Acquiring new customers and retaining loyal customers have been two important tasks for retailers. One critical issue to retain loyal customers is to know the customers well so that the retailers can provide the right products, do the right promotions and maintain customers from switching away to competitors, i.e. churn. In this study, we investigated the partial churners’ behaviors by (1) identifying key churn predictors, (2) establishing a churn prediction procedure, and (3) applying classification techniques to detect the possible partial churners. Further, the performance of each classification technique was examined and evaluated. We adapted and modified a two-year period customer and transaction data from a retailer to verify our proposed approach. Discussion and managerial implications are provided at the end.
Ching, Russell K.H.; Cheng, Liewen; Ni, Sheng-Fu; and Chen, Jashen, "Applying Data Classification Techniques for Churn Prediction in Retailing" (2007). ICEB 2007 Proceedings (Taipei, Taiwan). 20.