Study on the design of CRM-oriented synthetic decision support system

With the popularization of e-commerce in recent years, customer relationship management (CRM) has gained much attention. Many companies have initiated projects to improve on customer orientation and plan the implementation of CRM systems. Among the desired benefits are increased customer satisfaction and retention by providing personalized products and value added services. With the aid of data warehouse, data mining and OLAP technology, businesses can formulate specific strategies for different customer bases more precisely. This paper presents a model and investigates the use of computational intelligent techniques for CRM. These techniques allow the complex functions of relating customer behaviour to internal business processes to be learned more easily and the industry expertise and experience from business managers to be integrated into the modeling framework directly. Hence they can be used in the CRM framework to enhance the creation of targeted strategies for specific customer bases.