Mahsa Hamidi
Omid Solaymani Fard

The customer segmentation is an effective method that enables us to get better know our clients and to better correspond, their various needs. Almost every company that sells products or services stores data of shopping. This type of data can be used to execute customer segmentation thus; the results of the analysis can be translated into marketing campaigns to increase sales. One of the most widely used techniques is RFM analysis, which allows us to create personalized special offers to improve sales and decrease customer retention. This paper's authors aim to evaluate a new fuzzy clustering algorithm and compare it with three other existing fuzzy-based clustering algorithms for customer segmentation using a RFM model. We also used the Xi_Beni index to find the optimal numbers of clusters for each algorithm, and measured the performance of each algorithm with internal evaluation indices. The dataset and codes used in this study can be found in GitHub.

Customer segmentation, Fuzzy clustering, RFM analysis