Web Analytics Reveal User Behavior: TTU Libraries' Experience with Google Analytics

Ian Barba, Ryan Cassidy, Esther De Leon, B. Justin Williams

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Proper planning and assessment surveys of projects for academic library Web sites will not always be predictive of real world use, no matter how many responses they might receive. In this case, multiple-phase development, librarian focus groups, and patron surveys performed before implementation of such a project inaccurately overrated utility and positive impact. The Web Site Support Team of Texas Tech University Libraries conducted post-assessment usage of a locally developed reference tool using Google Analytics, which revealed a significant disparity between expectations and results. Web analytics tools, while not able to predict users' needs, are adept at describing users' behavior. This user-provided evidence is invaluable for informing the decisions that academic libraries make about their Web sites. While the initial incarnation of the reference tool failed to provide the intended service, Web analytics allowed the team to refine, modify, and integrate elements of the tool into other areas of the Web site, saving the project from being completely scrapped. Other academic libraries and libraries in large organizations are encouraged to use Web analytics and click analytics tools to assess the outcomes of Web projects. Such data can reveal blind spots in predictive usage, which may originate even in the patron base, and can allow modification of projects based upon real user behavior.

Original languageEnglish
Pages (from-to)389-400
Number of pages12
JournalJournal of Web Librarianship
Volume7
Issue number4
DOIs
StatePublished - 2013

Keywords

  • Google Analytics
  • Web analytics
  • academic library Web sites
  • user behavior

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