In this study, a new model of combining variables affecting the classification of customers is introduced which is based on a distribution system of goods and services. Given the problems that the RFM model has in various distribution systems, a new model for resolving
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In this study, a new model of combining variables affecting the classification of customers is introduced which is based on a distribution system of goods and services. Given the problems that the RFM model has in various distribution systems, a new model for resolving these problems is presented. The core of this model is the older RFM. The new model that has been proposed as PRFM, consists of four dimensions: Profit margins (P), time period from customer's last purchase (R), Frequency of transactions (F) and the Monetary Value (M). Adding variable (P) makes a huge change in customer clustering and classification systems and makes it more optimized for future planning. For review and approval, the model was implemented in one of the largest and most diversified distribution companies in Iran. Using Ward's clustering, the optimal number of clusters was prepared and entered by hierarchical clustering and based on Euclidian distance customers are clustered and separated. One of the most important results of this study is introducing a new model and resolving the problems of the old RFM model in determining customer's value.
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