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Current trends in web data analysis

Published:01 November 2006Publication History
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Abstract

Considering potential reasons for the underutilization of clickstream data and suggesting ways to enhance its use.

References

  1. Catham, B., Manning, H., Gardner, K.M., and Amato, M. Why Web site analytics matter. The TechStrategy Report. Forrester Research, Apr. 2003; www.forrester.com.]]Google ScholarGoogle Scholar
  2. Creese, G. Web analytics: Translating clicks into business. White Paper, Aberdeen Group, 2000; www.aberdeen.com.]]Google ScholarGoogle Scholar
  3. Creese, G. E-channel awareness: Usage, satisfaction, and buying intentions. White Paper, Aberdeen Group, 2003; www.aberdeen.com.]]Google ScholarGoogle Scholar
  4. Fu, Y., Sandhu, K., and Shih, M. A generalization-based approach to clustering of Web usage sessions. In B. Masand and M. Spiliopoulou, Web Usage Analysis and User Profiling. Spring Verlag, London, 2000.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Goldberg, J. Why Web usage statistics are (worse than) meaningless, 2001; www.goldmark.org/netrants/Webstats/.]]Google ScholarGoogle Scholar
  6. Haigh, S. and Megarity, J. Measuring Web site usage: Log file analysis. National Library of Canada, (Aug. 4, 1998), Ottawa, ON; www.nlc-bnc.ca/9/1/p1-256-e.html.]]Google ScholarGoogle Scholar
  7. Keylime Software, Inc. The evolution of Web analytics: From server measurement to customer relationship optimization. White Paper, Apr. 2002; www.limesoft.com.]]Google ScholarGoogle Scholar
  8. Kimball, R. and Merz, R. The Data Webhouse Toolkit. Wiley, New York, 1999.]]Google ScholarGoogle Scholar
  9. Moe, W.W. and Fader, P. Capturing evolving visit behavior in clickstream data. Journal of Interactive Marketing 18, 1 (Winter 2004), 5--19.]]Google ScholarGoogle ScholarCross RefCross Ref
  10. Parshal, B. Web analytics: A bird's-eye view of practices and plans. White Paper, 2001; www.techrepublic.com.]]Google ScholarGoogle Scholar
  11. Sterne, J. Web Metric: Proven Methods for Measuring Web Site Success. Wiley, New York, 2002.]] Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Underhill, P. Why We Buy: The Science of Shopping. Simon and Schuster, New York, 1999.]] Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Current trends in web data analysis

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            Amit Rudra

            Over the last few years, logging Web traffic and recording the corresponding data have become very important for businesses using the Web as the principal means of marketing their wares. Obviously, just recording such information is not the main reason for logging such data; rather, the analysis of this vital source of information pertaining to existing and potential customers is of paramount interest when selling merchandise on the Internet. This article outlines current trends in analyzing such information. It provides a reasonably good description of the trends toward analysis of Web data. Principally, it highlights the reasons why businesses underutilize clickstream data. Understandably, incomplete data turns out to be the main problem for this (the other two reasons are the use of too many analytical methods and inherent problems with data analysis). Written in a delightfully simple manner, the article explains all concepts covered and is readable by anyone, whether a marketing or business executive or those in information technology (IT). The authors’ framework, the Web forensic pyramid, is based on the well-known concept of Web metrics [1]. Online Computing Reviews Service

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              cover image Communications of the ACM
              Communications of the ACM  Volume 49, Issue 11
              Entertainment networking
              November 2006
              82 pages
              ISSN:0001-0782
              EISSN:1557-7317
              DOI:10.1145/1167838
              Issue’s Table of Contents

              Copyright © 2006 ACM

              Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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              New York, NY, United States

              Publication History

              • Published: 1 November 2006

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