Identification of Customers in the CRM system using Data Mining and Fuzzy AHP Method

Abstract

Today, the interaction between organizations and especially the banks and customers in the form of customer relationship management has considerably changed. One of the main challenges for customer-centric organizations in the CRM system is to identify customers, to differentiate between different groups and allocate resources to them value and profitability. As well as providing appropriate services to potential customers, with the increased competition between banks and financial institutions is very important. This is possible by identifying customers and analyzing their behavior. In this regard, this study has tried to identify different groups of Iranian banks by taking advantage of WRFMLP developed model. The transaction data of 19500 customers in the period 2014/03/21 to 2015/04/20 is used. The two-step data-mining algorithms was used to identify different groups of customers. A comparison conducted among three clustering algorithms showed the highest quality. The Fuzzy AHP method was used to recognize the customer’s value in created groups and weighting input parameters. Finally, cluster analysis was performed using decision tree algorithms