An intelligent CRM system for identifying high-risk customers: An ensemble data mining approach

Abstract

In this study, we propose an intelligent customer relationship management (CRM) system that uses support vector machine (SVM) ensembles to help enterprise managers effectively manage customer relationship from a risk avoidance perspective. Different from the classical CRM for retaining and targeting profitable customers, the main focus of our proposed CRM system is to identify high-risk customers for avoiding potential loss. Through experiment analysis, we find that the Bayesian-based SVM ensemble data mining model with diverse components and "choose from space" selection strategy show the best performance over the testing samples. © Springer-Verlag Berlin Heidelberg 2007.