- Author:
- Bernard J. Jansen
This lecture presents an overview of the Web analytics process, with a focus on providing insight and actionable outcomes from collecting and analyzing Internet data. The lecture first provides an overview of Web analytics, providing in essence, a condensed version of the entire lecture. The lecture then outlines the theoretical and methodological foundations of Web analytics in order to make obvious the strengths and shortcomings of Web analytics as an approach. These foundational elements include the psychological basis in behaviorism and methodological underpinning of trace data as an empirical method. These foundational elements are illuminated further through a brief history of Web analytics from the original transaction log studies in the 1960s through the information science investigations of library systems to the focus on Websites, systems, and applications. Following a discussion of on-going interaction data within the clickstream created using log files and page tagging for analytics of Website and search logs, the lecture then presents a Web analytic process to convert these basic data to meaningful key performance indicators in order to measure likely converts that are tailored to the organizational goals or potential opportunities. Supplementary data collection techniques are addressed, including surveys and laboratory studies. The overall goal of this lecture is to provide implementable information and a methodology for understanding Web analytics in order to improve Web systems, increase customer satisfaction, and target revenue through effective analysis of userWebsite interactions. Table of Contents: Understanding Web Analytics / The Foundations of Web Analytics: Theory and Methods / The History of Web Analytics / Data Collection for Web Analytics / Web Analytics Fundamentals / Web Analytics Strategy / Web Analytics as Competitive Intelligence / Supplementary Methods for Augmenting Web Analytics / Search Log Analytics / Conclusion / Key Terms / Blogs for Further Reading / References
Cited By
- Kumar V and Ogunmola G (2020). Web Analytics for Knowledge Creation, International Journal of Cyber Behavior, Psychology and Learning, 10:1, (1-14), Online publication date: 1-Jan-2020.
- Brown A, Lush B and Jansen B Pixel efficiency analysis Proceedings of the 79th ASIS&T Annual Meeting: Creating Knowledge, Enhancing Lives through Information & Technology, (1-10)
- Coughlin D and Jansen B (2016). Modeling journal bibliometrics to predict downloads and inform purchase decisions at university research libraries, Journal of the Association for Information Science and Technology, 67:9, (2263-2273), Online publication date: 1-Sep-2016.
- Coughlin D, Campbell M and Jansen B (2016). A web analytics approach for appraising electronic resources in academic libraries, Journal of the Association for Information Science and Technology, 67:3, (518-534), Online publication date: 1-Mar-2016.
Evans M, Kerlin L and Jay C "I Woke Up as a Newspaper" Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, (477-488)- Thomas P (2014). Using Interaction Data to Explain Difficulty Navigating Online, ACM Transactions on the Web, 8:4, (1-41), Online publication date: 6-Nov-2014.
- Sleeper M, Consolvo S and Staddon J Exploring the benefits and uses of web analytics tools for non-transactional websites Proceedings of the 2014 conference on Designing interactive systems, (681-684)
- Coughlin D, Campbell M and Jansen B Measuring the value of library content collections Proceedings of the 76th ASIS&T Annual Meeting: Beyond the Cloud: Rethinking Information Boundaries, (1-13)
- Klamma R Community Learning Analytics --- Challenges and Opportunities Proceedings of the 12th International Conference on Advances in Web-Based Learning --- ICWL 2013 - Volume 8167, (284-293)
- Renzel D and Klamma R From micro to macro Proceedings of the Third International Conference on Learning Analytics and Knowledge, (250-254)
- Thomas P Explaining difficulty navigating a website using page view data Proceedings of the Seventeenth Australasian Document Computing Symposium, (31-38)
- Kohli S, Kaur S and Singh G A Website Content Analysis Approach Based on Keyword Similarity Analysis Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01, (254-257)
- Fransson J Intention and task context connected with session in a cultural heritage collection Proceedings of the 4th Information Interaction in Context Symposium, (138-144)
- Ortiz-Cordova A and Jansen B (2012). Classifying web search queries to identify high revenue generating customers, Journal of the American Society for Information Science and Technology, 63:7, (1426-1441), Online publication date: 1-Jul-2012.
- Kallehauge J (2010). Stage-driven information seeking process, Journal of Information Science, 36:2, (242-262), Online publication date: 1-Apr-2010.
- Silvestri F (2018). Mining Query Logs, Foundations and Trends in Information Retrieval, 4:1—2, (1-174), Online publication date: 1-Jan-2010.
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