Attention Insight

Attention Insight is an AI-powered pre-launch analytics platform that generates eye-tracking heatmaps and visual attention metrics for websites, ads, product designs, and videos — without requiring any human participants. The platform's homepage states it has tested over 611,709 images and claims its AI produces heatmaps that are up to 96% accurate compared to real eye-tracking studies.

What It Is

Attention Insight sits in the visual UX research and design validation category. It uses a Convolutional Neural Network trained on data from real eye-tracking studies — the FAQ states the algorithm was built from a dataset of 30,800 images — to predict where viewers will focus their attention within the first 4–5 seconds of viewing a design. The output is a set of quantitative and visual metrics that designers, marketers, and UX professionals can use to validate concepts, compare design variations, and present data-backed decisions to stakeholders before launch.

Core Metrics and Features

The platform delivers a suite of attention analytics accessible from a web app and several integrations:

• Attention Heatmap — warm-to-cold color overlay showing which areas attract the most and least attention
• Percentage of Attention (AOI) — exact percentage of attention received by a user-defined Area of Interest, such as a CTA button or headline
• Focus Map — shows which elements are noticed or missed within the first 4 seconds
• Clarity Score — rates design clarity on a 1–100 scale across four categories (Severe Difficulty, Moderate Difficulty, Optimal Clarity, Too Simple), benchmarked against top Alexa-ranked sites in the same category
• Focus Score — measures attention density and concentration
• Contrast Map — divides the image into zones to assess color contrast against WCAG 2.2 guidelines
• Design Comparison — side-by-side A/B testing of two or more design variants
• AI Recommendations — generated by a Vision LLM model, providing tailored suggestions on conversions, attention distribution, color, and contrast
• AI Recommendations for AOI — targeted LLM-generated suggestions for specific design objects the user defines
• Instant Reports — downloadable PDF or PPT reports including all metrics, available in English or Spanish, with white-label theme option

Integrations and Plugins

Attention Insight extends into several design and browser environments:

• Figma plugin (including a Visual Usability Checker variant)
• Adobe Express add-on (free)
• Adobe InDesign plugin
• Adobe Photoshop plugin
• Sketch plugin
• Google Chrome Extension (allows analysis of live webpages, including below-the-fold sections, with control over cookie banners and pop-ups)
• REST API for embedding heatmap generation into third-party workflows

The platform supports analysis of desktop designs, mobile designs, marketing materials (banners, posters), and short video clips.

Audience and Use Cases

The platform targets designers, UX professionals, and marketers who need fast, pre-launch feedback without recruiting test participants. The FAQ lists use cases including conversion rate optimization, A/B testing marketing materials, auditing existing designs, validating design ideas, proving design decisions to clients, and benchmarking against competitors. The homepage states the tool is "trusted by over 2500 marketers worldwide" (vendor-published claim). The FAQ notes the algorithm is not recommended for designs in right-to-left or downward-reading languages such as Hebrew or Mandarin.

Technology Foundation

The underlying model is a Convolutional Neural Network trained on eye-tracking fixation data from previous research studies. According to the FAQ, the training dataset includes 30,800 images and participant demographics spanning ages 7 to 60+, with 58% women and 42% men. The platform's technology page claims accuracy of 90–96% compared to real eye-tracking studies. Because the model predicts attention from the first 4–5 seconds of viewing, the FAQ states demographic differences in visual attention are minor during that initial window, which is why the tool does not offer separate heatmaps by demographic group.