Research on E-commerce Customer Segmentation Based on RFAC Model

In order to expand the performance and enhance the competitiveness, various e-commerce enterprises divide their customers into different groups in order to provide differentiated services and targeted marketing. This paper improves and proposes the RFAC model on the basis of the traditional RFM model. The entropy weighting method is used to determine the weights of feature values, the k-means++ clustering algorithm is used to cluster the customer groups, and the data of an e-commerce enterprise is used to carry out an empirical study to obtain the result of customers segmentation of e-commerce enterprises. This study shows that: the improved algorithm helps to improve the clustering effect; the e-commerce customer segmentation method based on RFAC model can effectively identify customers and provide decision supports for e-commerce enterprises' customer segmentation.