Application Of Association Rules In CRM

With the high-speed development of the economy of china and constant improvement of the living standards of the people, house has already become residents'basic living demand. Meanwhile, the importance of real estate to our national economy is being strengthened constantly. However, with the constant issue of some macro controlling policy, the behavior of customer gradual and ripe with reason, customer's demand to commodity apartment has growing greatly no matter from the scope or the depth. The fierce market competition of real estate is being strengthened constantly and has entered the buyer's market progressively, enterprises can only pay more attention to the demand of market and customer in order to make the accurate judgment to various changes of the market.The paper based on the item of real estate companies on the use of association rules , extracting useful management and the actual demand. After the analysis of the mining association rules of the basic principles and technical characteristics, the discussion focused on the problem of the application of association rules in CRM information extraction methods of data mining. This document has done following work:First, from the real estate customer relationship management and customer relationship management needs of the basic information technology– DW and DM association rules in the theory of information extraction methods. The real estate business customer satisfaction and loyalty analysis, summed up the implementation of mining association rules of real estate enterprises can increase customer satisfaction, Increase corporate profits and lower corporate sales and promotional costs.In addition, the papers do a survey on the area residents to buy the housing in 2007,in LinHe situation. Using Analysis tool of the survey obtained more valuable mining models and rules. These models and more objective rules reflect the current residents of the housing demand in LinHe and terrified the conclusion is possible, effective and quantified.