The Study Of Data Mining Of Customers' Information Of Tianjin's Real Estate Market

With the development of Tianjin's real estate market, the difference of real estate enterprises' products and services is more and more small. Real estate management mode of enterprise is facing the transition from "regarding products as the centre "to" taking customer as the centre". The enterprise will improve, if it concern demand of customers, understand their value. At present, more and more enterprises thought that they should know and understand demands of their customers and keep customers; at the same time, they should mine valuable knowledge among customers' data. This knowledge is very important to real estate enterprises beating their enemies.This paper brings data mining technique to the study of customers' information of Tianjin's real estate market. And it comprehensively uses data mining method, CRM theories and Tianjin's real estate industry's background knowledge, establishing housing product's customers' knowing' satisfaction evaluation guideline and idiographic flow. In this thesis, it gives a model of data warehousing for customer's information based on data mining. Through empirical approach and related enterprises investigation, it designs a questionnaire system to collect data. In empirical part, it uses factor analysis, multidimensional scaling analysis and multiple correspondence analysis etc. data mining methods. Several model including crowd segmentation that is about to identify an ideal area; multidimensional scaling analysis buying ideal house' conditions; housing product's knowing satisfaction factor analysis etc. are given in this part. It finds some valuable results. It hopes that this thesis can help our house developers to carry more precise quantitative analysis and scientific forecast so that improving their competition power and satisfying demands of Tianjin's citizenship.