Thanks for the feedback and also for being the first person to comment on my new blog!

I understand what you’re saying about the kind of data merge you can get with the synchronization of think-aloud and eyetracking, and I do agree that it looks like a useful approach to take. My point really is that are often likely to be trade-offs when you combine two approaches. For example, you’d never attempt quantify task completion time in a think-aloud protocol because the constant human intervention interrupts the task. Thus, you get think-aloud data at the expense of quantitative data. The same must be true to a degree with eyetracking studies – if you interact with the test subject, you’re not really quantifying the same thing as you would were they left to do the task on their own. This doesn’t mean that one approach is necessarily better than the other; it just depends on what the question is that you want to answer with your user testing. In some cases, a mixture of eyetracking and think-aloud may be best approach to take. In others, pure eyetracking studies in a more formal test scenario may be the right way to get the data you need.

I think or – better – I’ve experimented that eyetracking and think-aloud can go together. You might want to use a simpler think-aloud protocol (since it’s obvious to the eyetracker what the user is looking at even though she doesn’t mention it in her think-aloud).

We use to both (i) videotape and (ii) gaze record the user behaviours (i) and interactions (ii) in a way that makes possible for us to have a deep quantitative (mainly ii) and qualitative (mainly i) analysis.
So – for example – we can say that while the user was upset (i) for not finding the “search” field she actually looked at it (ii) several times with no understanding of the field functions. This kind of data merge would be impossible without the syncronization of eyetracking test and think-aloud.

Just my humble opinion.