sajjad shokohyar; ali rezaeian; amir boroufar
Volume 20, Issue 4 , January 2017, , Pages 65-94
Abstract
Interaction of companies with customers in the form of customer relationship management has changed significantly. Identifying characteristics of different customers and allocating resources to them according to their value to the firm has become one of the main concerns in customer relationship management. ...
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Interaction of companies with customers in the form of customer relationship management has changed significantly. Identifying characteristics of different customers and allocating resources to them according to their value to the firm has become one of the main concerns in customer relationship management. The purpose of this paper is to provide an appropriate model for customer segmentation based on some of the most important financial and demographics characteristics influencing factors of customer lifetime value (CLV). The process proposed in this study was performed in Saman insurance company. After determining RFM model indices, which include date, frequency and monetary of purchase, AHP method used for weighting them among 180000 customers. The optimal number of clusters based on the silhouette and impact of RFM indicators was done by using Two-step algorithm and then customers classified through K-Means clustering algorithm. Results provided a platform to analyze the characteristics of customers in three main sections. Also, by prioritizing clusters based on the RFM indices, valuable customers were identified. Finally, some suggestions were presented to the company to improve its customer relationship management system.