The Study Of The Securities Industry Customer Relationship Management Based On Cluster Analysis

Customer Relationship Management (CRM) appeared in the United States in the early 90s of the 20 century, and in the late of the last century came into China. CRM ultimately help the enterprises get more customers, retain the original customers, enhance the customer's loyalty and achieve the objective of creating value for customers. Therefore, in the securities industry, the introduction of customer relationship management is essential. Enterprises in the implementation and improvement of the customer as the center , the most important, press on the customer segmentation, and supply different services to customers based on the contribution of enterprises, So how to become customer segment is a key. For the industry characteristics of the securities industry as well as the large sum of the customer, the paper only applies to customer segmentation field of customer relationship management of the securities companies on K-means clustering algorithm, by improving the selection of the initial cluster center, optimize algorithm. Finally, based on clustering results, the customers are divided different customer segments, and for the securities firms propose a reasonable policy and recommendations. This paper is divided six chapters, the first chapter introduces the background, the purpose and significance of the paper, summarize CRM research review and proposes the research ideas and research methods.The second chapter describes customer relationship management. Introduced the concept, function and classification, and compare the status of domestic and international customer relationship management applications, based on it propose CRM application disadvantage in China.The third chapter is the need for the introduction of customer relationship management. After the introducing of the general securities industry of domestic and international, propose application misunderstanding of the domestic securities industry CRM, and supply the corresponding solutions. Finally, express the importance of customer segmentation in securities industry.The fourth chapter is to build the model of customer segments based on cluster analysis. At first, introduce the cluster analysis and K-means algorithm theories. Point out its advantages and disadvantages, and improve the selection of the initial center, optimize the algorithm, gain good result. The fifth chapter is to be in customer segmentation of customer information the securities industry, eventually obtain three types of customers, to provide a theoretical foundation for different services to securities firms.The last chapter is the conclusion. The study conclusion is valuated, and the drawbacks of the study and improvement directions are pointed out.