Analysis Of Taobao Shop Customer And Sales Based On Data Mining Technology

With the rapid development of e-commerce in China,consumers' consumption habits are gradually changing from offline store shopping to online shopping.TaoBao.com was founded in2003,it occupies more than 80% of the online shopping market in our country.More attentions are paid to data mining technology along with the electronic commerce entered the era of big data.This article summarized domestic and foreign literature review.This article choose NL cosmetics store as the research sample,and the data mining process includes two parts.The first part is:using K-Means algorithm to segment customers of NL store,selecting customers' shopping history,add to favorites,purchase within a year,average purchase times and the latest consumption as the evaluation index;the customer can be divided into senior VIP,regular VIP and regular customers.Analysis shows that,senior VIP customers with 8 years online time have higher consumption ability and loyalty;Ordinary VIP customers with 5 years online time have moderate consumption ability;Ordinary customers with less than 5 years online time purchase little product in NL store,they mainly concentrated in a small number of products,and their loyalties are weaker.The second part: use Bayesian classifier to predict NL consumers' shopping prefers;take the customer's level,the number of skin care products B and C purchased in NL store,and discounts property as basic classification,through the prediction of 232 customers,the model prediction accuracy is 66.4%.According to the data mining results,it can draw potential information behind data,through these information,marketing programs can be designed according to different customers.