What Is Predictive Eye-Tracking and How Is It Different from Live Eye-Tracking?

Predictive eye-tracking with AI is built on various international live eye-tracking studies, conducted in neuroscience labs. The key distinction is simple: predictive eye-tracking predicts, while live eye-tracking measures. AI-powered eye-tracking simulates intuitive, automatic visual attention that occurs during the first 1–3 seconds after someone is exposed to visual stimuli. It focuses on where people are likely to look first. Live eye-tracking, by contrast, tracks real-time gaze behaviour over the full duration of exposure, capturing everything from visual search to engagement and confusion. While predictive models are quantitative and consistent, live testing produces qualitative and highly personalized results (unless conducted at scale, which is rarely feasible).

Both methods serve different purposes and can complement each other in research and validation workflows.

How Does Predictive Eye-Tracking Work? (Brainsight’s Model)

Brainsight’s predictive eye-tracking is powered by validated neuroscience and proprietary AI models trained on visual behaviour patterns. It simulates how the human eye processes visual information in the first few seconds of exposure. This process is rooted in evolution: our reptilian brain instinctively detects key visual cues like faces, contrast, movement, colors, and shapes — all in under 3 seconds. This automatic “visual scan” helps us identify relevant content fast, often before conscious attention kicks in. Since this behaviour is universal across humans, it is highly predictable and consistent, making it possible to model with high accuracy.

How Accurate Is Predictive Eye-Tracking Compared to Live Testing?

By combining neuroscience, proprietary eye-tracking data, and thousands of lab sessions, Brainsight achieves up to 94% similarity between predicted and live eye-tracking results. Validations have been conducted in international studies, including work by MIT (USA) and the University of Tübingen (Germany). Our own AI model is built by Braingineers, a leading neuroscience agency with a deep track record in live participant testing.

Watch this video to spot the difference between predictive eye-tracking and live eye-tracking:

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It’s fascinating to see how closely the predicted heatmaps mirror real eye-tracking results. One visible difference is that AI-generated heatmaps appear more stable, while live eye-tracking maps show dynamic movement caused by individual variability. Despite these differences, the outcome is closely aligned, making predictive eye-tracking a reliable and scalable alternative for early-stage attention insights.

When should you use predictive eye-tracking vs. live eye-tracking?

Predictive eye-tracking fits well with formats where users only spend 1–3 seconds looking, such as display ads, DOOH, social media posts, product thumbnails, mobile app screens, etc. A few examples of use cases are: 

Validate ad creatives for first-glance attention:

- Test landing pages for visual clarity and reduce bounce rates

- Analyze UX design hierarchy (e.g., CTAvisibility, content flow)

- Pre-test multiple creative versions quickly, without live panels‍‍

Live eye-tracking is better suited when you want to explore:

- Emotional engagement (often combined withEEG/biometrics)

- User frustration or confusion

- Complex user flows or task-based interaction

In our former neuroscience lab studies, we used live tracking to detect when in their journey users got engaged or lost, and why they did; insights only real-world observation can deliver. Usually this was a research question from clients when they had analyzed their data (like campaign- or website performance with tools like Hotjar/Contentsquare) and wished to deep-dive on their findings to understand what to do next. With current technologies, this can be partially done online as well (live, online eye-tracking studies).

To dive further into the differences, also see our blogpost that was published in Marketing Facts: "What Every Marketer Should know about Predictive Eye-Tracking". Below we'll explain what predictive attention is based on: