Title: An integrated AHP-RFM method to banking customer segmentation

Authors: Seyed Mahdi Rezaeinia; Abbas Keramati; Amir Albadvi

Addresses: Computer Engineering Department, University of Damghan, P.O. Box 3671641167, Saadi Square, Damghan, Iran. ' Industrial Engineering Department, University of Tehran, P.O. Box 11365/4536, Tehran, Iran. ' Information Technology Department, Tarbiat Modares University, Jalal Ale Ahmad Highway, Tehran, 14115-111 Tehran, Iran

Abstract: 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.

Keywords: customer loyalty; banking industry; RFM method; clustering algorithms; customer segmentation; electronic CRM; e-CRM; customer relationship management; commercial banks; customer retention; recency; frequency; monetary value; analytical hierarchy process; AHP.

DOI: 10.1504/IJECRM.2012.048721

International Journal of Electronic Customer Relationship Management, 2012 Vol.6 No.2, pp.153 - 168

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 23 Aug 2012 *

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