Practice eye tracking vocabulary: fixations, saccades, heat maps, attention patterns, CTA visibility, and AOI (area of interest) analysis in UX research.
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In eye tracking research, what is a 'fixation'?
A fixation is a period during which the eye is relatively still and focused on a specific point — this is when visual information is actually processed. Fixations typically last 150-600ms. Eye tracking studies measure where fixations occur, how long they last, and in what order — revealing what users actually look at vs. what designers assumed they would look at.
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What is a 'saccade' in eye tracking?
Saccades are the fast eye jumps between fixation points — the eye effectively 'teleports' from one location to another in 20-200ms, and no visual processing happens during the movement. Eye tracking data consists of alternating fixations (processing) and saccades (movement). Saccade patterns reveal how users scan a page — in an F-pattern, Z-pattern, or other scanning strategies.
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'Heat map shows where users look.' What does a heat map represent in eye tracking?
Eye tracking heat maps aggregate fixation data from multiple participants into a single visualisation. Hot spots (red) show elements that attracted the most attention and longest gaze time — these are highly visible. Cold spots (blue/no colour) show areas that were ignored. Heat maps reveal whether users notice key design elements like navigation, CTAs, and value propositions.
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'The user never looked at the CTA.' What does this eye tracking finding indicate?
If a CTA (Call to Action) receives no fixations, it's effectively invisible to users — they're not looking at it. This is a serious design problem: the button may exist but if users never see it, it won't drive conversions. Eye tracking findings like this prompt redesign: move the CTA within the natural scan path, increase contrast, add whitespace around it, or increase its visual weight.
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What is 'AOI (Area of Interest) analysis' in eye tracking research?
AOI analysis defines labelled regions on the stimulus (e.g., 'header navigation', 'hero image', 'CTA button', 'price') and calculates eye tracking metrics for each region: number of fixations, total dwell time, time to first fixation, and percentage of participants who looked at it. This enables statistical comparison between areas and between design variants — for example, 'users fixate on the price area before the CTA'.