The Case Analysis Of Customer Segmentation Based On Data Mining Case

In China’s large and fast-growing market of women’s shoes, the top ten brands’ market share is only 38.4%, accounting for about 1/3 of the total sales across the country.With huge market capacity of footwear industry making competition increasingly intense, the first brand start attacking on all fronts and second brands are not to be outdone, besides many shoe companies are not satisfied with the present development situation, making an effort to broaden greater market.To be dominant in the footwear market, enterprise should focus on two things: on the one hand to continue to attract new customers, at this time,they shuould be about to rely on their own high quality products,quality service and good reputation; On the other hand to keep old customers, to enhance the old customer loyalty, enterprise need to understand customer preferences, to meet the different needs of customers to avoid customer loss.The cost of attracting a new customer is 5 to 7 times that of retaining old customers, but because of limited resources, enterprise is impossible to qualitative analysis of each old customers to get different preferences and different needs, it needs to subdivide the huge old customer groups.the purpose is that we take a targeted marketing strategy in view of different groups of customers, so as to achieve a win-win situation thatcan meet customer demand and make profits.The core of this thesis research is a fashion group of listed companies in the mainly their research and manufacturing capabilities and brand management, business stretching across greater China(mainland China,Hong Kong, Taiwan), Asia, Europe and North America, and being one of the most successful domestic brand in China. bacause current popular customer segmentation theory mainly focus on the consumer market segment and the existing customer segmentation theory according to the customer to buy the product characteristics of subdivision of analysis and research is relatively less, so the research of this thesis is that make the style of this brand shoes as segmentation variables.This paper, mainly based on the enterprise sales data for analysis,combined with actual situation of enterprises, divided into different customer base,combined with the customer purchase frequency and amount at the same time through the customer segmentation theory,directly reflecting the brand customers’ preferences and the importance of each type of target customers to the enterprise. so that enterprise can make different marketing strategies according to the needs of different customers and contribution to the enterprise, thus reducing the cost of sales of and enhancing the competitive ability of enterprises.In this paper, combined with the use of SQL Server database, R Software and the K- means clustering algorithm in data mining,cluster with the customers. Thought clustering analysis of results of 5 to 12 classes, class that divided into 5,9,12 is more appropriate,then compare summary of these three clustering results, providing the research ideas for customer segmentation of the footwear enterprise.