Decision support system for a customer relationship management case study

Data mining which has become very common and gained importance recently, is a tool which provides to discover hidden and valuable information in large datasets. One of the widely used areas of data mining is Customer Relationship Management (CRM). CRM is an approach used to understand customer?s behaviors and increase the customer satisfaction. The aim of this study, researching the data minig and CRM concepts which has become widespread and important in recent years, in addition to applying a data mining model to banking sector as an example and representing the result in a mobile platform. This study has built a classifier using the naive Bayesian classification. The accuracy rate of the model is determined by doing cross validation. The results demonstrated the applicability and effectiveness of the proposed model. Naive Bayesian classifier reported high acceptable accuracy. So the classification rules can be used to support decision making for achieving a good CRM for businesses. Keywords: Data mining, customer relationship management, CRM, mobile