Increasing Effectiveness of Churn Prediction Software

Abstract

Despite the development of several churn prediction software that investigate hundreds of factors, there is still much space for improving the accuracy of churn prediction. This explorative case study research investigated the behavioral factors, economic factors, and carrier policies causing churn and revealed a new set of important factors that cause churn that should be incorporated into churn prediction models to enhance the accuracy of churn prediction software.