Research And Software Implementation Of Meshed Customer-Group Segmentation Based On Behavior

How can we show the website operating and marketing status objectively and opportunely, so that we can achieve scientific prediction and rapid decision-making, is the key to the success of an e-commerce website. To fully understand the effect of website operation and get broad improvement, we need the help from WEB analysis system to collected statistical data and do the proper analysis.However, currently most of the WEB analysis systems are based on flow rate, that is suitable to the analysis of the web media. This kind of analysis systems can estimate the value of the media, thus estimate the advertising cost against a specific media.For e-commerce WEB site analysis system, however, the thing customers concerning most is consumer's psychology and behavior. The consumer's psychology and behavior, also known as the Consumer's U & A (Usage & Attitude) study, covers many parts of marketing. It can help us understand consumer's psychology, buying behavior, using behavior and its changes, thus provide us a scientific way to adjust strategy of marketing. It can also help companies to quickly and accurately select the target customer group and formulate the appropriate strategy of marketing.First of all, the paper explores a behavior-based mesh segmentation method of customer-group, allowed e-commerce business company use a more convenient and intuitive way to analyze and show consumer's behavior. The method is to classify customers into different group through the web content they visiting, then in the same group, according to the level of contents, divide the customer into different customer segment through a variety of KPI; According specific KPI to each customer segment, adjust marketing strategy and market plan. Secondly, this paper proposed a common KPI metrics for e-commerce industry WEB. Third, this paper brings about the WEB analytic system for e-commerce companies. Fourth, this paper gives a research direct based on the unique identify Internet visitors. Fifth, this paper describes how to collect visitor information and its coding implementation. Online customer's behavior data collection guarantee a quicker response, thus make it easy to cooperate with companies web marketing and help the companies know exactly the web operations at first time. This paper mainly focus on the online customer's behavior research, analytical approach of demographic is not the point.