Using Google Analytics for improving library website content and design: a case study.
Fang, Wei
Introduction
As more and more digital content goes online, libraries today are
fundamentally different than they were as recently as five years ago.
Websites have become an essential component of library service, and
designing these websites involves both technical and administrative
decision-making. During the past five years, the Rutgers-Newark Law
Library (RNLL) has used different methods to figure out exactly what our
visitors are looking for on our website. Recently, we used Google
Analytics to track our visitors' behaviors, and pinpointed the
motivations behind their information-seeking. The visually enhanced
reports by Google Analytics provided information on where visitors came
from, what pages they visited, how long they stayed on each page, how
deep into the site they navigated, where their visits ended, and where
they went from there. By analyzing the data from Google Analytics, we
made changes to our website and compared web usage data from before and
after the changes, concluding that our website was improved in a number
of ways.
Objectives
The goal of this case study was to use Google Analytics to improve
the design and content of the Rutgers-Newark Law Library's main
website to better fit our visitors' needs. Our objectives were:
* To track the usage of the library main website
* To track visitors' behaviors
* To determine the efficiency of the website's menu system
* To make suggestions for improving user experiences
* To establish the most effective way for redesigning the website
Methodology
There are different methods for analyzing website traffic and
usability. Our user services department at RNLL used to ask patrons to
fill out paper-based surveys that asked questions regarding users'
experiences with the website. However, paper-based surveys have
limitations since the target groups are limited by their physical
locations. The digital services department also built a webpage to
conduct similar surveys online. Online surveys overcome physical
location limitations, but because of their subjective nature they still
cannot guarantee accuracy of results. In general, questions given in a
survey can be open-ended or closed-ended: closed questions are
considered more efficient and reliable while open questions can help get
unanticipated answers in respondents' own words. Also, survey
results could be dramatically affected by the way the questions are
worded (Fink, 2002, pp. 4-6). Plus, these methods were time-consuming
and required a great deal of human input.
Some schools have inserted counters on their home pages to monitor
traffic volume coming to the site (Dyrli, 2006, p. 72). But this simple
method is far from being good enough for those seeking deeper
information about their websites as well as their visitors. Some schools
have also used web server log files to gather similar information, and a
lot of research has been conducted on web log mining (Srikant and Yang,
2001; Spiliopoulou, Faulstich, and Wilkler, 1999). For instance,
Nicholas et al. (2006) have used log files to track user behaviors in
finding information in a large digital library. Huntington et al.
(2006), also used the log file to design a better web menu system.
Let's put aside for now how effective their proposed approaches
are. Simply cleansing and digging web server log files, which have
thousands of tab separated lines, is a nightmare. There are some
utilities that can help people analyze log files, but their functions
are very limited and the results are not accurate if the log files are
not set up correctly.
In contrast, web analytics offer objective and multi-faceted
statistical data in a visual way for webmasters to better understand the
interaction between their visitors and their websites. According to the
Web Analytics Association (2006), "Web Analytics is the
measurement, collection, analysis and reporting of Internet data for the
purposes of understanding and optimizing Web usage." With web
analytics, one does not need to worry about location-based problems
inherent in paper-based surveys or about receiving inaccurate
information. Plus, all the data is collected automatically with high
accuracy. Examples of available web analytics tools include VisiStat,
StatCounter, ClickTracks, and Google Analytics. By far the most
sophisticated web analytics tool is Google Analytics (Dyrli, 2006,
p.72). It is a valuable tool for those who need to determine their
website's performance in a fast and reliable way (Jasra, 2006).
Google Analytics was made available by Google to the public in August
2006. It provides hosted service for web analytics, through which
collecting and analyzing web usage data can be done in a finger-snap.
In this article, we examine Google Analytics' functionalities
and discuss how this free yet powerful utility has helped improve our
website development. This is a case study with an experimental approach.
Our findings can provide insights for other libraries on using Google
Analytics for website redesign.
Background: Rutgers-Newark Law Library for the Center of Law and
Justice
Rutgers-Newark Law Library is part of Rutgers School of Law-Newark.
With more than half a million volumes, RNLL is the largest law library
in New Jersey. Its collections include the statutes and court decisions
of all 50 states, federal statutes and caselaw, federal and New Jersey
regulations and administrative decisions, federal and New Jersey
legislative history materials, the codes of ordinances for many New
Jersey municipalities, Anglo-American legal periodicals, the primary
materials of international law, extensive historical materials on
English law, and a special collection of criminology and criminal
justice materials.
The primary mission of the library's website is to serve the
educational and research needs of the faculty and students of the
Rutgers University School of Law. To the extent that it is compatible
with its primary mission, the library also provides service to others.
According to the information gathered by Google Analytics, our two major
websites, the Rutgers-Newark Law Library website and the New Jersey
Digital Legal Library website, attract more than 2,200 visitors per day.
Thanks to Google Analytics, we now know that our visitors come from all
over the world, including non-English speaking countries, such as China.
Google Analytics Background
In March 2005, Google acquired a web analytics firm called Urchin Software. Thousands of popular websites and marketers used to use
software solutions from Urchin to better understand user experience as
well as to optimize content (Google, 2006b). Later, in November 2005,
Google released the online version of Urchin, named Google Analytics.
Unlike the original Urchin, which was priced from $899 to $4,995 (Xooni,
2006), Google offers this hosted service for free. Due to the popularity
of the service, Google placed new applicants on a waiting list until
Google Analytics became generally available to the public in mid-August
2006.
Anyone with a Google account can use Google Analytics. Once a
Google account holder signs up for Google Analytics, Google sends a
confirmation email and provides code to insert into each webpage to be
tracked. The code has to be inserted right before the </body> line
in the HTML code of each page to be analyzed. Our webpages are generated
dynamically from some templates, so our whole installation procedure was
done within 20 minutes.
Google Analytics can be easily deployed on multiple websites
(Whiting, 2005). Tracking code has to be inserted in each and every page
to be tracked. We had to ensure that this insertion was done in a
precise way, or our tracking results would not be accurate. As
we've mentioned, our website is dynamically created based on page
templates. It was not a difficult task to insert tracking code into our
sites. However, this could be a nightmare for those who have hundreds of
static webpages.
Usually, Google Analytics will start tracking as soon as coded
webpages are online. However, reports offered by Google Analytics
average a two-hour delay. For instance, results for 10:00 a.m. show up
around noon, meaning that visitors' activities cannot be tracked in
real time.
According to Google Analytics' Terms of Service, "the
Service is provided without charge to you for up to 5 million pageviews
per month per account, and if you have an active Adwords campaign in
good standing, the Service is provided without charge to you without a
pageview limitation" (Google, 2006d).
Google Analytics data can be exported; however, we cannot import
our own data into Google Analytics. For example, web server log files
cannot be imported into Google Analytics. As Google Analytics states on
its website (Google, 2006c), it generates "aggregated non-personal
information" to share with third parties. (Google, 2006a). Thus,
high-security websites are recommended not to use this service.
RNLL's Use of Google Analytics
The Digital Services Librarian took advantage of the following
Google Analytics features: easy installation, keyword comparison,
visualized summaries, trend reporting, defined funnel navigation,
content by titles, site overlay, visitor segmentation, and data export.
We will discuss these features in more detail below.
As mentioned in the Google Analytics background section, using
Google Analytics requires nothing but copying and pasting the tracking
code into each of our webpages. Since all the webpages on our website
are generated dynamically, we simply inserted the tracking code in the
template, and all the pages based on this template were thus tracked.
Google Analytics has the capability of tracking both paid search
and unpaid search from Google or other search engines for keywords that
take the visitors to our website. This feature allows webmasters to
perform keyword comparisons across search engines and get insight into
popular keywords that bring in visitors.
The Visualized Summaries feature is what we liked the most. Though
many librarians may not be interested in numbers and statistics, Google
Analytics provides an excellent analytic solution that contains 80
predefined visualized reports that explain complex statistical data in a
simple and easy-to-understand manner. For instance, on logging into
Google Analytics, we saw a quick summary of our website activities for
the current week (see Figure 1). This summary told us how many visitors
had visited our website, how many pages they had viewed, how many of
them were new visitors or returning visitors, where they were coming
from and which website or search engine had referred them to our
website. This "digital dashboard" feature greatly enhanced our
productivity, since we didn't need to spend a lot of time reading
numbers and analyzing data. It also provided powerful evidence to
convince other librarians and administrators of the necessity of making
changes to the website.
[FIGURE 1 OMITTED]
The Trend Reporting feature allowed us to compare data from
different date ranges. We used this feature mainly for comparing data
before and after the website redesign. For instance, new visitors to our
website have increased by 21% and returning visitors have increased by
44% (see Figure 12).
[FIGURE 12 OMITTED]
Navigation is a major part of the user experience on the web
(Lazar, 2003). Were our visitors following the path we had designed, or
were they just groping around? By using Defined Funnel Navigation, we
found out how many users were accurately following the path we had
designed to reach a target page (goal). This tool allows webmasters to
define up to four goals, each with ten steps (links), to monitor
visitors' navigation path (Tyler and Ledford, 2006). For example,
Defined Funnel Navigation showed that 2.33% of the visitors to our New
Jersey Digital Legal Library website clicked on the link to our Council
on Affordable Housing (COAH) collection main page (see Figure 2). Among
those who visited our COAH collection main page, 100% of them browsed
our collection by years. 4% of the visitors who accessed the Browse by
Year page got to it through direct links.
[FIGURE 2 OMITTED]
Content by Titles presents a list of the most popular items on our
website. By analyzing data from this feature, we figured out what
content was attracting visitors. For instance, we learned that our top
hit between September 18, 2006 and October 9, 2006 was the Same-Sex
Marriage page (see Figure 3).
[FIGURE 3 OMITTED]
Site Overlay shows instance clicking summaries laid over an actual
webpage (see Figure 4). This feature gave us a direct way to find out if
a link had been clicked, as well as the number of clicks on each link.
Even more excitingly, when we clicked on a link on a Site Overlay page,
we were redirected to whatever it linked to, and that page would then
display in the same Site Overlay summary style. In short, we could
collect statistical data as we browsed through our website within Google
Analytics.
[FIGURE 4 OMITTED]
The Visitor Segmentation feature adds 18 more predefined segments
for further drill-down into any of 80 Google Analytics reports (see
Figure 5). By employing this feature, we could combine any Google
Analytics report with other information, such as country, region, and
keyword, to generate a new report that presents visitors' detailed
information. For instance, we could see detailed information about
visitors who viewed our same-sex marriage page and where they were
coming from--that is, visitor segmentation based on region (see Figure
6).
[FIGURES 5-6 OMITTED]
Google Analytics allows users to export report data in text, XML,
and MS Excel formats. This feature is powerful because it generates data
that can by analyzed with other statistical programs. Figure 7 is an
example of exported data in text format. This list showed our visitor
loyalty information. It could be imported to MS Excel or other
statistical software for further analysis.
RNLL's Findings from Google Analytics
We have been tracking our two websites since July 29, 2006. We have
mainly monitored Site Overlay, Content by Titles, Funnel Navigation,
Visitor Segmentation, and Visualized Summaries. Information on
visitors' connection speed and computer configuration was also
collected and analyzed. Based on the information collected and analyzed
by Google Analytics from July 29 to September 10, 2006, we discovered
that:
1. Though about 85% of visitors used high-speed internet
connections, such as cable, DSL or corporate networks, 15% of visitors
still used dial-up or other low-speed connections.
2. 85% of visitors used Internet Explorer as their browser, and
about 11% of visitors used Firefox.
3. 55% of visitors used screen resolutions of 1024 x 768, and 21%
of them used 800 x 600.
4. The right-hand menu on our main website provided clickable news
headlines from JURIST, which is a JURIST is a "web-based legal news
and real-time legal research service" hosted by the University of
Pittsburgh School of Law. The Site Overlay showed that these links
generated very few clicks. This menu took up about 20% of the webpage
layout, so it was definitely underused.
5. According to Content by Titles, the Research Portals on the
left-hand menu of our main website had fewer visits than we had
anticipated.
6. New Jersey Digital Legal Library is our major digital project
for serving the law community in New Jersey. Our Defined Funnel
Navigation indicated that very few visitors were referred to this
website from our main website.
7. Initially, we tried to use the Site Overlay feature to see the
number of clicks for each link, but during the viewing process we
realized that items in the Quick Links section on the left-hand menu
were hard to differentiate (Berger, 2006) because all the links were
underlined and they didn't change when moused over. Also, Quick
Links such as Contact Us, Library Hours, and Library FAQ on the
left-hand menu actually pointed to different portions of the same
webpage.
8. Visitor Segmentation showed that 83% of visitors were coming
from the United States. About 50% of U.S. visitors were from New Jersey,
and 76% of these were from Belleville and Newark. These results matched
our predictions for patrons' geographical patterns, and Google
Analytics was the first tool to provide evidence to confirm those
predictions.
Hypotheses and the RNLL's Website Redesign
Google Analytics can report facts about the monitored website but
is unable to make suggestions on how to improve it. In order to make
effective changes, our reference librarians and administrators were
involved in the decision-making process. The decision-making process for
our website redesign was as follows:
Once the Digital Services Librarian received and interpreted the
reports from Google Analytics, he distributed the interpretation of the
reports to reference librarians and administrators. Based on their
feedback, the Digital Services Librarian developed new design
suggestions that in turn received further comments. Final decisions
about website design were made by administrators. All accepted changes
were implemented by the Digital Services Librarian, who continued to
monitor Google Analytics Reports and repeated the above process as
necessary.
Based on the information collected on visitors' connection
speed, we realized that it would not be a good idea to add more
graphical content to the new design since 15% of our visitors still used
low-speed connections. Also, we decided to keep our 800 x 600 webpage
template based on the screen resolution information of our visitors. We
noticed that 96% of visitors were using Microsoft Internet Explorer or
Firefox as their browsers. Our current JavaScript and Cascading Style
Sheets worked perfectly with these browsers and thus we could continue
to use them. In other words, we decided not to change the layout and
style of our website (see Figure 8). On the other hand, we changed a
number of things on our website as the result of using Google Analytics.
[FIGURE 8 OMITTED]
Hypothesis 1: Adding a Most Viewed Items section based on the
Content by Titles list will attract more visitors to these pages.
We decided to add a Most Viewed Items section to the right-hand
menu (see Figure 9, RC 1). These items were based on the Content by
Titles list from Google Analytics. Although they were the most popular
items on our website, Google Analytics reports showed that visitors
actually located them by using search engines. Adding a Most Viewed
Items section could better promote popular content that had previously
been deeply buried. It could also help retain first-time visitors.
[FIGURE 9 OMITTED]
Hypothesis 2: Adding an Other Links of Interest section to the main
page's menu will further promote popular pages.
On the right-hand menu bar, we developed a new section called
"Other Links of Interest" (see Figure 9, RC2). The reference
librarians suggested inserting our major content, the Internet Law
Guide, at the top of this section (see Figure 9, RC3). They also
suggested two popular external links for this section (see Figure 9,
RC5). Based on the information collected from Google Analytics, the
Digital Services Librarian suggested two top hits (see Figure 9, RC4)
from the New Jersey Digital Legal Library so that visitors could also be
brought to our own major projects.
Hypothesis 3: Reorganizing and reformatting the menu will better
meet the needs of visitors and librarians.
For all the items on the right- and left-hand menu bars, we added a
mouse-over effect and increased the font size (see Figure 10, C4). We
bulleted items so that they can be easily differentiated from each other
(see Figure 10, C3) (Wan, 2006). In order to better promote the Research
Portals, we moved them to the top of the left-hand menu (see Figure 10,
BO and C1). We then reorganized both the Quick Links section and the law
information page, which is one of the new Quick Links (see Figure 10,
C2). In addition, we moved Contact Information to the law library
information page (see Figure 10, DO). However, reference librarians
indicated that they still wanted one-click access to the Hours, Contact
Us, and Site Map information that used to be in the left-hand menu bar.
It takes at least two clicks to find this information after clicking on
the new Law Library Information link, so we created a new footer section
that has one-click access to these items (see Figure 11).
[FIGURES 10-11 OMITTED]
After discovering that the JURIST headlines were rarely clicked on,
we agreed to reduce the space taken by these headlines (see Figure 9,
RO1). These links were kept on our main website since administrators
thought that they were of interest to some users. In order to reduce the
space taken up by JURIST headlines, the Digital Services Librarian
designed a new program so that those headlines would roll over every six
seconds in a much smaller form (see Figure 9, RC6). By making this
reduction, we generated about two thirds more space on our right-hand
menu. We inserted some new sections and items, hoping that they would be
more popular than the JURIST headlines. We hoped that the redesign of
menus will bring more users and keep them at our pages.
Discussion
We launched the redesigned RNLL website on September 18, 2006. We
have continued to track the website through Google Analytics since then.
We defined the pre-modification time range from August 27 to September
17, 2006, for a total of 22 days. For comparison, we defined a
post-modification time range, the 22 days between September 18 and
October 9, 2006. All dates were after the school's opening date.
The results supported our hope that the redesign would improve our
website, as we discuss below.
Site Overlay supported our first hypothesis that a Most Viewed
Items section would be popular with visitors: each of these top links
averaged 30% more traffic after the site redesign.
Google Analytics also supported our second hypothesis that adding
an Other Links of Interest section to the main page would further
promote popular pages. For example, we added links to the NJ Digital
Legal Library website. Google Analytics showed that referrals from our
main website to NJDLL increased by 23.4%. Considering the fact that this
website had about 200 visitors per day, this 23.4% gain was significant.
Finally, Google Analytics supported our third hypothesis that
reorganizing and reformatting the menu would better meet the needs of
visitors and librarians. Clicks to these links increased after we moved
the Research Portals section from the middle to the top of the left-hand
menu: Faculty by 42%, Students and Others by 55%. Another change that
had a major impact was the addition of the Law Library Information link;
16% of those who visited the Library Guide page had followed that link.
We used Google Analytics to determine whether or not the redesign
worked, based both on the number of times visitors came and returned to
the site and on how many pages they viewed during each visit. Overall,
we found that new visitors increased by 21% and returning visitors
increased by 44% (see Figure 12). Return visits told us that there was
enough content for our users to continue coming. This was confirmed by a
3% decrease in the percentage of visitors who visited our website only
once and a 2.5% increase in the percentage of visitors who visited three
or more times (see Figure 13). Also, the number of pages viewed during
each visit told us whether our visitors were attracted by our content.
The number of people who viewed more than three pages increased by 29%;
this showed that more visitors were attracted by our content and that
they stayed and viewed more pages instead of coming and going
transiently. By promoting interesting content that previously had been
deeply buried in our website, we successfully attracted more return
visitors and achieved better loyalty.
Based on above analysis, we concluded that our visitors were
satisfied by our new design. Authors of popular pages are inspired by
the positive feedback from our visitors and are willing to keep updating
their pages as frequently as possible. Our reference librarians and
administrators think that we've made positive movement and are
satisfied.
Conclusion
As we have discussed, Google Analytics is a great tool for
constructing user-centered websites. It offers a user-friendly interface
and informational reports that allow for quick identification of
problems. We've discussed how our library used the features of
Google Analytics and how its reports helped us make design decisions for
our website. A comparison of the data before and after the redesign show
that we improved our website, which now brings in more traffic, achieves
better loyalty, and has better navigation for visitors. Libraries
interested in knowing more about the interaction between their websites
and visitors should consider using this service.
We are in the process of redesigning the NJDLL website using Google
Analytics, and we will present our findings in the future. Also,
we've decided to deploy Google Analytics in our catalog to track
catalog visitors and find ways to improve their experience in the
catalog. Meanwhile, we will continue to explore Google Analytics'
many features.
Selected Web Analytics Tools
ClickTracks (2006). About Us. Retrieved October 10, 2006, from
http://www.clicktracks.com/about_us.php
Google Analytics (2006). Google Analytics. Retrieved October 10,
2006, from http://www.google.com/analytics/
StatCounter (2006). Our Mission. Retrieved October 10, 2006, from
http://www.statcounter.com/about/our_mission.html
VisiStat. (2006). VisiStat. Retrieved October 10, 2006, from
http://www.visistat.com/
References
Berger, P. (2006). How to evaluate websites for better or worse.
Information Searcher 16(2), 1-10.
Dyrli, O. E. (2006). How effective is your Web site? Free online
tools help measure site success. District Administration, 42(9), 72.
Fink, A. (2002). How to ask survey questions. Thousand Oaks,
Calif.: SAGE Publications.
Google. (2006a). Google Privacy Center: 7. What is aggregated
non-personal information? Retrieved September 22, 2006, from
http://www.google.com/intl//privacy_faq.html#aggregatedinfo
Google. (2006b). Google corporate information: Google milestones.
Retrieved September 22, 2006, from http://www.google.com/corporate /
history.html#2005
Google. (2006c).Google Privacy Policy. Retrieved September 22,
2006, from http://www.google.com/intl//privacy.html
Google. (2006d). Google Analytics Terms of Service. Retrieved
October 1, 2006, from http://www.google.com/analytics/tos.html
Huntington, P., et. al. (2006). Improving the relevance of web
menus using search logs: a BBCi case study. Aslib Proceedings 58(1/2),
118-128.
Jasra, M. (2006, August 16). Web analytics comparison--Google vs.
VisiStat. The Enquiro. Retrieved from
http://www.enquiro.com/marketing-monitor/
Web-Analytics-Comparison-Google-VisiStat.asp
Lazar, J. (2003). The World Wide Web. In: J. Jacko and A. Sears
(Eds.) The human-computer interaction handbook: fundamentals, evolving
technologies and emerging applications (pp. 714-730). Mahwah, NJ:
Lawrence Erlbaum.
Mason, N. (2006). The four parts of web optimization. In Google
Analytics. Retrieved September 26, 2006, from
http://www.google.com/analytics/cu/ac_the_four_parts.html
Nicholas, D., et al. (2006). Finding information in (very large)
digital libraries: a deep log approach to determining the differences in
use according to method of access. Journal of Academic Librarianship
32(2), 119-126.
Spiliopoulou, M., Faulstich, L. C., and Wilkler, K. (1999). A data
miner analyzing the navigational behaviors of web users. In Proceedings
of the Workshop on Machine Learning in User Modeling of the ACAI99.
Greece.
Srikant, R. and Yang, Y. (2001). Mining web logs to improve website
organization. World Wide Web Conference (WWW10). Hong Kong.
Tyler, M. E. and Ledford, J. L. (2006). Google Analytics. Somerset,
NJ: Wiley.
Wan, G. (2006). Visualizations for digital libraries. Information
Technology and Libraries 25(2), 88-94.
Web Analytics Association. (2006). The Web Analytics Association.
Retrieved October 2, 2006, from http://www.webanalyticsassociation.org/
Whiting, R. (2005, December 5). The Google effect. Information
Week. Retrieved December 5, 2005, from http://www.informationweek.com/
Xooni. (2006). Compare Google Analytics to Urchin.Xooni. Retrieved
September 29, 2006, from
http://www.xooni.com/products/compare_ga_to_urchin.html
Wei Fang
Digital Services Librarian
Rutgers-Newark Law Library for the Center of Law and Justice
Newark, New Jersey 07102
Figure 7: Data exported from Google Analytics
Profile Name: law-library.rutgers.edu
Date Range : 9/18/2006 - 10/9/2006
9/17/06
Visit Number Visits
1 17679
2 1967
3 619
4 310
5 190
6 126
7 96
8 76
15-25 259
26-50 306
51-100 383
101-200 392
201+ 1043
Visitor Loyalty
Date Range (2): 8/27/2006 -
Visit Number Visits(2)
1 14595
2 1452
3 441
4 192
5 112
6 74
7 48
8 42
15-25 171
26-50 242
51-100 175
101-200 378
201+ 681
Figure 13: Visitor Loyalty Analysis
Date Range 1:
9/18 - 10/9/2006 Dante Range 2
8/27 - 9/17/2006
Total visits 23446 18603
% single-visit visitors 75.4% 78.5%
Total visitors with at least three visits 3800 2556
% visitors with at least three visits 16.2% 13.7%