Study On Application Of Cluster Analysis In Customer Segmentation Of A Bank Enterprise In Shanghai

In recent years, as competition among banks, the banking environment in China has undergone tremendous changes, from "a seller's market" to today's "buyer's market", some foreign banks to join, but the monopoly of the traditional banking advantages no longer exist. Therefore, it is a manifestation of the banking sector more competitive scramble for resources on the client, not only in how to win new customers, also reflected in how to better service existing customers, improve customer satisfaction, and tap new earnings growth. Customer relationship management as one of the major concerns the banking industry.In this paper, focuses on data mining technology management in the cluster analysis. Study on the banking business, especially the application of customer segmentation. Through studying the charateristics of the banking business, I propose and realize the customer segmentation model based on customer relations management (CRM) theory and the structure and the characters of banking customer data. The model has four Indicators:scale of customer funds, geograhic scope, online banking and flctuation of ending balance. In the model, it uses K-means algorithm as a method of customer segmentation. I use the SPSS software as the data mining tools and analyze the real customers'data of the certain bank in accordance with the customer segmentation model. According to results, I finally provide corresponding marketing strategy and services market strategy and services and a set of relatively complete and feasible projects of customer analysis.