The Research On The Application Of Data Mining For Retail Business CRM

With the development of market economy,the competition among retail business enterprises is becoming more and more serious.People have already realized the importance of customers to enterprises and the enterprises will not exist without good customer resources.Along with the rapid progress of information technology,the business enterprises have accumulated large amounts of historical data,but the abundant data were not taken good use of because of lacking powerful analysis tool.Therefore,it is an emergent task for enterprises that they have to catch the valuable customer information,so that they may supply the customers with individual service,improve customer satisfaction and develop high-valued customers.This paper takes qualitative analysis combined with quantitative analysis method, theoretical research combined with demonstrative research method,dynamic research combined with static research method and interdisciplinary method,and studies the application of data mining for retail business CRM from multi aspects.Firstly,from the theoretical research aspect,this paper concludes four models of retail business CRM based on the plentiful literatures,that is,customer value model,customer satisfaction model,customer classification model and customer purchase association model. Secondly,from the demonstrative research aspect,this paper studies and analyzes a customer relationship management problem of food chain store in retail business by SPSS Clementine tool,according to CRISP-DM standard business mining processing. Seeing about customer basic information from static aspect,this paper realizes the customer card classification model and gains the main character of each kind of member card customers,so it can supply supportive information to the chain store in member card sale field.Then,from the dynamic research aspect,this paper realizes customer behavior clustering model through the customer sale data,according to the customer's average profit and purchasing frequency,so it can help the retail enterprises adopt corresponding policy for different kind of customers by their different characters to improve customer satisfaction and loyalty.Moreover,this paper does further research in customer sale data and gains the product information by each customer's purchasing power at the same time,and then realizes the customer purchase association model, whose association rules can supply the chain store with decision support in product layout and crossing sale fields.At last,this paper proposes corresponding practical policy for retail business CRM by mining result from separate models so that it can help retail enterprises to improve customer value and realize the maximum profits.The research result of this paper will give retail enterprises new idea on how to develop the business and improve the customer management level,so that it will be helpful to the enterprises to improve the customer contribution and loyalty and catch the competition advantages in the future.