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Customer Subdivision Research On Crm Based On Data Mining In Securities Industry

Posted on:2006-06-28Degree:MasterType:Thesis
Country:ChinaCandidate:H Z TianFull Text:PDF
GTID:2156360152987262Subject:Management Science and Engineering
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With the deepening of reform and opening up and putting forward a Well-off Society goal, Chinese economic has developed rapidly. As a very important part of economic field, securities has made great achievements, but at the same time, it is facing more and more competitions and challenges. At present, because of the similarity and imitation of products, the life cycle of products becomes shorter. And the competitions among securities are focusing on retaining and attracting customer. How to have a better understanding of the customer's characteristics and demanding, how to design effective products and service and how to improve the customer's income and satisfaction, are the key points of customer relationship management (CRM) in the securities industry.The key point of understanding customer's characteristic and demanding is to establish data warehouse able to meet with CRM's requirement, and to collect customer information including customer's attribute, capital status, transaction character and so on, and then to mine data deeply by suitable methods and tools, and to build reasonable model in order to subdivide customers. Through the analysis, the company can design scientific and sound service products to abstract customer.With a view to above reasons, this dissertation discusses CRM in securities industry through macro and micro research. From macro aspect, starting with the characteristic of CRM in securities industry, this dissertation has some research on the characteristic, framework and functions of data warehouse, and discusses the methods of data mining, and how to carry out CRM by Web data mining on the web-broker business. From micro aspect, this dissertation investigates the subdividing operation by an example of the subdivision of CRM in securities industry, and carries out data load and extract, chooses date mining methods and establishes data model.The dissertation emphasis the following researches:1. The CRM framework characteristic and requirement in securities industry, and the multi-dimension model's building.2. The data mining characteristic and method research according to CRM in securities industry.3. The sorts, methods and processes of securities customer subdivision.4. The application research about Multi-Dimension data analysis of CRM in securities industry.5. The Web data mining application research on CRM in securities industry.Base on introducing the general method of data mining, the dissertation uses Neural Network method exploringly to subdivide customers in securities industry, which get an effective result. During the process, it stores, loads and extracts data with SQL Server 2000, makes Clustering Analysis with SPSS, builds customer subdivision model with Neural Network, discuss the application of OLAP in the CRM of securities industry.Through above research, the dissertation puts forward how to build data warehouse effectively, designs data model in light of data mining and analysis of CRM in securities industry in our country. In addition, the dissertation points out how to choose different data mining method and data mining tools with the purpose of different aim in the phase of data mining.Currently, the applications of CRM in our country are still in the CRM operational phase mainly. Carrying out the research of analytic CRM can help enterprise to enhance its CRM level. So the research does not only have practical meaning to CRM in securities industry, but also provide a reference to the CRM in other industry.M.D. Candidate: Tian hongzhong(Management Science & Engineer)Supervised by:Yang Baoan...
Keywords/Search Tags:securities industry, data warehouse, data mining, customer relationship management (CRM), customer subdivision
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