Integration model of fuzzy c means clustering algorithm and topsis method for customer lifetime value assessment

Abstract

Nowadays, companies should establish a long-term relationship with their customers throughout customer relationship management (CRM). In order to be a winner in the market competition, marketing managers want to maximize customer lifetime value (CLV) and customer equity. So, creating a customer value assessment system is obligatory for companies to identify customers' value, develop strategies for customers' segments, and preserve the high value for them. Commonly, customer lifetime value is evaluated by RFM (recency, frequency and monetary) method. In this paper a model for customer value assessment integrated with multi-criteria decision making method and Fuzzy clustering method based on customer purchasing behavior was proposed. Fuzzy Analytical Hierarchy Process was utilized to calculate the weight of RFM variables. Then, based on the weighted RFM values, Fuzzy c-means clustering was used in order to cluster customers. Finally, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) has been employed to rank customer lifetime value. A case study was used to demonstrate the employment of the proposed model.