Key Takeaways from the MaestroQA Quality Summit: High-ROI Quality Programs in Action

We just wrapped up our Quality Summit in Orlando, where industry leaders shared their experiences building high-ROI Quality Programs that drive real impact. From enhancing BPO efficiency and chatbot optimization to compliance-driven QA and targeted audits, our customers revealed how they’ve transformed their programs using MaestroQA.

Below are some of the key strategies and lessons shared by Scopely, Zilch, and Tinder, highlighting how they’ve taken their QA programs beyond the traditional score and into real business impact.

Scopely: Increasing BPO Efficiency and Chatbot Performance with QA

As a leading mobile gaming company, Scopely recognized the need for greater efficiency in BPO management and chatbot optimization. By leveraging screen capture, system analytics, and structured coaching, they were able to unlock significant performance improvements across their support teams.

Creating Visibility to Improve BPO Efficiency

One of the biggest challenges Scopely faced was low visibility into BPO productivity. By actively monitoring agent idle time through screen recording, they identified inefficiencies and were able to increase tickets per hour from 1 to 5.

They also discovered that agents were toggling between 10 different tools for certain case types, leading to high handle times. Through screen capture analysis, they streamlined the workflow down to 2-3 essential tools, improving efficiency without sacrificing quality.

Optimizing Chatbots with Targeted QA Sprints

Scopely also launched a Chatbot QA initiative, applying QA sprints to chatbot interactions, focusing on negative sentiment and deflection trends. The results were clear:

• Chatbot CSAT increased from 2.5 to 5.0
• Chatbot deflection dropped from 48% to 15%
• Negative sentiment decreased from 20% to nearly 0%

By incorporating real-time, targeted QA, Scopely moved beyond traditional quality monitoring and into active performance optimization, driving measurable improvements in both human and AI-driven support.

"We've reset our BPO relationship with new alignment on transparency and efficiency and have moved past the quality 'analysis' phase into truly impacting the customer experience with Quality."

Why This Matters

Scopely’s approach highlights how QA isn’t just about scoring interactions—it’s a strategic tool for operational efficiency.

• QA insights should drive BPO alignment, coaching, and workflow improvements.
• Screen capture and analytics unlock hidden inefficiencies in agent performance.
• Chatbot interactions require the same level of QA scrutiny as human agents.

By shifting from passive QA scoring to active performance monitoring, Scopely improved both agent and AI-driven interactions, directly impacting customer satisfaction and efficiency.

Zilch: Using AI to Improve Compliance and Identify Vulnerable Customers

As a leading UK-based fintech company, Zilch operates in a highly regulated space, where identifying and supporting vulnerable customers is a critical business and compliance priority. Their challenge was ensuring no regulatory complaints or at-risk customer interactions went undetected, while also making their compliance reporting more accurate and defensible.

Using MaestroQA’s AI capabilities, Zilch transformed its compliance monitoring and QA approach—shifting from manual review processes to a more targeted, AI-powered system.

Turning Compliance Challenges into a Scalable AI-Driven Process

Zilch faced two major compliance risks:

1. Missed regulatory complaints—which could lead to audits, fines, or reputational damage.
2. Failure to identify vulnerable customers, putting at-risk individuals through incorrect or inadequate service processes.

To address this, Zilch implemented AI-powered complaint and risk identification within MaestroQA, enabling their team to:

• Automatically surface 100% of conversations involving regulated complaints and vulnerable customers.
• Route flagged interactions into SME dashboards for immediate review and remediation.
• Use AI-driven filtering and categorization to ensure the most critical cases are reviewed first, reducing manual workload while improving accuracy.

AI-Powered Compliance Monitoring: The “LLM Pancake” Approach

Instead of relying on traditional keyword-based filters, Zilch developed a layered AI analysis strategy internally referred to as the “LLM Pancake” approach.

1. Initial filtering with LLM Classifiers to surface potential complaints or mentions of financial distress.
2. Three additional layers of LLMs to progressively refine and categorize complaints and vulnerable customer interactions.
3. Human oversight to review AI findings and improve accuracy, ensuring nothing critical is misclassified.

“We set up AI classifiers to catch potential complaints—things like ‘I want to escalate’ or ‘I’m distressed.’ But that alone wasn’t enough. We needed layers of refinement to separate actual complaints from unrelated issues.”

By combining automation with human expertise, Zilch significantly improved its ability to detect regulatory risks in real time while reducing QA team workload.

Aligning Compliance, QA, and Business Strategy

Beyond improving complaint detection, this initiative reshaped how compliance, QA, and business teams work together.

• The Compliance team now uses MaestroQA dashboards as a primary reporting source for regulatory audits, ensuring complete transparency.
• BPO training is now directly informed by AI-driven insights, allowing teams to focus coaching efforts on recurring complaint patterns.
• Vulnerable customer cases are prioritized, ensuring Zilch proactively assists individuals facing financial distress, disabilities, or major life changes.

The Shift from QA as a Cost Center to a Strategic Driver

Zilch’s investment in AI-powered QA hasn’t just improved compliance—it has shifted the perception of QA within the organization.

“Previously, people saw MaestroQA as just a quality tool. But as we rolled out AI-driven compliance workflows, we started getting more internal requests to analyze different issues. Now, QA is viewed as a value-driving function.”

By implementing proactive risk monitoring, reducing manual effort, and improving regulatory reporting, Zilch demonstrated how QA can evolve from a reactive function into a core business enabler.

Why This Matters

Zilch’s story is a powerful example of how AI-driven QA can reshape compliance strategies.

• Regulated industries need more than traditional QA—compliance monitoring must be proactive, automated, and defensible.
• AI doesn’t replace human oversight—it amplifies impact by surfacing the most critical risks in real time.
• Quality programs should be more than performance scorecards—they should be essential to business operations, compliance, and customer protection.

By taking a strategic approach to compliance-focused QA, Zilch has built a program that reduces risk, improves efficiency, and strengthens customer trust—all while proving the value of AI-powered quality insights.

“This level of data has given us compliance reporting accuracy and coverage we've never had before—it’s created a whole new relationship between quality, BPOs, complaints, and operations teams.”

Tinder: Aligning QA with Executive Priorities Through Targeted QA

Tinder’s Trust & Safety QA team recognized a major challenge: random QA audits weren’t surfacing the most critical issues. To align with executive priorities, they transitioned from random sampling to a targeted QA approach, focusing on high-impact cases tied to business goals.

From Random QA to Strategic Quality Audits

Instead of conducting random audits across their support operations, Tinder integrated internal case management tools with MaestroQA to enable more purpose-driven QA efforts. This allowed them to:

• Filter and analyze cases aligned with executive priorities, such as ensuring a safe and enjoyable user experience.
• Create hyper-specific root cause analysis rubrics, improving the depth of QA insights.
• Pivot a portion of QA resources toward flagged cases, ensuring more focused auditing and actionability.

Driving Process and Training Improvements

Through their first targeted QA sprint, Tinder was able to:

• Optimize BPO workflows based on insights from flagged cases.
• Incorporate new data into internal systems to improve Trust & Safety processes.
• Strengthen training programs based on targeted root-cause analysis.

Tinder’s leadership team immediately saw the value of targeted QA, leading to further investment in expanding these initiatives.

"The response from our internal and BPO teams has been overwhelmingly positive. We are now allocating more and more resources to targeted QA sprints."

Why This Matters

Tinder’s shift from random to targeted QA highlights how QA teams can move beyond basic audits and into high-impact strategic initiatives.

• QA should be directly tied to executive priorities to maximize business impact.
• Random audits often miss key patterns—targeted QA enables precision and actionability.
• QA insights should inform cross-functional teams, influencing product, Trust & Safety, and operations.

By focusing QA resources on business-critical cases, Tinder has proven the value of strategic quality programs, driving real operational and policy changes.

The Future of QA: Insights, Not Just Scores

One of the biggest themes from this year’s Quality Summit was that QA should not just be about grading agents—it should be a strategic function that drives real business impact.

Key Lessons from This Year’s Summit:

• Quality programs should align with business outcomes. Teams that integrate QA into strategic priorities see the highest impact.
• Visibility is essential. Whether through screen capture, AI, or performance analytics, teams that track and act on insights in real time create real change.
• Chatbots require QA too. QA shouldn’t stop at human agents—chatbots must be monitored, optimized, and continuously improved.
• Compliance can’t be an afterthought. AI-powered compliance monitoring ensures regulatory risks are proactively identified before they become issues.
• Random QA is no longer enough. Leading teams are shifting toward targeted QA strategies that prioritize real impact over routine audits.

The teams featured at this year’s summit have proven that QA is more than a scorecard—it’s a strategic function that drives efficiency, compliance, and business success.

If your QA program is still stuck in traditional auditing, it’s time to rethink the approach. With the right tools and a focus on insights over scores, QA teams can unlock real business impact and lead the charge in improving customer experience, compliance, and operational performance.

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Ready to evolve your QA strategy? Reach out to us today!

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