Survey Of Customer Segmentation In P Bank Based On Data Warehouse

As the rapid economic development in China, the business of foreign-funded banks in China have carried out in a deep-going way, as well as each local commercial Banks are expanding their business over the whole country, the competition among local commercial banks are gradually intense. The focus of the competition among banks is customer, so the effective Customer Segmentation is the precondition to control and improve the competitiveness of a bank. The bank must fully understand the value of the existing customers, maintain the premium customer resource, and provide them individual and attractive services, so as to improve their loyalty initiative and take the advantage use of the limit resource to create as much benefit as possible. Personal financial service has become a new profit growth point; it also has been recognized by commercial banks. This Survey will explore the importance of the Customer Segmentation and how to apply the Customer Segmentation Theory to P bank.After banking data collected Data Warehouse Technology was introduced. The introducing of Data Warehouse Technology has provided strong support on a series of policy-making applications in banking industry such as improving the general management standard, establishing the customer relationship system, carrying out the customer segmentation and so on. This survey is based on the application of Data Warehouse Technology in P bank in Dalian, aimed on the customer segmentation, applied the data mining and such relative technology and instrument to establish effective and reasonable customer segmentation model, so as to improve the level of the decision-making and management of the bank.First the survey will summarize the current status of the customer segmentation and the application of data warehouse technology in general, then explain customer segmentation theory in P bank and data warehouse technology; after that to establish a customer evaluation model, which is used for customer segmentation based on customer value; next to establish datamarts applying data mining instrument and frame cluster analysis model; the conclusions lead to successfully implementing customer segmentation, give accurate character descriptions to each kinds of customers groups and put forward marketing suggestions tailored for each groups.The conclusion of this survey shall help to manage customer relationship, maintain valuable customers, develop potential of customers and improve customer's value and loyalty initiative for P Banks, which also has very important theoretical value and practical significance.