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題名 消費者消費行為研究-以生活工場為例
作者 吳林興
貢獻者 周宣光<br>陳春龍
吳林興
關鍵詞 資料庫行銷
資料探勘
顧客忠誠
顧客保留率
顧客終身價值
RFM
Database Marketing
Data Mining
Customer Loyalty
Customer Retention
CLV
日期 2004
上傳時間 18-Sep-2009 17:40:20 (UTC+8)
摘要 傳統上透過行銷研究,如設計問卷透過市場調查、問卷調查等等活動來取得消費者資訊,但在資訊化的時代,利用POS系統所收集到且存在於資料庫中的銷售資料,忠實紀錄所有消費者的消費行為,其中亦隱含著消費者對品牌忠誠度、產品偏好性、價格敏感度等等消費行為。藉由著這些基礎,可進一步探索顧客輪廓(Customer Profile)、顧客忠誠度(Customer Loyalty)及顧客保留率(Customer Retention),同時預測未來各種行銷活動的可能結果;進而擴大其應用範圍,進行新客源、新產品的開發工作。本研究以資料庫行銷、資料探勘等等理論基礎、統計學技術等等方法,以居家用品業為例,進行資料庫行銷(Database Marketing)的實證工作。實證資料來源為「生活工場」連鎖居家用品店現有之基本資料。並以此資料為基礎,探究顧客購買的消費特性,並以其類別、系列分析其產品關聯性審視其產品組合類別。另外一方面,利用資料庫中的銷售資料及VIP基本資料,以RFM(Recency, Frequency, Monetary)顧客分群方法,分離出不同的顧客族群,並在每一個族群中作交差比對(Cross-Checking),探究各族群的顧客輪廓及其消費特徵。利用門市基本資料、銷售明細資料等,分析出地域消費特徵。最後,再以金卡、貴賓卡、生活卡三大族群的消費特性及與RFM族群之交差比對,並計算出不同卡別的顧客終身價值(Customer Lifetime Value, CLV),以期提供「生活工場」與國內連鎖零售體系之產業,未來在對顧客關係經營之參考。
In tradition, marketing research acquires the information of consumers through questionnaire design, marketing survey, etc. However, in the information age, the POS system is capable to collect the sales information and record them in the data base. It precisely records the consumer behaviors which include the brand loyalty, product preference and price sensitivity. Based on the information, it could more deeply discover the customer profile, customer loyalty and customer retention. It can also forecast the possibility of marketing event for the future and expand to other applications such as new customer creation and new product development.
     
     This research, based on the theory of database marketing, data mining methodology and statistic technology, substantiates database marketing in a case study of a home center. Actual data are provided by Working House, a home center chain store. Those data bases establish a foundation of exploring the consumer purchasing characteristic, analyzing series of product classifications and examining the product association and combination. On the other hand, based on the sales information and VIP database, RFM (Recency, Frequency, and Monetary) is utilized to cluster customer segments and research the customer profiling and shopping characteristic by cross checking each shopping group. Data from store locations and sales information are thus employed to explore the geographic characteristic of shoppers.
     
     In conclusion, based on the usage data of Gold Card, VIP Card, and Working House Card and cross checks with RFM clustering groups, the Customer Lifetime Value (CLV) of each card will be calculated and accumulated to provide Working House and other retailers the reference for managing customer relationship in the future.
第一章 緒論 1
     第一節 研究背景 1
     第二節 研究動機 3
     第三節 研究目的 7
     第四節 研究對象與範圍 8
     第五節 研究架構 9
     
     第二章 文獻探討 11
     第一節 資料庫行銷 13
     第二節 顧客忠誠度 18
     第三節 顧客保留率 24
     第四節 顧客終身價 27
     
     第三章 資料探勘方法 31
     第一節 資料探勘 31
     壹 資料探勘的定義 31
     貳 資料探勘的流程 32
     參 資料探勘的任務 34
     肆 資料探勘的技術與方法 35
     第二節 RFM模型 38
     壹 RFM的定義 38
     貳 RFM群集法 41
     
     第四章 生活工場個案研究 45
     第一節 個案公司背景 45
     壹 公司簡介 45
     貳 公司組織 47
     第二節 個案公司資料實證 48
     壹 資料來源 48
     貳 資料清理 49
     參 資料實證 51
     
     第五章 結論與建議 72
     第一節 研究結果與結論 72
     第二節 研究限制 73
     第三節 後續研究與建議 73
     
     
     參考文獻
     英文部份 75
     中文部份 80
     網路部份 81
     
     附錄
     附錄一:大類分類 82
     附錄二:小類分類 82
     附錄三:各縣市店年營業額╱消費次數 84
     附錄四:整體銷售前十名產品 85
     附錄五:會員銷售前十名產品 85
參考文獻 英文部份:
1.Berger, Paul D. and Nada I. Nasr, "Customer Lifetime Value: Marketing Model and Application", Journal of Interactive Marketing, Vol.12, 1998, pp 17-30.
2.Berry, M.J.A. and G. Linoff, Data Mining Techniques: For Marketing, Sales, and Customer Support, New York, John Wiley and Sons, 1997.
3.Blattberg, R. A. and J. Deighton, "Manage Marketing by the Customer Equity Test", Harvard Business Review, 1996, pp 136-144.
4.Blattberg, Robert C., and Gary Getz and Jacquelyn S. Thomas, Customer Equity - Building and Managing Relationships As Valuable Assets, Harvard Business School Press, 2001, pp 67-75.
5.Bolton, Ruth N., "A Dynamic Model of the Duration of the Customer`s Relationship with a Continuous Service Provider : The Role of Satisfaction", Marketing Science, 1998, 17 (1), pp 45-65.
6.Brachman, R. J, Khabaza, T., Kloesgen, W., Piatestsky-Shapriro, G. and Simoudis, E, "Mining business databases", Communication of the ACM, November, Vol. 39 No. 11, 1996, pp 42-48.
7.Cabena, P., Discovering Data Mining: From Concept to Implementation, Upper Saddle River, New York, Prentice Hall, 1998.
8.Cespedes, Frank V. and H. Jeff Smith, "Database Marketing : New Rules for Policy and Practice", Sloan Management Review, Summer 1993, pp 7-22.
9.David Shepard Associates, Inc., The New Direct Marketing: How to Implement a Profit-Driven Database Marketing Strategy, New York, Irwin, 1995, pp 258.
10.Duffy, Dennis L., "Customer loyalty strategies", Journal of Consumer Marketing, Vol. 15 No. 5, 1998, pp435-448.
11.Dwyer, F. Robert, "Customer Lifetime Valuation to Support Marketing Decision Making", Journal of Direct Marketing, Vol. 3, 1989, pp 8-15.
12.Fayyad, U., G. Piatetsky-Shapriro and P. Smyth, "The KDD process for Extracting Useful Knowledge from Volumes of Data", Communication of ACM, Vol. 39, Iss.11, Nov. 1996, pp 27-34.
13.Fayyad, U., "Data mining and knowledge discovery: Making sense out of data", IEEE Expert, Vol. 11, Iss. 5, Oct. 1996, pp 20-25.
14.Fayyad, U., G. Piatetsky-Shapriro, P. Smyth, and Uthurusamy, "Advance in Knowledge Discovery and Data Mining", AAAI/MIT Press, 1996.
15.Fu, Y, "Data Mining Task: Techniques and Application", IEEE Potentials Press, 1997.
16.Geller, Lois, "Customer Retention Being With The Basics", Direct Marketing, September, 1997, 60, 5, pp 58-62.
17.Gronholdt, Lars, Anne Martensen and Kai Kristensen, "The Relationship Between Customer Satisfaction and Loyalty : Cross-Industry Differences", Total Quality Management, 2000, Vol. 11 NOS. 4/5&6, S509-S514.
18.Grupe, F.H. and M. M. Owrang, "Database Mining Discovering New Knowledge and Cooperative Advantage", Information System Management, 1995.
19.Han. J. and M. Kamber, Data Mining: Concepts and Techniques, San Francisco, C.A, Morgan Kaufmann, 2000.
20.Hughes, Arthur Middleton, The Complete Database Marketing, McGraw Hill, 1994.
21.Jackson, Barbara Bund, Winning and Keeping Industrial Customers, Lexington, MA: Lexington Books, 1985.
22.Jacoby, Jacob, and Robert Chestnut, Brand Loyalty, New York: John Wiely & Sons, 1978, pp 22.
23.Kahan Ron, "Using database marketing techniques to enhance your one-to-one marketing initiatives", Journal of Consumer Marketing, Vol. 15 No. 5, 1998, pp 491-493.
24.Keane Timothy J. and Paul Wang, "Application for the Lifetime Value Model in Modern Newspaper Publishing", Journal of Direct Marketing, Vol. 9, 1995, pp 59-66.
25.Kolter, P. and Armstrong G., Principle of Marketing, 7th Ed., Englewood Gliffs, NJ: Prentice-Hall, 1996.
26.Kuhl, Julius and Jurgen Beckmann, "Historical Perspective in the Study of Action Control" in Action Control: From Cognition to Behavior, Julius Kuhl and Jurgen Beckmann, eds, Berlin: 1985, Spring-Verlage, pp 89-100.
27.Marcus, Claudio, "A practical yet meaningful approach to customer segmentation", Journal of Consumer Marketing, Vol. 15, No. 5, 1998, pp 494-504.
28.Massnick, F, The Customer is CEO: How to Measure What Your Customer Want and Make Sure They Get It, Amacom, 1997.
29.McClymont, Hoda and Graham Jocumsen, "How to implement marketing strategies using database approaches", Journal of Database Marketing & Customer Strategy Management, Vol. 11, No. 2, Dec. 2003, pp 135-148.
30.Mulhern, Francis J., "Customer Profitability Analysis: Measurement, Concentration, and Research Direction", Journal of Interactive Marketing, Vol. 13, 1999, pp 25-40.
31.Oliver, Richard L., Satisfaction : A Behavior Perspective On the Consumer, New York: Irwin/McGraw-Hill, 1997, pp 392.
32.Oliver, Richard L, "Whence Consumer Loyalty?", Journal of Marketing, Vol. 63 (Special Issue), 1999, pp 33-44.
33.Payne, Adrian and John Richard, Relationship Marketing, Customer Retention and Service Firm Profitability, Paper presented at the First Relationship Workshop, Marash University, Melbourne, 1993.
34.Peppers, Don and Martha Rogers, The One to One Future : Building Relationships One Customer at a Time, Currency Doubleday, 1993, pp 52.
35.Petrison, Lisa A., and Robert C. Blattberg, and Paul Wang, "Database Marketing - Past, Present, and Future", Journal of Direct Marketing, Volume 11, Number 4 Fall, 1997, pp 109-125.
36.Reichheld, Fredrick F. and W. Earl Sasser, "Zero Defections: Quality Comes to Services", Harvard Business Review, September-October, 1990, pp 105-111.
37.Reichheld, Frederick F, The Loyalty Effect - The Hidden Force Behind Growth, Profits, and Lasting Value, Bain & Company, Inc., Harvard Business School Press, 1996, pp 36-63.
38.Reicheld, Frederick F., "Learning from Customer Defections", Harvard Business Review, 1996, March-April, pp 56-69.
39.Roberts, Mary Lou, "Expanding the Role of Direct Marketing Database", Journal of Direct Marketing, Volume 11, Number 4 Fall, 1997, pp 26-35.
40.Rud, Olivia Parr, Data Mining Cookbook: Modeling Data for Marketing, Risk, and Customer Relationship Management, John Wiley and Sons, Inc., 2001, pp 283-284.
41.Rust, Roland and Anthony Zahorik, "Customer Satisfaction, Customer Retention, and Market Share", Journal of Retailing, 69 (Summer), 1993, pp 193-215.
42.SaferPak Limited Company, "Customer loyalty : how to measure it, understand it and use it to drive business success", SaferPak Limited Company, 2004, Nov.
43.Schijns, Jos M. C. and Gaby J. Schroder, "Segment Selection by Relationship Strength", Journal of Direct Marketing, Vol. 10, 1996, pp69-79.
44.Shani, David and Sujana Chalasani, "Exploiting Using Relationship Marketing", The Journal of Consumer Marketing, Vol. 9 No. 3, Summer, 1992, pp 33-42.
45.Shankar, Venkatesh and Amy K. Smith and Arvind Rangaswamy, "Customer Satisfaction and Loyalty in Online and Offline Environment", International Journal of Research in Marketing, Vol. 20, Issue: 2, June 2003, pp 153-175.
46.Tao, Yu-Hui and Chu-Chen Rosa Yeh, "Simple database marketing tool in customer analysis and retention", International Journal of Information Management, Vol. 23, 2003, pp 291-301.
47.Wang, Paul, and Ted Splegel, "Database Marketing and Its Measurements of Success", Journal of Direct Marketing, Vol. 8, No. 2, Spring, 1994, pp 74-81.
48.Wyner, Gordon A, "Customer Valuation: Linking Behavior and Economics", Marketing Research, Vol. 8, No. 2, Summer 1996, pp 36-38.
中文部份:
1.李仁芳,「7-ELEVEN統一超商縱橫台灣-厚基組織論」,遠流,1995,第9-79頁。
2.周春芳,「流通業現代化與電子商務」,五南,2000,第8-14頁。
3.Jiawci Han和Micheline Kamber原著,曾龍譯,「資料探礦概念與技術」,Elsevier (Singapore)與維科,2003,第2-29頁。
4.遠擎管理顧問公司,「顧客關係管理深度解析」,遠擎管理顧問,2001,第4頁。
5.Michael J.A. Berry和Gordon S. Linoff原著,彭文正譯,「資料採礦-顧客關係管理暨電子行銷之應用,數博網,2001,第20-448頁。
6.Arthur Middleton Hughes原著,張倩茜議,「資料庫行銷實用策略」,美商麥格羅•希爾,2001,第70-182頁。
7.王梅,「生活在工場-鄧學中的創意魔法」,天下文化,2002,第37-38頁。
網站部份:
1.http://datas.ncl.edu.tw/theabs/1/,全國博碩士論文摘要檢索系統,搜尋時間:2005/1/4, 17:40
2.http://www.7-11.com.tw/,統一超商7-ELEVEN資訊網,搜尋時間:2005/1/11, 14:15
3.http://www.wellcome.com.tw/,頂好Wellcome超市資訊網,搜尋時間:2005/1/11, 14:21
4.http://www.sogo.com.tw/,太平洋SOGO資訊網,搜尋時間:2005/1/11, 14:30
5.http://www.saferpak.com,英國SafePak顧問公司,搜尋時間:2005/1/11, 14:09
6.http://www.dbmarketing.com,Database Marketing Institute, USA,搜尋時間:2005/1/11, 14:22
7.http://www.workinghouse.com.tw,生活工場資訊網,搜尋時間:2005/1/11, 14:30
8.http://jenda.lib.nccu.edu.tw,國立政治大學圖書館遠距圖書服務系統,搜尋時間:2005/1/4, 17:45
9.http://www.amazon.com,亞馬遜網路書店全球資訊網,搜尋時間:2005/1/4, 17:55
10.http://www.mcgraw-hill.com.tw,麥格羅•希爾國際出版公司,搜尋時間:2005/1/4, 18:05
11.http://www.ncl.edu.tw,國家圖書館全球資訊網,搜尋時間:2005/1/4, 18:18
12.http://infolib.ncl.edu.tw,國家圖書館附設資訊圖書館資訊網,搜尋時間:2005/1/4, 18:22
13.http://www.books.com.tw,博客來網路書店資訊網,搜尋時間:2004/1/4, 18:28
14.http://www.superpoll.net,數博網,搜尋時間:2005/1/11, 14:35
描述 碩士
國立政治大學
經營管理碩士學程(EMBA)
90932616
93
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0090932616
資料類型 thesis
dc.contributor.advisor 周宣光<br>陳春龍zh_TW
dc.contributor.author (Authors) 吳林興zh_TW
dc.creator (作者) 吳林興zh_TW
dc.date (日期) 2004en_US
dc.date.accessioned 18-Sep-2009 17:40:20 (UTC+8)-
dc.date.available 18-Sep-2009 17:40:20 (UTC+8)-
dc.date.issued (上傳時間) 18-Sep-2009 17:40:20 (UTC+8)-
dc.identifier (Other Identifiers) G0090932616en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/36240-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 經營管理碩士學程(EMBA)zh_TW
dc.description (描述) 90932616zh_TW
dc.description (描述) 93zh_TW
dc.description.abstract (摘要) 傳統上透過行銷研究,如設計問卷透過市場調查、問卷調查等等活動來取得消費者資訊,但在資訊化的時代,利用POS系統所收集到且存在於資料庫中的銷售資料,忠實紀錄所有消費者的消費行為,其中亦隱含著消費者對品牌忠誠度、產品偏好性、價格敏感度等等消費行為。藉由著這些基礎,可進一步探索顧客輪廓(Customer Profile)、顧客忠誠度(Customer Loyalty)及顧客保留率(Customer Retention),同時預測未來各種行銷活動的可能結果;進而擴大其應用範圍,進行新客源、新產品的開發工作。本研究以資料庫行銷、資料探勘等等理論基礎、統計學技術等等方法,以居家用品業為例,進行資料庫行銷(Database Marketing)的實證工作。實證資料來源為「生活工場」連鎖居家用品店現有之基本資料。並以此資料為基礎,探究顧客購買的消費特性,並以其類別、系列分析其產品關聯性審視其產品組合類別。另外一方面,利用資料庫中的銷售資料及VIP基本資料,以RFM(Recency, Frequency, Monetary)顧客分群方法,分離出不同的顧客族群,並在每一個族群中作交差比對(Cross-Checking),探究各族群的顧客輪廓及其消費特徵。利用門市基本資料、銷售明細資料等,分析出地域消費特徵。最後,再以金卡、貴賓卡、生活卡三大族群的消費特性及與RFM族群之交差比對,並計算出不同卡別的顧客終身價值(Customer Lifetime Value, CLV),以期提供「生活工場」與國內連鎖零售體系之產業,未來在對顧客關係經營之參考。zh_TW
dc.description.abstract (摘要) In tradition, marketing research acquires the information of consumers through questionnaire design, marketing survey, etc. However, in the information age, the POS system is capable to collect the sales information and record them in the data base. It precisely records the consumer behaviors which include the brand loyalty, product preference and price sensitivity. Based on the information, it could more deeply discover the customer profile, customer loyalty and customer retention. It can also forecast the possibility of marketing event for the future and expand to other applications such as new customer creation and new product development.
     
     This research, based on the theory of database marketing, data mining methodology and statistic technology, substantiates database marketing in a case study of a home center. Actual data are provided by Working House, a home center chain store. Those data bases establish a foundation of exploring the consumer purchasing characteristic, analyzing series of product classifications and examining the product association and combination. On the other hand, based on the sales information and VIP database, RFM (Recency, Frequency, and Monetary) is utilized to cluster customer segments and research the customer profiling and shopping characteristic by cross checking each shopping group. Data from store locations and sales information are thus employed to explore the geographic characteristic of shoppers.
     
     In conclusion, based on the usage data of Gold Card, VIP Card, and Working House Card and cross checks with RFM clustering groups, the Customer Lifetime Value (CLV) of each card will be calculated and accumulated to provide Working House and other retailers the reference for managing customer relationship in the future.
en_US
dc.description.abstract (摘要) 第一章 緒論 1
     第一節 研究背景 1
     第二節 研究動機 3
     第三節 研究目的 7
     第四節 研究對象與範圍 8
     第五節 研究架構 9
     
     第二章 文獻探討 11
     第一節 資料庫行銷 13
     第二節 顧客忠誠度 18
     第三節 顧客保留率 24
     第四節 顧客終身價 27
     
     第三章 資料探勘方法 31
     第一節 資料探勘 31
     壹 資料探勘的定義 31
     貳 資料探勘的流程 32
     參 資料探勘的任務 34
     肆 資料探勘的技術與方法 35
     第二節 RFM模型 38
     壹 RFM的定義 38
     貳 RFM群集法 41
     
     第四章 生活工場個案研究 45
     第一節 個案公司背景 45
     壹 公司簡介 45
     貳 公司組織 47
     第二節 個案公司資料實證 48
     壹 資料來源 48
     貳 資料清理 49
     參 資料實證 51
     
     第五章 結論與建議 72
     第一節 研究結果與結論 72
     第二節 研究限制 73
     第三節 後續研究與建議 73
     
     
     參考文獻
     英文部份 75
     中文部份 80
     網路部份 81
     
     附錄
     附錄一:大類分類 82
     附錄二:小類分類 82
     附錄三:各縣市店年營業額╱消費次數 84
     附錄四:整體銷售前十名產品 85
     附錄五:會員銷售前十名產品 85
-
dc.description.tableofcontents 第一章 緒論 1
     第一節 研究背景 1
     第二節 研究動機 3
     第三節 研究目的 7
     第四節 研究對象與範圍 8
     第五節 研究架構 9
     
     第二章 文獻探討 11
     第一節 資料庫行銷 13
     第二節 顧客忠誠度 18
     第三節 顧客保留率 24
     第四節 顧客終身價 27
     
     第三章 資料探勘方法 31
     第一節 資料探勘 31
     壹 資料探勘的定義 31
     貳 資料探勘的流程 32
     參 資料探勘的任務 34
     肆 資料探勘的技術與方法 35
     第二節 RFM模型 38
     壹 RFM的定義 38
     貳 RFM群集法 41
     
     第四章 生活工場個案研究 45
     第一節 個案公司背景 45
     壹 公司簡介 45
     貳 公司組織 47
     第二節 個案公司資料實證 48
     壹 資料來源 48
     貳 資料清理 49
     參 資料實證 51
     
     第五章 結論與建議 72
     第一節 研究結果與結論 72
     第二節 研究限制 73
     第三節 後續研究與建議 73
     
     
     參考文獻
     英文部份 75
     中文部份 80
     網路部份 81
     
     附錄
     附錄一:大類分類 82
     附錄二:小類分類 82
     附錄三:各縣市店年營業額╱消費次數 84
     附錄四:整體銷售前十名產品 85
     附錄五:會員銷售前十名產品 85
zh_TW
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0090932616en_US
dc.subject (關鍵詞) 資料庫行銷zh_TW
dc.subject (關鍵詞) 資料探勘zh_TW
dc.subject (關鍵詞) 顧客忠誠zh_TW
dc.subject (關鍵詞) 顧客保留率zh_TW
dc.subject (關鍵詞) 顧客終身價值zh_TW
dc.subject (關鍵詞) RFMen_US
dc.subject (關鍵詞) Database Marketingen_US
dc.subject (關鍵詞) Data Miningen_US
dc.subject (關鍵詞) Customer Loyaltyen_US
dc.subject (關鍵詞) Customer Retentionen_US
dc.subject (關鍵詞) CLVen_US
dc.title (題名) 消費者消費行為研究-以生活工場為例zh_TW
dc.type (資料類型) thesisen
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