近年來，受到食安風暴的影響，消費者食安意識抬頭，使得國內有機市場蓬勃發展。一些規模小的有機商店資源有限，如何運用資訊科技篩選出其高價值顧客及挖掘潛在顧客，並針對顧客重要性予以不同的行銷策略與管理辦法，不僅可提升企業競爭優勢，更可以為企業省下許多成本。
本研究以虎尾鎮某有機商店為例，以顧客消費紀錄進行顧客價值評估以區分最有價值顧客群。本研究應用資料探勘軟體PolyAnalyst 6.5分析自2015年至2017年間2532筆顧客消費紀錄進行顧客分級。經資料探勘之集群分析與K平均演算法分群後結果如下：1. 集群分析後A級顧客消費總額占46.19%、消費頻率最高者共129位；B級顧客消費總額占32.38%、消費頻率次高者共407位；C級顧客消費總額占16.87%、頻率較低者共840位；D級顧客消費總額占4.56%、消費頻率低於3次者共1156位。2. K平均演算法分析後A級顧客消費總額占13.66%、消費頻率最高者共16位；B級顧客消費總額占20.65%、消費頻率次高者共59位；C級顧客消費總額占32.90%、頻率較低者共275位；D級顧客消費總額占32.79%、消費頻率低於3次者共2182位。
藉由兩種分群方式兩相比對後，將K平均演算法之A、B兩群定義為頂級顧客對其採用最佳的服務，C群顧客利用各種促銷方案提升其購買慾，D級顧客可運用電子商務，來增加無法到店消費之顧客之產品購買方式。

In recent years, consumers' awareness of food safety has risen, making the domestic organic market flourish. Due to the limited resources of some small-scale organic stores, how to use information technology to screen out their high-value customers and discover potential customers has become an important issue. These stores need to provide different marketing strategies and management methods for high-value customers, which not only can enhance the competitive advantage of the store, but also save the store a lot of marketing expenses.
This study takes an organic store in Huwei as an example, and conducts customer value evaluation based on customer consumption records to distinguish the most valuable customer groups. Cluster analysis and K-means analysis of data mining software PolyAnalyst 6.5 are used to classify customers based on their consumption amount and frequency. The results are as follows:
1. After cluster analysis, the numbers of customers classified in Class A, B, C, and D are 129, 407, 840, and 1156, respectively.
2. After K-means analysis, the numbers of customers classified in Class A, B, C, and D are 16, 59, 275, and 2182, respectively.

中文摘要......................................i
英文摘要......................................ii
誌謝..........................................iii
目錄..........................................iv
表目錄........................................vi
圖目錄........................................vii
第一章 緒論...................................1
1.1 研究背景..................................1
1.2 研究目的..................................2
1.3 研究範圍與限制.............................2
1.4 研究步驟..................................3
第二章 文獻探討................................5
2.1 資料探勘..................................5
2.1.1 資料探勘之介紹...........................5
2.1.2 集群分析................................12
2.1.3 K平均演算法.............................12
2.2 顧客關係管理..............................14
2.2.1 顧客關係管理之介紹.......................14
2.2.2 顧客關係管理之定義.......................15
2.2.3 顧客關係管理發展模式與執行流..............17
2.2.4 資料探勘應用於顧客關係管理................18
2.2.5 顧客價值................................20
2.2.6 顧客價值金字塔模型.......................21
2.3 台灣有機市場..............................23
2.3.1 有機農業之介紹...........................23
2.3.2 有機食品................................24
2.3.3 有機相關認證.............................24
第三章 研究方法................................27
3.1 資料探勘軟體PolyAnalyst 6.5................27
3.2 研究流程..................................28
3.3 研究資料..................................29
3.3.1 顧客消費資料庫...........................29
3.3.2 前置處理................................30
3.4 資料探勘過程...............................30
第四章 研究結果................................31
4.1 集群分析法分群結果.........................31
4.2 K平均演算法分群結果........................33
4.3 集群分析法與K平均演算法之比較...............36
第五章 結論與建議..............................38
5.1 結論......................................38
5.2 建議......................................39
參考文獻.......................................40
英文論文大綱...................................44

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