Research Of Customer Acquisition System Based On Web Data Mining

The pervasively application of interment and differentiation internet information enable increasing number of companies and clients complete their transaction online. In modern network environment, the companies which participate in the competition through E-business might face all kinds of information and data. How to mine useful knowledge is a significant task of web data mining.This paper is written after a research on different bases such as web data mining, CRM, network economics. This paper designs a network customer acquisition model, which divides the whole acquisition period into four stages: anonymous visitor, free member, active member, and buyer. This paper design different data mining task for each stage, in other word, it target the problem in each stage. In general, all the measure taken will improve the acquisition ability of website. Then this paper uses the web data mining tool Clementine and data from a web shop to prove the availability of this model. This conclusion point out this model could significantly accelerate the transfer rate, either in single stage or whole period.There are diversity fields to use this research, it can be applied in network marketing and CRM of B2C Company, also it can provide to small web merchants as a value adding service, what's more, it can be separately sold as SaaS to the company who need it. In the end of this paper, it gives some innovative opinion and some weakness need to be completed.