Case Study On Apparel Retail Terminal's Customer Relationship Management Based On Data Mining

Under the background of client economic,customer consumption concept is gradually changing.With the substance enriched and the globalization of markets,customer's shopping experience demand is gradually growing.Businesses are facing greater competition and opportunities.Apparel terminal shops are under pressure from the economic downturn and network marketing squeeze.So how to enhance the customer experience and reduce customer churn has become an important topic for clothing business executives and researchers.Therefore the efficiently and accurately use of customer relationship management system has important research value.The first topic on the main part of the subject based on the practice in a men's wear terminal,combined with literature review,analysis the operational processes and the implementation mechanisms of customer relationship management system.Through the case analysis,identify customer churn factor and gives solutions,obtain two problems which can be solved by the customer relationship management system.The two problems named store services defect and product joint marketing defect.Subsequently,in order to solve the store service defects,the subject use the method of interviews,questionnaire and SPSS data analysis.Treat clothing terminal management personnel for the interviewee,the high-end men's consumer groups as investigation object,do the survey on the 18 daily services which nowadays clothing terminal carried out generally.After the analysis of the data,find the correlation between the gender,the consumer age,education,occupation,monthly income properties and the various types of daily service demand.Give recommendations for the results of each daily service.To solve the problem of improper product related marketing,the subject transfer data from customer relationship management system,filter the data and select 22 variables for data mining.Data mining cluster analysis,clustering of different consumers,find the potential common in the purchase of the product.Data mining association rules analysis,associate various types of apparel products,find potential sequence of buying.Give solutions to solve the problem of improper product related marketing.Finally,combine the two solutions,give support to the apparel terminal customer relationship management.Research ideas and research methods of this paper can also beused for the other apparel categories,help clothing terminal stores reduce churn,enhance the customer experience,promote the effective of clothing terminal daily services,improve product related marketing accuracy.