AI’s impact on the customer service and contact center space is hard to overstate.
Whether it’s the use of virtual agents, AI-powered proactive outreach, or the range of features that human agents now have access to, the sector has been completely changed.
Interestingly, amongst all these tools, it is the unheralded interaction analysis that might have the strongest case for being the area most impacted by the technology.
Contact centers have been recording calls for decades. Yet, prior to AI, many were still making decisions based on a small sample of those conversations.
Under the previous system, businesses could see how a contact ended, but not always why a customer got in touch, where the journey broke down, or whether internal assumptions matched what was really happening.
In a discussion with CX Today, Russell White, Transformation Lead at Bluecrest, a UK health intelligence company, explained why this was such an issue, detailing how Bluecrest sees its contact center as the front door to preventative care.
“Every call we answer is potentially a health problem found early.”
After deploying NiCE CXone and Interaction Analytics, Bluecrest moved from reviewing a limited sample of calls to analyzing 100% of customer interactions. The company can now categorize calls and use TopicAI to identify customer intent at a scale its previous setup could not support.
Why Call Sampling Leaves Contact Centers Guessing
Manual dispositions have their uses. They can record whether a customer booked an appointment, made a payment, or completed a purchase.
But they rarely provide much detail on the customer’s reason for calling, the friction they encountered, or the path they took before reaching an agent.
Contact center leaders may believe a particular process is working because they see an acceptable outcome on a dashboard.
Meanwhile, customers may be repeatedly contacting the business because of an unclear website journey, an unavailable self-service option, or a problem that is being incorrectly categorized.
Bluecrest found this in its own digital journeys.
The company introduced online self-service for customers to reschedule appointments. The expectation was fairly simple: if customers could change appointments online, fewer would call the contact center to do it. But that did not happen.
Interaction analytics showed that rescheduling intent remained just as high after self-service launched. Bluecrest had not created a failed digital journey. It had given customers more flexibility, which meant more people were now choosing to reschedule.
That is a useful warning for CX teams measuring self-service success through containment alone. Fewer calls are not always the right outcome. In some cases, an increase in activity may show that customers have finally found an easier way to complete a task.
The job is to understand the intent behind the interaction, not just celebrate or panic at the volume.
Turning Customer Conversations into Action
Of course, analyzing every interaction does not improve a contact center on its own.
Reece Harper, Account Executive at NiCE, said the value comes from building insight into people, processes, and operating decisions.
Bluecrest had a clear view of what it wanted to achieve and used the data to keep refining its roadmap.
“The technology is able to deliver that for our customers, but it’s ultimately about what you do with that information and how you build that into the people and the process,” Harper said.
That approach is evident in Bluecrest’s Health Monitor subscription service.
