Abstract
The Internet is one of the most significant and efficient ways for communication technology which has the potential to revolutionize business and marketing techniques. To understand efficiently who is visiting our Web site and how they are using it is the primary key for the success of the marketing based on Internet. The traffic analysis systems via Web server log files only provide partial and non-real time information about customer activities on your Web site, it’s insufficient to support better business decisions which need detailed and real time information about customers’ activities on your Web site. In this paper, we provide our experiences on an implementation of the sophisticated analysis system based on click stream analysis technologies. A case study is also provided to show practical values of this system.
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References
Grant, A.W.H., Schlesinger, L.A.: Realize Your Customers’ Full Profit Potential. Harvard Business Review, 58–72 (1995)
Hill, D.: Love My Brand. Brandweek (1998)
Ruediger, A., Grant-Thompson, S., Harrington, W., Singer, M.: What Leading Banks are Learning about Big Databases and Marketing. McKinsey Quarterly (1997)
Web Mining Whitepaper: Driving Business Decisions in Web Time. Accrue Software (2000)
eBusiness Analysis and Accrue Insight. Accrue Software (1999)
Koch, M., Schubert, P.: Personalization and Community Communication for Customer Support. In: 6th International Conference on Work with Display Units - World Wide Work (WWDU2002), Berchtesgaden, Germany (2002)
Ginsburg, M.: Realizing a Framework to Create, Support, and Understand Virtual Communities. In: Infonomics/Merit Workshop on Digitization of Commerce: e-Intermediation, Maastricht, Netherlands (2001)
Knox, M.: Clickstream Dimensions: Information System Requirements. Gartner (2001)
Knox, M., Buytendijk, F.: By definition: Web Analytics Need Explaining. Gartner (2001)
Buytendijk, F.: Web Analytics: So What? Gartner (2001)
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© 2004 Springer-Verlag Berlin Heidelberg
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Kim, S., Leem, C.S. (2004). A Case Study on the Real-Time Click Stream Analysis System. In: Zhang, J., He, JH., Fu, Y. (eds) Computational and Information Science. CIS 2004. Lecture Notes in Computer Science, vol 3314. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30497-5_122
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DOI: https://doi.org/10.1007/978-3-540-30497-5_122
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-24127-0
Online ISBN: 978-3-540-30497-5
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