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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

• deleted 16y ago
  [deleted]
• fab1an 16y ago
  Great question. When we started to researching the models, we expected to build a lot of different ones for different demographics and target groups. However, it turned out that - for the first few seconds of viewing behaviour - we couldn't identify statistically significant differences between a lot of groups - students vs. elder people, male vs. female etc. Note that is only valid for the majority of "normal" websites - we haven't started tracking adult stuff (maybe we should...:) How do we infer whether viewing behaviour between different groups is different / not so different? We take one eye-tracking study with only males and another one with only females, e.g., and try to predict the results of the first with the other (and vice-versa) - if the predictive accuracy remains stable, as compared to the results we get within one group itself, the difference isn't large enough to build another model. We did find differences between two groups, however: people who spent a lot of time online vs. people who barely go online. We're woking on a new model for the "newbies". Also, we're about to roll out a model for males with color vision deficiency - that's 10% of all males who simply won't see the big RED button! :)