Web Analytics and Usability Testing
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This document discusses how web analytics and usability testing each have strengths and weaknesses for understanding user behavior on websites. It recommends triangulating the two approaches to gain a more complete picture. Specifically, it suggests using usability testing to understand user goals and intent, identify potential problems, and confirm findings from analytics. Analytics can provide real-world data on user behavior at scale but lacks context. By combining the approaches, researchers can focus testing efforts and understand the severity and extent of any issues. A case study example is provided on how triangulation helped understand specific form errors and abandonment rates.
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Web Analytics and Usability Testing
- 1. Web Analytics and Usability Testing: Triangulate your way to better design recommendations by Eva Kaniasty
- 2. What’s your favorite method?
- 4. Who wins the battle?
- 6. Usability Testing Moderator Required Moderator Bias Recruiting Bias Unrepresentative Participants Artificial Situation Task Design Bias Small Sample Results not Generalizable
- 7. Usability Testing 3 users experienced X… Consider changing X to Y.
- 8. Usability Testing is Disconnected
- 9. Web Analytics are Awesome!
- 10. Web Analytics No Moderator Automatic Data Collection/Analysis Real Users “ In the Wild” Real Goals Real Tasks Representative/ Large Sample Size
- 11. Numbers and graphs: universally beloved
- 14. Visitor/Session Tracking Confirm Usability Test findings Inform usability testing tasks Some visitor characteristics: locations, browsers, OS Visit & page view trends Engagement measures: time on page Search data: keyword referrals Custom tracking: detailed information on paths/goal conversion Uses Data Gathered
- 16. Clickmaps/Heatmaps IA Visual hierarchy Interface refinement Info not on just which pages are being accessed, but from where Full picture of users’ interactions with the page Measure of user interest/engagement Some segmentation by browser/screen size/time to click Uses Data Gathered
- 18. Email Data Mining Utest Recruiting Profiles Personas Demographics Geography User Profiles Site usage data: accounts on amazon, facebook, linkedin, etc. Uses Data Gathered
- 20. Session Recording Identify potential usability problems QA/Browser Testing View all interactions with page, including mouse movements Scroll maps Form analytics Uses Data Gathered
- 21. A/B or Multivariate Testing
- 22. A/B or Multivariate Testing IA Visual hierarchy Interface refinement Relative success of design alternatives: impact on conversion and other engagement measures Uses Data Gathered
- 24. Unmoderated Usability Testing Alternative to usability testing, when large samples are required Compensate on weaknesses of survey methods Immediate feedback from real users as they engage with the website Uses Data Gathered
- 25. Custom Metrics
- 26. Custom Metrics Sky is the limit Functionality usage Form errors Patterns of use Conversion measurement Uses Data Gathered
- 27. The what. But why?
- 28. Analytics Suck
- 29. Web Analytics Data on current state only Overwhelming amounts of data to analyze One-dimensional view (i.e. Page-level data only from Clickmaps) Limited information about context No info about user intent
- 30. Usability Testing is Awesome
- 31. Usability Testing Ability to test new interfaces/ prototypes Moderator can probe to clarify intent Info about goals Rich data/ holistic view
- 32. Triangulate!
- 33. Triangulate Focus Deep Data Goals and Intent Confirm Problems Extent Severity Usability Testing Analytics
- 34. Case Study Form errors No abandonment Confusion about messaging Detail on types/extent of errors True abandonment rates Visual hierarchy problems Usability Testing Analytics
- 35. Triangulate Surveys Analytics Usability Testing
- 36. Questions first
- 37. CSI or Law & Order?
- 38. Questions? Twitter: @kaniasty [email_address] kaniasty.com
- 39. Resources Google Analytics Crazyegg Clicktales Keynote Systems