Attention insight platform predicts, where users will look while engaging with content.
It lets identify visual attention errors and get insights on user’s attention shifts without data collection.
- Areas of interest
- Complexity score
A system is based on deep learning and trained with previous eye tracking studies data.
Approximately 30 800 images.
The age of each study participant varies from 7 years old to about 60+ years old. However, most participants fell into the 21–30 age bracket.
Most eye-tracking studies have almost equal gender distribution. On average, every study has been tested by 58 % women and 42 % men.
Although, we publish that accuracy of prediction for websites is 90 %, our inside number is 93 %. The reason is that we don’t have enough users per study to get a reliable golden number yet.
An eye-tracking device has been recording the participants’ eye movement for 4 s.