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博碩士論文 etd-0823107-153617 詳細資訊
Title page for etd-0823107-153617
論文名稱
Title
以會員特徵、搜尋行為與購買紀錄探討網路行銷活動-以S公司為例
none
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
76
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2007-06-27
繳交日期
Date of Submission
2007-08-23
關鍵字
Keywords
主成分分析、分群、市場區隔、網路行銷、搜尋行為
Searching Behaviors, E-Marketing, Market Segmentation, Clustering, PCA
統計
Statistics
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中文摘要
由於資訊科技與網際網路的蓬勃發展,相較於過去行銷人員常只能搜集到銷售結果資料,現今網際網路的成熟環境與完整的資料記錄更能深入了解顧客瀏覽點閱的搜尋行為。而這些資料的產生相較於以往也呈現大幅度的成長。在電腦硬體的進步下,我們已經有能力儲存這些大量的資料,但這些關於購買決策過程的資料在未經處理與分析的情況下,決策者往往不能有效的瞭解其所隱含的資訊。

本研究以某3C零售連鎖商店作為實證研究對象,並認為消費者對於產品的需求或接受度,事實上已反映在其過去對於產品的消費選擇與搜尋行為當中,若搜尋行為與過去消費紀錄中存在著某種關係能協助企業找出最適合消費者需求之網路行銷資訊,應能有效提升網路行銷回應率,對於行銷決策應有莫大的助益。因此運用上述觀念提出整合資料分析技術的會員分群模式替S公司的網路行銷活動進行會員分群以作為網路行銷區隔,改善現有的行銷溝通並深具實務運用的價值。

過去區隔目標顧客之研究中,經常以人口統計區隔化、地理性區隔化或社會經濟區隔市場,但是協助實體兼點選(brick-and-click)之企業進行網路行銷顧客購買基礎行為的區隔,卻未有適合的分群模式。本研究主要以顧客行為區隔作為研究重心,利用購買者對網路的使用及反應為基礎,先以主成分分析萃取出行為變數,再運用兩階段分群法區分成不同的群體,透過本研究所提出之探索性分群模式,將會員集成數個群內同質、群間異質之生活型態群,亦即是一種自然形成的市場區隔,協助企業找出在網路上經營哪些特定產品,區隔產品;亦或是協助實體兼點選之企業區隔會員、區隔網站服務使用權限,而不再漫無目的在網路上經營商品與會員,採取適當的網路行銷溝通決策。
Abstract
Due to the development of Information Technology and World Wide Web, now sales can understand more about customer's browsing behaviors through the World Wide Web. Compared with now, sales could only get the sale data in the past. There is a huge grown of these data availability compared with the past. As the advance of computer hardware, we have more ability to store these data. However, with these data of buyers' making decision process not being analyzed, decision makers often could not understand the hidden information effectively.

The 3C retail chain stores had been selected as a case study for this research. We thought that consumer's need and acceptance toward products had already been reflected in the past consuming choices and searching behavior records. If we can find out the correlation between the searching behaviors and actual consuming records, this will assist business obtain the most appropriate marketing information on the web and increase response effectively. This will be tremendously profitable for marketing decision making. Using above theory, we suggest that data integration analysis model among members is applied to distinguish the marking segmentation for website promotion of company A. We hope that the model will improve current marketing communication and provide the practice value.

In the past, we normally apply demographic statistics, geographical distribution or social economy to segment consumers for the research about divining target customers. However, there has been no appropriate segmentation model to assist business of actual brick-and-click to segmentation on the basic behavior of the customer purchase for internet marketing promotions yet.

The consumer's behaviors had been applied as segmentation and the buyer's usage and response toward website had been utilized as foundation for this research. Principal components analysis had been applied to extract behavior variable; then Two-Stage Classification Method had applied to divide members into different groups. We divide members into life style groups of the one with similar data points and the one with different data points by the exploratory segmentation model for this research. This will be a nature formation of market segmentation to assist business to pin point what products to be sold on the web and how to differentiate the products. As well as assist business to segment member effectively, distinguish area website service and usage limitation. Business will no longer shoot blind for marketing to members and will be able to make the proper e-marketing communication decision.
目次 Table of Contents
致 謝 詞 ii
中 文 摘 要 iii
中 文 摘 要 iv
Abstract v
目錄 vii
表目錄 x
圖目錄 xii
第ㄧ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 4
第四節 研究對象與範圍 5
第五節 研究步驟與流程 5
第二章 相關理論與文獻探討 7
第一節 市場區隔與目標行銷 7
第二節 顧客關係管理 14
第三節 線上搜尋行為 17
第四節 網路行銷與顧客分群相關文獻探討 20
第五節 多變量統計分析 23
第三章 研究方法 27
第一節 個案公司介紹 28
第二節 研究設計 29
第三節 研究變數及操作性定義 30
第四節 資料前置處理 32
第五節 資料分析方法 34
第四章 實證分析 38
第一節 敘述性統計資料 38
第二節 資料前置處理 43
第三節 集群分析 47
第五章 結論與建議 56
第一節 研究結論 56
第二節 研究意函 58
第三節 研究限制及後續研究建議 59
參考文獻 60
參考文獻 References
中文部份

1.方文昌審訂,J. Strauss and R. Frost 著,網路行銷 E-Marketing,第二版,智勝文化發行,2003。
2.方世榮譯,Kotler著,行銷管理學,十一版,東華書局,2003。
3.文心屏,網路新世代圖像,網路通訊,第48 期,1995。
4.王美慧、郭怡君,運用線性結構關係模式探討百貨公司之顧客忠誠度,中華民國第10屆全國品質管理研討會論文集,2004。
5.丘美珍,經理人月刊,巨思文化,22(9),2006。
6.江素貞、張佑瑋,應用資料探勘進行顧客關係管理之研究-以台灣汽車電子業為例,2006電子商務與數位生活研討會論文集,2006。
7.李章偉,資料庫行銷之顧客價值分析:以3C流通業為例,國立台灣大學國際企業研究所碩士論文,2001。
8.周文賢,多變量統計分析:SAS/STAT使用方法,初版,智勝書局,2002。
9.邱進福,3C零售連鎖通路之關係行銷研究,世新大學傳播研究所碩士論文,2003。
10.季延平譯,W. Hanson 著,網際網路行銷 Internet Marketing,初版,華泰文化發行,2000。
11.林俊毅,網路行銷的現況與迷思,0 與1Byte 科技雜誌,1997。
12.林師模、陳苑欽,多變量分析:管理上的應用,初版,雙葉書郎,2003。
13.林東清,資訊管理,初版,2002。
14.何志義,消費者對促銷活動態度之研究,國立政治大學企業管理研究所碩士論文,1989。
15.邱宏彬、蘇建源,一個可彈性支援顧客關係管理與資料庫行銷之模糊RFM MODEL,電子商務學報,6(2),149-174。
16.吳明隆,SPSS統計應用實務,台北:松崗電腦圖書資料。
17.陳思瀚、羅淑娟,以自我組織映射圖神經網路為基底之兩階層分群方法分析RFM變數,2006電子商務與數位生活研討會論文集,2006。
18.陳順宇,多變量分析,四版,華泰書局,2005。
19.黃俊英,行銷學,華泰書局,2002。
20.黃俊英,行銷學的世界,第三版,天下文化出版,2005。
21.梁定澎主編,電子商務理論與實務,二版,華泰書局,2002。
22.張百棧、蔡介元,應用資料挖掘於顧客關係管理之研究-以化妝品業為例,中華民國工業工程協會期刊,第19期,2002,p.45-59。
23.張雅幀,3C零售連鎖通路之資料庫行銷策略探討,國立高雄第一科技大學行銷與流通管理研究所碩士論文,2004。
24.楊子青,購物車資料在網路行銷溝通決策之應用,國立中山大學資訊管理學系研究所碩士論文,1999。
25.趙盈傑,3C連鎖體系經營策略之分析,淡江大學管理科學研究所碩士論文,1998。
26.劉一賜,網路廣告第一課:蠻荒西部角力賽的生存之道,初版,時報文化,1999。
27.劉如興,信用卡資料庫行銷之顧客價值分析與促銷成效之研究,台灣大學國際企業學研究所碩士論文,2001。
28.賴耐志,應用資料探勘於市場區隔分析,台北科技大學商業自動化與管理研究所碩士論文,2002。

英文部分
1.Alfred, S. B. (1981), “Market Segmentation by Personal values and Salient Product Attributes,” Journal of Advertising Research, 32(2), pp.29-35
2.Best, Robert J. (2000), “Market-Based Management,” Upper Saddle River, NJ: Prentice Hall.
3.Butler, Patrick and Joe, Peppard (1998), “Consumer Purchasing on the Internet: Processes and Prospects,” European Management Journal, 16(15), London, pp.600-610.
4.Chaffey, D. (2000), “Achieving Internet Marketing Success,” The Marketing Review, 1(1), pp.35-59.
5.Day, George S. (2000), “Capabilities for Forging Customer Relationships,” Working Paper Series, Marketing Science Institute, Report No. 00(118).
6.Dourish, Paul and Edwards, W. Keith and LaMarca, Anthony and Lamping, John and Petersen, Karin and Salisbury, Michael and Terry, Douglas B. and Thornton, James (2000), “Extending Document Management Systems with User-Specific Active Properties,” ACM Transactions on Information Systems, 18(2), pp.140-170.
7.Engel, J. F. and Kollat, D. T. and Blackwell, R. D. (1984), “Consumer behavior,” Hinsdale, Illinois: The Dryden Press.
8.Goodman, John (1992), “Leveraging the Customer Database to your Competitive Advantage,” Direct Marketing, 55(8), pp.26-27.
9.Groth, Robert (1999), “Data Mining: Building Competitive Advantage,” Prentice Hall PTR.
10.Hodges, M. and Markey, E. J. and Winner, L. (1997), “Is Web Business Good Business? ,” Technology Review, 100(6), pp.22-32.
11.Kahan, R. (1998), “Using database marketing techniques to enhance your one-to-one marketing initiative,” Journal of Consumer Marketing, 15(5), pp.491-493
12.Kaiser, H.F. (1974), “A Second Generation Little Jiffy,” Psychometrika, Vol. 35, pp.401-405
13.Kotler, Philip (1994), “Marketing Management: Analysis. Planning. Implementation. and Control,” 8th Edition, Prentice-Hall Inc.
14.Kotler, Philip (2000), “Marketing management,” New Jersey: Prentice Hall.
15.Kotler, Philip and Armstrong (1999), “Principle of Marketing,” 8th ed., Englewood Cliffs, N.J.: Prentice-Hall.
16.Krauss, M. (1998), “How the Web is Changing the Customers,” Marketing News, 32(10), pp.10.
17.McCarthy, E. Jerome (1981), “Basic Marketing: A Managerial Approach Haomewood,” Illinois: Richard D. Irwin Inc., 7th ed.
18.McKenna, Regis (1995), “Real-Time Marketing,” Harvard Business Review, August, pp.87.
19.Mehta, R. and Sivadas, E. (1995), “Direct Marketing on the Internet:An Empirical Assessment of Consumer Attitudes,” Journal of Direct Marketing, 9(3), pp.21-32.
20.Moe, Wendy W. (2003), “Buying, Searching, or Browsing: Differentiating Between Online Shoppers Using In-Store Navigational Clickstream,” Journal of Consumer Psychology, 13(1and2), 29–39.
21.Peppers, D. and Rogers, M. (1999), "The One to One Manager: Real-World Lessons in Customer Relationship Management," Doubleday, New York.
22.Quelch, J.A. and Klein, L.R. (1996), “The Internet and International Marketing,” Sloan Management Review, 37(3), pp.60-75.
23.Sullivan T. (1997), “Reading reader reaction: A proposal for inferential analysis of web server log files,” In Proc. 3rd Conf. Human Factors the Web, Denver, Colorado, June
24.Wendell, S.R. (1956), “Product differentiation and market segmentation as alternative marketing strategies,” Journal of Marketing, pp. 3-7.
25.Wyner, G. A. (1996), “Customer Profitability: Linking Behavior to Economic,” Marketing Research, 8(2), pp.36-38.
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