They worked with a major international financial retailer. Their job: recover overdue accounts through outbound calls. They measured what everyone measures — total calls, amounts collected, monthly targets. But one metric was deceiving them every single day.

The illusion of productivity

In most contact centers, the logic seems straightforward: more calls = more results. Agents who make the most calls are seen as the hardest workers. Those with fewer calls get flagged.

But here's the problem: call volume doesn't tell you what's actually happening.

An agent can make 80 calls a day and look incredibly productive on paper. But what if 75 of those calls went to voicemail, wrong numbers, or disconnected lines? What if only 5 were actual conversations with real customers?

Meanwhile, another agent also makes 80 calls — but 60 of them are real conversations with decision-makers.

Which agent deserves your coaching time?

What the data revealed

When we analyzed 100% of their calls using AI, the picture became crystal clear. Here's what a typical comparison looked like:

Same call volume. Radically different outcomes.

Before this visibility, supervisors couldn't distinguish between these two agents. Both appeared equally "productive." The real performers were invisible, and the real problems were hidden.

The principle that changed everything

We introduced what we call compound metrics — measurements that combine multiple variables to reveal the full picture. Instead of looking at calls alone or collections alone, we created segments based on relationships:

The insight was counterintuitive but powerful: the agents with the highest potential ROI on coaching weren't the lowest performers — they were the ones with high activity but underwhelming results.

These agents were already putting in the effort. They just needed better technique. A small improvement in their conversion rate would have massive impact because of their volume.

Meanwhile, low-activity agents with low results? Coaching them moved the needle far less.

What they couldn't see before

Prior to this analysis, the operations team faced a painful reality:

Spreadsheets everywhere. Different Excel files tracking individual metrics that never connected. No way to correlate call volume with actual customer contact. No way to see compound relationships.

Manual monitoring covered only 2% of calls. The quality team simply didn't have bandwidth to listen to more. And their job wasn't just listening — they also had to deliver feedback, document findings, and prepare reports.

Decisions came too late. By the time patterns became visible through end-of-month reports, weeks of opportunity had already been lost.

Training was unfocused. Without clarity on who needed what, everyone got the same generic coaching. The result? Minimal improvement and high frustration.

The results

Within days — not months — of implementing the performance grouping dashboard, the team had complete visibility. Here's what changed:

The unexpected outcome

But the story doesn't end with internal improvements.

Their client — the financial retailer — had been demanding greater visibility and AI-powered analytics. They wanted to see what was really happening in the operation, not just surface-level KPIs.

By implementing this level of analysis, the agency didn't just improve their performance. They became the only provider in their portfolio offering this depth of insight.

The result? Their client began shifting market share away from competitors and toward them. Better visibility led to better results, which led to more business.

The question for your operation

Most contact centers still measure what's easy to measure: handle time, calls per hour, monthly totals.

But the metrics that actually drive results are the compound ones — the relationships between variables that reveal where effort translates into outcomes, and where it doesn't.

If you can't distinguish between an agent making 80 calls to voicemail and an agent making 80 calls to real customers, you're making decisions with incomplete information.