Clicks & Notes

02 March 2005

Usability, IA, and Analytics - Prioritize Usability Testing and Web Analytics

  • usability testing and web analytics have a common goal – measuring a site’s ability to drive user conversions – but they approach this differently:

    Web analytics measure visitor intent and persuasive momentum, as well as the site’s ability to move visitors through a conversion scenario.

    Usability examines the site’s interface and process barriers that keep visitors from accomplishing a conversion task.

  • using analytics allows you to track actual actions taken on the site, in real time, with a very large sample group
  • usability testing, with individual respondents, provides insight into what happens in particular instances; however, artificial nature of the testing environment doesn’t necessarily provide an accurate reflection of user engagement
  • on combining the two approaches:

    Generally speaking, use Web analytics to determine where to make site changes and usability tests to determine what to test.

(Via Column Two.)

Update 03 March 2005: One thing that occured to me (and is not – in my mind – explicity stated in the above-noted article) about making use of both web analytics and usability testing when optimizing your site:

  • analytics will tell you where the roadblocks occur on your site; usability testing will tell you why

Hurol Inan - Web Analytics – The Voice of Users in Information Architecture Projects, and Hurol Inan - Information Architecture through Web Analytics

  • both articles discuss incorporating web analytics into the information architecture process
  • areas examined by a web analyst include:
    • Website usage by content category
    • Popular and not-so-popular elements of each content category
    • Affinity between content categories
    • Major tasks and possible frustration points
    • On-site search usage, including where users revert to searching

Hurol Inan - Information Architecture – The Key to HTML Email Optimization

  • designing an HTML email is also a form of information architecture
  • regarding email click-to-open rates:

    A great majority of users only click on a single link – with the average number of clicks by a clicking user ranging anywhere from 1.2 to 1.8

  • applying IA principles to email can improve this rate dramatically – in one case:

    We saw a 50% improvement on the click-to-open rate and a four-fold increase on clicks on feature content.

(Preceding three links via iaSlash.)

See also this previous post: Web Analytics and Continual Site Optimization

⇒ Filed under:  by jen @ 11:23 pm


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© Jennifer Vetterli, 2005