本研究以顧客的交易資料為探勘資料來源,每一筆交易資料包含顧客曾經購買的商品項目,文中以某一商品為探勘目標,利用資料探勘(data mining)中的分類分析(classification analysis)分別從以下兩方面建構商品適性行銷策略:一是考量商品出現在交易資料中,本研究設計一個建構決策樹的方法,以顯示那些商品項目與目標商品之間有關聯性,藉此做為發掘目標商品適性的顧客;二是考量商品出現在交易資料中具有購買次序性,本研究設計一個建構次序決策樹的方法,以顯示那些商品項目與目標商品之間有關聯性,藉此做為發掘具有購買次序之目標商品適性的顧客。文中根據提出的方法,設計與建置一個商品適性行銷策略探勘系統,本研究探勘結果,對企業擬定商品適性行銷策略,將可以提供非常有用的參考資訊。
This paper uses customers' transaction data as the source data of mining. Each transaction data contains a customer ever bought product items. Let a product as the target of mining, and use classification analysis to plan adaptive marketing strategies of the product from two aspects. One is to consider whether products are contained in transaction data or not, we design a method to construct a decision tree to show that there is association between those items and the product. It is the basis to find the adaptive consumers of the product. The other is to consider extra the sequences of products in transaction data. We design a method to construct a sequence decision tree to show that there is association between those sequences items and the product. It is the basis to find the adaptive consumers of the product with sequential buying. A mining system of adaptive marketing strategies of products is designed and constructed based on the both methods. The mining results of this research can provide very useful information to plan the adaptive marketing strategies of products for the business.