and complete details and information to your customers, not just a canned response. So, did they give out correct answers, and did they effectively use the tools to make sure the customer received those answers?  

Compliance and Security 

While compliance and security concerns vary depending on the type of company you’re working with, you still need to make sure that your agent is following your company policies and procedures to ensure their health and safety in the workplace, as well as broader compliance considerations.  

It’s the 4C framework. You should check in to make sure that every facet of the framework is being part of your call center scorecard.  

Step 5. Criteria for chat & email scorecards 

Your scorecard will include key areas which should fit in the rubric sections. Your goal here is to align these key areas or criteria with brand standards. Some criteria align with chat and email, but there’s also an overlap between written and oral communication methods.  

Quickness to Respond 

Responsiveness is tied in with the chat and phone interactions, but it could affect email responses as well.  

• How quickly does your agent respond?  
• For chat and phone calls, are there long pauses? 
• Is it clear that the agent can respond to all questions with speed and accuracy?  

Problem Resolution 

When faced with a customer support issue, your agent should be able to resolve the problem. That should not discourage the agent from seeking help from a supervisor, particularly with an abusive client. Here are some questions to consider:  

• Was the customer satisfied with the outcome?  
• How quickly did the agent transfer the call?  
• Was an attempt made to resolve the issue prior to transferring the call?  

Compliance with Regulatory Rules 

Healthcare and financial services often require additional regulatory rules and strict guidelines when communicating with those audiences. So the questions would include:  

• Did the agent follow the strict guidelines and rules?  
• Did the agent read the required script?  

Grammar & Spelling 

This issue is more prevalent via chat and email, but it can be a make-or-break issue. Here are some questions to consider:  

• Did the agent use correct grammar, punctuation, and spelling? 
• Was the greeting appropriate in timeliness and conciseness? 
• Was the communication clear and well-informed? 
• Are grammar and spelling issues apparent in multiple channels?

Empathy 

Part of the goal of your interactions with customers is to facilitate human interaction, which is made possible with empathy. Not everyone has empathy, but it’s one of those soft skills that will help you and your agents to succeed.  

Authenticity 

Similarly, authenticity is a crucial part of delivering quality customer service. While there’s no one right way to be authentic with customers, you can usually accomplish a comradeship and easy-going vibe by being relaxed. Your agents might use less formal language, chat informally, and connect with your customers.  

Tone 

The tone of your agent’s voice usually comes across more strongly in voice communication, but you can get a sense of tone in writing as well. Whether it’s obvious or understated, you can get a sense of whether the messaging is positive, sarcastic, or even abusive.  

Etiquette 

You probably don’t have to worry about Emily Post, but you need to make sure that you’re using a professional tone, that you’re not being too familiar with your customers, that you’re not discussing controversial topics, and that you’re being clear and concise.  

Messaging  

Messaging should be professional. Communication should be clear, concise, and on-brand. Your goal here is to connect with your customers, but you don’t want to waste their time.  

Step 6. Create your questions for your scorecard 

Now that you have a sense of what information you’re gathering, you can now start creating questions for your call center scorecard. Here are a few examples you could use:  

• Did the agent correctly tag the ticket? 
• Did the agent use correct grammar?  
• Did the agent correctly identify the issue in the customer interaction?  
• Did the agent follow the correct process?  
• Was the issue resolved to the customer’s satisfaction?  

Creating a call center agent scorecard template just shows how easy it is to create quality monitoring. Once you’ve started digging into pain points and determining the best way to gather insights, these quality assurance processes will be easier and faster in the future. 

How to Score Your Criteria 

The next step is to determine what you’ve actually learned from your Quality Assurance Scorecard. You can score your criteria using something as simple as an Excel spreadsheet. Or you could use QA software to score your criteria and gather insights. There are a few types of questions you could ask:  

• Yes/No questions 
• 0-5 scales  
• Poor => Average => Good => Excellent 

Then, you attach a value to each weighted answer to evaluate the customer’s experience and the agent’s performance. When you’re asking questions about soft skills, it’s a bit more difficult to extrapolate performance based on your customer’s performance. It could just be that the caller got a poor impression of the agent, based on something that was completely innocuous. 

Analyzing Results: Compare Scorecards to Performance Data 

As you score your criteria, you also need to compare the scorecard results with actual performance data, like the CSAT score. It’s important partly because of the reason above. You need to gather as much information about the quality of your customer service as possible. Then, dig into the numbers and determine areas where you need to improve.  

Final Thoughts 

Remember, your QA Scorecard is simply a tool you can use to improve the quality of the service you provide to your customers. It’s not set in stone. It’s an evolving tool that will continue to offer insight into the level of service and support you’re offering.  

The legendary "zen master" NBA coach of the Chicago Bulls and Los Angeles Lakers, Phil Jackson, was at the helm of some of the most exciting championship teams and players in the entire league's franchise. Michael Jordan, Scottie Pippen, Kobe Bryant, and Shaquille O'Neal (to name a few) count Phil Jackson as the reason that they were able to shine bright as major basketball superstars. 

Phil Jackson was a powerful example of how good coaching brings out the best performance in a team, despite different personalities, talents, and ways of doing things. This is what a good coach does in any organization - and if you're coaching customer service agents, you need to keep your skills sharp as well. 

We've gathered twenty tips to help you design a coaching strategy that supports you in showing up as the best customer service coach you can be. Though we'll focus more on a coaching session with an individual, these tips can mostly be applied to group sessions as well. Get ready to build a customer service coaching program that leads your team to championship status through impactful training sessions embodying brand values and keeping the team on a positive note!

What is Call Center Coaching?

Call center coaching is a crucial aspect of delivering quality customer service. It involves providing training and guidance to call center agents to improve their performance and deliver excellent customer experiences.

With effective coaching, agents can enhance their communication and problem-solving skills, handle customer complaints efficiently, and meet or exceed performance metrics. This results in better customer satisfaction, retention, and business growth.

Call center coaching also helps agents to feel supported and motivated, leading to increased job satisfaction and employee retention. In this article, we will explore the importance of call center coaching and how it can benefit both agents and customers.

How to Train Call Center Agents for Performance Improvements

Call center managers are always looking for ways to improve customer service and agent performance. One effective method is through call center coaching sessions. By implementing a QA program and regular coaching sessions, call center agents can receive the training they need to improve their skills and provide better service to customers.

Coaching call center agents involves identifying areas of improvement, providing feedback, and setting achievable goals. This process not only benefits the agents, but also the overall success of the call center. With the right coaching approach, call center managers can see a significant improvement in agent performance and customer satisfaction.

Call Center Coaching Tips

1. Build a Foundation Based on Planning and QA

The foundation of any skills training is having a well-defined outcome for your call center agents to work toward to improve service quality. You can say "customer service" and "quality assurance" all day long, but within your organization, what do those things mean in real, tangible terms? Creating a customer interaction path to a well-satisfied, even ecstatic, customer that your agents can follow from the beginning is the first step in quality assurance. 

Knowing what common pitfalls are part of the customer experience and designing a customer service training program that gives your agents the tools to anticipate and mitigate mistakes is key. However, even with the best-laid plans, there are still times where things go wrong. Having a plan for mitigation in a variety of circumstances gives a new team member the tools to handle an unsatisfied customer with ease instead of floundering in a high-pressure situation.  

Supercharge your manual quality program with speech & text analytics. Learn more about Auto QA from MaestroQA.

2. Build Customer Service Coaching Templates

Though every agent is unique, a scalable coaching strategy will involve coaching templates for training sessions. Templates will give you a quantifiable coaching session process to help your call center agents grow from beginners to excellent customer service champions and you won't have to reinvent the wheel every single time. 

Templates can certainly account for different personality types and styles, but overall should work toward the common goal of increasing customer service capabilities. An added bonus of templates? Coaches can study and practice them so that coaching sessions feel more organic and effective: as the templated foundation is mastered, the coach has more room for creativity and intuition. 

3. Emphasize Skill Building

The best coaches in every industry are constantly growing and working on their skills so they can stay sharp in their roles. As a customer service agent, learning new skills, sharpening your foundational tools, and learning and growing in your abilities are essential to leading your team to success. There are plenty of resources out there from podcasts and webinars, books, and online learning, and as events are opening up in real life, network gatherings and seminars are a great way to get inspired so you can go back to your team and inspire them.

4. Be Strategic With Your Coaching 

Do you have a Kobe Bryant on your team? Congratulations! That person still needs encouragement, affirmation, and guidance - your job is to let them know how they're appreciated. Not everyone on the team is a Kobe, and this is where strategic coaching comes in. 

By coaching your call center agents where they're at, you can be more hands-on with the ones that are still finding their footing and help them develop the skills they need to catch up to their other teammates. Encouragement is key here; communicate that you believe in them, what you see as their strengths, and bring home the point that once they build where they're currently lacking in a skillset that they have a bright future ahead of them. 

5. 1:1 is Always Preferred

One of the gifts of one-on-one feedback is truly being "seen" as an individual, and taking the time to give truly personal attention during a coaching session will do wonders in terms of boosting morale and motivation. 

Group training can be useful from time to time, but during a one-on-one coaching session, customer service supervisors can acknowledge and nurture an individual's strengths, while the sometimes awkward topic of areas for improvement won't be aired out to a room full of colleagues. As an added bonus, individual coaching sessions give you and your agents a chance to build a trusted relationship as coach and coachee, one which will truly create a win-win situation for everyone.

6. Set Expectations Ahead of Time

Have you ever sat down on a Sunday afternoon to plan out what's ahead for your week? If you have, you probably found that you felt more clear, focused, and effective through the coming days knowing what you set out to accomplish and what needed to be done to get there. 

Setting an agenda or plan for a customer service training session helps both the agent and the coach in the same way: both parties know what to expect so there are no surprises, why they're there, so there's less likelihood of sidetracking from the conversation on hand, and a set amount of time so your agent can get to work implementing their performance data, positive feedback and enhance self-directed learning. Read more about how to prepare for a successful coaching session here.

7. Have a QA Scorecard to Review

Your Kobes and your rising stars alike both need something quantifiable to work toward and "prove" that they're making progress with performance data. A QA scorecard, or quality assurance scorecard, is an essential customer service training tool to orient team leaders, call center managers, and customer service agents to real measurable results so that the idea of customer service transforms from something subjective to something quantifiable. That way, neither the coach nor the customer service agent needs to wonder, second-guess or manipulate information. 

Even better, a scorecard gives your customer service staff something to strive for or beat, as they have quantitative guidance on delivering outstanding customer service. To learn more about creating an effective QA scorecard, read here.  

Measure what matters the most with customizable call center QA scorecards. Learn more about MaestroQA's quality assurance scorecard builder solutions. 

8. Assign Specific, Measurable, Action Items

Life and business happen in action, so you must be able to translate your coaching sessions from talking to doing. Using the foundational guides of your company's customer service metrics, your QA scorecard, and any other metrics that your agent would benefit from developing, at the end of your coaching session ask the agent what action items they're going to take between now and the next session. This will imprint in their mind what they are committing to while showing you what they heard and took away from your session. 

All action items must be measurable and specific. For example, "I commit to producing a 10% decrease in my average handle time (AHT)," as opposed to "I'll respond faster."  

9. Keep Your Customer Service Training Engaging

Have you ever had a friend who went to a Tony Robbins seminar and they just would not stop posting about it for what felt like 5,000 weeks afterward and you were wondering why they were so obsessed? Well, if you've been to one yourself, you would know that the world's most famous life coach holds performance seminars that are much more experience than they are lectures. He literally gets his attendees to walk across fire to show them they can achieve anything they desire. We are not recommending you have your agents walk across fire, but by incorporating heightened emotional states into your training programs, your agents will connect powerfully to the messages and takeaways. 

This is where your continued skill-building comes in as a coach. Take them through visualizations of success, remind them of a time they achieved something they thought they couldn't, or help them get out of their head and into a flow state during your training sessions. Monthly or quarterly group training can be an excellent opportunity to create experiential training programs.

10. Customer Satisfaction is the Goal

Have you ever gotten into your car without a predetermined destination? You probably ran into some cool things or a little town off the beaten path, but your company isn't going to be driven to success without direction. Knowing that you're after a very specific destination - high-quality customer interactions - and repeating that destination and goal helps your team stay focused on where you are all going. 

Repetition is key, as it's human nature to get distracted, so don't worry about sounding like a broken record. Don't forget a huge part of customer service coaching through individual coaching sessions is providing your agents with the tools to handle tricky customer encounters.

11. Exceptional Customer Service Starts with Exceptional Management

This tip ties back to number three: as a business leader, management team members should set the tone and example for what they would like to see echoed from any team member expected to deliver exceptional service. 

Walking your talk shows your team that you have integrity and gives your call center agents an actual model of behavior and performance to model. They must see this consistently as it will permeate their mindset and boost their morale over time. You're asking your agents to step up their game and go outside of their comfort zone and your performance needs to reflect that, too.

Streamline QA and make it actionable with the industry's most-loved tool. Get started with MaestroQA for Managers.

12. Start Your Coaching Sessions Early

Customer service coaching success is all about building a foundation and setting a tone from the very start. Making it clear to your agents that strategic coaching resulting in commitments to measurable and specific action items from the beginning of their employment with you makes growth, feedback, and accountability an expectation, not something that pops up quarterly or yearly. 

The added bonus of giving your agents the experience of mentorship from the very beginning is that your agents' morale is likely to be boosted from the very start, as they won't feel like they're treading water or have to play guessing games. Don't forget to integrate your agent's personal goals into their coaching plan for some personalized added excitement while they're tracking progress.

13. Be Strategic with Positive and Negative Feedback

As uncomfortable as it is, everyone on your team is going to need to hear the ugly along with the good - yes, even your Kobe Bryant. As pleasant as it is to have coaching sessions full of high-fives and nothing-but-net celebrations, this is never the norm. 

Remember, as a coach, it is your job to create a container where people are inspired to grow, and that growth happens outside of their comfort zone through constructive feedback that might be difficult to hear and deliver. 

Delivering less-than-positive feedback needs to be done differently with each agent; some can receive it and implement it without taking it personally, while others need more coddling. As a member of workforce management, it's up to you to take note of personality traits from your very first coaching sessions so you can provide constructive feedback. Conversely, understanding how each individual can hear and receive positive feedback is just as important. Knowing what they're doing right will help soften the blow if they have to undergo a particularly intense customer service coaching session.

14. Don't Forget About Soft Skills

Speaking of different personalities, it's important to get off the metrics checklist every once in a while to acknowledge the interpersonal skills that each agent brings to the table. Even though you can't measure psychological factors, using positive language and specific feedback about integral personality traits that an agent possesses is just as important as metric performance. 

If you have an agent who's especially adept at active listening and transforming an irate customer into a brand advocate after feeling heard and understood for five minutes, let them know how valuable that is.

If you have a Type A agent with charm and charisma reaching to the stratosphere, let them know that you see that and you love it. These are more personal touchstones that your agents will appreciate you taking a minute or two to acknowledge. Conversely, you can invite agents to identify opportunities for developing communication methods that could enhance the customer experience.

15. Pair New Agents With Experienced Ones

Another way to motivate employees is by pairing new call center agents with experienced team leads for an added layer of mentorship that promotes employee engagement amongst individual employees. This supports effective coaching and gives new agents a glimpse into a positive service experience. A coach who is constantly honing their soft skills will eventually develop an intuitive sense of which experienced agents new agents will respond and connect with. Every person has a different learning and personality style, and keeping certain compatibilities in mind will maximize the value of this tip in the long run.

16. Periodically Refresh Skills 

Why would Kobe continue to practice his free-throws day after day even after proving himself as one of the greatest of all time? Because it's fundamental - and no champion is above the fundamentals. 

Practicing foundational skills and going back to the basics might seem unnecessary, especially if you're watching the numbers on a QA scorecard go up. However, that's exactly the time to guide your agents back to the free throw. 

As adults, we learn by repetition, and this is another spot where you shouldn't worry about being a broken record. If you're worried about an agent getting bored, remember tip number nine and find ways to keep the experience engaging. 

17. Make Sure Your Agents Have a Deep Understanding

Do your agents understand your product, service, mission, vision, and values inside and out? Even if the knowledge doesn't relate exactly to their job description, possessing deep knowledge of everything the company stands for and is capable of gives your agents useful backup tools that could come in handy in unexpected customer interactions. 

On top of that, when your agents are connected with the company "why," they're able to connect deeper with tip number ten in a way that gives their role a powerful context from which to work.

18. Role Playing

Role-playing can be a powerful tool for helping your agents practice their skills, whether they're brand new and are learning the ropes or they need a confidence boost in connection with areas with room for improvement. 

Be sure to keep this exercise fun and expect that the agent might be a little shy and awkward at first. Remind them they're in a safe space to practice and it's the perfect way to get all their nerves out so they can rock it when it's game time.

19. Make Sure Individual Agents are on the Same Page

While your coaching style should be tailored to individual personality types, the overall results of your coaching program are designed to help you coach employees so that there is a uniform understanding of training priorities within a company's values and brand identity. 

Be sure that your coaching guides your entire team toward the same goal: awesome customer service. They're all sure to talk amongst each other, and discrepancies in messaging and goals will be sniffed out. 

If there is a current initiative, all sessions should reinforce it. Values and mission should be clear to all players involved and if someone seems like they're having trouble grasping the destination, gently remind them of the overarching vision for the company.

20. Invest in QA Software to Help with Customer Coaching

Your coaching skills are the personal touch that your customer agents need and as a coach, you need as much support as you can get as well. Investing in QA software helps streamline the customer coaching process with sophisticated features and ease of use, creating an overall elegant solution that is perfect parts your magic and perfect parts the support you need from modern-day technology. Learn more about what MaestroQA can do to help maximize the magic of your customer service coaching!

When it comes to business success, optimizing how you manage customer experiences is everything. Your products and services can be top quality, but if your customer becomes frustrated with your in-person or online service management process, you will lose their business and tarnish your company’s reputation. 

You can avoid these costly issues if you proactively take steps to understand the customer experience, but identifying issues and resolutions is a never-ending project of it’s own. That’s why an advanced customer experience management framework is invaluable for customer experience optimization in today's business world. 

1. Integrate Your Call Center Helpdesk + Phone System With QA Software

When you integrate your call center helpdesk + phone system software with QA software, you will notice an immediate improvement in efficiency when it comes to grading and understanding customer interactions. These integrations allow you to leave Google forms and spreadsheets behind, which is a major timesaver. 

When the iconic shaving supply brand Harry’s began using QA software, their team quickly noted a huge increase in time savings. They observed that email and chat audit time decreased by 50%, and agents were able to focus more on customer contacts and on adding more comprehensive QA efforts, particularly for holiday sales. As a result, they improved the call center customer experience.

2. Prioritize Specific Scorecards and Feedback With Minimum Thresholds

Customer experience quality assurance is bolstered by the right programs. Your CX software should allow you to create specific scorecards to measure agent performance in your call center across a wide variety of customer interaction types. You can set a minimum threshold score for grading, which alerts you to the agents who are struggling the most. You can then focus on agents who consistently have lower scores than other employees (often, these are the newest agents on your team) and optimize coaching practices to boost their performance - and make the most impact on your customer experience.

3. Filter Tickets by Average Difficulty Level

You can get creative with your QA software so that it provides more sophisticated insights as well. In fact, some business teams have learned how to filter tickets so that they are always grading the most helpful feedback.

For instance, Handy’s grading team takes time to parse out dissatisfied (DSAT) tickets. These are tickets with either negative customer satisfaction (CSAT) scores or those flagged by agents who want a review of a difficult interaction with a customer. This method means the graders are not wasting their time on basic feedback but on tickets that provide more actionable and revelatory information that enhances customer experience optimization.

4. Automate Actions Triggered by CX Metrics

With your CX software, you can automate actions triggered by CX metrics, which expedites corrections and improvements. If you have a customer that gives you a net promoter score (NPS) score of 0–6 (detractor) and asks for follow-up contact, your software can automatically create a ticket that appears in your CRM or Contact Center platform. By doing so, you ensure that a sensitive matter is addressed and not accidentally overlooked, which would negatively affect your customer experience optimization.

You can choose any CX metric to trigger an automatic response, such as CSAT, customer effort score (CES), or any linear scale. This applies to simple star systems as well. You can set your system to automate a response if you receive 1 or 2 stars. 

5. Keep Your Workforce Engaged With a Workforce Management System

The benefits of a CX system go beyond customer experience optimization. They also contribute to a more engaged workforce. This software helps CX managers anticipate fluctuations in support volumes so that they can schedule the appropriate number of agents to address ticket demand. In other words, you do not present your agents with an unreasonable workload, thus allowing them a personal life. 

Also, better training and tools lead to happier, more effective agents who will be more likely to stay with the company. They embrace constructive feedback from customers because they want to improve their skills and to protect the company’s brand. 

6. Optimize Your CX Processes with MaestroQA

Automating customer experience optimization processes means more satisfied customers, better-trained agents, and increased profits for your company. Without these optimizations, you may miss important feedback about your products, services, and staff. Those working with CX may not have all the information they need when they need it. Your reaction to your customers will then be disjointed and flawed.

With MaestroQA, you can enjoy seamless customer service management software that automates vital processes, better data capture and analysis that leads to happier customers and employees. For excellent customer experience optimization and quality assurance, request a free demo today. 

Regardless of the type of business you're running, one of your most invaluable assets is and will always be your customers and the interactions you have with them.

That, in essence, is why understanding what takes place on your customer service calls is so important: it helps guarantee that you're offering a level of quality, care, and attention to detail that people simply won't be able to find anywhere else.

But at the same time, how you interpret what happens on those calls is just as important as doing it at all. You need to consider what "quality" means within the context of your own organization, and even what your long-term goals are for the customer service component of your business.

Getting to this point isn't necessarily difficult, but it does require you to keep a few important points in mind.

Why Evaluate Customer Service Performance?

Evaluating customer service performance helps make sure that each touch point that someone has with your business is not only consistent, but is of a level of quality that they've come to expect.

Whether you realize it or not, that customer service call is a true reflection of your brand. If it's a negative experience, people will look at your products and services the same way - and that is not something you want to happen.

All told, the benefits of customer service quality assurance include but are certainly not limited to:

• Increased customer satisfaction. People feel like they're getting something of value beyond just the purchase they've already made.
• Superior financial performance. Satisfied customers don't just buy more, they also stay with your company longer. Not only that, but they're also more likely to recommend your products or services to friends and family members, too.
• Improved brand awareness and brand loyalty. People who have high quality experiences with a company are far more likely to tell others about it, extending your reach.
• Building better coaching programs. QA managers can help build a much better program for agent progression, thus creating a more consistent and helpful experience for every last customer who calls.
• Improved agent engagement and reputation. The more engaged agents are, the better customer experiences will be. That improves the reputation of your company significantly, which in and of itself is the most important benefit of all.

Grading Customer Service Calls

When it comes to actually grading customer service calls, each individual interaction with a customer is graded by first recording and analyzing the call itself.

If you've ever called a company and heard a message before being connected to an agent that said, "This call is being recorded for quality assurance," you've been a part of this process.

At that point, a scorecard with questions is used that relates to specific criteria - meaning the goals that you want each call to accomplish.

Those are correlated with certain key performance indicators (KPIs) and larger company objectives, all to determine just how successful the call actually was.

Understand Your Goals for Customer Service QA

Having said all of that, there are still a few points that companies often stumble on - mistakes that should be avoided at all costs.

For example, it's always crucial to make sure that the team of agents and managers are all on the same page - meaning that they all understand what needs to be done on customer calls, more importantly, why.

The quality assurance program cannot exist in a vacuum, siloed off from the rest of the company. All key stakeholders need to agree on a direction, as this is how you align the program with the larger vision of the company. Your QA scorecard that you’re using to grade calls needs to embody and represent these values to keep everything aligned. 

Define Your Criteria

As stated, one of the most important parts of any quality assurance program comes down to your ability to define the criteria that matters most to you.

All organizations are different - if you took a look at your closest competitor, you'd likely be looking at a very different business from your own with different priorities. Therefore, the criteria you choose need to be influenced with the exact same mentality.

Measuring the overall customer experience and team efficiency may be a priority, for example. You could judge your customer service program's productivity over time.

Here Are Some of the Most Important KPIs

While it's true that the metrics you choose will vary based on what you're trying to accomplish, there are a few helpful ones that will make evaluating the performance of your program as efficient as possible.

These include but are not limited to ones like:

• First Call Resolution, or FCR. This keeps track of the number of customer issues that take only one call to complete.
• Average Handle Time, or AHT. As the name suggests, this measures how long your average customer is spending on the phone.
• Average Speed of Answering, or ASA. This measures the amount of time it takes for someone to reach an agent in the first place.
• Customer Satisfaction Score, or CSAT. This dives deep into how pleased customers were with the experience of making that call.
• Net Promoter Score, or NPS. This measures how loyal someone is to your business.
• Agent's Tone and Language. This gives you a better indication of how agents are expressing themselves during calls.

The Best Way to Measure Call Center Quality Assurance Metrics

In the end, customer service quality assurance programs are a great way to improve the performance of a business by elevating the experience and satisfaction for customers. The first and most important step is to put yourself in the mind of the customer and imagine what would define a good vs. bad customer experience.  Answering an incoming call quickly (ie, low ASA) may not be as important as how long the caller has to remain on the line until a resolution (long AHT), or if they have to call back multiple times (low FCR).

When you consider the fact that serving customers is a large part of why a business is successful in the first place, it's easy to see why this is all so essential. MaestroQA can be a trusted partner in untangling the knot - if you're interested in learning more, request a demo today.

If you’re reading this, chances are you’re under a lot of pressure to deliver exceptional customer experiences—and you’re not alone. After all, more than two-thirds of companies compete primarily on the basis of CX, according to a study from Gartner.

Today’s customers have little patience for sub-par customer support experiences, and they won’t hesitate to switch brands if the service isn’t up to their standards. In fact, nearly half of people have ditched a brand because of a bad customer service experience in the past year.

An ideal customer service experience is efficient and easy: customers don’t want to chat with support agents all day, but they also want their issues solved correctly. In this article, we’ll cover five components every agent interaction should have in order to keep customers satisfied and loyal.

Let’s get started.
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1. First Contact Resolution

For 33% of people, the most important aspect of a good customer service experience is getting their problem fixed in a single interaction, according to Microsoft’s State of Global Customer Service Report.

Support agents often focus on resolving tickets quickly (we’ll get to that in a bit). But resolving a ticket the first time a customer reaches out is even more important. The first step to making that happen is calculating your First Call Resolution (FCR) rate.

The formula for FCR rate is simple: divide the number of support tickets that were resolved on the first contact by the total tickets from the same time period. That percentage is your FCR rate (74% is the average, according to MetricNet).

If your FCR rate is lower than you’d like it to be, here are two ways to improve it:

• Coach agents to identify and address the root cause of customer issues—not the symptoms. Let’s say a customer uses harsh language when venting their frustration about a software product. An agent’s follow-up questions might reveal that the customer overlooked a quick fix because they’re unfamiliar with the product.
• Preempt problems by addressing frequently asked questions about your product, service, or policies. For example, if multiple customers in the past had trouble updating their subscription frequency, a quick reminder upfront can save time down the road.

2. Adherence to Quality Standards

High-quality customer support means different things for different businesses, but in general, it includes soft skills like tone of voice and following protocols. At MaestroQA, we analyzed 265,000 customer interactions and found that authenticity, a friendly tone, and empathy had the strongest correlation with customer satisfaction (CSAT).

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Let’s not get ahead of ourselves, though. Before you coach your agents to adhere to quality standards, you have to establish those standards in the first place. For example, here are Intercom’s support values:

• Thriving under pressure
• Connecting personally with empathy
• Being an owner
• Being resourceful

Once you pinpoint your brand’s quality standards, you need a process to help agents stick to them. That’s where a quality assurance (QA) program comes in, where managers review customer interactions and quantify how well agents live up to your quality standards.

The backbone of every QA program is a QA scorecard (or rubric). This consists of a questionnaire and a system to grade agents for each question. Here’s what that looks like:

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3. Minimal Customer Effort

Difficult customer service experiences don’t just annoy customers—they erode loyalty too. In fact, 96% of people who experience a high-effort customer service interaction become less loyal to that brand, according to Gartner.

But what exactly constitutes “high-effort,” and how can you make those experiences easier?

Harvard Business Review noted that the main driver behind excessive customer effort is having to reach out to a company multiple times to fix a problem. Customers are already strapped for time; the last thing they need is a series of phone calls with support.

To avoid this issue, review past interactions to spot patterns that lead to repeat calls. For example, a new agent might not know when to escalate an issue or transfer the customer to a different agent, both of which can yield incomplete resolutions.

Another factor that inflates customer effort is asking customers for information that’s already available in the agent’s CRM. That includes account numbers, order numbers, and the date an order was placed.

If that’s the case, use 1:1 coaching sessions as an opportunity to show agents how to quickly grab that information from your CRM to save your customer’s precious time—even if it’s only a few seconds.

4. Fast Resolution (Without Cutting Corners)

There are two words every customer dreads: “Please hold.”

Any customer service experience—whether via email, phone, social media, or chat—that’s dragged out longer than necessary is frustrating. To help agents cut down on the time it takes to resolve tickets, CX teams need to get familiar with Average Handle Time (AHT).

For starters, here’s how you calculate AHT:

AHT = (total call time + total hold time + follow-up time) / total number of calls

AHT benchmarks vary depending on the industry. For example, Call Centre Helper notes that a good AHT for financial services is 4.75 minutes, while the benchmark for telecommunications companies is about 8.5 minutes.

Regardless of where you fall on that spectrum, here are two ways to reduce your AHT without sacrificing quality:

• Establish or expand your internal knowledge base (IKB) so agents can look up answers to recurring questions without eating up the clock. When Lyft teamed up with MaestroQA to optimize their IKB, their AHT dropped drastically.
• Automate tedious tasks so agents can channel their energy to high-level issues. For example, ClassPass noticed that subscription cancellations took up a ton of time, so they fully automated the process and saved 6,250 days’ worth of annual chat time.

5. Omnichannel Support

Omnichannel support means giving customers the flexibility to choose the type of support they want, whether that’s a phone call, live chat, or self-service. For example, an experienced customer might prefer a support article, while a new customer may feel more comfortable talking to an agent.

Offering omnichannel support might seem like a lot of work upfront, but it pays dividends in the long run. According to Zendesk, brands that provide omnichannel support options experience higher CSAT scores and faster response times.

Monday.com’s support hub is a prime example of omnichannel support. Customers can get quick answers via a knowledge base, webinars, or even a VIP training package. Then, if customers need additional help, they can contact the support team 24/7.

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Improving Customer Experiences Is the Ultimate Competitive Advantage

Every company has a different formula for success. For some, it’s product innovations; for others, it’s clever marketing. But one factor no brand can afford to neglect is a top-tier customer experience. More than 60% of people have cut ties with a business because of a poor customer service experience, according to Microsoft.

Think of CX like gas in a car: you can have heated seats and a V8 engine, but if your tank is empty, those features are irrelevant. So use this list to check your fuel level, and adjust accordingly.

Want to see how world-class data translates to world-class customer experiences? Request your demo of MaestroQA today.

Right now, the fate of most companies doesn’t depend on branding, product features, or even price—it depends on the quality of their customer experiences.

Gartner reports that more than two thirds of businesses compete primarily on the basis of customer experience (CX). But you can’t create exceptional experiences if you don’t understand your customers’ preferences and pain points.

That’s where Voice of the Customer (VOC) comes in.

VOC data is the foundation for building a loyal, satisfied fan base for your brand. That’s why CX teams that mine customer interactions for audience insights (and apply them) gain an edge over their competitors.

In this article, we’ll explain how to collect VOC data and apply it to optimize your customer experiences.

What Is Voice of the Customer (VOC)?Voice of the Customer (VOC) is the process of systematically capturing customer feedback to understand their expectations, preferences, and struggles.

As the name implies, VOC requires companies to listen to what customers say—not assume what they think based on gut feelings or cherry-picked anecdotes. VOC data is collected through a combination of quantitative and qualitative research techniques to get a holistic understanding of customer sentiment.

Think of VOC like your brand’s customer service “algorithm:” the feedback from customers equips your support agents with the insights they need to serve up the best possible customer experiences.

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Voice of the Customer Research: Diversify Your Data

Voice of the Customer is a catch-all term for collecting audience feedback. Accordingly, there are several research methods you can use.

Every audience has its nuances, so VOC can’t be confined to one or two metrics. That creates blind spots. Instead, CX teams need a blend of qualitative and quantitative research techniques to get a 360-degree view of what customers are saying about the brand.

Here are six tactics you can mix and match to keep your finger on the pulse of your VOC:

1. Customer Satisfaction (CSAT) Surveys

A CSAT survey is the most popular method to collect customer satisfaction data. CX teams send these surveys after a customer interacts with a support agent.

CSAT surveys consist of one question: How satisfied are you with your experience?

Customers use a scale of 1-5 to rate their experience, with 1 being “extremely dissatisfied” and 5 being ”extremely satisfied.“

2. Net Promoter Score (NPS)

NPS estimates the likelihood of a customer referring your company to a friend, family member, or colleague.

You’ve heard the famous NPS survey countless times: “How likely are you to recommend us to someone?”

NPS alone isn’t enough to indicate how loyal your customers are, but it’s a solid starting point.

3. Review Customer Support Call Recordings

In terms of Voice of Customer research, it doesn’t get more literal than this. Listening to recorded conversations is a great way to pinpoint what’s driving customers crazy, what they love, and everything in between.

One way to review key conversations is by setting up a call tagging system. This lets your agents flag problematic conversations so you can review them later to see what went wrong.

Now you know the rationale behind that ever-popular disclaimer: “This call may be recorded for quality assurance purposes.”

4. Conduct Customer Interviews & Focus Groups

Organizing feedback sessions with customers is time-intensive and, accordingly, tough to scale. But the upside is you get granular insights other VOC research techniques might miss.

To make the most out of this method, invite customers that fall into three groups:

• VIP customers: your big spenders and brand advocates
• Passive customers: talking to people who use your product or service but aren’t particularly engaged helps you find the missing link that turns them into brand advocates
• At-risk customers: those who are churning, or you’re struggling to retain

Ask each of these groups about their experience with your company so you can preempt problems and double down on what’s driving success.

5. Social Media Listening

Social media feeds offer the most candid look into how customers talk about you. Social listening tools like Hootsuite and Buffer let you track mentions of your brand or relevant keywords, giving you a real-time look into the conversation around your brand.

For example, you might notice customers tweeting about problems with a product update or Instagram stories of people giving you a shout-out.

Whatever the case, social listening tools allow you to engage quickly and compile data for training purposes.

6. Keep Tabs on Customer Reviews

If someone takes time out of their day to write a review (whether positive or negative), pay close attention. Customer reviews are a rich source of VOC insights, especially on third-party review websites like G2, Google, or TrustPilot, where prospective customers do research before making a purchase.

Sifting through negative reviews isn’t fun for any CX leader, but it’s essential to identify areas for improvement and set your agents up for future success.

You have options when it comes to VOC research methods—but it’s not enough to collect data. You have to apply it.

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Apply VOC Data to Improve Customer Experiences: 4 Strategies

VOC data is illuminating, but it doesn’t do any good sitting in a spreadsheet. Let’s look at four ways you can use VOC data to boost agent performance and elevate the customer experience.

1. Review Quantitative VOC Data Alongside Quality Assurance (QA) Reviews

Performance metrics like CSAT and NPS indicate whether customers are satisfied or loyal, but they can’t tell you which aspects of customer experience contributed to the customer’s survey response.

CX teams can contextualize quantitative data with quality assurance (QA) scores, which gauge how well agents adhere to a brand’s internal standards for customer service quality. QA scores are determined by CX managers using a QA scorecard, which includes questions like:

• Did the agent use a friendly tone?
• Did the agent follow the proper steps to resolve the customer’s issue?
• Did the agent clearly explain the solution to the customer?

This strategy helps CX teams understand the “what” and the “why” behind customer experiences so agents can perform up to their potential.

2. Guide Agent Coaching Sessions with VOC Data

Customer service coaching is critical to helping agents reach their potential. But in order to maximize the effectiveness of these 1:1 sessions, CX teams need to rely less on opinions and more on data.

Here’s an example of how VOC data improves customer service coaching:

Let’s say you review your VOC research and find that customers are happy with how friendly your agents are, but they had to reach out to support multiple times to fix their problem.

Instead of apologizing and hoping for the best, you can apply that insight to future coaching sessions. Specifically, you’d help agents prioritize First Call Resolution (FCR) rate.

3. Identify and Improve Weak Spots in Your Customer Support Processes

Just like user feedback helps engineers fix bugs in an app, VOC data helps CX teams tweak their processes to make customer experiences smoother.

For example, the online fitness subscription company ClassPass found their biggest driver of negative sentiment was cancellation chats. That led them to an idea that reduced customer effort (and let agents focus on other tasks).

“In 2019 alone, we spent the equivalent of 6,250 days—that’s more than 17 years—chatting with 1.5 million contacts for cancellations,” said Sydney McDowell, CX Enablement Lead at ClassPass. “COVID-19 compounded this situation, so we decided to fully automate this process. Now we have zero cancellation chats handled by agents.”

4. Improve the Onboarding Experience for New Agents

Lessons are often learned the hard way in the world of CX. But that doesn’t mean new hires should go through the same gauntlet as agents who’ve been around the block.

To shorten the learning curve for new agents, share past VOC insights during onboarding. This helps them get a grip on what works (and what doesn’t) before they engage with their first customer.

For example, if past negative sentiment on social media stems from a specific product issue, make sure new hires have a thorough understanding of the product so they can preempt that problem with future customers.

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Listening to Customers Isn’t Optional

In a world where more than 80% of businesses expect to compete on the basis of customer experience, neglecting your audience’s feedback has dire consequences.

Fortunately, listening closely to your customers gives you a competitive edge—and data from Aberdeen proves it.

Brands with best-in-class VOC programs (those that put sentiment data into action) have higher retention rates, higher profit margins, and higher employee engagement rates compared to average or below-average organizations.

Are you ready to raise the bar for customer experience? Request a demo of MaestroQA today.

Your next customer service coaching session is coming up, you might be feeling nervous, and possibly even anxious about a potentially long list of ways to improve. Coaching sessions don't have to be that way! In fact, if you come with questions, ideas, and (most importantly) data, it can be a collaborative process that improves your customer service skills and advances your career.

Before we dive into specifics, let’s quickly cover the agenda you can expect during a 30-minute coaching session:

• Review Quality Assurance (QA) scores: 5 minutes
• Review productivity metrics: 5 minutes
• Discuss feedback on scores and metrics: 10 minutes
• Discuss goals and action items: 5 minutes
• Discuss miscellaneous questions and insights: 5 minutes

The more you prepare for these meetings, the more value you’ll get out of them. Here are five tips to ensure you make the most of your time. (If you’re a CX coach or manager, be sure to share this resource with your agents!)

1. Come Prepared with Performance Data

Data is the foundation for a productive coaching session because it grounds your conversation in evidence—not opinions. Every agent has unique strengths and areas for improvement, so digging into the data ensures you get the individualized feedback you need to excel.

If your company uses customer service coaching software like MaestroQA, your performance metrics are centralized in a dashboard like this:

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There are two pillars of data to familiarize yourself with before heading into your coaching session:

Quality Assurance (QA) Scores

Your QA scores indicate how well you performed against your company’s standards for customer service interactions. This may include criteria such as adhering to the brand’s communication style guide or following the right process to resolve an issue.

If you’re new to QA scores or just need to refresh your memory, check out our complete guide here.

Productivity Metrics

These metrics gauge customer sentiment and reflect how efficiently you resolved their issues. Here are four common metrics you might discuss with your coach:

• Customer Satisfaction (CSAT) Score: Indicates how happy a customer is with the assistance you provided
• First Contact Resolution (FCR) Rate: The percentage of issues you resolve the first time a customer contacts you for support
• Average Handle Time (AHT): The average time it takes you to resolve support tickets
• Net Promoter Score (NPS): Estimates the likelihood that a customer will recommend your company

Productivity metrics aren’t as actionable as QA scores because they only indicate if—not why—your customer interactions are successful or not. In other words, this data is a jumping-off point, but it’s not the end all be all of your career.

It’s natural for productivity metrics to fluctuate, so don’t get down on yourself if you don’t improve them every month.

2. Review Feedback and Progress

Ideally, your coach gave you some feedback or assigned you some tasks and/or goals in a previous session. Now you have an opportunity to circle back on the progress you made and call out any challenges you faced along the way.

Here’s an example of what your coaching notes might look like:

If you feel like you aren’t being challenged, let your coach know you have higher expectations for yourself. On the other hand, don’t be afraid to speak up if you feel overwhelmed by unrealistic goals or a mounting to-do list. In either case, your coach can work with you to align your workload with your capabilities.

If you’re going into your first coaching session and you don’t have much to review, get proactive and ask about the company’s internal standards for performance. This gives you a feel for what goals to set for yourself, which is a perfect segue into...

3. Collaborate with Your Coach to Set Goals and Action Items

Once you have a clear understanding of your performance data and progress, you’re ready to set goals and plan how you’ll achieve them. Your coach may suggest a specific goal, but it’s important to remember that the goal-setting process is a collaborative one. If you’re not comfortable with a goal or think you can aim higher, this is your time to say so.

Here are some examples of customer service goals:

• Refine your soft skills like empathy or authenticity.
• Increase your technical knowledge about a product or service.
• Improve your CSAT scores.
• Reduce your number of escalated tickets.
• Get more familiar with the brand’s communication style guide.
• Decrease your Average Handle Time.

Setting a goal is great, but it can be tough to stay on track without a step-by-step plan to reach it. That’s where action items come in—these are the links between goals and results.

For example, if you want to improve your rapport with customers, ask: “I want to establish more authentic connections with customers—what are some specific steps I can take over the next few weeks?” In this case, an action item could be completing an online course about emotional intelligence from a learning management system like Lessonly.

When you work alongside your coach to set action items, make sure they meet the SMART criteria: specific, measurable, attainable, relevant, and time-bound.

4. Bring Your Point of View to the Table

The ideal coaching session is one where you feel equally comfortable sharing and receiving feedback.

For example, you might feel that you were scored unfairly on a recent QA scorecard. In this case, appealing the score is the first step to resolving the discrepancy between your impression and the score you received.

Let’s say the QA grader noted that there was friction between you and a customer when they had trouble getting a refund. Instead of accepting a low score, start a conversation with your coach by saying, “I felt the interaction went smoothly. The customer seemed satisfied throughout the conversation and thanked me for my help at the end of the call. I think my score should reflect that. What do you think?”

As an agent, you have a unique vantage point into the customer experience and the company as a whole. If you see any red flags, don’t hesitate to speak up. If you notice a bug in your company’s product or find a resource that can help your team solve problems more efficiently, pass that information along to your coach, who can relay it up the chain.

Your feedback doesn’t need to be limited to customer support topics, though.

Take a minute to discuss your morale, stress levels, and work-life balance. Considering how high the agent turnover rate is, CX leaders appreciate insights that can prevent burnout and help them retain their top talent. If you feel like your concerns aren't being taken seriously, initiate a discussion with a human resources (HR) representative.

5. Ask About Professional Advancement Opportunities

Your coaching session might not be the right moment to ask for a promotion or raise, but it is the moment to determine the steps you need to take to earn one. Toward the end of your meeting, take some time to discuss your career goals and how you perceive your current role on the team.

Here’s an example of how you can broach the subject: “I’m really happy with the progress the team and I have made over the past few months. What is the typical timeline for promotions, and what can I do to reach the next level?”

You may feel uncomfortable talking about promotions, but discussing long-term planning can actually be reassuring to CX leaders because it demonstrates that you’re committed to the team.

Customer Service Coaching Is a Team Sport

Your coach has the insights and expertise to put you on the path to success. But there’s still plenty of room for you to take ownership of your growth as a customer service professional.

To maximize the value of your learning experiences, get proactive by digging into the data, offering feedback, and asking questions. You’ll know you’re having a productive coaching session when it feels more like a conversation than a lecture.

Ask your coaches to consider MaestroQA as part of their coaching toolkit here.

Customer support teams face countless challenges every day—but the most troubling one is agent turnover. Attrition rates for contact center representatives range from 30-45% compared to the U.S. average of 12-15% for all industries, according to Quality Assurance and Training Connection.

In the midst of the Great Resignation of 2021, there isn’t an easy answer as to why agents are so keen to jump ship. But it is clear that high turnover rates aren’t sustainable.

Constantly recruiting, hiring, and onboarding new agents is time-consuming and costly. Not to mention it’s detrimental to the quality of your customer service. No team is immune to turnover, but you can put the odds of employee retention in your favor.

Reducing customer support representative turnover requires a deep understanding of your agents’ day-to-day experience and proactive strategies to keep them engaged.

Let’s explore how you can make that happen.

Start by Evaluating the Agent ExperienceBefore you launch any initiatives to retain your agents, it’s essential to find out why they might be tempted to leave in the first place. Here are two ways leaders get a clear view into the agent experience.

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Get Feedback from Anonymous Employee Engagement Surveys

The most proactive way to gauge the quality of your agents’ experience is through anonymous surveys, which allow them to voice concerns and frustrations without fear of judgment.

There are several options for survey mechanisms, from dedicated employee engagement platforms like Great Place to Work to free tools like SurveyMonkey and Google Forms.

Including yes-or-no questions in your survey helps you quantify the agent experience, but to uncover why agents feel the way they do, include space for open-ended comments.

Here are some sample questions that can generate actionable insights:

• Do you feel like your voice is heard?
• Do you have a good working relationship with your manager?
• Do you clearly understand your goals and objectives?
• Do you have the resources you need to do your job effectively?

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Conduct Exit Interviews

If an agent resigns, set aside 30 minutes to ask them about their decision to leave, as well as what suggestions they have to improve the experience for their former colleagues.

Here are some ideas for exit interview questions:

• Why did you begin looking for a new job?
• Did you feel you were prepared to do your job well?
• How would you describe our team’s culture?
• Is there anything we could’ve done to keep you here?
• Did you have clear goals and objectives?
• What changes would you make to our culture/processes?

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Understand the 4 Common Causes of Customer Support Agent Turnover (and What to Do About Them)

Retaining talented agents requires leaders to address the root causes—not the symptoms—of turnover. Let’s explore four issues that contribute to attrition and how you can mitigate them.

1. Unrealistic Expectations and Workloads

Customer support is notoriously demanding work, and managers rank agent workloads among the biggest challenges they face. Putting agents under pressure to handle more tickets and continually improve CSAT scores is a recipe for burnout, which HR leaders say sabotages retention.

What to do:

• Implement or expand self-service options like help centers and chatbots to take the strain off agents.  Note: technology can supplement human help, but it can’t replace it. Tech isn’t an excuse to hire fewer agents and give the same amount of work to a smaller team.
• Give agents tools and resources to handle tickets more efficiently: canned responses or maybe new customer service software.
• Hire more agents—sometimes this is the only realistic way to maintain reasonable workloads.

2. Non-Competitive Compensation

There’s no shortage of customer service jobs available. In fact, there are nearly 3 million customer service jobs in the United States, according to the U.S. Bureau of Labor Statistics. Naturally, agents won’t hesitate to jump ship if they can make more money elsewhere.

What to do:

• Compare your agents’ pay to similar jobs in your area as well as your competitors. Matching or beating the going rate may persuade an agent to stay if they’re on the fence. For a detailed breakdown of customer service representative compensation by location, check out this report from the U.S. Bureau of Labor Statistics.
• Consider offering benefits. According to the Work Institute’s 2020 Retention Report, the percentage of interviewees citing benefits as the most important reason for leaving has more than doubled since 2010.
• Offer bonuses and raises as incentives so agents know they aren’t stuck at a dead end.
• Offer the ability to work remotely—more than half of adults want to work primarily from home, even after the pandemic.

3. Inadequate Coaching

Most agents undergo baseline, check-the-list training during their onboarding process. But letting them loose without ongoing, formal coaching can erode their confidence and cause confusion, leading them to seek opportunities elsewhere.

To engage agents and maximize their potential, they need consistent, 1:1 coaching sessions. These close knowledge gaps and keep agents aligned on their individual and team goals.

What to do:

• Collect quality assurance (QA) data to find opportunities for improvement. For example, you might find an agent struggles with product knowledge.
• Establish a cadence to ensure consistent feedback—one coaching session per month is ideal.
• Set up a system to monitor agents’ progress over time. For example, MaestroQA’s coaching dashboard gives 360-degree insights into agent performance metrics. This gives agents a clear understanding of their strengths and what they need to focus on.
• Encourage 2-way feedback during coaching sessions. Letting agents voice their opinions is vital to making them feel like human beings, not cogs in a machine.

4. No Clear Path to Grow

When customer service agents don’t see a path for professional development, they (understandably) disengage and seek other options to level up their career. In fact, career development is the number one cause for employee turnover, according to a report from Work Institute.

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What to do:

• Create pre-defined tracks for agents to follow in order to climb the ranks. This roadmap creates clear expectations for advancement, so agents aren’t confused as to why a peer receives a promotion or raise.
• Implement an internal mentorship program where senior agents can help newcomers chart their career path or just be a sounding board.
• Highlight team members’ promotions and key wins to remind everyone that career growth is possible within the organization.

Your Agents are a Valuable Asset. Treat Them Accordingly.

More than two-thirds of brands compete mainly on the basis of customer experience, according to data from Gartner. When the fate of a company hinges on customer support agents, retaining top-performing talent is paramount.

Employee retention doesn’t happen by coincidence, though. It’s the byproduct of strong leadership, empathy, and a culture that actively helps employees grow personally and professionally.

Teams that invest in their agents will reap the rewards of a strong culture and elite customer service. But treating them like a number on a spreadsheet will only increase the turnover rate.

Ready to see how data can give your customer service team a competitive edge in coaching? Get your demo of MaestroQA today.

Take a minute to think about all of your recurring expenses: streaming services, workplace apps, gym memberships, the list goes on. Now, consider which of those companies you’d stick with even if a cheaper option became available.

If you make that distinction, you’re starting to understand the difference between customer retention and customer loyalty.

Customer retention (hanging onto repeat buyers) is often touted as the holy grail of business operations. But repeat customers aren’t as valuable as loyal customers, who go beyond spending money to spread the word about a brand.

Even though customer loyalty has a somewhat magical quality (which you’ve witnessed if you’ve ever tried to get an Apple fan to switch to a PC), it doesn’t happen by accident. It’s a process—and it starts with your customer service team.

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Customer Loyalty vs. Customer Retention: What’s the Difference?

“Customer loyalty” and “customer retention” are sometimes used interchangeably, but there’s an important difference between these two terms.

A retained customer is someone who makes repeat purchases from a company, whether through a subscription or by consistently choosing them over a competitor. However, this customer isn’t necessarily passionate about the brand. If they see an ad for a newer or cheaper option, they won’t hesitate to make the switch.

A loyal customer, on the other hand, gives a brand more than money. They willingly tell their family, friends, or colleagues about the brand—and they’re likely to stick with the brand, no matter how enticing competitor’s product or ad campaign might be.

For example, maybe you've bought the same dish soap for years, simply out of habit. That company has retained you. But if a new brand runs a sale or has interesting packaging, you give it a chance because you're not particularly loyal. But when it comes time to take your car to the shop, you go to the mechanic you trust, and no amount of advertising from their competitor will change your mind. That's loyalty.

In short, the variable that separates customer loyalty from customer retention is an emotional connection.

Why Customer Loyalty Matters More than Customer Retention

Customer retention is important for a brand’s bottom line. In fact, acquiring a new customer can be up to 25 times more expensive than retaining a current one. But cultivating loyalty ensures your fan base sticks around instead of switching to a competitor.

Here are three key reasons loyalty must be top-of-mind for all CX leaders.

1. Loyal Customers Generate New Customers

Loyal customers don’t just have a transactional relationship with a brand—they are brand advocates who attract new customers via word-of-mouth.

When consumers are inundated with endless options, referrals can be a brand’s lifeblood. In fact, 92% of people trust recommendations from friends and family more than any form of advertising, according to Nielsen.

2. Loyal Customers Pay Up

When the price of a product or service affects someone’s purchasing habits, that’s a form of price sensitivity.

Let’s say a new Wi-Fi provider offers you the same service for 15% less than you pay now. If you switch for that reason, you’re price sensitive.

Loyal customers, however, are price-insensitive (to a degree). In other words, they’re willing to pay more for a brand they’re familiar with, whether that’s because of stellar customer service, convenience, or aesthetics.

Apple has arguably the most price-insensitive fan base in the world. They can raise their prices and still have devout Apple users lined up around the block.

3. Loyal Customers Make Your Brand Competition-Proof

It’s hard to turn your back on a brand that consistently wows you with remarkable customer experiences. Make no mistake: competitors will go to great lengths to steal customers through aggressive advertising and lower prices. But at the end of the day, loyalty is stronger than any marketing campaign.

How Do You Know if Your Customers Are Loyal?

Unlike performance metrics such as customer satisfaction (CSAT) and first call resolution (FCR), loyalty is an intangible characteristic, meaning there isn’t a specific formula you can use to measure it.

However, one way to get an idea of how loyal your customers are is by tracking Net Promoter Score (NPS). NPS determines the likelihood of a customer recommending a brand to someone they know. You measure NPS with a single-question survey. Here’s an example:

On a scale of 1-10, how likely are you to recommend [company] to a friend or colleague? 1 = extremely unlikely and 10 = very likely.

The responses to NPS surveys can suggest if a customer is loyal, but it can’t tell you why they’re loyal (or why not). To work around this problem, CX teams should review NPS in tandem with quality assurance (QA) scorecards.

QA scores add context to NPS scores because they indicate where a support agent might have missed the mark in terms of adhering to the brand’s quality standards. For example, if the agent used the wrong process to resolve an issue and caused an unnecessary delay, that could erode a customer’s loyalty to the brand.

Another way to gauge customer loyalty is by asking how new customers found you. During onboarding, include a survey question along the lines of, “How did you hear about us? Social media, podcast, news article, friend, coworker, etc.”

If you notice a lot of new customers find you through referrals, that’s usually a sign of a loyal fan base. Alternatively, generating unique promo codes for your customers to share can be a way to track exactly which customers are also your biggest advocates.

3 Ways CX Teams Turn Repeat Customers into Loyal Customers

If you want to improve customer loyalty, you have to improve the customer experience. That starts with agent interactions. Here are three ways CX teams can turn repeat customers into raving fans.

1. Make Customer Interactions as Easy as Possible

The strongest predictor of brand loyalty is how easy customer interactions are, according to Gartner. This echoes Harvard Business Review’s findings that going the extra mile to delight customers isn’t as effective as making their experiences easier.

The main driver of high customer effort scores (CES) is having to contact customer service multiple times to resolve an issue, according to Harvard Business Review. Accordingly, agents must prioritize first call resolution (FCR). That starts with coaching them to anticipate problems before they arise and addressing the root cause of customer complaints (not the symptoms).

2. Coach Agents on Soft Skills

At MaestroQA, we analyzed more than 265,000 interactions from 80+ ecommerce brands to see which customer service skills drive customer satisfaction. The top three were empathy, authenticity, and a friendly tone.

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These soft skills can make the difference between a “meh” experience and an experience that inspires customers to advocate on your behalf. But how can you teach those soft skills to agents?

That starts with leveling up your customer service coaching.

For example, review agent’s call scripts to identify gaps in their performance and use those insights to inform 1:1 coaching sessions.

3. Leverage Quality Assurance (QA) Insights to Improve Agent Interactions

Top-performing customer support agents are natural problem solvers with high levels of emotional intelligence. But without a system that standardizes those traits, you can’t measure and improve them.

That’s where Quality Assurance (QA) data comes in.

QA scores measure how well agents perform up to a company’s standards for customer service. That gives CX teams actionable insights into what they need to do to elevate customer experiences.

Consider MeUndies, a direct-to-consumer underwear and apparel company. A critical part of their customer experience is portraying the MeUndies brand voice. But since brand voice tends to be intangible, CX leaders struggled to define and teach it.

To overcome that challenge, MeUndies created a rubric built around their brand voice (see below).

Each item on the rubric is reflected in their QA scorecard , and graded by CX managers, so agents always know which areas require more focus. This data-backed approach to consistent, branded communication helped MeUndies grow 1,583% in just three years.

Loyalty Is the Ultimate Competitive Advantage

When customers have the freedom to choose from countless brands with nearly identical products and services, cultivating loyalty hinges on intangible aspects like providing authentic, efficient customer support.

In fact, 95% of customers will recommend a company if they rate their customer experience as “very good,” according to a study by the XM institute. By contrast, only 15% of consumers are willing to recommend a brand with a poor customer experience.

Top-notch customer support might not grab headlines, but it’s what sets brands apart from commodities.

From rewards programs to referral bonuses, there are countless ways to increase customer loyalty. But none are as effective as providing top-notch customer service experiences.

Ninety-five percent of consumers say customer service is important to their loyalty to and choice of a brand, according to Microsoft’s State of Global Customer Service Report. Further, more than half of consumers will cut ties with a business because of poor customer service.

The term “customer loyalty” has different meanings depending on who you ask, but it can be loosely defined as a customer’s positive, emotional connection to a brand (which ideally yields ongoing purchases).

The most straightforward path to increasing that positive connection is investing in dependable, helpful customer service experiences. In this article, we’ll cover a few specific strategies for customer experience (CX) teams. But first, let’s explore the connection between customer service and customer loyalty.

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How Does Customer Service Influence Customer Loyalty?

Customer service and customer loyalty are intimately linked—and there’s evidence to prove it. Here are three ways CX teams influence brand loyalty, according to a study of 10,000 consumers by the XM Institute.

1. Customer Experiences Distinguish Brands from Commodities

With the advent of ecommerce, people can easily browse and compare dozens of brands that sell near-identical products and services. As a result, brand loyalty often hinges on intangible aspects of business like stellar customer experiences, which create a point of differentiation.

But don’t just take our word for it: 94% of consumers who rate a company’s customer experience as “very good” are more inclined to buy again in the future, according to the XM Institute.

2. Happy Customers Become Brand Advocates

Truly loyal customers go beyond repeat purchases—they give your brand free publicity.

Prioritizing customer service experiences is a surefire way to improve your Net Promoter Score (NPS), which measures the likelihood of a customer advocating on your behalf. Specifically, 95% of consumers will recommend a company if the brand’s customer experience is “very good.” However, just 15% of consumers will recommend a brand that delivers poor customer experiences.

3. Great Customer Experiences Minimize the Impact of Mistakes

Every company makes mistakes, but not every business is forgiven—and that’s often the result of bad customer service.

Seventy-five percent of people are “very likely” to forgive a company’s error, but only if that company’s customer experience is “very good.” Meanwhile, if a company delivers “very poor” customer experiences, the amount of people willing to forgive a mistake plummets to just 14%.

In short: your customer support agents are on the front lines in the battle for customer loyalty.

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3 Ways Customer Service Teams Can Increase Customer Loyalty

In the digital age, customer service interactions are often the only human touchpoint customers have with businesses, so your team has to nail it (no pressure!). Let’s explore three ways your CX team can seize this opportunity to increase customer loyalty.

1. Minimize Customer Effort Levels

Customer Effort Score (CES) is the strongest indicator of customer loyalty. In fact, 94% of people who have low-effort interactions with customer support plan to purchase from a brand again, compared to just 4% of people who have high-effort interactions, according to Gartner.

The primary cause of excessive customer effort is having to contact customer support multiple times to resolve a problem, according to Harvard Business Review. CX teams can prevent this by coaching agents to improve their first call resolution (FCR) rates. That’s done by addressing the root causes of issues (not the symptoms) and pre-empting problems before they arise.

Consider ClassPass, the online fitness class subscription service. ClassPass noticed their agents were spending an exorbitant amount of time chatting with customers who wanted to cancel their plans.  

“In 2019 alone, we spent the equivalent of 6,250 days—that’s more than 17 years—chatting with 1.5 million contacts for cancellations,” said Sydney McDowell, CX enablement lead at ClassPass.

COVID-19 compounded this issue, so ClassPass decided to automate their cancellation process and let customers place their accounts on hold instead of waiting for them to cancel.

By reducing that friction, ClassPass achieved an 83% customer retention rate throughout COVID-19 compared to their expected retention of 61%. On top of that, they now have zero cancellation chats handled by agents—that’s 6,250 days of agent worked saved every year.

Keeping the human touch in customer service is great, but most people don’t crave sympathy; they crave results—and fast.

2. Empower Agents with Actionable Information

The most frustrating part of bad customer experiences is dealing with agents who don’t have the knowledge or ability to solve a problem, according to Microsoft’s State of Global Customer Service Report.

If you want to increase customer loyalty, you can’t let your agents fall behind the learning curve; you need a system that sets agents up for success from the get-go.

One company that’s mastered the art of agent education is Brooklinen, a luxury home essentials retailer. Brooklinen leveled up their agent learning experience by instituting a “CX University” comprised of three pillars to ensure agents are prepared for any encounter:

Learning Management System:Lessonly facilitates interactive video training modules that align with each agent’s learning style.

Internal Knowledge Base (IKB): A company wiki hosted on Guru lets agents quickly find and share information about policies, procedures, and best practices.

Quality Assurance (QA) Program: Grading customer support tickets through the lens of internal quality standards helps CX managers deliver personalized feedback and spot gaps in the previous two pillars.

“Giving specific and ongoing feedback has had a great impact on increasing our CSAT scores as well as our Average Handle Time,” said Casey Brewer, senior associate, CX Quality Assurance at Brooklinen.

3. Use a Win-Back Scorecard to Reduce Churn

Support agents are under constant pressure to reduce churn. Your team’s current tactics to win back customers might be offering discounts and incentives, but those have to come second to understanding the true reason a customer wants to call it quits.

Closely examining interactions where customers cancel ensures agents follow proper protocol. It also surfaces new insights that lead to better customer experiences. That’s where a win-back scorecard comes in.

A win-back scorecard is a type of QA scorecard that helps CX teams pinpoint the underlying reason for customer churn and determines whether agents follow the approved process to salvage the relationship.

Here are a few questions to include in your win-back scorecard:

• Did the agent identify the customer’s reason for leaving?
• Did the agent attempt to win back the customer by following our appeasement framework?
• If the customer still decided to leave, did the agent provide a good exit experience?

The more data you collect, the easier it is to see which actions work to win back customers (and which don’t).

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Customer Loyalty Isn’t Just a “Feel Good” Concept

Cultivating a community of super-fans is deeply rewarding for CX managers and key stakeholders. But loyalty is more than a concept; it’s the lifeblood of a brand.

Today, more than two-thirds of companies compete primarily on the basis of customer experience, according to Gartner. In other words, their support teams determine whether the business sinks or floats.

In a time where differentiation is challenging and consumers have more options than ever, exceptional customer service experiences are the ultimate competitive advantage.

Want to learn more about building customer loyalty through CX? Download our free ebook here.

Should you stop trying to delight customers? That question seems absurd, especially for customer service leaders. But the answer might surprise you. Hear us out.

Making customer service interactions easier — not fast or delightful — is the key to keeping customers loyal and satisfied. And there’s data to prove it.

96% of people who experience a high-effort customer service interaction decrease their loyalty to the brand compared only 9% with low-effort interactions, according to research from Gartner.

This insight is a wake-up call for CX teams. Coaching agents to remove obstacles and lower customer effort not only increases loyalty — it saves money and improves agent retention, too. The first step is knowing your customer effort score (CES).

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What Is Customer Effort Score (CES)?

Customer effort score is a customer service metric that indicates how easy (or difficult) it is for a customer to resolve an issue or find the information they need from a brand. CES is influenced by factors like the duration of interactions, having to switch between agents, or the lack of quality information in a self-service hub.

CX teams determine CES by sending a single CES survey question to customers after they interact with a support agent, such as, “How much effort did it take to resolve your question today?”

The sooner the survey is sent after the interaction, the more accurate the results.

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3 Reasons Every CX Team Needs to Track Customer Effort Scores

In a study to see how customer effort levels impact people’s perception of organizations, the global research firm Gartner gleaned three key insights that should be on every CX manager’s radar:

1. Customer effort predicts customer loyalty

94% of customers who have low-effort interactions intend to buy from a brand again, compared to just 4% of customers who have high-effort service interactions.

CX teams can use customer experience metrics like customer satisfaction (CSAT) scores and Net Promoter Score (NPS) to gauge customer loyalty and retention, but CES is usually a more reliable indicator for future purchase behavior — and there’s evidence to back it up. “Customer effort is 40% more accurate at predicting customer loyalty as opposed to customer satisfaction [CSAT],” says Andrew Schumacher, senior principal, Advisory, Gartner.

2. Low-effort interactions save money

Low-effort interactions are 37% less expensive than high-effort interactions, according to Gartner. That’s because low-effort customer experiences save considerable agent time: specifically, they eliminate up to 50% of escalations, 40% of customer call-backs, and 54% of channel switching (for example, when a customer tries self-service but ends up calling an agent instead).

3. Low-effort interactions improve agent retention

Agents build confidence when they consistently remove barriers and simplify customer interactions. As a result, agents’ intent to stick around increases up to 17% when they deliver better customer experiences.

How to Create a Customer Effort Score Survey

Customer effort scores are derived from customer feedback surveys. There are two components of a CES survey: the question and the type of scale.

1. Choose your survey question

Customer effort score questions have to reflect the insights you want. For example, if you want to know how much effort customers exert when they return a product, you’d ask: Was our return process easy for you to complete?

Here are a few additional examples of CES survey questions CX teams might ask:

• How easy was it to resolve your issue today?
• Do you agree/disagree [company] made it easy to handle your issue?
• How much effort did it take to exchange your order?

Answers to CES survey questions can’t be a simple “yes” or “no,” so you need to choose a scale.

2. Choose a type of scale for your CES survey

There are two primary types of scales to use for CES surveys:

Likert Scale: This five-point scale lets customers express how much they agree or disagree with a statement. Here’s an example:

How much do you agree or disagree with the following statement: [Company] made it easy to resolve my issue today?

1 = strongly disagree
2 = disagree
3 = neutral
4 = agree
5 = strongly agree

Numerical Scale: Here, customers express their sentiment on a scale of 1-5, with 1-2 being negative and 4-5 being positive. Here’s an example:

How much effort did it take to resolve your issue today?

1 = too much effort
2 = decent amount of effort
3 = neutral
4 = minimal effort
5 = no effort

Note that for both options, you can also expand your scale to 1-10 instead of 1-5. Once you receive all of your responses, you’re ready to plug the numbers into an easy formula to get your CES.

How to Calculate Customer Effort Score

Calculating CES is quick and easy:

1. Add up all CES survey scores.
2. Divide the sum by the number of responses.

So, if 50 people responded to your 1-5 scale CES survey and the sum of their scores is 211, your equation looks like this:

211 ÷ 50 = 4.22

Your CES is 4.22 out of 5, which is great.

Customer Effort Score Benchmarks: What Is a Good CES?

Since CES questions and scales differ across industries and organizations, there isn’t a clear CES benchmark to aim for. That said, aim for your average CES to fall into the “positive” category. So, on a 1-5 scale, that means 4 or higher. Or if you use a 1-10 scale, 7 or higher.

No matter what your CES is, it doesn’t hurt to aim higher. Remember, better CES scores correlate with loyalty, agent retention, and money saved — there’s no such thing as a CES that’s “too good.”

How to Improve Your Customer Effort Score: 4 Tips

Reducing customer effort is a team sport — coaches, QA managers, and agents all have responsibilities. These four tips ensure every level of the CX team does their part.

1. Coach agents to focus on first call resolution (FCR)

The primary cause of excessive customer effort is having to reach out to support multiple times to resolve an issue, according to Harvard Business Review. This echoes Microsoft’s finding that the most important aspect of a customer service experience is fixing the issue in a single interaction — no matter how long it takes.

Customer service coaches can combat this by working with agents to improve their first call resolution (FCR) rates. That requires addressing the root causes of issues (not the symptoms) and preempting problems before they arise. Agents develop these skills by studying past interactions during coaching sessions to spot patterns.

2. Analyze CES in tandem with quality assurance (QA) scores

CES tells you how much effort a customer exerted during a support interaction, but it doesn’t tell you why. That’s where QA scores come in.

Let’s say several customers "disagree" with the following statement after working with the same agent: "The customer support agent made it easy to cancel my subscription."

Instead of simply hoping the agent does better next time, a manager or coach can look at the agent’s QA scorecard from that interaction to see what, exactly, made the experience difficult for the customer.

Maybe the agent didn’t adhere to the approved process or didn’t gather the correct information from the customer upfront. Whatever the case, analyzing CES alongside QA contextualizes sub-par scores to guide future coaching sessions and improve the customer feedback.

3. Give customers options for issue resolution

“Why can’t I just talk to a real human?” We’ve all asked that question before — and it’s a valid one. Customers may exert excessive effort trying to navigate self-service options like online help centers, which can hurt CES. That’s why it’s important to offer multiple support channels.

For example, monday.com’s support hub offers quick answers via a knowledge base, video tutorials, a community forum, webinars, and more. Then, if customers need personalized support, they have 24/7 support available.

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4. Turn negative customer feedback into learning material

Poor customer experiences are often more instructive for CX teams than positive ones when it comes to CES.

“Many companies conduct postcall surveys to measure internal performance,” says Matthew Dixon et al. in Harvard Business Review. “However, they may neglect to use the data they collect to learn from unhappy customers.”

Obviously, the priority is fixing the customer’s problem before asking them more questions and reducing the customer’s effort. But it’s important to follow up after a high-effort service interaction to get their side of the story. Then use those insights to inform agent training and prevent those mistakes from happening again.

The Myth of Going the Extra Mile

Conventional wisdom holds that customers stay loyal to brands that “go the extra mile” to wow them. But as Harvard Business Review points out, exceeding customer expectations during service interactions “makes customers only marginally more loyal than simply meeting their needs.”

Don’t overthink it: the quickest path to customer satisfaction is making interactions as easy as possible.

“Few things generate more goodwill and repeat business than being effortless to deal with,” says Matt Watkinson, author of The Ten Principles Behind Great Customer Experiences.

Imagine you’re back in high school and it’s report card time. You have mostly As and Bs but a D- in your toughest class. You’re desperate to improve your GPA, so you ask the teacher what you can do next semester to improve. But instead of getting to the root of your struggle, she tosses you a textbook and says, “Figure it out.”

Unfortunately, this same problem applies to customer support agents who want to level up their skills. Only half of underperforming agents say they receive the training they need to do their job well, according to Salesforce.

So how can customer experience leaders bridge that gap? Customer service coaching.

Personalized, data-driven coaching sessions are the most powerful way to elevate agent performance and, in turn, improve customer experiences. In this article, we’ll outline five elements of a 30-minute coaching session to stay organized and accountable when delivering feedback.
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1. The Coach Sets Expectations Ahead of Time

Setting expectations ahead of time keeps coaching sessions focused and efficient. Unfortunately, 63% of meetings don't have an agenda, according to Attentiv. This is especially detrimental in a learning environment where structure fosters retention.

Effective customer service coaching starts before the session with an agenda, so agents can gather their thoughts ahead of time. You can share the agenda in a calendar invite, internal messaging, or a shared coaching dashboard.

For starters, encourage agents to come to coaching sessions with two to three questions or challenges, like “How can I balance First Call Resolution with Average Handle Time?” This works best asynchronously in a shared document, so coaches have time to digest the information, and agents aren’t put on the spot.

Likewise, the coach must come prepared with data and materials to guide the discussion with the agent, such as key wins, areas for improvement, transcripts, and screen recordings.

2. Coach Reviews Quality Assurance (QA) Scores with Agent: 10 Minutes

Quality Assurance (QA) scores should be the foundation of your coaching strategy because they provide granular, individualized insights—not arbitrary opinions—into how an agent performs against a company’s quality standards.

QA scores are calculated with a QA scorecard that includes rubrics for traits like friendliness, grammar, and adherence to approved processes.

In this phase of the coaching session, walk the agent through their recent QA scores along with their score trajectory over time to establish a mutual, clear understanding of the areas in which they excel and the areas where they need help.

Here are a few ways to analyze an agent's QA scores to uncover strengths and opportunities:

1. Compare the agent’s QA score across different rubrics, such as grammar and tone.
2. Compare the agent’s QA score by rubric criteria, such as whether the agent correctly identified the customer’s issue.
3. Compare the agent’s performance to their peers on the team.

3. Coach Reviews Productivity Metrics with Agent: 5 Minutes

Evaluating customer service productivity metrics provides a snapshot of how effectively agents resolve customer issues, as well as how they influence customers’ perception of the company in general.

Here are four foundational productivity metrics CX teams track:

1. Customer Satisfaction (CSAT) Score: Quantifies how satisfied a customer is with the service they received
2. First Contact Resolution (FCR) Rate: The percentage of customer issues resolved the first time they reach out for support
3. Average Handle Time (AHT): The average time it takes the agent to resolve customer support issues
4. Net Promoter Score (NPS): Indicates the likelihood that a customer will refer a product or service to someone else

Productivity metrics typically aren’t as actionable as QA scores since they only tell you if but not why the agent performs up to par (or not). However, coaches can eliminate this blind spot by reviewing productivity metrics in tandem with QA scores.

For example, if an agent’s CSAT score declines, the coach can review their QA scores for that specific ticket side-by-side to identify the root cause of the issue, whether it was a harsh tone of voice or lack of empathy.  

Agents get down on themselves if they struggle to improve these metrics, so it’s important to balance constructive criticism with praise during this phase of the session. Instead of fixating on weak spots, set aside a few minutes to highlight key wins, milestones, and improvements.

4. Coach Shares Personalized, Evidence-Based Feedback: 10 Minutes

The more data you collect, the more you’ll see how no two agents have the same needs. Accordingly, coaching can’t be relegated to check-the-box modules or generalized training if you want optimum performance. It has to be a 1:1 experience.

For example, two agents could both score 81 out of 90 points on their QA scorecards but for vastly different reasons. That’s where data comes in to ensure each agent has an individualized path to improvement.

Maybe one agent struggled to use the brand voice in his interaction, while another agent needs to improve her use of visual aids to solve customer issues. Uncovering these nuances within QA scorecards keeps agents focused on growth and reassures their status as individuals, not just cogs in a big machine.

Another effective method for sharing feedback is walking through screen recordings of an agent’s interaction with a customer. Rather than relying on data alone, screen recordings give a 360 view into the agent’s problem-solving process, leading to more actionable and targeted feedback.

Take Tails.com, a dog food subscription service. It used MaestroQA’s Screen Capture feature to get full visibility into agent behavior. While watching one agent’s interactions with customers, the CX team identified 17 new opportunities for improvement, from simple keyboard shortcuts and optimized support ticket navigation to computer monitor configuration.

Tying those loose ends reduced the agent’s AHT by 50%.

“Instead of just giving someone a hard number, I can have a more complete conversation with them about everything that factored into their QA score,” said Daniel Jensen, CX quality and training team Leader, Tails.com. “We’re building agent confidence and rapport by coaching them on how to solve inquiries they struggled with.”

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5. Coach Assigns Specific, Measurable Action Items: 5 Minutes

Collaborating with agents to set goals is great, but there’s a missing link between goals and results: action items.

Broad-brush suggestions like “improve CSAT” can confuse and frustrate agents if they don’t have a detailed roadmap to achieve that. However, time-bound action items keep agents accountable since they can be tracked and correlated with improved metrics or key milestones.

Let’s say a coach sets an objective for an agent to reduce their AHT by 10% by the end of the quarter. The coach can pair that objective with an action item, such as “Discuss ways to improve call processes with five peers by Friday, and bring ideas to discuss”, or “review Lessonly training material on improving AHT”.

The key to action items is staying organized. MaestroQA’s coaching dashboards make it easy to track and manage to-dos in a centralized dashboard. Every action item created in a coaching session appears on the coaching page. Then, as completed action items are marked off, coaches and agents alike can flip back and forth to view completed and incomplete action items. The dashboard also displays learning management system (LMS) materials and tutorials assigned to the agent to review.

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Personalized Customer Service Coaching Is the Key to Performance

From streaming services and social media to ecommerce brands, people crave customization. Individualized experiences, whether a recommendation for a show to binge or a book to buy, keep us engaged.

The same applies to professional development, especially when it comes to improving customer service agent performance. Implementing a coaching strategy without considering agents’ unique needs is like Netflix sending the same suggestions to all 200+ million of its subscribers.

But if you’re ready to arm yourself with data and help agents reach their potential, get a demo of MaestroQA and experience the new standard for customer service coaching.

A Google search for “customer service coaching” turns up nearly 300 million results that give conflicting, vague, or unhelpful advice. This can be infuriating for customer experience (CX) leaders, especially when you’re under pressure to improve agent performance.

Plug-and-play coaching tactics don’t account for the complexity of agents’ interactions, not to mention they can create friction between CX leaders and agents who feel misunderstood. So, for now, let’s set aside the tips and tricks to focus on the foundation of an effective customer service coaching strategy: data.

Applying individualized data to customer service coaching closes communication gaps between CX managers and agents, enabling more efficient learning. In this article, we’ll explain why data is the key to boosting agent performance, what metrics to track, and how to incorporate data into your coaching sessions.

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3 Benefits of Incorporating Data into Customer Service Coaching

Data is like a GPS for customer service coaching—it tells you what direction to take with agents and how close you are to your goals. Here are three key benefits CX teams can glean from data-backed coaching.

1. Data Enables Customized Feedback

Templated training modules can be useful for ramping up new agents or introducing new product features. However, check-the-box training falls short when it comes to helping agents solve unique, complex customer issues.

Every agent excels (and struggles) in different aspects of their work. Accordingly, extracting tangible insights based on their individual performance data lets you know what to focus on during coaching sessions.

For example, if an agent’s record shows they consistently take longer than their peers to close tickets, you get a clear signal to coach them up on quick resolutions rather than taking up their time (and yours) with less pressing matters.

2. Coaches and Agents Get Irrefutable Evidence of Performance Levels

Without data, coaches and agents are left to guess when it comes to evaluating performance levels. This is problematic because agent evaluations may be unfair, inaccurate, or inconsistent.

Coaches can bridge this knowledge gap by referencing data such as First Call Resolution (FCR) rate or Average Handle Time (AHT) to evaluate performance. These metrics create a single source of truth and prevent coaching sessions from being tainted by subjective opinions.

For example, if an agent and coach disagree over what it means to “solve customer issues thoroughly,” the coach can use internal benchmarks for FCR as a reference point.

3. Data Makes It Easier to Set Realistic Goals

Benchmarking agent performance isn't the only thing that's difficult without concrete data: Setting reasonable, measurable goals is also a shot in the dark. Agents can feel lost when setting goals if they don’t have a system to gauge their progress over time.

The most efficient way to benchmark performance is with Quality Assurance (QA) scores, which supply a goldmine of data to set goals based on a historical precedent, not arbitrary standards. (We’ll discuss this in-depth in the next section.)

Coaches can even use data to incentivize agent performance. For example, if the agent exceeds the company’s standard for QA scores, they could receive a bonus at the end of the quarter.

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2 Types of Data You Need to Level Up Your Customer Service Coaching

CX teams need two main categories of data to optimize coaching sessions: data about how agents adhere to a company's unique quality standards and data that gauges how efficiently and effectively agents resolve customer issues.

1. Quality Assurance (QA) Scores

QA scores are actionable metrics that indicate how agents perform relative to the company’s standard for quality. That can include factors such as friendliness, authenticity, and adherence to approved processes.

For example, if a QA grader gives an agent 78 out of 90 points on their QA scorecard, the coach can examine the scores for each criterion on the scorecard and immediately know which aspects of their customer interactions to address in upcoming coaching sessions to achieve a higher score.

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QA scores are the most reliable source of intel to coach agents effectively because they provide a granular look into the areas in which they thrive and where they need a boost. In fact, after monday.com increased its volume of quality audits by 48%, it slashed its AHT from 24.1 minutes to 16.9 minutes—an improvement of almost 30%.

2. Agent Performance Metrics

These four foundational metrics quantify efficiency and customers’ perceptions of the agent or the brand in general. While they aren’t as actionable as QA scores, they can still spark productive dialogues between coaches and agents, especially when it comes to the company’s customer service KPIs.

Customer Satisfaction (CSAT) Score

CSAT scores indicate how satisfied customers are after receiving assistance from an agent. CSAT scores are relatively quick to calculate and analyze. The downside is they’re one-dimensional because the score alone can’t tell you which aspects of customer experience contributed to the customer’s survey response.

To get over this obstacle, CX teams can review CSAT scores in tandem with QA reviews. This contextualizes why a customer gave a specific CSAT rating: Did the agent use a friendly tone? Did the agent get to the root cause of the problem? Was their issue resolved in a timely manner?

Applying these insights to the coaching sessions should improve CSAT scores.

First Call Resolution (FCR) Rate

If an agent has a low FCR rate, this is a coaching opportunity to help them become more thorough with customers, whether that’s by diagnosing the root causes of problems, preempting customer issues, or taking advantage of knowledge management solutions.

Just as with CSAT, analyzing FCR within the context of QA scores uncovers insights into why certain interactions exceeded FCR expectations or why they fell short.

Average Handle Time (AHT)

Monitoring AHT helps CX leaders see if an agent takes too long to resolve customer issues. Once AHT is tracked, coaches can take the necessary steps to improve it, whether teaching agents how to leverage an internal knowledge base to find solutions quicker or when to reroute tickets to a teammate who’s better prepared to solve the problem.

Keep in mind that AHT can’t (and shouldn’t) be the sole indicator of productivity when the agent’s ultimate goal is delivering quality experiences and solving customer problems thoroughly.

Net Promoter Score (NPS)

Tracking and discussing NPS can help coaches and agents see a correlation between customer interactions and a customer’s willingness to advocate for the brand.

NPS shouldn’t be the focal point of coaching sessions since it’s often influenced by factors outside of agents’ control. That said, if NPS scores indicate that customers consistently don’t want to recommend the brand after interacting with a specific agent, that can be a sign to gear coaching toward soft skills such as empathy and authenticity.