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AI-Powered design analytics

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.

Pilots with:
How to analyse design?
The heatmap is a visual representation of how user’s attention distributed in design.

Heatmaps use different colors to depict the amount of fixations for different parts. Warm colors like red and yellow represents which areas attracted more fixations.
Areas Of Interest calculates the percentage (%) of attention that object got.

It enables users to compare the performance of different variations of the same object design. AOI are set by user when the test is created in the system.
Complexity score is the key ingredient to describe how attractive web page looks like to new users.

It ranges from 1-100 and show how visually overloaded design is. 100 is super complex.
Artificial intelligence

A system is based on deep learning and trained with previous eye tracking studies data.

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To get a result
Aggregate eye tracking data sets
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Accuracy of prediction for websites
Designs analysed
Let’s grab and keep your customer’s attention. 
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Popular FAQs

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.