Application Of Data Mining Methods In B2C E-commerce

Since the new century the Internet technology develop more and more fast in modern society, also bring us a new business culture. B2C (Business-To-Consumer) e-commerce business model is just the most exciting part of the development. As the main background of data mining technology, statistics can play a great role in this development.In this paper, based on the data in quantity from two B2C e-commerce websites company, the systematic data mining process of the three main branches are done, which is association rule mining, clustering and classification. Each branch corresponds to a section of this paper's article, including association rule mining applications in the retail websites in chapter 2 to mine useful association rules between goods in a single shop, clustering analysis of the groupon website in chapter 3 to categorize the shop by its location in the city, and logistic regression model in response to the application of marketing in chapter 4 to try give the effective lift for marketing project. In each chapter we first detail the B2C e-commerce website and business requirements of data sets, and then we simply literature some data mining algorithms to be use later, also give the prevalence of the main advantages and disadvantages, finally we using statistical software (R and SAS) to analyze data and get results, which specifically show that data mining technology can play a great role in B2C e-commerce.