Customer churn prediction using a hybrid method and censored data

Customers are believed to be the main part of any organization’s assets and customer retention as well as customer churn management are important responsibilities of organizations. In today’s competitive environment, organization must do their best to retain their existing customers since attracting new customers cost significantly more than taking care of existing ones. In this paper, we present a hybrid method based on neural network and Cox regression analysis where neural network is used for outlier data and Cox regression method is implemented for prediction of future events. The proposed model of this paper has been implemented on some data and the results are compared based on five criteria including prediction accuracy, errors’ type I and II, root mean square error and mean absolute deviation. The preliminary results indicate that the proposed model of this paper performs better than alternative methods.