A few weeks ago, I posted some information about the dangers linked to the mistaken interpretation of ocular data.
While data capture is greatly facilitated thanks to companies like Tobii (I would like to take this opportunity to thank the whole Tobii team for its in-depth work on hardware eyetracking), the analysis of data requires thorough knowledge of the perceptive-cognitive system.
Unfortunately, nowadays to make eyetracking popular, the software on offer is too simplistic to draw reliable conclusions.
What is the conclusion from all the eyetracking surveys? Individual pathways and/or heatmaps.
What analysis can be made on the basis of these data?
- Displaying each user’s pathways. Yes, but how do we draw an overall conclusion from this about the qualities of an interface?
- Displaying all eye fixations. Yes, but what about the order of discovering interface zones, the timing of this discovery, etc.
To us, as experts in behavioural sciences, these data are very important as is fixation quality: has the user read the contents or did he simply pass through there before having time to read? Has he had difficulty understanding the contents, has he hesitated between two browsing components, etc.
Confronted with these unanswered questions, Netway has created its own eye data analysis software on the basis of our own algorithms: EAGLE
Today I present to you two of the tools in our Eagle software. They have been used to analyse Cuil and Google.
Emergence of attention focus
A heatmap will show all fixations but will give neither the order of discovery nor the proportion of users who looked at a zone at the same time.
Our tool makes it possible to analyse the order of discovery of interface zones.
These data are highly valuable to display the distribution of eye fixations of all testers during an interface visit.
- Users leave zone 1 on the Google interface, which is deemed to have attracted most attention, within the first three seconds, reaching approx. 30% of visits after only 3.5 seconds of visits.
- after 6 seconds, zone 3 attains 50% of ocular visits, rising to 90% after 9 seconds, while zone 1 attains 50% of ocular visits after only 10 seconds of visiting the page.
- after 15 seconds, zones 1 and 2 share 50% of ocular visits.
- from the 20th second, 90% of ocular visits are in zone 2.
- Only after 4.5 seconds and up to 8 seconds is advertising used as a way to solve the scenario only by 25%. Overall, advertising never exceeds 25% of ocular visits.
Continue analysing the rest by yourself;)
- zone 1 is visited right from the first seconds
- from 2.5 to 30 seconds, all 6 contents zones are visited in the same way. From time to time, a particular block slightly stands out from the rest but that is not representative.
During the first 10 seconds, Google generates a “standard” behaviour but with avoidance of advertising zones or related links whereas Cuil manages to avoid this type of avoidance behaviour, distributing fixations throughout the contents zones but without a “standard” pathway.
A heatmap will show the relative presence of ocular fixations. The fact is that there are many different types of fixations, depending their length.
For instance, fixation should last between 200 and 350 ms to be able to read. Imagine a zone in which there are many fixations but where no one has read the contents: the heatmap will highlight a major heat zone and yet no one will have read the contents!
Our fixation quality analysis tool makes it possible to highlight the type of ocular fixations and the quality of information uptake within these zones.
- 33% of all ocular fixations recorded on Google are contents-reading fixations.
- 40% of all ocular fixations recorded on Cuil are contents-reading fixations
Information uptake quality on Cuil is better than on Google.
We also record data on pupil diameter, major visual attention zones, etc.
These are only two types of data among more than 50 types which one never sees and which nevertheless make it possible to make fine distinctions between simplistic results recorded in eyetracking.
Imagine the potential of these data when an expert in behavioural sciences analyses interfaces.
Have a nice week.