Improving the User’s Experience through Web Analytics*

SAA Research ForumChicago, Illinois August 28, 2007

Christopher J. PromAssistant University Archivist

University of Illinois at Urbana-Champaignprom@uiuc.edu

*Special thanks to Beth Yakel, Aprille McKay, and Helen Tibbo!

What is Web Analytics

• Web Measurement: gathering and parsing the data• Web Analytics: interpreting measurement reports so

that some action can be taken – Eric T. Peterson, Web Site Measurement Hacks, p. 3

• “the measurement, collection, analysis and reporting of Internet data for the purposes of understanding and

optimizing Web usage”-- Neil Mason, “The Four Parts of Web Analytics,” http://www.google.com/analytics/cu/ac_the_four_parts.html

Why use it?

• Most archival user study involve intervention or surveys/interviews

• Both are useful • But. . .

– All interventions affect behavior– What people say they do is notoriously inaccurate

• Allows unobtrusive observation of actions (NOT motives or initiative)

• May provide basis for action or further study

Daniel Russell, regarding Google’s Eyetracking studies: “people behave

differently here, they want to make researcher happy, have

been given a free lunch”

Internal Log Data138,041 hits on collection records

6,721 hits on “browse by digital content”

117,468 hits on search page

14,210 hits on “browse by provenance” (12,737 non-staff)

1,855 hits on full finding aid

2,287 hits on “browse by subject”

1,255 hits on “browse by title”

449 hits on “PDF/Deep Search”

Step 1: Analyze—Overview of UIUC ‘non-virtual’ use in 2005/06

Step Two—Understand: Current Website Structure/Purpose

Structure• Facilitate

Contact• Provide

Descriptive Information

• About us; Link to Programs

• Mediate use• Promote

Services

Archival Website Goals:•Provide information on services?•Provide access to descriptive information?•Drive on-line or on-site use?•Facilitate research, service, learning? (Developing Archival Metrics http://www.si.umich.edu/ArchivalMetrics/ )

More Complex

Step Three—Inform: Develop a Privacy Policy

• Google http://www.google.com/analytics/tos.html

– COLLECTS what they term “anonymous traffic data” (includes IP Address)

– REPORTS summary information only– Requires use of a privacy policy

• UIUC Archives http://web.library.uiuc.edu/ahx/about/privacy.php

Step 4—Plan and limit scope:What I tried to measure

• Q1:How do people get to our site?• Q2: What are the most popular pages/groups of

content?• Q3: What are most popular searches?• Q4: How do users move through the net and our

site toward 4 ‘goals’?– Use search form– View record series description– View full finding aid– Send email

Better

My ‘Goal Conversion Funnel’

User visits or uses materials remotely!

Caveat: Does not include direct ‘hits’ via

Google, or other external referrers

Caveat: Does not include emails sent

directly to the address illiarch@uiuc.edu

User enters site after Google Search

- or -

Question One: “Referrers”

Google as “Referrer”

Question Two: Top Content Areas

Pagevisits by Functional Area of Website

About0.4%

Holdings Database

63.3%

Features0.5%Email and

Downloads2.2%

Program Areas25.3%

Homepage6.3%

Guides1.1%

Services0.8%

Top Content:Homepage

July 4 Weekends

6.3%

“Archon” (Holdings Database) Area

Lesson: the Holdings database is the heart of our web presence

Views Record Series Descriptions

Hmmm….

Question Three: What do users search for?

• Can measure both external and internal searches

• Drill down to see ‘clickstream’ and exit pages

Google Keywords (Searches)

4. Movement toward Goals

Goals Overview

Lesson: Most users view our collection information at some point

Goal 1: Views Record Series Description

Re-running searches to analyze how users get to and leave the site

“Clara Hamilton”

YIKES!!!

Wow!Deadend!

“Daily Illini”

17 (!) in Google Result Set

LessonWe MUST provide links to digital content (where it exists) or create it (where it does not exist and users are trying to find it).

“Strip Mines and Illinois”

Clicked! LessonsImportance of controlled subjects area

<title> element usage

Optimize ‘landing page’

It’s the digital content, stupid

Conclusion 1: Beware Making Assumptions about Online Use

• That users enter our main page, then search

• That users see our homepage and use instructional/policy materials linked from it

• That users want to walk a prescribed path to the physical records (DON’T assume visitor intent,

Peterson, p. 25)• That digital content is a ‘value added’

function (in reality it is essential)

Conclusion 2: Google ranksdigital content ‘higher’

Images

Full Description

Conclusion 3: Tailor Site Improvements to Revised Goals

• Add more contextual information to landing pages (e.g. subject)

• Identify materials for digitization (keyword analysis)

• Improve Google page rank by integrating better information into title (66 character rule)

• Improve user experience by being concise and putting most important information first

Conclusion 4: Emphasize content, not description

• GA provides metrics that can drive decision making

• Use keyword analysis to identify content for digitization

Improving the User’s Experience through Web Analytics*

SAA Research ForumChicago, Illinois August 28, 2007

Christopher J. PromAssistant University Archivist

University of Illinois at Urbana-Champaignprom@uiuc.edu

*Special thanks to Beth Yakel, Aprille McKay, and Helen Tibbo!