مشخصات پژوهش

Application of data mining techniques in customer relationship management (CRM) is well-known. One of the important issues in CRM is customer segmentation. Customer segmentation based on customer lifetime value (CLV) is a useful approach that recently used by researchers. Although many other studies used CLV for end customer segmentation, but the aim of this study is using CLV for retailer segmentation. RFM model (Recency, Frequency, and Monetary value) is one of the most powerful and simplest models for estimating customer life time value. In this paper, we have used an extended version of the RFM model, the LRFM model, which is obtained by adding L (relationship length) to the RFM model to cluster retailers of a hygienic manufacturer in Iran. K-means clustering algorithm with K-optimum according to Davies-Bouldin index is applied on LRFM variables. The results of retailer segmentation help the marketing managers of the manufacturer to formulate segment-specific marketing actions for retailers.