An integrated customer relationship management and Data Mining framework for customer classification and risk analysis in health sector

Abstract

In today's competitive environment, having a customer oriented approach is inevitable for organizations. At this point, in order to achieve customer satisfaction, customer relationship management (CRM) targets to provide products and services which meet customer expectation. Data which is collected about customers is an important source to determine their needs. Therefore, analysis is made to determine characteristic features of customers by using the data in data bases of the companies. Thanks to this data, it is possible to determine the product choice of customers and to put forth the opportunities that can be provided to customers. Data Mining (DM) is a process of revealing a meaningful information and image by the analysis of data. In this study, the data of a company which is operating in health sector in Turkey was analysed using some data mining algorithms like Naive Bayes which is an algorithm of classification rule, J48 which is one of the algorithms to generate decision tree and k-nearest neighbour IBk algorithm. Thus, customers were classified by product groups and risk factors. As a result of the study, it is aimed to develop a marketing strategy and a more effective sales campaign for the company by using the classification results. As well, to the best of our knowledge, our paper is the first study which realized in health sector.