A few weeks ago, I was talking with a friend who leads the customer experience (CX) team at a large B2B company. She described a common challenge in her voice of the customer (VoC) program.
Her team had gathered and analyzed lots of customer feedback regarding interactions with support representatives in the contact center, and the results were clear. Customers thought issue resolution time was too long, and that perception was killing overall loyalty.
The CX leader immediately took the findings to the head of support to make the case for change. She had already built significant momentum and accountability around CX, so the support leader was receptive. He quickly understood the problem and wanted to fix it.
Then he brought the conversation to a halt with a simple question: How long should resolution time be? The CX leader couldn’t answer, because she only had customer feedback. She needed operational data about actual resolution times in order guide the support leader’s business decision.
If she had captured actual resolution times in addition to customers’ perceptions of resolution times, she could have analyzed the statistical relationship between the two and identified the actual time at which customer perceptions tanked. For example, she could have told the head of support that resolution times needed to be 8 hours or less, not just less in general.
As we continued talking, we realized that the absence of operational data didn’t just affect the CX leader’s ability to guide business decisions. It also affected her ability to measure the ROI of the decisions she did manage to guide.
Earlier in the year, customer feedback had pointed to a specific area where customers thought support reps needed better knowledge, and she had successfully made the case for enhanced training in that area. Following the new training, employee knowledge ratings had started to increase. So did first call resolution (FCR).
The CX leader knew these trends were related, but she couldn’t prove it. Had she combined her customer feedback (employee knowledge ratings) with operational data (FCR), she could have shown that customers who rated employee knowledge high were actually less likely to call multiple times regarding an issue. This would have allowed her to attribute the significant cost savings associated with decreased calls to the change she had initiated. Without this combined dataset, she could only argue that the connection intuitively made sense – not enough for her executive team.
At MaritzCX, we believe that combining customer feedback with operational data is a hallmark of VoC’s next generation, which we call voice of customer intelligence (VoCi). This table describes the benefits of VOCi vs. standalone feedback and operational data using the examples described above.