Churn Reduction in the Wireless Industry

Competition in the wireless telecommunications industry is rampant. To maintain profitability, wireless carriers must control churn, the loss of subscribers who switch from one carrier to another. We explore statistical techniques for churn prediction and, based on these predictions. an optimal policy for identifying customers to whom incentives should be offered to increase retention. Our experiments are based on a data base of nearly 47,000 U.S. domestic subscribers, and includes information about their usage, billing, credit, application, and complaint history. We show that under a wide variety of assumptions concerning the cost of intervention and the retention rate resulting from intervention, churn prediction and remediation can yield significant savings to a carrier. We also show the importance of a data representation crafted by domain experts.