How Sprint Encashed On Analytics and Machine Learning For Increasing Customer Retention

Sprint is one of the top mobile network operator in the US. The telecommunications industry in the US being extremely saturated, new customer sign-ups for Sprint were low. In fact, the only customers operators get would be by stealing from other providers.

Post experiencing a elevated churn rate among customers, Sprint worked with Pegasystems to utilize real time analytics and machine learning to solve for the customer retention problem.

Using real-time analytics and machine learning, Pegasystems established a system to address the problem. The system looked across a set of data about a customer and made a real-time decision when the customer was on the phone. The system also analyzed what the risk of churn for the customer was and how much Sprint was willing to spend to keep them around as a customer.

As an immediate outcome, the system resulted in a 30 percent increase in offer acceptance. The larger impact for this benefited the customer retention performance with a 10 percent increase in customer retention six months after that conversation.