You’d be surprised at just how many CEOs are picking up the phone and calling their own contact centers.
Not to check on staffing levels or review a transcript; just to experience it as a customer would.
There is a pleasure in discovering that, despite being surrounded by and well-informed about all the data and latest technological advancements in the contact center space, many CEOs are still resorting to the good old-fashioned methods.
Unfortunately, according to Claudio Rodrigues, Chief Product Officer at Omilia, the answer is rarely flattering:
“You will see many CEOs calling their contact centers just to see how the experience goes. And so many times they are disappointed.”
That disappointment points to something that the contact center industry has been slow to fully reckon with.
For years, the dominant frame for evaluating contact center performance has been cost, be it cost per call, cost to serve, or headcount reduction. AI arrived and largely inherited that framing. The result is a generation of deployments optimized to deflect volume... and not a lot else.
The leaders pulling ahead right now are working from a different premise. Instead of treating it as a cost line, they are treating it as the most direct, high-stakes interface a business has with its customers.
Treat it like a drain on the budget, and that's exactly what it becomes.
What a Fragmented Stack Actually Costs You
The reason most contact centers haven't made the leap from automation to genuine intelligence is a technology architecture problem.
A typical enterprise contact center runs on a collection of disconnected tools: a CRM holding customer data, a separate platform storing call recordings for compliance, a workforce optimization tool monitoring agent adherence to SOPs, and a knowledge base sitting somewhere else entirely.
Each one generates data, but very little of that data talks to the rest.
“They never get the full picture,” says Rodrigues.
“Each system understands one part of the customer. Nobody understands THE customer.”
The intelligence loop that would allow a contact center to learn from every interaction, spot gaps, and improve continuously requires two things to be true simultaneously:
- You need to be listening to both the agent and the customer at the same time
- You need a single place where that information lands and gets structured
Without that, the loop never closes. You may get local optimizations – a slight improvement here, a tweak there – but never the compound gains that come from genuinely connected data.