Cluster Analysis Based Research On Consumer Relationship Management For Investment Projects

With the further spread of the economic crisis, the central government’s"expanding domestic demand, guaranteeing growth" become the main objectives ofthe macro-control. Governments around the investment sector should build analysis ofhistorical data collation mining, excavation customer information, to enhance thequality of investment, improve work efficiency for the investment sector has a veryimportant practical significance to the “growth” objective.In this paper, through analysis of historical data saved by the investment sectorinvestment projects finishing, we have recommend a historical database of investmentprojects; a Merchants customer profile database; method of cluster analysis, analysisof historical data in the investment characteristics of customers and statistics aresummarized, so that the use of the results of the data analysis, you can make someuseful suggestions and comments on the existing investment work to enhance theefficiency of investment work.Firstly, to collate historical investment sector investment projects. The paper isbased on data analysis needs, design a database table, years of historical dataconsolidation, finishing the complex data into structured data, on the one hand, toestablish an investment project data standards, to facilitate the further accumulation ofthe latter part of the investment project data; another provides a convenient one hand,living in a variety of historical data analysis.Secondly, based on the historical data of the investment projects, customer value,customer reputation and customer demands three areas, we establish an investmentprojects customer feature model. Customer value customers the benefits of investmentunits in the investment projects, including historical value, the current value andpotential value of the three aspects; customer reputation is the evaluation of thecustomer’s corporate reputation; customer demands put forward in the investmentprojects the demands of the evaluation. This customer feature model is to value acustomer to measure evaluation and recommendations for investment decisions.Finally, based on the established customer feature model, combined with thehistorical data of the investment projects, through the method of cluster analysis, weobtain a number of Merchants customers to choose the guidance and advice from the existing historical data. This paper use SPSS data analysis tools, to build a clusteranalysis solution.Based on the analysis of historical data of the investment projects, organize, theestablishment of the customer feature model of an investment project, and proposed acluster analysis of investment projects as the core customer relationship analysissolutions. Through the validation of the experimental data, the customer feature modelestablished in this paper can be a good characterization of the customer profile of theinvestment projects, the proposed investment projects customer relationship solutionsmay provide a more reasonable and effective investment advice, investment work forthe relevant departments in theory efficiency, effectiveness enhancement to provideeffective help.