Quality Assurance Creates Value When It Builds Trust

Originally published on LinkedIn on June 10, 2026.

One customer hangs up feeling unheard. The agent followed the script, checked every required box, and earned a near-perfect quality score.

Another customer hangs up relieved. Their problem is solved. They know what happens next and feel confident moving forward. Yet the interaction loses points on the scorecard.

Both agents review their QA scorecard. They see numbers, comments, a score, and perhaps an action item. What they don't necessarily receive is the kind of coaching that helps them understand the customer experience behind the evaluation—or how to improve it.

As contact centers increasingly adopt AI-powered quality assurance tools, that distinction has become more important than ever. Organizations can now evaluate every customer interaction, identify trends in real time, and surface opportunities at a scale that was unimaginable just a few years ago. But while autonomous QA can tell us what happened during a customer interaction, it cannot always tell us why it happened—or provide the context needed to turn an evaluation into meaningful coaching.

I've seen how this plays out in my role. At Percepta, we use DAISY as a first-pass QA tool to identify trends and opportunities across customer interactions. But we view those insights as a starting point, not the full story.

Autonomous QA can identify patterns at scale, but human QA provides the context needed to understand customer experience.

Earlier this year, I was reminded of that reality in a way that changed how I think about quality assurance.

Moving Feedback from "Gotcha" to Guidance

During a case study workshop with fellow quality assurance analysts, I shared a challenge our team had been working through: we were seeing an increase in appeals from supervisors.

At first glance, it seemed like a scoring issue. Supervisors were spending valuable time questioning evaluations, and our initial instinct was to focus on consistency and calibration.

But as we dug deeper into the appeals, a different picture emerged.

Most supervisors weren't arguing that standards should be lowered. In fact, they generally agreed with the expectations. What they were questioning was whether the evaluation fully reflected the context of the interaction. They wanted to understand why points had been deducted and how the feedback would help the agent perform better the next time a similar situation occurred.

The more we discussed those cases, the more I realized the appeals weren't really about scores. They were about trust. When feedback feels disconnected from the realities of an interaction, conversations shift from improvement to justification, and everyone loses sight of the real objective: helping people grow.

That realization prompted us to rethink the role quality assurance should play.

Coaching Creates Better Outcomes

Rather than treating evaluations primarily as audit tools, we began focusing more intentionally on coaching. That meant ensuring feedback answered three important questions: What happened? Why did it matter? And how could the agent handle a similar situation in the future?

Accountability still matters. But feedback is most effective when it gives employees a clear path forward.

As we shifted our approach, evaluations became more actionable and more balanced. Quality analysts spent less time documenting mistakes and more time providing meaningful guidance. Supervisors had more productive coaching conversations. Agents gained a better understanding of expectations and, just as importantly, the reasoning behind them.

One piece of feedback from an agent captured the change better than any metric could:

I appreciate the detailed actionable feedback QA provided. It was clear and helped me identify specific areas to improve.

The results reinforced what we had learned. Formal appeals declined by 88%, a sign that agents no longer felt they needed to challenge every evaluation simply to feel heard. When questions did arise, clear supporting rationale and policy-backed feedback helped resolve disagreements more quickly and with less escalation.

The impact extended beyond the appeals process. Supervisors spent less time mediating disputes and more time coaching their teams. Conversations that once centered on defending scores increasingly focused on improving performance. Over time, QA became a more valuable operational input, with agents and supervisors viewing quality feedback as a source of support rather than an outside authority assigning penalties.

For me, that was the most important outcome. We weren't lowering standards. We were building trust in the process.

The Future of QA Is Human-Centered

The contact center industry is under increasing pressure to automate. Autonomous QA offers tremendous benefits, and organizations should take advantage of the visibility and efficiency these tools provide.

But customer experience is fundamentally human. Customers don't remember whether every box was checked on a scorecard. They remember whether someone listened. They remember whether the agent adapted to their situation. They remember whether the interaction left them feeling confident, supported, and understood.

Those are the moments that build trust, strengthen loyalty, and create memorable experiences—moments that automation alone may not fully capture.

That's why I don't see the future of quality assurance as a choice between technology and people, but a partnership between the two. Autonomous QA can help us listen to every interaction and identify patterns we might otherwise miss. Human QA provides the context that transforms those patterns into meaningful coaching and continuous improvement.

For me, that's the real lesson from our appeals experience. Quality assurance delivers its greatest value when it moves beyond scoring and becomes a tool for development. When feedback is clear, actionable, and grounded in context, it strengthens trust, improves employee engagement, and ultimately creates better outcomes for customers.

And in a customer-centric organization, that's what quality should be measured against.

About our Guest Author: 

As a Quality Assurance Supervisor at Percepta, Unshal'e Gray helps improve quality, coaching, and customer experience across automotive contact center operations. By partnering closely with Operations, analyzing performance trends, and refining coaching practices, she works to improve consistency, strengthen customer experiences, and turn quality insights into meaningful action.