Analysis Of Customer Loyalty Based On Data Mining

Data Mining is an important research subject in the field of Information Technology. It means a process of extract the implicit, previously unknown, and potentially useful knowledge from voluminous, non-complete, fuzzy, stochastic data. It is application for crossing course, it people logarithms according to from the low level and simple search, promoting to scoop out the knowledge from the data, providing the decision support Classification and prediction is important research aspect that two kinds of data analysis form, also is, in data mining, can used for withdrawing to describe important data model or future data in predicting trends. After 20 years of development, on the theory, data mining techniques is becoming more and more consummate and is expanding its application area. Now, data mining has been used in telecom, finance, busyness, weather forecast, DNA, stock market, intrusion detection and customer segmentation etc.This text is around the applied problem in prediction of customer's loyalty launches the discussion. Studied the classification first with the related calculate way that predict, laid equal stress on to order to discuss the line return to return the analysis to divide into section the principle of the machine with the CART; The next in order, adopt two above a calculate ways combine combinative other data excavation technique, aim at the customer in the business enterprise the loyalty the analysis the problem set up the customer the loyalty the analysis the system; finally, analyze customer loyalty of Haier company based its customer relationship data. The main content of the thesis is as follows:First, we described the background of research and pointed out its significance. The domestic and foreign situation of data mining research was analyzed from theoretical and applying aspects. After analyzing the general progress of knowledge discovery we gave a classic framework of a data mining system, analyzed main function of every module and expatiate on the technique of data mining.Second, introduce the common means of classification and prediction, such as decision tree, Bayes classification, neural network, genetic algorithms, rough sets etc. Analyzing and comparing the disadvantages and advantages of this algorithms. And giving the valuation with the method that increases accurate rate in classification.Thirdly, detailed discussing the line regression, particularly the principle and its parameters that the diverse line regression. Given Tread Prediction Function according tothe diverse line regression.Describe the theory of CART classification and gives an algorithm which integrates the tree building phase and pruning phase.Fourth, complete the customer loyalty analysis system. Gave the concept of customer loyalty, explain the important meaning of customer loyalty to the business enterprise; introduced the main function of the system: prepare the data, discover the main customers and predict customer loyalty; the customer loyalty of Haier Company is analyzed by the customer loyalty analysis system. In order to analyze the customer loyalty of Haier Company, the process and way, which we choose and deal with the analyzed data, is discussed. Predict the trend of customer loyalty by using regression and classification. Change the localization of the past customer loyalty system which can only classify the sort of the customers, but not predict the trend. So it proof that LTPA (Loyalty Trend Prediction Arithmetic) is practicability.Finally, all the results are summarized, and the study prospect is discussed.