電子商務，這是在90年代才興起的經營模式。在過去的社會演進裡，人類從最早的農業經濟進步為製造經濟，一切以產品、品質為出發；隨著知識時代的來臨，製造不再只是一味大量生產，更為重要的是站在顧客角度思考，而慢慢從製造經濟轉變為服務經濟，以顧客的滿意為重。 以滿足顧客的需求來看，網路商店必須具備高效率、可授權的、動態的且反應速度快的特性。消費者需要個人化資訊來做決定，然而，這似乎都是現有電子商務網站所欠缺的。 本研究將會採用資料探勘、灰關聯分析、層級分析法與灰色預測來達成客製化的行銷策略、產生客觀的產品排名與客製化的產品排名，並加以預測客戶的喜好。 / E-commerce, it’s a new business model from 90’s. On the social evolution track, from agriculture economy to manufacture economy, product and quality is the spotlight. With the coming of knowledge era, manufacturing is not just mass-productive, this era’s spotlight is the customer satisfaction. The evolution track had moved from manufacture economy to service-oriented economy. If sellers want to meet customers’ need, it should had some features, such as efficient, empower, dynamic, quick response, and so forth. Customers need tailor-made information to make the purchasing decision. However, nowadays internet stores cannot meet this need. This research will utilize data-mining, grey relation analysis, analysis hierarchy process and grey perdition to draw up tailor-made marketing strategies, generating objective product ranking and tailor-mage product ranking, and predict customers’ preference trend.