Improved Pareto/NBD Model and Its Applications in Customer Segmentation based on Personal Information Combination

Abstract

In recent years, the Pareto/NBD model has gotten the favor of many scholars because of its accurate ability of predicting the future customer purchase frequency. Firstly, the paper analyzed the disadvantages of Pareto/NBD model; Secondly, the paper put forward an improved Pareto/NBD model which integrated the customer personalized information in order to resolve the problem in the Pareto/NBD model and improve the accuracy of prediction; Thirdly, the paper used the real sales data of a Dalian Mall as the sample, empirically tested the superiority of the improved Pareto/NBD model to the original Pareto/NBD model. Finally, this paper combined with the improved Pareto/NBD model and the Gamma-Gamma model to predict each customer lifetime value, and put forward the segmentation method based on CLV and management strategy, help the enterprises implement differentiated marketing and enhance the level of customer relationship management (CRM).