Matchmaking With Math: How Analytics Beats Intuition to Win Customers

Credit insurance and debt protection product seller Assurant Solutions ran a classic customer service
call center–operationally optimized, “skills-routed,” managerially enlightened. But when it explored analytics-based approaches to rethinking how the center worked, a strange thing happened: The success
rate for customer interactions tripled.

According to Cameron Hurst, vice president of Targeted Solutions at Assurant, the result surprised them. “We learned that operational efficiency and those traditional metrics of customer experience like abandon rate, service levels and average speed to answer are not the things that keep a customer on the books.” They found instead that technology could assist the company in retaining customers by leveraging the fact that some customer service reps are extremely successful at dealing with certain types of customers. Matching each specific in-calling customer to a specific customer service rep made a huge difference. Science and analytics couldn’t quite establish why a particular rapport would be likely to happen, but they could look at past experience and predict with a lot of accuracy that a rapport would be likely to happen.

In this SMR case-study interview, Hurst explains how Assurant Solutions figured out the right questions to ask, used analytics to focus on new ways to match customers with reps and figured out the best ways to solve the problem of conflicting goals.