An integrated AHP-RFM method to banking customer segmentation. (1st January 2012) - Rezaeinia, Seyed Mahdi; Keramati, Abbas; Albadvi, Amir
The recognition and retention of valuable customers are of great importance for the banks, and other financial institutions. In this regard, the banks make their customers segmented in a variety of methods. In this paper, the data from customers of a commercial bank were considered and segmented using proposed weighted RFM method. Although RFM is not a new method, however, its new versions, including weighted RFM, have been applied in recent years, because they are highly accurate and efficient. In this research, we proposed the AHP method to calculate the weights of recency, frequency and monetary values. Also, we applied clustering algorithm like K-means to segment the customers. At last, we calculated and re-evaluated each customer group after a few months in order to test the results.