Table Of ContentJuly 2011
vol. 47 / no. 5
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Using Web Analytics
in the Library
Kate Marek
Library Technology
R e p o R T s
Expert Guides to Library Systems and Services
�Using�Web�Analytics�in�the�Library
Kate Marek
alatechsource.org
American Library Association
About�the�Author
Library Technology
R e p o R T s Kate Marek, Ph.D., is a library educator, trainer, and
consultant. She is a Professor at the Graduate School of
Library and Information Science, Dominican University,
ALA TechSource purchases fund advocacy, awareness, and where she teaches in the areas of technology and policy.
accreditation programs for library professionals worldwide.
She is a leader in online teaching design and delivery.
Volume 47, Number 5 Kate has worked in the LIS profession for over 25 years
Using Web Analytics in the Library as a professional librarian, a teacher, a trainer, and a con-
ISBN: 978-0-8389-5833-9 sultant.
Kate has a B.A. from the University of Texas at Aus-
American Library Association
tin, an MLIS from Dominican University, and a Ph.D. in
50 East Huron St.
Library and Information Management from Emporia State
Chicago, IL 60611-2795 USA
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800-545-2433, ext. 4299 course design and delivery through InSync Training, Inc.
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comprehensively track the use of library websites,
Editor online resources, and services is more important than
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can be applied in a library setting. The author pro-
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vides a comprehensive overview of web analytics that
Judith Lauber
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Megan O’Neill guide to implementing Google Analytics, one of the
[email protected] most popular web analytics tools, and offers case stud-
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Contents
Chapter�1—Web�Analytics�Overview� 5
What Is Web Analytics? 5
Combining Quantitative with Qualitative Data 6
Website Goals and Implementing Web Analytics 6
Analytics Data and Insights 7
Web Analytics Tools 7
A Note About User Privacy 8
Google’s Approach to Privacy with Google Analytics 8
Privacy and Service 9
Resources 9
Notes 9
Chapter�2—Getting�to�Know�Web�Analytics� 11
Web Tracking Basics: Data Collection Mechanisms 11
GA Basics 13
Possible Actions 15
Resources 16
Notes 16
Chapter�3—Installing�and�Configuring�Google�Analytics�17
Getting Started 17
Configuration Best Practices 22
Setting Up Goals and Funnels in Google Analytics 22
Resources 25
Notes 25
Chapter�4—Reporting�and�Analysis� 26
General Overview of Metrics and Reporting Options 26
First-Level Metrics 26
Viewing Reports 27
Your Dashboard 27
Google Analytics Reports 28
Backing Up and Exporting Data 30
Access to Reports 30
Benchmarking 31
Data Visualization 31
Conclusion 31
Resources 31
Notes 32
Chapter�5—Case�Studies� 33
Additional Case Studies 40
Social Media Metrics 50
Summary 54
Notes 54
Chapter 1
Web Analytics Overview
Abstract
offer a diverse set of interactive tools such as book
discussions, live chat, print resources for download,
This chapter of Using Web Analytics in the Library pro- video instruction and support for research, and blogs
vides an overview of Web Analytics, the types of services that invite user participation. All of these initiatives
available, and the type of data that they can provide. heighten engagement among the community.
Thus librarians are faced with the challenge of
W
e live in an age of accountability. For librar- creating innovative tools in a changing society, while
ies, that means it is no longer enough just at the same documenting responsible use of our
to inform our stakeholders that the work we resources. In addition, we want to demonstrate within
do is worthwhile, is good for the community, and is a our own organizations that our website is constantly
responsible use of the taxpayers’ (or owners’) money. responding to trends and user needs. Finding tools to
Instead, we must justify our services, from both finan- assist with these challenges is essential. Web analytics
cial and logistical points of view. Librarians must oper- is just such a tool.
ate with a “return on investment” mindset, learning to
demonstrate value offered for both public and private
What�Is�Web�Analytics?
dollars.
At the same time, we have been shifting to a user-
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focused paradigm for the past decade. While our tradi- Web analytics is a process through which statistics ibra
tional way of conducting business has been one-direc- about website use are gathered and compiled electron- ry
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tional, where we have made decisions for programs ically. An analytics program can be used as a tool to e
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and services based on our own professional perspec- help you get to know your users—who they are, where n
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tives, we have recently become aware of the value they are coming from, and how they use your site. lo
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of listening to patrons and of crafting programs and Ultimately, having access to information about your y
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services based in large part on their input. With the users helps you to make appropriate decisions about e
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growth of social networking tools being a major facili- your site, whether those decisions apply to major rede- or
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tator of societal change, users have become partners in signs of your site or to ongoing tweaking and minor
a
numerous aspects of libraries’ daily operations. changes reflective of shifts in customer usage or in la
Nowhere is this more evident than in the library’s your own current programs and services. tec
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digital branch,1 or its Web presence. The library web- The origins of web analytics are from commer- so
u
site has become vital as a community outreach tool cial website design, where tracking users’ behaviors rc
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and as an ongoing source of information to its users. and actions directly relates to consumers’ purchas- .org
However, rather than a one-directional, electronically ing behavior. However, web analytics can be just as
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posted version of a flyer or newsletter, the contem- valuable for a nonprofit website as for an e-commerce uly
porary website is truly a place of community inter- site. One approach is to monetize your website goals, 2
0
1
action among its users. The website can extend the applying a dollar figure to certain activities such as 1
services available at the brick and mortar library and user visits or online program registrations. Essentially,
5
�Using�Web�Analytics�in�the�Library� Kate Marek
Chapter x
however, librarians should simply translate the theo- feedback about their website visit. The answers to these
ries of profit-based customer usage into the goals and questions will provide you with a wealth of information
situations that are specific to your organization. No and will put your analytics data in context.
matter the kind of organization, the website should For a more intensive user feedback project, con-
seek to understand the visitors’ experience and be sider a formal usability study. Two books by Steve
responsive to their needs. Krug are wonderfully helpful in introducing both the
purpose and the execution of user studies: Don’t Make
Me Think: A Common Sense Approach to Web Usabil-
Combining�Quantitative�with� 3
ity and Rocket Surgery Made Easy. Another excellent
Qualitative�Data tool is Usability Testing for Library Websites: A Hands-
4
On Guide, by Norlin and Winters. Each of these tools
Perhaps the best known name in the field of web ana- can help you get familiar with a process whereby you
lytics is Avinash Kaushik. In addition to two books, observe actual users in real time trying to complete
Kaushik writes an excellent blog, Occam’s Razor, and tasks on your website. The information you gather is
has numerous videos online regarding best practices of invaluable in learning about user behavior, and the
web analytics use. As mentioned previously as typical observations (often surprising) provide critical infor-
of web analytics literature, much of Kaushik’s work mation for web designers.
focuses on e-commerce, as his own history in the field
is from work with several major commercial compa-
Website�Goals�and�Implementing�
nies. Today he is the Analytics Evangelist for Google.
Web�Analytics
Occam’s Razor
Do you have goals for your website? Before you ever
www.kaushik.net/avinash start to collect and review data, you should have key
performance goals in mind for your digital branch. Do
you have a strategy for your website and its role in your
Kaushik’s enthusiasm for web analytics is conta- overall strategic plan and your mission? First, establish
gious. It’s difficult to read his books, read his blog, your website goals, based on your library’s mission and
or watch any of his numerous web instruction videos strategic plan. Build the website to reflect that mission
without also becoming passionate about web analyt- and that plan. With clear goals in mind, you can use the
ics. But one of Kaushik’s overriding philosophies about data to help you make decisions about your website.
5
web analytics is that the raw data tells only a portion Avinash Kaushik calls these “actionable insights.”
of the story: the “what.” To get at the “why,” and even Kaushik sees no reason to collect data if there is
the “how,” you must get into the mindset of the user. no direct match to a potential decision for improving
As Kaushik says, you must ask them (the users), using your website. He also stresses the 10/90 rule, which
methods such as electronic surveys, focus groups, and states that 10 percent of an organization’s cost for
user testing. web analytics is for the tool itself and its setup, and
One method of asking for users’ feedback is to 90 percent of the expenditure is for a person (or team
1
1
0 automatically direct users to an online survey, using of persons) to analyze the data for actionable insights.
2
y a tool such as SurveyMonkey or Zoomerang. Kaushik It’s not just about the numbers; analysis is key, and
ul
J writes that three open-ended questions are enough: that analysis is the most challenging part of the pro-
g cess. As you consider implementing web analytics, it is
e.or 1. “What was the purpose of your visit to our website important that everyone has a firm understanding of
c
ur today?” the critical role of savvy personnel in regards to data
o
hs 2. “Were you able to complete your task today?” analysis for your specific organization. A strong cul-
c
ate 3. “If . . . not, why not?”2 ture of data will include both the numbers and the
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people-generated actionable insights.
s
t Another caveat about data collected from web ana-
or SurveyMonkey
p lytics tools is that the numbers themselves are never
e
y R www.surveymonkey.com 100 percent accurate. Much of this has to do with how
og the analytics tools work, which will be explained at
nol Zoomerang various points in this report. Whatever the source of
ch www.zoomerang.com the odd inaccuracies, they are ultimately not particu-
e
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y larly significant. What are important are trends over
ar time (six months to two years), patterns of usage (such
br
Li If the visitors can compete your survey in just a few as seasonal spikes or dips), and insights you can draw
short minutes, they are much more likely to offer you through advanced tools such as user segmentation (for
6
�Using�Web�Analytics�in�the�Library Kate Marek
Chapter x
example, finding out what your Polish language users • Unique visits and returning visits: The unique
are seeking). Slight discrepancies in the numbers are visits metric indicates the number of visits to your
normal and should not be considered worrisome. site by different users, while returning visits indi-
cates users who return from at least one previous
visit. Since return visits are measured by cook-
Analytics�Data�and�Insights
ies, users who turn off cookies will be counted
as unique rather than return visitors. This is an
Are your visitors doing what you expect them to do, example of how the metrics numbers may not be
or what you want them to do? Are they following the 100 percent accurate.
path you thought they would follow when you designed Obviously you want to have an increasing
your menu system? Are visitors to your Digital Library number of visitors over time, but in general web-
page finding the link to historical photos of your city site visits will trend upward, and this fact alone
or the university’s archival images? These are some of will not give you a lot of actionable insights.
the questions you should be able to answer by using Partner this metric with other information, such
an analytics program. You can follow a user’s click- as increasing numbers of return visits to the YA
stream, find out which pages get the most visits, gather blog when the YA librarian makes more frequent
numbers about how long users stay on each page and entries, demonstrating increased engagement with
where they come from. You could in theory track every the target community.
visitor to your site, and each click of each of those visi- • Bounce rate: This metric counts visitors who
tors. Kaushik refers to “the paradox of data”: there is so left your site after visiting only one page. A high
6
much data, but so many barriers to good insights. bounce rate is often considered undesirable, and
With so many metrics available, what should you you will see this assumption in the literature. How-
be looking for, and what conclusions can you draw ever, bounce rate is another example of a metric
from those metrics? These questions will be investi- that should be compared to the actual page. If visi-
gated in more detail throughout this report (see espe- tors are finding exactly what they want when they
cially chapter 2 for a longer glossary), but for now I land on a page in your site, either at the opening
will offer a just a few examples. As you look at these page or some other file within the site, they may
examples, consider how you could use these statistics indeed leave after viewing only that individual
to make changes in your website content and design, page. A high bounce rate for e-commerce would
and how you could also use the statistics to justify be considered bad since the customer did not con-
website personnel and support. tinue to browse and eventually make a purchase.
In information websites, analysis of bounce rate is
• Page views: This is just what it sounds like: num- more complex.
ber of times an individual page is viewed. You • Visitor information: Many metrics can give you
can watch the numbers in this category for trends insights about your users, including geographic
over time, seasonal spikes and dips, and compari- location, browser used, operating system used,
sons with other pages in your website. You can and what path they took through your site. The
tell from the various page view rates within your more you know about your visitors, the more
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website which pages are most popular, and which you can adapt your site to meet their needs. For ibra
pages are rarely viewed. Another way to use these example, if you find that many people are using ry
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figures is to compare your total page views per mobile devices to view your site, you will know e
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h
month with your walk-in numbers. Thus, what that designing for mobile interfaces should be a n
o
percentage of your total use is from your digital priority for your web development team. lo
g
branch? This comparison will of course be an y
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estimate, since many customers use the website When getting started, concentrate on a few effec- e
p
and also visit in person, but it is nevertheless an tive metrics for your own site and follow those. As you or
ts
extremely useful comparison. build experience and confidence with those metrics,
a
• Time on page: You can study this metric in con- you will begin to add more dimension to your analysis. la
junction with the purpose of the page. For exam- Start small, as the amount of data can be absolutely tec
h
ple, you may not want a visitor to spend much overwhelming unless approached with planning. Web so
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time on an opening page with basic information analytics need not be an in-house example of informa- rc
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and descriptive links. A short time on page aver- tion overload. .org
age could indicate that people are finding what
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tohffeeyr rwicahnetr qcuoinctkelnyt., Hsuocwh eavse br,i balinoogtrhaeprh pica cgiet amtioany Web�Analytics�Tools uly 2
0
1
helps or blog posts. In such cases, you would pre- 1
fer a longer time on page. There has been an exponential growth in the web
7
�Using�Web�Analytics�in�the�Library� Kate Marek
Chapter x
analytics field in the last decade. Google launched Harmon, discusses at length the issue of nonprofit
its free tool, Google Analytics, in 2006, and the field organizations’ struggle with website end-users’ pri-
has continued to boom since then. Many commercial vacy. Ultimately Harmon concludes that clear com-
tools exist, including Coremetrics, Adobe’s Omniture, munication with the site’s users from the outset is the
7
and WebTrends. Open source tools are also available, best approach. When TechSoup’s own website added
including Piwik, which is billed as an open source Google Analytics, the leaders posted an entry to their
alternative to Google Analytics. blog explaining the role of analytics in their overall
Google Analytics has become an extremely popu- communication strategy, the potential implications of
lar tool among libraries, due not only to its tremendous adding the analytics tool, and clear reasons for their
power, but also to its free availability, its ease of use, decision. Harmon quotes library consultant Jessamyn
its flexibility, and its clear reporting mechanisms. This West as saying, “Have good reasons [for using web
report will use Google Analytics as a model for library analytics]. If you don’t have good reasons, that sends
implementation. The various chapters of the report will the message that you really haven’t thought about the
8
look at details of the Google Analytics program, how implications of these tools.”
to install and set up the program for your own library, If you don’t already have a privacy policy for your
and how to interpret the reports. Individual case studies website, beginning to use an analytics program is an
from libraries will show real-world examples of Google excellent time to move this to the top of your prior-
Analytics in use, where librarians have used Google ity list. A privacy statement should include informa-
Analytics to help them better understand their users’ tion for your visitors about what personal data they
website behaviors and understand how they can con- may be asked to provide, either as registered users or
tinually improve their customers’ website experience. as guests, what information may be collected without
their explicit knowledge (such as their geographic
location), how you will store and use the information,
Piwik
and what third parties (such as the analytics program
http://piwik.org host) may have access to it.9 Finally, you will also want
to offer your users clear instructions of how they might
opt out of as much as the data collection as possible.
A�Note�About�User�Privacy
Google’s�Approach�to�Privacy�with�
As you begin to learn more about web analytics and Google�Analytics
its capabilities, you will see that a tremendous amount
of data can be collected about your end users. This The approach to privacy at the other end, the host
behind-the-scenes data collection may make many company for the analytics tool itself, is a key part
librarians uncomfortable. However, the reality is that of the decision process in regards to using web ana-
virtually all websites collect some user data through lytics. (Some librarians prefer open source analytics
the operation of server logs. While completely elimi- programs run from their own local servers for just
nating data capture is an unrealistic goal, intentionally this reason.) However, just as libraries choose auto-
1
1
0 adding a tracking tool such as Google Analytics to col- mated circulation systems and online public access
2
y lect personal information about the library’s website catalogs with patron privacy built in, so too can we
ul
J visitors may seem to be the antithesis of our service select analytics tools that build in sensitivity to user
g philosophy. How can we reconcile the priority of per- anonymity. Google Analytics (GA) is a good model
or
e. sonal privacy with the organizational need to examine in this respect, as the company is clear, direct, and
c
ur website usage and statistics? intentional in its privacy policies. GA has its own
o
s
h Essentially, what is important to libraries is that internal policies that strongly support end-user pri-
c
e
at our users operate with complete anonymity at all vacy. It actually includes a privacy statement in its
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times and that they also maintain ultimate control of licensing agreement, and encourages full disclosure
s
t their data. The ability to opt out of any data collection and individual privacy statements for all users of
or
p is key and should be clearly offered as an option to our their tools.
e
y R website visitors. In addition, we must be thoughtful Brian Clifton, a GA expert and author of Advanced
og about what data to collect and how it will be used. Web Metrics with Google Analytics, says Google made
nol Libraries must strike a balance between user privacy an intentional decision not to collect user information
h
c and organizational effectiveness, with the scales from the beginning of its analytics program develop-
e
T
y always being tipped in favor of user choice. ment. GA works through the use of cookies, a preva-
ar The excellent TechSoup article “Site Statistics lent tool in web analytics. When you install GA, you
br
Li and User Privacy for Nonprofit Websites,” by Elliot add a string of code to each webpage for which you
8
�Using�Web�Analytics�in�the�Library Kate Marek
