This is awesome. I had a quite fun time allowing my eyes to play over the pages as if I was looking at them to book a flight and took the care to make a summary retrospective note of where my eyes had travelled.
I'm normally completely unaware of where my eyes move on a page. Interestingly, I found that when I switched my view from the normal to the eye-quant diagram, it was immediately apparent that they'd got it harrowingly right. They really do seem to have the play of my attention pretty much down. Almost scary.
This gets me thinking. I don't know what eyequant's business model is, but it occurs to me that they could do an amusing sideline in training web-designers accurately to anticipate where people will look when they see web-pages. I feel that if I did 300 normal/eyequant pairs in sequence, I could gradually become aware both of my eye-movements, and also of those that people would normally make.
I'm reminded of the research that shows that the feedback loops available to doctors who predict disease from x-rays is too slow, so that often their skills deteriorate without them knowing as their career progresses. It was shown that if these doctors are given x-rays from the past to judge where the results are already known, so that they can then be given immediate feedback, their skills quickly recover and then improve. Feedback's obviously vital to learning.
Graphic designers, even if their web-pages are being A/B tested the whole time, just don't get sufficiently speedy and dense feedback to ever gain anything but the most rudimentary skill in anticipating where people's attention will go.
Eyequant seems to have this nailed. Guess that's what you get with Christoph Koch on your team. But it would be pretty awesome if the technology could be used to help make graphic designers (or anyone indeed) to become aware of the forces on their attention.
As a HCI nerd I find this tech very interesting but I am skeptical about the extraordinary claim that EyeQuant - the technology developed and employed by Whitematter labs in this analysis - can, "predicts within seconds where users will look and what users will see" [1]. Where is the equally extraordinary evidence? Any kind of prediction of human behavior is very hard and subject to all kinds of exceptions. For instance, are the predictions applicable to all people wrt age, gender, culture, etc? What about something as basic as people whose language are Right-to-left (arabic, hebrew)? I haven't found any information in English that offers any scientific explanation how EyeQuant performs its predictions.
glad you asked - (I'm one of co-founders of EyeQuant.)
In a nutshell, EyeQuant's predictions use a model of human attention that is based on hundreds of empirical eye-tracking studies, which were conducted at the Neurobiopsychology Lab at the University of Osnabrueck, Germany - also, we're cooperating with Caltech and USC.
The models only represent the cultural background of tracked subjects - it's strictly data-driven. Our current model is representative for western subjects; it can't predict, e. g., people who usually read Farsi.
It also only predicts the first 3-5 seconds.
Here's the method:
In the eye-tracking studies, we present subjects with websites from different categories and track their fixations - more importantly, we also analyze the statistical features of the fixated spots (around 50 of them to date): color contrasts, luminance, shapes and location, to name a few of the very basic ones.
In the next step we build models based on the weight of these features and evaluate them with other eye-tracking studies as a gold standard. One eye-tracking study typically predicts another one with 90-95% accuracy for the first few seconds (ROC). With EyeQuant, and after 5 years of foundational research, we achieve around 84% predictive accuracy - that's pretty close to what you'll get with an empirical study, but the results are available within seconds.
Thanks for providing more information about EyeQuant. One thing that I wonder about is how sensitive your system is wrt the customer's users. If I am running a gaming site where most users are men between ages 12-39, will you only use data from test subjects that share similar characteristics?
It's cool that the young upstarts have the better UI. In a sense, it makes sense that the advertisements on Expedia and Orbitz are so distracting: advertising is supposed to grab attention! I wonder how much money these big players are making off these ads, and if it is enough to counter-act the effect of a poor UI. Over time users will discover HipMonk and other travel sites and won't come back.
EyeQuant isn't replacing eye-tracking studies in the narrow sense - it's a completely new use case:
We predict the first 3-5 seconds, not more - but the results are available instantly via a web service (and as a flat rate.)
This helps you to optimize designs iteratively: you upload a screenshot, get the results and optimize the design accordingly - now the great thing is, that you can re-test your changed version instantly, which wasn't possible before.
In our lab, we do a lot of eye-tracking to just evaluate and the results (and refine the models) - here's a comparison with a large eye-tracking study conducted by Tobii: http://bit.ly/frTdh5
Hipmunk is great, but I could not actually book a flight there. For that I was sent to Orbitz, which showed a long list of flights along with the one I already selected.
