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研究生:劉蕙
研究生(外文):Hui Liu
論文名稱:以群集分析與序列型樣輔助資料庫行銷策略
論文名稱(外文):Applying Clustering Analysis and Sequential Pattern to Assist Database Marketing Strategy
指導教授:劉俞志劉俞志引用關係
學位類別:碩士
校院名稱:元智大學
系所名稱:資訊管理學系
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2006
畢業學年度:94
語文別:中文
論文頁數:53
中文關鍵詞:資料庫行銷行銷策略顧客忠誠度資料探勘
外文關鍵詞:Database marketingMarketing strategyCustomer loyaltyData Mining
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企業成功的關鍵點在於瞭解顧客的需求並迅速回應,資料庫行銷就是分析資料庫中客戶消費資料所潛藏的訊息,以製定行銷策略、發展行銷活動。本文以某公司為例,首先根據其業務與資料特質,提出資料庫行銷策略發展之流程與步驟,並提出資料庫行銷模型架構,此架構以混合群集分析與序列型樣分析法分別進行客戶分群與產品分類。除了提供顧客忠誠度之計算方式,探討價格促銷活動對於顧客的影響,更進一步藉由實驗結果歸納分析結論,作為行銷策略之參考。期藉由區隔化分析,對於不同群集研擬不同行銷策略,加強顧客忠誠度。
Enterprise success depends on the ability to efficiently understand and timely response to customer consumption behavior. Database marketing is to analyze customer consumption messages obtained from the customer transaction database, and development of marketing strategies and related activities. This work comprises a case study of Company Z. Based on the firm business and data characteristics, this work first provides the process and steps involved in devising database marketing strategies, as well as the architecture of the database marketing model. The architecture uses a mixture of clustering analysis and sequential pattern to process customer segmentation and product categorization, respectively. This work not only presents a measurement of customer loyalty and studies how price and promotion activities affect the customer; but also analyses the experimental results as reference of advanced marketing strategy. We believe that segmentation analysis and using different marketing strategies based on clusters can improve customer loyalty.
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一、 緒論................................................................................................................1
1.1 研究背景與動機............................................................................................1
1.2 研究目的........................................................................................................2
1.3 研究範圍與限制............................................................................................2
1.4 研究流程........................................................................................................3
二、 文獻探討........................................................................................................4
2.1 資料探勘概述................................................................................................4
2.2 資料庫行銷....................................................................................................5
2.3 群集分析........................................................................................................9
2.4 序列型樣分析..............................................................................................14
三、 研究方法......................................................................................................16
3.1 研究架構......................................................................................................16
3.2 資料庫行銷策略發展之流程步驟..............................................................18
3.3 資料來源與範圍..........................................................................................19
3.4 個案業務現況..............................................................................................21
3.5 顧客價值計算之方法..................................................................................24
四、 實證分析......................................................................................................27
4.1 原始資料萃取與轉換..................................................................................27
4.2 顧客分群......................................................................................................28
4.3 群集結果之驗證..........................................................................................38
4.4 序列型樣分析..............................................................................................41
4.5 結果分析總結..............................................................................................43
五、 結論與未來研究..........................................................................................49
參考文獻......................................................................................................................51
一、英文部份
1.Fayyad, U. (1996), “The KDD process for extracting useful knowledge from volumes of data,” Communications of the ACM, 39, Iss.11, pp. 27-34.
2.Goodman, John (1992), “Leveraging the Customer Database to Your Competitive Advantage,” Direct Marketing, pp.26-27.
3.Hughes, Arthur M. (1994), Strategic Database Marketing, Chicago: Probus Publishing.
4.Hughes, A. M. (2001), “Strategic Database Marketing,” McGraw-Hill Enterprises Inc.
5.J. MacQueen (1967), “Some methods for classification and analysis of multivariate observations,” In Proc. of the 5th Berkeley Symp. On Mathematical Statistics and Probability, pp. 281-297.
6.Kleissner, C. (1998), “Data Mining for the Enterprise,” Proceedings of the 31st Annual Hawaii International Conference On System Sciences, pp. 295-304.
7.Mehmed Kantardzic (2002), “ Data Mining: Concepts, Models, Methods, and Algorithms,” Wiley Publishing.
8.Michael J.A. Berry and Gordon S. Linoff (2004), “ Data Mining Techniques For Marketing, Sales, and Customer Relationship Management,” Wiley Publishing.
9.PANG-NING TAN, MICHAEL STEINBACH and VIPIN KUMAR (2006), “Introduction to Data Mining,” Pearson Education Publishing.
10.Roberts, M. L. (1992), “Expanding the Role of the Direct Marketing Database,” Journal of Direct Marketing, 2(2), 51-60.
11.Shaw, R. and M. Stone (1990), “Competitive Superiority Through Database Marketing,” Long Range Planning, 21(5), 24-40.
12.S. L. Lauritzen (1995), “The EM algorithm for graphical association models with missing data,” Computational Statistics and Data Analysis, 19:191-201.
13.Wong, K.W., Fung, C.C., Tamas, G. and Douglas, C. (2004), “Intelligent data mining and personalization for Customer Relationship Management,” ICARCV 2004 – Proceedings of the 8th International Conference on Control, Automation, Robotics and Vision, pp. 1796-1801.
14.ZhaoHui Tang and Jamie MacLennan (2005), “Data Mining with SQL Server 2005,” Wiley Publishing.
二、中文部份
15.洪嘉蓉,2004,服務品質、滿意度與忠誠度關係之研究─以中華電信公司ADSL顧客為例,私立大葉大學資訊管理學系碩士論文。
16.陳國聖,2004,資料探勘於外籍勞工逃逸管理之研究,南台科技大學資訊管理系碩士論文。
17.紀家維,2003,應用脊迴歸分析於資料採礦預測系統之研究,輔仁大學應用統計學研究所碩士論文。
18.楊清潭,2003,應用資料探勘技術於顧客價值分析之研究,東吳大學商學院資訊科學係碩士論文。
19.林盈源,2003,決策樹在資料庫行銷決策之應用,國立成功大學碩士論文。
20.張志揚,2003,挖掘具不同時間單位之時間序列型樣,國立臺灣科技大學資訊管理系碩士論文。
21.林玫瑄,2002,消費者異質性與時序動態互動模型之研究─以資料庫行銷之顧客價值分析為例,國立臺灣大學國際企業學研究所碩士論文。
22.游政憲,2000,網路瀏覽行為線上分析機制之研究,國立臺北科技大學商業自動化與管理研究所碩士論文。

23.ARC遠擎管理顧問公司審譯,Ronald S. Swift著,深化顧客關係管理:運用<關係管理科技>建構CRM系統,初版,麗勤管理顧問,台北,2005。
24.曾憲雄、蔡秀滿、蘇東興、曾秋蓉、王慶堯著,資料探勘,初版,旗標,台北,2005。
25.吳國禎譯,荒川圭基著,行銷管理電腦化之戰略與戰術,經濟部國貿局,台北,1992。
26.張倩茜譯,Arthur M. Hughes著,資料庫行銷實用策略,初版,麥格羅希爾,台北,2001。
三、網站部分
27.黃健峻,“EASY Database Marketing”, http://www.easydm.com/
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