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Anindita Paul
ASIST Conference 2009, Poster Sessions,
November 6-11, 2009, Vancouver, BC P a g e | 1
Web Analytics in Library Practice: Exploration of Issues
Anindita Paul
Doctoral Candidate
School of Information Science and Learning Technologies
University of Missouri
Abstract
In this study the use of web analytics in libraries is examined. The study seeks to understand how
analytics as a tool for libraries would be feasible to interpret users’ behavior on the library’s website.
Evaluating library and information services are important for library decision makers who are constantly
faced with situations where they need to make decisions regarding the quality of services offered by the
libraries. Such decisions need investment and hence adequate support for any such decisions can be
vital in providing insights into planning and changes to the library services. The data was collected on the
University of Missouri’s (MU) library website using Google analytics and an ’interactive group interview’ of
the library’s usability committee. The poster discusses the issues that analytics implementation could face
in a library setting. The study would benefit libraries in understanding how can web analytics be used as
an evaluation tool for libraries especially as an enhancement over the traditional evaluation tools.
Background
Libraries provide an enormous amount of valuable content that gets overlooked due to the
availability of instant access of information through the web. This has prompted libraries to make much of
the content available online in order to retain its patrons. Studies have been conducted to provide libraries
a holistic measure for assessing their services (Nicholson, 2004; Saraf & Mezbah-ul-islam, 2002). These
holistic measures ask libraries to look at the user’s perspective and incorporate these perspectives in the
decision making process. Libraries also face a challenge of dealing with increased knowledge base that
on one hand provides the rigor needed, and on the other hand might be limited to be used across
contexts and cultures (Eldredge, 2006). Nicholson (2006a) states some of the drawbacks of traditional
Evidence Based Librarianship (EBL), which lacks appropriate research articles that librarians can use.
Also, the time taken to collect evidence sometimes results in lesser number of publications and hence
reduces the power of the traditional EBL. Eldredge (2006) acknowledges the drawbacks and hence calls
for certain fair and truthful practices that should be followed to minimize the downsides of traditional EBL.
Evaluating library and information services are important for library decision makers who are
constantly faced with situations where they need to make decisions regarding the quality of services
offered by the libraries. Such decisions need investment and hence adequate support for any such
decisions can be vital in providing insights into planning and changes to the library services. Libraries
have numerous constraints that they need to deal with in the planning process. In such a scenario, library
decision makers need to rely on information gained from evaluation process and have to constantly weigh
between the services, resources, and overall effectivity of libraries (Hernon & McClure, 1990, p.1).
Hernon & McClure (1990, p. 235) talks about the need for library managers to rely on empirical evidence.
They also mention that managers prefer “intuitive” or “seat-of-the-pants” decision making that would not
require them to spend time to obtain “evaluative data on a particular issue or decision problem (p.235).
Web analytics provides a way to constantly capture the online actions of the visitors of a website
by measuring visitor traffic (Khoo et al., 2008) hence providing information about users’ navigation
behavior, user and page clusters, as well as possible correlations between web pages and user groups
(Eirinaki and Vazirgiannis, 2003). The web analytics packages available today provide increased
functionality by providing data in a visual format that helps in understanding the online visitors behavior
on a particular website (Tyler and Ledford, 2006, p.7; Eirinaki and Vazirgiannis, 2003). Use of web
analytics as a tool has been recognized in businesses that seek to improve their internal as well as
marketing productivity through an understanding of the user (Jacoby and Luqi, 2007; Sen et al., 2006;
Srinivasan et al., 2004). Libraries have a different motivation compared to e-commerce websites.
Libraries and e-commerce websites both want to provide services to the users, or enable the users to
Anindita Paul
ASIST Conference 2009, Poster Sessions,
November 6-11, 2009, Vancouver, BC P a g e | 2
fulfill the intended task seamlessly however the goals of a library vary from that of the ecommerce
websites in terms of their expectations from the visiting users.
Method
The study was undertaken as a part of a larger study that investigated the use of web analytics in
understanding users’ online behavior in a library setting. The data was collected on the University of
Missouri’s (MU) library website using Google analytics and an ’interactive group interview’ (Patton, 2001)
of the library’s usability committee. Google analytics is a free tool provided by Google, and was
implemented on the MU library website on March 2007. The objective of this poster is to present the
issues of implementing analytics in libraries for the purposes of decision making. Six members of the
library’s web advisory committee were interviewed in the interactive group interview. A preliminary
analysis was done of the Google analytics reports of the library and the results were presented to the six
members of the library’s advisory committee. The presentation was a prop to get feedback from the
library committee about the use and benefits of their Google analytics implementation and the possible
direct and indirect consequences of such an implementation.
Findings
The analysis for this study is ongoing. However, some of the interim issues that were found involved
those that were directly related to the aspects of the website such as content or design, navigation,
services offered, search-ability of information; some other issues related to the interpretation of the web
analytics package used when seen in a library setting. Librarians also showed interest to know more
about their users’ behavior even if that information would not support any management decision. An
important finding is that web analytics as a tool for libraries need to be reassessed in terms of the
definition of the metrics and its interpretation in a library context. Further analysis will provide specific
details of the different issues that librarians would like to know under each of the broader categories of
content, navigation, services offered etc.
References
Eirinaki, M. & Vazirgiannis, M. (2003, February). Web mining for Web personalization. ACM Transactions
on Internet Technology, 3(1), 1-27.
Eldredge, J. (2006). Evidence-based librarianship: The EBL process. Library Hi Tech 24(3), 341-354.
Hernon, P., & McClure, C. (1990). Evaluation and library decision making. Norwood,NJ: Ablex Publishing
Corporation.
Jacoby, G. A. & Luqi (2007, February). Intranet model and metrics: Measuring intranet overall value
contributions based on a corporation’s critical business requirements. Communications of the
ACM, 50(2), 43- 50.
Khoo, M., Pagano, J., Washington, A.L., Recker, M., Palmer, B., and Donahue, R. A. Using web metrics
to analyze digital libraries. International Conference on Digital Libraries. Proceedings of the 8
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ACM/IEEE-CS joint conference on Digital Libraries, 375-384.
Nicholson, S. (2004). A conceptual framework for the holistic measurement and cumulative evaluation of
library services. Proceedings of the 67
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ASIS&T Annual Meeting, 41, 496-506.
Nicholson, S. (2006a). Approaching librarianship from the data: Using Bibliomining for evidence-based
librarianship. Library Hi-Tech 24(3). 369-375
Patton, M. Q. (Ed.). (2001). Qualitative Research & Evaluation Methods (3rd ed.). USA: Sage
Publications, Inc.
Saraf, V. & Mezbah-ul-Islam, M. (2002). Measuring library effectiveness: A holistic approach. Journal of
Library and Information Science 27 (2), 81-105.
Sen, A., Dacin, P. A. & Pattichis, C. (2006, November). Current trends in Web data analysis.
Communications of the ACM, 49 (11), 85-91
Srinivasan, S., Amir, A., Deshpande, P. & Zbarsky, V. (2004). Grammar-based task analysis of Web logs.
Proceedings of the thirteenth ACM international conference on information and knowledge
management, 244-245. NY: ACM Press.
