Mobile Eye Tracking | Measure Natural Viewing Behavior | eye square
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Observing people naturally interacting with products and media is for us both an ideal and a challenge.  The possibilities that mobile eye tracking offers are extremely diverse and go far beyond laboratory studies.

Our mobile eye tracker PUPIL was developed in cooperation with MIT graduates

For over 20 years, eye square has researched in the area of visual attention at various touchpoints. Together with graduates from MIT Massachusetts Institute of Technology, we are developing 3D-printed glasses with high-resolution cameras. The principle remains the same: a camera is directed at the environment (World Cam), and one on the pupil (Eye Cam). An algorithm projects one onto the other.

The Pupil Eye Tracker measures the attention of your customers in HD

Your options

The pupil Eye Tracker is tailored to our needs: HD resolution, can be worn for hours and is truly lightweight; self-calibrating for a quick start, even under unfavorable conditions. For us, this is a revolution in mobile research. For our clients, it allows us to provide totally new study types, saving costs and time.


A sample of applications:

  • reading real, paper magazines right off of a shelf.
  • use of navigation systems while driving.
  • orientation on real supermarket shelves.

Mobile devices can be tracked particularly well with head-mounted eye trackers. They are able to automatically detect markers, making the analysis process easier. The 2-4 markers define a particular device (phone, tablet, TV) or an area (dashboard, newspaper).

40 grams, the lightest Eye Tracker in the world

In practice, what does this method look like?

For Facebook, we visited 763 study participants from six countries (Germany, France, England, USA, Brazil, and Indonesia) in their households and conducted the most comprehensive, global, multiscreen eye-tracking ethnographic study to date.
To collect data, we used a unique mobile combination of HD eye tracking, content recording and encoding. We paid attention to which screens on what devices had the users’ attentions, along with what content was on which screens.