Customer Behavior in Banking Industry: Comparison of Data Mining Techniques

Abstract

Nowadays organizations have perceived the importance of managing customer relationship and its potential benefits. Customer relationship management supports organizations to deliver beneficial relations with customers. Customer satisfaction and retention are the leading objectives of any organization and this cannot be done without knowing the loyalty of the customer. Accordingly, to identify the loyalty of the customers, Kmeans algorithm was applied to the bank customers' data and clustering was conducted. The customer behavior is estimated by neural network and C5.0 models. Results show that C5.0 better fits the customer behavior. In addition, estimation of customer behavior leads organizations to more successful customer management strategies. 