顧客是企業可以長久經營下去主要的關鍵，因此對於企業而言顧客是無形的資產，顧客的價值不只侷限於每次的交易當中帶給企業的利潤，而是未來與顧客的關係當中企業能得到的總利潤 (V Kumar & George, 2007)。現今因為大數據的崛起「精準行銷」已經不再是難事，透過數據資料庫的分析與探勘可以精準了解顧客的消費行為以了解單一顧客對於企業的價值，進而使企業的利潤極大化。
本研究將資料處理技術套用在台灣的歷史悠久的零售業當中協助之有效的管理顧客，收集、整理M公司的會員以及交易資料進行後，使用RFM模型與NES模型分析出不同的客群，將顧客分為新顧客、主力顧客與沈睡顧客，觀察顧客在不同時間的流向後，利用顧客的終身價值 (CLV) 和折扣敏感度進行沉睡顧客之喚醒策略建議，最後利用預測模型優化企業之行銷工具的使用與提出保留顧客的戰略執行方案，讓企業針對適當的顧客進行保留、降低行銷成本。
本研究以台灣綜合商品零售業作為研究對象，以學術上的理論為基礎搭配目前產業之管理情況，找出可以讓公司獲利的關鍵顧客以提供企業一套可利用的分析和運用方法並將之運用於實務當中。

Customers are essential for enterprises to have long-term operation. Therefore, customers are regarded as intangible asset. The value of customers is not limited to the profit brought in each transaction, but total profit that can get from the relationship with customers in future. (V Kumar & George, 2007) Nowadays, because of the rise of big data, “precision marketing" is no longer difficult. Through the analysis and exploration of the data database, enterprises can accurately understand every single customer's consumption behavior as to maximize the profits of enterprises.
To assist long-established company to manage customers in a more effective method, we apply data processing technology to the retail industry in Taiwan. In this research, RFM models and NES models are used to analyze profiles of members and transaction data as to further segment customers into different groups, which are new customers, main customers and sleep customers. After observing customer flow in different time, we use the customer lifetime value (CLV) and discount sensitivity to make strategy suggestions, and propose a customer retention plan. It is a plan that uses predictive models to optimize marketing tools for enterprises to retain right customers and reduce marketing costs.
In this research, we analyze practical customer data of one retail sale in non-specialized store on the basis of academic theories. Finding out the key customers who can make the company profitable, we provide analytic and operational methods which are suitable for enterprises to apply in their marketing strategies.

第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 3
第二章 文獻探討 4
第一節 顧客關係管理 4
第二節 顧客分群 7
第三節 折扣效果 9
第三章 研究方法 11
第一節 研究流程 11
第二節 研究方法 12
第四章 個案分析 15
第一節 個案背景 15
第二節 資料原型 15
第三節 基本資料分析 16
第四節 篩選變數 19
第五節 顧客分群 19
第六節 策略建議 30
第五章 結論 52
第一節 研究結論 52
第二節 研究貢獻 54
第三節 研究限制與未來發展 55

參考文獻 57

一、 文獻部分
林師模, & 陳苑欽. (2003). 多變量分析: 管理上的應用: 雙葉書廊.
林陽助, 李宜致, 林吉祥, & 林婉婷. (2009). 折扣幅度, 促銷方式與品牌知名度對消費者品牌評價及購買意願之影響—以行動電話為例. 東吳經濟商學學報 (67), 1-46.
張心馨, & 蔡獻富. (2004). 以 Data Mining 技術結合 SOM 和 K-Mean 的消費者分群方法於顧客關係管理和績效獲利性評估之實證研究. 資訊管理學報, 11(4), 161-203.
Anderson, E. W., & Mittal, V. (2000). Strengthening the satisfaction-profit chain. Journal of Service Research, 3(2), 107-120.
Berger, P. D., & Nasr, N. I. (1998). Customer lifetime value: Marketing models and applications. Journal of interactive marketing, 12(1), 17-30.
Briesch, R. A., Chintagunta, P. K., & Matzkin, R. L. (2002). Semiparametric estimation of brand choice behavior. Journal of the American Statistical Association, 97(460), 973-982.
Cheng, C.-H., & Chen, Y.-S. (2009). Classifying the segmentation of customer value via RFM model and RS theory. Expert systems with applications, 36(3), 4176-4184.
Cooil, B., Keiningham, T. L., Aksoy, L., & Hsu, M. (2007). A longitudinal analysis of customer satisfaction and share of wallet: Investigating the moderating effect of customer characteristics. Journal of marketing, 71(1), 67-83.
Cortiñas, M., Elorz, M., & Múgica, J. M. (2008). The use of loyalty-cards databases: Differences in regular price and discount sensitivity in the brand choice decision between card and non-card holders. Journal of Retailing and Consumer Services, 15(1), 52-62.
Dong, Y., Yao, Y., & Cui, T. H. (2011). When acquisition spoils retention: Direct selling vs. Delegation under CRM. Management Science, 57(7), 1288-1299.
Dwyer, F. R. (1997). Customer lifetime valuation to support marketing decision making. Journal of interactive marketing, 11(4), 6-13.
Gupta, S., Hanssens, D., Hardie, B., Kahn, W., Kumar, V., Lin, N., . . . Sriram, S. (2006). Modeling customer lifetime value. Journal of Service Research, 9(2), 139-155.
Gupta, S., Lehmann, D. R., & Stuart, J. A. (2004). Valuing customers. Journal of marketing research, 41(1), 7-18.
Hughes, A. M. (2000). Strategic database marketing: the masterplan for starting and managing a profitable, customer-based marketing program (Vol. 12): McGraw-Hill New York.
Jackson, B. (1985). Winning and Keeping Industrial Customers—The Dynamics of Customer Relationships; Lexington—Toronto 1985. Google Scholar.
Kalwani, M. U., & Yim, C. K. (1992). Consumer price and promotion expectations: An experimental study. Journal of marketing research, 90-100.
Kaplan, R. S., & Narayanan, V. (2001). Customer profitability measurement and management. Harvard Business School.
Keng, C.-J., Huang, T.-L., Zheng, L.-J., & Hsu, M. K. (2007). Modeling service encounters and customer experiential value in retailing: An empirical investigation of shopping mall customers in Taiwan. International Journal of Service Industry Management, 18(4), 349-367.
Kim, J., Suh, E., & Hwang, H. (2003). A model for evaluating the effectiveness of CRM using the balanced scorecard. Journal of interactive marketing, 17(2), 5-19.
Kotler, P. (1994). Marketing management, analysis, planning, implementation, and control, Philip Kotler: London: Prentice-Hall International.
Kotler, P., Armstrong, G., Saunders, J., & Wong, V. (1996). Principles of all Marketing: The European Edition: Prentice-Hall International, Hemel Hempstead.
Kumar, V., & George, M. (2007). Measuring and maximizing customer equity: a critical analysis. Journal of the Academy of Marketing Science, 35(2), 157-171.
Kumar, V., Lemon, K. N., & Parasuraman, A. (2006). Managing customers for value: An overview and research agenda. Journal of Service Research, 9(2), 87-94.
Lal, R., & Bell, D. E. (2003). The impact of frequent shopper programs in grocery retailing. Quantitative marketing and economics, 1(2), 179-202.
Lhoest-Snoeck, S., van Nierop, E., & Verhoef, P. C. (2014). For new customers only: A study on the effect of acquisition campaigns on a service company's existing customers' CLV. Journal of interactive marketing, 28(3), 210-224.
Mathur, M., & Kumar, S. (2013). Customer Retention Through Prioritization: Integrating Time-Dependent Context of Relationship Dynamics. Journal of International Consumer Marketing, 25(5), 332-343.
Mulhern, F. J. (1999). Customer profitability analysis: Measurement, concentration, and research directions. Journal of interactive marketing, 13(1), 25-40.
Nikumanesh, E., & Albadvi, A. (2014). Customer's life–time value using the RFM model in the banking industry: a case study. International Journal of Electronic Customer Relationship Management, 8(1-3), 15-30.
Rust, R. T., Lemon, K. N., & Zeithaml, V. A. (2004). Return on marketing: Using customer equity to focus marketing strategy. Journal of marketing, 68(1), 109-127.
Swift, R. S. (2001). Accelerating customer relationships: Using CRM and relationship technologies: Prentice Hall Professional.
Wu, J., & Lin, Z. (2005). Research on customer segmentation model by clustering. Paper presented at the Proceedings of the 7th international conference on Electronic commerce.
Yin, R. K. (2013). Case study research: Design and methods: Sage publications.

二、其他部分
陳傑豪(2015)，大數據玩行銷。
傳統零售商不轉型將走上死路！看美國 Wal-Mart 如何逆境重生 https://buzzorange.com/techorange/2013/04/19/big-data-walmart/
在你下單前就出貨！Amazon 用大數據鞏固電商龍頭https://transbiz.com.tw/amazon-big-data/