本研究旨在探討如何利用購物籃分析法來深入了解顧客的消費行為，並進一步提升企業的行銷策略。現代行銷學之父Philip Kotler將行銷定義為滿足目標族群需求並獲利的科學與藝術，這一觀點在過去數十年中被廣泛認同並應用於企業實踐中。隨著數位技術的迅猛發展，企業開始借助這些技術來支援行銷活動，從而獲得競爭優勢並提高顧客滿意度。本研究採用了購物籃分析法，通過分析零售資料中的物品關聯，幫助商家理解哪些產品經常一起被購買，藉此制定存貨管理和促銷策略。我們專注探討了支持度、信賴度和提升度三個指標，並引入經驗貝葉氏方法修正提升度以提高結果的準確性。我們的研究發現，現有的促銷活動會對資料分析結果產生偏差，因此我們提出了相應的解決方案來排除這些影響。此外，我們通過後處理有效地辨別和排除偽相關規則，確保所得的關聯規則是真實且有意義的。實證研究結果顯示，利用常態分配檢驗可以有效篩選出受到促銷影響的產品組合，並且在資料稀疏的情況下結合信賴度來排除偽相關組合。另外，我們提出了一個提升結果啟發性的概念，使最後的分析結果可以帶給企業對顧客行為更深入的洞察。

This study explores how market basket analysis can be utilized to gain deeper insights into customer purchasing behavior and enhance marketing strategies. As defined by Philip Ko-tler, marketing involves identifying and fulfilling customer needs profitably. With advance-ments in digital technology, businesses increasingly leverage data to support their market-ing efforts, gaining a competitive edge and improving customer satisfaction.
Market basket analysis, a widely-used technique, reveals product associations in retail data, helping businesses understand which products are frequently purchased together. By ana-lyzing support, confidence, and lift metrics, this study refines traditional approaches, incor-porating methods to eliminate biases from promotional activities and identify spurious cor-relations. The findings demonstrate how this enhanced analysis can lead to more effective inventory management, promotional strategies, and customer insights, ultimately driving better business outcomes.

中文文獻
吳奇廷（2018）。應用機器學習於精準行銷之研究[為出版之碩士論文]。國立成功大學會計學研究所。
吳俊儀. (2021). 家樂福與Appier協力解鎖顧客品牌忠誠度 優化行銷強化電商市場. Retrieved from https://www.ctee.com.tw/news/20210714700387-431207
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