Research On The Medical Enterprise CRM Construction And Data Mining Application

The medical enterprise CRM is to improve the relationship between medical enterprise and the customer and put forward a new management mechanism, is holding all the new customer-centric philosophy, has important theoretical and practical significance. Data mining is the data from the massive "mining" useful information, the technology in the field of medical enterprise is the current research focus, Such as the medical enterprise can be solved and the customer relationship management, sales data analysis of the problem of cross-selling drugs, deployment of enterprise business intelligence, dynamic analysis of market demand and so on. This paper develops a framework for medical enterprise and functions of CRM systems, while medical enterprise based on data mining technology sales and customer relationship management were studied.The main points of this dissertation are listed as following:On the basis of the introduction of CRM and data mining in this thesis, according to the actual needs of medicine industry, the thesis clarities the goal of CRM system in medicine industry, and identifies the functions of CRM system in chapter 2. Meanwhile, a CRM system design case of medicine industry is proposed.Based on the association rules method, the sales information data mining of medicine industry CRM is realized in chapter 3. According to the characteristic of intercross sales, a method of evaluating the association rule of two items sales promotion is provided. Thus, the method is optimized the medicine drug putting order.The chapter 4 of the thesis focuses on the classification analysis of medicine industry CRM customers. Based on the PCA method, a discrete processing and feature optimization algorithm for medicine industry CRM customers is presented. The customers are classified efficiently by using cluster KNN method. The experimental evidence shows this approach enhances improves the efficiency of classification analysis in some degree.