摘要
隨著科技的發展，3C已經成為現在人不可或缺的產品之一，消費者可以從更多方面接收更多商品資訊，在產品種類選擇很多的情況下，不管實體店面或是網路銷售方面，根據會員過去之購買行為，適時推薦適合的產品，刺激消費者的購買量，並維持與顧客良好的關係，是現今廠商所面臨的重要課題。 本研究以3C資料庫之顧客交易紀錄資料，再透過購物籃分析法中的因素分析法，探討購物籃中的產品組合，找出產品之間的相關性。最後，利用決策樹分析法中的自動互動檢視法，找出各產品購物籃中的目標客群。 研究結果顯示，除了全體目標客群之購物籃外，在退刷紀錄方面，還可再以年齡層與性別區分，縮小目標客群，針對這些購物籃之產品組合，期望以熱門產品帶動冷門產品來銷售。對於以上結果，廠商可以針對高相關性的產品組合，在產品擺架、產品推薦與聯合促銷上，能有更適合的策略，增加消費者的購買意願，提升銷售量。
並列摘要
With the development of science and technology, 3C has become one of the indispensable products. Consumers can receive more and more products informations whether it’s from the brick and mortar store or online sales. Enterprises can recommend suitable products to stimulate consumption by according members’ past consuming behavior. Maintaining a good relationship with consumers is an important issue from now on. In this study, we use the factor analysis to find the product combinations and the correlation between products from the 3C database. Finally, we use the chi-square automatic interaction detection to find the target consumers in every basket. The result of this study shows that we can distinguish the consumers’ target by ages and gender not only in the whole target consumers but also in the refund of credit cards. We hope to promote the amount of sales by driving poor-sale goods with good-sale goods. Integrating the above-mentioned, enterprises can determine strategies appropriately on the display of products, products promotion and joint promotion to increase the sales.