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EyeQuant, a Berlin firm that helps companies such as Google(s goog), Spotify and Barnes & Noble(s bks) figure out where their users are most likely to look, has raised $650,000 in funding. It intends to use the cash to branch out from webpage and email analysis to the mobile space and beyond.
EyeQuant is an intriguing outfit, using neuroscience as a marketing aid. Similarly to 3M(s mmm)’s Visual Attention Service, Feng-Gui and AttentionWizard, EyeQuant tells clients which parts of a webpage or ad are most likely to draw the user’s gaze. It does so in an automated fashion, which is only 90 percent as accurate as performing eye-tracking with live subjects, but much quicker and cheaper.
Here, for example, is EyeQuant’s take on GigaOM’s front page:
However, CEO and co-founder Fabian Stelzer suggested to me that EyeQuant has a significant technical advantage over those rivals:
“In terms of direct competitors, there are a few companies that claim to do the same thing that we do, but there’s a big difference in the way they do it. They are all using an open source library that’s freely available for download and was actually built by people who are now on-board with EyeQuant for teaching.
“The professors we work with are the inventors of the method, which was initially built to understand the human visual cortex better and model it. If you do a PhD in the neuroscience of attention, you would be using that code.”
Stelzer suggested this open source library was “a good starting point” but not tailored to websites, mobile apps or outdoor advertising, which require a “data-driven model” based on lengthy eye-tracking experiments.
EyeQuant is the exclusive licensee (for sales and marketing purposes — there are apparently non-civilian licensees as well) of a Caltech patent authored by those professors, Christof Koch and Laurent Itti. Co-founder Peter Koenig is also a neuroscience professor.
“The specific process of taking eye tracking data and turning it into specific models is something only we can do,” Stelzer said. He added that the team had refined this peer-reviewed modelling method to the point where new models can be developed within a month.
And that’s where the $650,000, raised from investors such as Ballpark Ventures and Robin McIlvenny, is going to go: rolling out new models for different sectors. Mobile app analysis is EyeQuant’s top priority, but it will also be applying its technology to the retail space – helping retailers arrange their wares more seductively, for example.