Analyze The Network Shopping Market Survey Data Based On Data Mining Technology

Customer purchasing behavior is influenced by external factors, namely externalstimulation; there are internal factors, namely personal characteristics. External factor is theexternal cause, for the customer to make a buying decision provides conditions, and theinternal factor is the basis of customer respond. The main factors influencing the buyingbehavior are the internal cause, that is, the customer’s personal characteristics.Technology because in the past, and the limit of the method, industry characteristics,absorb the huge amounts of data by the Internet through online indeed brought electricityenterprise short-term deal with space, and the cost of extracting data source directly fromoffline mode and pattern is not yet mature, but the market’s largest data sources is always online, the nature of e-commerce through electronic means to serve the traditional businessprocess, help them reduce cost increase efficiency. So established offline channels of dataacquisition interface directly, instead of just rely on pure online data as a source is a key link.At the same time, online data collection to data center, the analytical data will be feedbackonline, with the use of more accurate value.In this article, through E-mail, QQ messages, micro letter group way to networkshopping market survey questionnaire sent to respondents, after the completion of therespondents would return the results through the corresponding manner. And at the same timeoffline some face-to-face questionnaire survey was done. Total recovery of the questionnaireresults from nearly200, mostly family, classmates, friends, colleagues, friends, network, etc.The purpose of this study is to use data mining algorithm and a variety of mining mode,aiming at to collect the sample data, in-depth analysis of online user behavior, draw certainregularity, provide reference opinions for electricity, to assist its market positioning. Ofcourse, this article belongs to experimental study, also hope that through such an experience,to learn and understand the technology of data mining, to lay the foundation for theapplication of the future better. The concrete research content is as follows:1, Data Mining Patterns: Cluster analysis, classification/prediction, association rules2, Methods the survey questionnaire3, Customer behavior analysis 4, a variety of data mining algorithms: the TwoStep algorithm, K-Means algorithm, theQUEST algorithm, Apriori algorithm.5, data statistical analysis software: SASS, Clementine data mining platform.After data analysis, five conclusions are:1and a half years, online shopping more and each time shopping for between100-500much affected by online credibility with customers, but the proportion of the user is not high.Half year shopping a lot, every time shopping amount between100-500users affected byonline credibility to a certain extent, and the two types of user accounts for a large proportionin the group.2and a half years, online shopping more and online sales between100-500customersmore easily influenced by online search rankings, lower support showed lower proportion ofthe customers. It shows that most customers don’t influence by online search rankings.3, online shopping history for5years or more than5years, half a year online shoppingfrequency is higher; Less online shopping history within a year; Online shopping history in1-5years of two-thirds of the people shopping once in a while, a third of people often onlineshopping.4, the amount of online shopping and online shopping history is direct ratio relation,online shopping history long crowd consumption amount is rising trend, and taller; Onlineshopping history shorter people consumption amount is conservative; Online shopping historyfor1-5years of the crowd is more, consumption, tend to be moderate.5, online potential customers the crowd can be roughly divided into the followingcategories:(1) Internet access time in more than four years.(2) Internet users aged between18and35.(3) have college or bachelor degree of Internet users.In this article has collected the authoritative Internet survey and management institutions,on the analysis of the data used to validate the analysis conclusion, the results prove that thebasic accurately.