Visual Attention Analysis Explained

What Is Visual Attention Analysis (VAA)?

Visual Attention Analysis (VAA) or Predictive Eye Tracking (PET) is a new type of neuromarketing technique that uses an AI-based predictive eye-tracking analysis system to evaluate the visual effectiveness of stimuli, ranging from branding and advertising to packaging design.

Visual Attention Analysis (VAA) Vision One

The system takes into account visual features such as colour, contrast, size, orientation, faces and much more to provide instant feedback on the visual performance of static and dynamic stimuli. Analysis is based on comparisons against real eye-tracking data sets to predict where a person will look, how long and even in what order. Outputs of VAA are similar to those of real eye-tracking, including heat maps, opacity maps and gaze plots. Users can also select Areas of Interest (AOIs), providing statistics on visibility, time to first fixation, fixation length and much more.

VAA is often used as an alternative to regular real eye tracking as it is a much cheaper, faster neuromarketing technique. VAA is often used alongside traditional market research to evaluate the effectiveness of print media, digital ads, packaging designs, shelf layouts and signage. For example, you could use VAA to determine which elements of a web page attract the most consumers’ attention, helping inform brands how to create more effective formats and layouts.

Latest News

Keep up to date with the latest news from Vision One.

Heurisitics Explained

Heuristics are mental shortcuts used to simplify decision-making. Common types include availability, representativeness, anchoring, and affect heuristics. They help speed up judgments but can lead to cognitive biases. Heuristics are essential in everyday thinking, user experience design, and behavioral research, highlighting how humans process information under uncertainty or limited time.

READ MORE
Data Science

Data science is the practice of extracting meaningful insights from large and complex datasets using statistical analysis, programming, and machine learning. In market research, it helps identify patterns, predict behaviours, and support data-driven decision-making across customer segmentation, trend analysis, pricing strategies, and campaign optimisation.

READ MORE