Using data mining techniques for improving customer relationship management

Abstract

Customer relationship management (CRM) refers to the managerial efforts to technologies and processes that helped to understand firms’ customers. For this reason data mining techniques have an important role to extract the hidden knowledge and information which is inherited in the data used by researchers. This investigation focuses on the current automotive maintenance industry in Iran and applies various data mining technologies to partitioning customers. Its purpose is to determine the group of potential customers who are more likely to purchase optional services. Whereas the dataset used in this study is the real data of company, many steps of preprocess were applied and dataset records have been divided into two categories by attributing labels to the records. After preprocess steps, CAID and C5.0 methods of decision tree have been applied to classify customers and help the desired organization to make decision. By the results of two decision tree methods, there are some more important features for the firm to making decision.