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Guide
Why you want AutoQA and things to consider
3 Most Common Reasons & Biggest Lessons Learned
AutoQA is transforming quality assurance processes for CX teams by providing greater efficiency, insights, and performance improvements. However, to unlock its full potential, businesses need to integrate AutoQA as part of a broader strategy. This guide outlines the three most common reasons CX teams adopt AutoQA and provides key lessons learned from organizations already using it.
Understanding Why AutoQA is So Valuable
CX leaders are increasingly turning to AutoQA to drive performance improvements. In a recent survey of CX teams, three key reasons stood out for adopting AutoQA. Below, we’ll explore how these reasons can help optimize QA processes, enhance VOC insights, and elevate agent performance across organizations.
Survey Results: Our community’s top reasons for seeking AutoQA
Optimizing QA Team
VOC Insights
Agent Performance Excellence
Reason 1: Optimizing Your QA Team
Goal: Prevent the need to scale QA directly with support team growth.
CX teams often look to AutoQA to improve efficiency and prevent the need to expand QA teams at the same rate as their support teams. However, while AutoQA can help automate parts of the grading process, there are limitations to consider.
Key Insights:
AutoQA can automate grading for soft skills like empathy or politeness, but complex issues—such as identifying root causes or ensuring accurate resolution—still require a human touch.
Even with AutoQA handling certain aspects of the scorecard, 94% of CX professionals surveyed said the entire conversation still needs to be reviewed manually for a comprehensive evaluation.
AutoQA can’t always reduce the time spent on grading. Even when soft skills are automated, the hardest questions, such as root cause analysis, often take the most time and require manual input.
If AutoQA did soft-skills 100% accurately, would I still need to listen to the full call to identify if we identified the issue and resolved it properly?
Yes 94%
No 0%
Other 6%
Do you need to check back-end systems to see if we identified and issued the resolution accurately?
Yes 84%
No 6%
Other 10%
Do you expect AutoQA to do the back-end system checking?
Yes 21%
No 68%
Other 11%
Lessons Learned:
AutoQA is not a shortcut to eliminating manual QA processes, but it is an invaluable tool for enhancing efficiency. The best results come from combining automation with human discretion, allowing CX teams to focus on more nuanced, high-value tasks.
Regardless of AutoQA's assistance, deeper evaluation remains necessary for tasks like identifying the root cause & issue resolution.
Reason 2: Extracting Voice-of-Customer (VOC) Insights
Goal: Gain deeper insights into customer feedback, operations, and product performance from conversations.
VOC insights are vital for driving improvements across the organization, but CX leaders often face challenges leveraging AI to capture the full spectrum of customer feedback.
Key Insights:
64% of CX professionals find it challenging to fully leverage AI for VOC insights, even though VOC is a critical part of achieving ROI.
AI is effective for detecting trends, but it struggles to capture nuanced feedback that may be critical to understanding customer sentiment. 73% of CX professionals report that they prefer manual review of customer interactions to extract truly meaningful insights.
AI-based VOC analysis can be an essential tool for cross-functional collaboration, enabling product, marketing, and customer service teams to make data-driven decisions. However, manual review remains necessary to ensure the insights are both accurate and actionable.
Do you expect someone to still read / listen / QA the conversations based on the AI-tagged VOC conversations?
Yes 73%
No 13%
TBD 13%
Has anyone had great success getting AI to identify nuanced VOC insights?
Yes 16%
No 64%
TBD 20%
Lessons Learned:
AI alone is not enough. A successful VOC program must combine AI's analytical power with manual review to capture the subtleties in customer interactions. This hybrid approach ensures the right insights are being used to drive meaningful change across teams.
Reason 3: Driving Agent Performance Excellence
Goal: Use AutoQA to boost agent performance and integrate insights with broader performance metrics.
AutoQA can provide deep insights into agent behavior, but CX teams often struggle to fully utilize these insights to drive performance improvements. The key is integrating AutoQA insights with other performance indicators and ensuring that team leads and agents are empowered to act on the findings.
Key Insights:
AutoQA must be combined with key performance metrics (e.g., CSAT, AHT, FCR) to give a full picture of agent performance. Without connecting AutoQA to these metrics, it will not provide the holistic insights necessary to make informed decisions.
Visibility is crucial: Agents and team leads need access to AutoQA data alongside these performance metrics to make informed improvements.
AutoQA insights are only valuable when they are effectively communicated to agents and team leads, allowing them to use these insights for coaching, training, and development.
Challenge Thought: Is it worth implementing AutoQA if you're not addressing the holistic challenge? Ensure that AutoQA insights are not just collected but also communicated and actioned upon—otherwise, it's like a tree falling in a forest with no one around to hear it.
Lessons Learned:
To get the most out of AutoQA, it needs to be integrated into a broader performance management strategy that includes regular coaching and feedback loops. Simply collecting data is not enough; the insights must be actioned to drive continuous improvement.
We changed our team name from Quality Assurance to Performance Excellence
What to Consider Before Implementing AutoQA
While AutoQA offers significant benefits, it’s essential to evaluate how it fits within your overall strategy. Here are three key considerations to help you make the most of your AutoQA investment:
Optimize with a Human Touch: AutoQA can automate parts of the process, but human involvement is still necessary for complex tasks. Balance automation with manual review to ensure accurate evaluations.
Cross-Functional Collaboration: VOC insights can benefit teams across the organization, including product development, marketing, and operations. Collaborate with other departments to maximize the impact of your AutoQA insights.
Empower Agents and Team Leads: Use AutoQA data to fuel coaching and development initiatives, giving agents and team leads the tools they need to improve performance. A proactive approach is essential to get the most out of AutoQA insights.
Why AutoQA is the Future of QA
AutoQA is not a magic bullet for quality assurance, but when implemented strategically, it can significantly improve efficiency, generate deeper insights, and elevate agent performance. By understanding the three most common reasons for adopting AutoQA—optimizing QA teams, extracting VOC insights, and driving agent performance excellence—businesses can develop a more holistic approach to CX and quality assurance.
If you're ready to transform your QA process, contact us to explore how MaestroQA's AutoQA solutions can help your team make the leap to the future of quality assurance. Our platform seamlessly integrates with your existing systems and provides the insights you need to drive real impact.
Webinar
Why You Want AutoQA and Things to Consider
Join us for a discussion with MaestroQA's CEO & Co-founder, Vasu Prathipati, as he outlines frameworks to determine the most suitable AutoQA approach for your needs.
