Customer Segmentation Model And Application Research Based On CLV And Customer Activity

This research presents a customer segmentation model based on the two-dimension variables:customer lifetime value (CLV) and customer activity (P (active)) with the study sample of historical transaction data of current deposit customer from a domestic commercial bank. The author explains in detail that how to use the model to instruct the commercial bank to establish marketing tactics and implement customer relationship management, so that to increase customer retention rate of high-value customers, and reduce the defection rate.First of all, considering the character of the current deposit business, data situation and the fruit of predecessors'research, this paper suggests the variables (x, tx; T, mx) definition to the stochastic model:BG/NBD model and Gamma-Gamma model. Then this study calculates CLV and P (active) according to these two models. The two indicators showed good prediction accuracy after testing.Secondly, this study constructs a customer segmentation model of current deposit customers. According to the results of previous research on the critical thresholds, the threshold of the two segmentation indicators was defined. The research validates the effectiveness of segmentation model by the empirical study. Empirical results show that:11% current deposit customers of commercial bank contributes 80% profits. On one hand, the result reflects the 20/80 principle, on the other hand, it illustrates that the profit contribution of current deposit customers of the commercial banks is more concentrated than the retail industry. Therefore, it seems more important to maintaining the high-value customers and monitoring the customer defection.Thirdly, the study indicated that this segmentation model is very important on customer retention. The segmentation model divides the current deposit customer into four subdivision customer groups:high-value customer group, potential-value customer group, low-value customer group, secondary-value customer group. Then the correlative customer maintaining tactics was suggested. The model can not only achieve the real-time monitoring of churn situation of the high-value customer churn and giving an early churn warning, but also can instruct the marketing staff to establish differential retention and regain plans and measures to different customer group, so that they can distribute marketing resources effectively.At last, this paper presents several tactics and suggestions on customer retention management. The research points out explicitly the commercial bank should take into account CLV and P(active) and segment the customer base, then on the basis of segmentation, the bank can distribute the marketing resource, and build differential retention and regain tactics.