Usability, IA, and Analytics
Clikz.com - 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
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