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Researching UX: Analytics

Book Description

Good UX is based on evidence. Qualitative evidence, such as user testing and field research, can only get you so far. To get the full picture of how users are engaging with your website or app, you'll need to use quantitative evidence in the form of analytics.

This book will show you, step by step, how you can use website and app analytics data to inform design choices and definitively improve user experience. Offering practical guidelines, with plenty of detailed examples, this book covers:

  • why you need to gather analytics data for your UX projects
  • getting set up with analytics tools
  • analyzing data
  • how to find problems in your analytics
  • using analytics to aid user research, measure and report on outcomes

Table of Contents

  1. Researching UX: Analytics
  2. Notice of Rights
  3. Notice of Liability
  4. Trademark Notice
  5. About Luke Hay
  6. About SitePoint
  7. Preface
    1. Who Should Read This Book
    2. Conventions Used
      1. Tips, Notes, and Warnings
    3. Supplementary Materials
  8. Why Analytics?
    1. The Importance of Analytics for UX
      1. Advantages of Using Analytics in Your UX Process
      2. Arguments Against Using Analytics
    2. Defining Qualitative and Quantitative Data
      1. Quantitative Methods
      2. Qualitative Methods
    3. A Look at Some of the Analytics Tools Available
      1. Website Analytics Tools
      2. Heatmapping and Session Recording Tools
      3. Split Testing Tools
      4. Other Useful Analytics Tools
    4. Using Tools Together
    5. Analytics Tools Summary
  9. Getting Set Up
    1. Checking Your Setup
      1. Accounts, Properties and Views
      2. Getting Access to Analytics
    2. Analytics Checklist
      1. Is the Analytics Code Installed on Every Page?
      2. Is the Analytics Code Installed in the Correct Place?
      3. Are Custom “Events” Set Up?
      4. Are Custom “Goals” Set Up?
      5. Is Ecommerce Tracking Set Up?
      6. Is Internal Site Search Set Up?
      7. Have Demographic Reports Been Enabled?
      8. How Much Data Do You Have Available?
      9. Does Your Analytics Data Match Other Data Sources?
      10. Is Your Analytics Account Well Annotated?
      11. Has Content Grouping Been Set Up?
    3. Common Pitfalls to Avoid
      1. Confusing Visits and Views
      2. Obsessing over Visits and Views
      3. Getting Drawn into the Numbers
      4. Thinking Low Numbers Are Always Bad
      5. Confusing Correlation with Causation
      6. Grouping All Visits Together
      7. Analyzing Too Broadly
      8. Focusing on Numbers Rather than Trends
      9. Including Bot or Spam Traffic
      10. Not Customizing Your Setup
      11. Not Generating Actionable Takeaways
    4. What Next?
  10. An Introduction to Analyzing Data
    1. Key Analytics Terms
      1. Dimensions and Metrics
      2. Sessions, Visits, Page Views and Unique Page Views
      3. Users and Visitors
      4. Visit/Session Duration and Time on Page
      5. Bounce and Exit Rates
      6. Conversions and Goals
      7. Segments and Filters
    2. A Guide to the Google Analytics Interface
      1. Navigating the Google Analytics Home Page
      2. Navigating the Main Google Analytics Interface
      3. Navigating Google Analytics Graphs
      4. Navigating Within Google Analytics Reports
    3. Analyzing Your Data
      1. Analysis Over Time
      2. Analyzing Different Groups
      3. Analyzing Data from Different Tools
      4. Analyzing Data Outside of Your Analytics Packages
    4. Analyzing for UX
  11. Finding Problems with Analytics
    1. Individual Pages
      1. Bounce and Exit Rates
      2. Time on Page
      3. Page Value
      4. Leakage
      5. 404 Error Pages
    2. Underperforming Content
      1. Content Grouping
    3. User Journeys
      1. Identifying Drop-off Points
      2. Navigating Between Individual Pages
      3. Goal Funnels
      4. Analyzing Funnels
    4. Interactions with On-page Elements
      1. Event Tracking
      2. Click Mapping
      3. Scroll Mapping
      4. Session Recordings
    5. Discovering “Hidden” Content
      1. Search vs No Search
      2. Search Terms
      3. Pages Where Search Is Used
    6. Device and Browser-specific Issues
      1. Browsers
      2. Devices
    7. Finding Problems with Analytics
  12. Analytics for User Research
    1. Where Analytics Sits in the Research Process
    2. Knowing Your Users
      1. How Do Users Find Your Website?
      2. Where Do Your Users Come From?
      3. What Language Do Your Users Speak?
      4. What Devices and Browsers Are They Using?
      5. What are the Genders and Ages of Your Users?
      6. How Frequently Are Your Users Visiting?
      7. What Content Are They Interested In?
    3. Using Data for Personas
      1. Using Data for Persona Creation
      2. Creating Persona-based Segments
      3. Using Persona-based Segments
    4. Benchmarking Against Competitors
      1. Benchmarking in Google Analytics
      2. Other Benchmarking Techniques
    5. An Analytics-first Approach to User Research
  13. Measuring and Reporting Outcomes
    1. Split Testing
      1. A/B Testing
      2. Multivariate Testing
      3. Multi-page Testing
      4. Which Type of Split Test Should I Use?
    2. What to Consider When Setting up Split Testing
      1. Targeting Your Test
      2. Choosing Your Goals
      3. Duration of Test
    3. Analyzing Split Test Results
      1. Statistical Significance
      2. Segmenting Your Results
      3. Integrating with Analytics
    4. Before/after Testing
      1. Running Before/after Testing
      2. Problems with Before/after Testing
      3. Analyzing Before/after Testing
    5. Design Changes and Returning Visitors
    6. Reporting to Clients or Internal Teams
      1. Reporting on the Results of Split Tests
      2. Reporting Before/after Results
      3. Ongoing Reporting
    7. Using Analytics for Continuous Improvement
    8. Measuring and Reporting are Crucial
    9. Conclusion
      1. Next Steps
  14. Google Analytics Glossary