Even before AI took the tech world (and, really, the world at large) by storm, businesses ran on data. Now that we’re several decades into The Information Age, and with AI hungrily consuming every piece of information we give it, the importance of data in business — and the data analytics that stems from it — has never been higher.
Every few months, the same headline makes the rounds again. AI is coming for contact center agents. Fewer seats. Fewer people. Lower costs. It’s a clean story. Easy to understand. And it’s wrong, or at least incomplete in the way that actually matters.
Contact center agents are asked to do something most people find genuinely hard: show up emotionally for strangers, all day, every day, regardless of what’s happening in their own lives. And they do it really well — until they don’t.
Over the past few years, we’ve spent a lot of time evaluating what truly drives performance in the contact center. What we’ve found is that success is not just about implementing new technology or refining workflows. It comes down to contact center employee engagement.
Generative AI has found its place in many parts of contact centers, helping to provide better customer service in many workflows across countless industries. Using it to automate call transcriptions and improve the accuracy and usefulness of transcriptions, is a welcome evolution for many customer experience (CX) leaders.
For CX leaders, ensuring agent productivity is paramount to a successful contact center. But "productivity" in and of itself doesn't mean much without key agent productivity metrics that ensure agents are efficient, effective, and, most importantly, provide stellar customer experiences.
Agents are at the heart of every customer interaction — and often at the breaking point. They juggle rising expectations, disconnected tools, and back-to-back conversations, all while trying to deliver the kind of service that keeps customers loyal.
