Editor’s note: Juliet Bakhmut is senior content strategist at research firm CoolTool, San Francisco. This is an edited version of a post that originally appeared under the title, “The ultimate guide on how to analyze eye tracking data.”
Running eye-tracking tests has become like a walk in the park. That is not a joke. Wireless eye-trackers and accessible software make it very easy for any researcher or marketer to get in-depth insights into consumers’ behavior on a website (including mobile sites), during the watching commercials (that is crucial for understanding advertising effectiveness) and at the moment of observing shelves with products (to get to know what package was the most attractive).
That said, the accuracy of eye-tracking insights still can be questionable, since many researchers don’t take into the account a number of peculiarities of the eye-tracking process which compromises the quality of final data.
In order to address this issue, we referred to the knowledge of neuroscientist Tim Holmes. Check out the tips below on how to conduct proper eye-tracking tests and to achieve ultimate data accuracy.
Even the most meticulously planned neuromarketing research, regardless of how perfect it looks on paper, can fail in real life conditions.
Before launching full-scale research, gather several participants and walk through the test logic with them. Test both the logic framework of the test and applied equipment.
Do it slowly, step-by-step, and consider participants’ feedback. It’s better to polish small inconsistencies and mismatches at the early stage of the research than to deal with consequences of large volumes of inaccurate data collection.
It’s worth calibrating your eye-tracking equipment correctly in order to ensure the proper mapping of gaze.
When testing a particular object on screen it’s always worth remembering that regardless of how strong w...