Eye-tracking is a research method that records where a person looks on a screen and the sequence of their eye movements. A tracker, usually an infrared sensor or webcam, follows the eyes while participants complete tasks.
The data includes fixations, brief periods when the eyes rest on an area, and saccades, rapid movements between areas. Teams visualize these patterns with heatmaps and gaze plots.
Use cases
Eye-tracking helps investigate where visual attention goes and which interface elements may be overlooked.
Missed call to action: Users report difficulty finding a discount field, while gaze data shows little attention below the order total.
Banner blindness: A key alert resembles advertising, and users barely look at it.
Content scanning: A product page receives attention mainly in certain areas, leaving important information overlooked.
How it's used in practice
Start with an attention question: Define what visual behavior you want to investigate.
Define areas of interest: Mark regions such as prices, navigation, or buttons for analysis.
Analyze gaze patterns: Compare fixation count, duration, and sequence across key areas.
Validate interpretations: Use interviews or task performance to understand why participants looked or didn't look at something.
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Pro-tip: Don't interpret a long fixation on its own. It could indicate interest, difficulty, or confusion. Use participant feedback or task behavior to understand it.
Challenges & limitations
Cost and setup: Research-grade equipment and controlled sessions can be expensive.
Lower webcam precision: Webcam-based tracking is less precise than infrared systems, making small interface elements harder to analyze reliably.
Data quality: Calibration problems, camera position, and participant movement can make some recordings unusable.
