Contained Is Not Resolved: Why AI Demands New Customer Service Metrics

Malte Kosub, is cofounder and CEO of Parloa, the company behind an agentic AI platform reimagining how enterprises connect with customers.

​Everyone has been in this situation: You reach out to a customer support line with a problem, but the bot doesn’t understand you and every path leads you somewhere other than the solution. After a few minutes, you give up.

For you, as the customer, the outcome is a total loss. Your problem remains unresolved, you’re frustrated and you have a reason to think twice before reaching out for help again.

But the company sees none of this. Since the automation kept the call, the system counts it as handled. The industry even has a word for this: contained. It doesn’t matter what the customer experience was. On the dashboard, contained looks like success.

I’ve spent nearly a decade building AI for customer experience, and I’ve come to believe that this is one of the most expensive habits in business: the metrics our industry has historically run on don’t measure what we think they measure. And as AI transforms the customer service experience, we risk carrying that mistake into the next era on a much larger scale.

​Why Our Systems Were Built To Deflect, Not Connect​

​None of this happened by accident.

For years, the name of the game in customer service was call deflection. Human capacity was expensive, so the goal was to keep customers away from it: Route them to the FAQ, the phone menu or the chatbot instead. And the metrics were designed to grade the deflection: average handle time, cost per contact and containment rates.

That design explains almost every service experience people hate. Agents rushing you off the phone because the clock is running. Departments bouncing you around so each team’s numbers stay clean. Having to repeat your story to a fourth person. The system was doing exactly what it was designed to do.

Deflection doesn’t just lose customers, though. It also loses the diagnosis.