Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study

Abstract

Customer segmentation is an essential activity for marketing executives. To penetrate to target market, they should analyze their clients very well. Undoubtfully customer lifetime value (CLV) is a compact calculation method to understand customer behaviors and their values. Various models are presented for CLV interpretation in literature. Two of them are statistical hypothesis tests and k-means. This case study provides the comparison these methods for a B2B IT company. The methodology can easily be used for similar purposes in other organizations. The successful clusters are obtained by k-means application.