Quick verdict — when to pick which
Your primary output is digital ad creatives, you want a headline number (Attention Score 0–100) plus named sub-metrics, and you need specific, principle-based fixes rather than just a heatmap visualization.
Your work spans UX screens, landing pages, product packaging, and mixed design formats — and you need a general-purpose saliency tool that treats all image inputs similarly.
Saliency heatmaps vs. ad creative scoring
Attention Insight is a horizontal tool. Upload any image — a website mockup, a packaging design, a social ad, a poster — and you'll get back a saliency heatmap that predicts where viewers are likely to look. It's designed to serve designers and UX researchers who need an attention preview without running an eye-tracking study.
GazeIQ is a vertical tool. We only do ad creatives, and we treat that as a feature, not a limitation. Because we know every input is a Meta Feed, Instagram Story, or Google Display ad, we can add a whole layer on top of the saliency map: the Attention Score (0–100), five named sub-metrics, platform mockups that simulate the ad in its native environment, and a recommendation engine that translates heatmap output into specific fixes.
That's the trade-off in one sentence: Attention Insight gives you a high-quality heatmap for anything; GazeIQ gives you a heatmap plus actionable scoring, recommendations, and variant comparison — but only for digital ad creatives.
Feature comparison: GazeIQ vs. Attention Insight
| Feature | Attention Insight | GazeIQ |
|---|---|---|
| Attention heatmap | Yes — general saliency | Yes — TranSalNet, CC=0.907 |
| Element-level scoring | Area-of-interest clarity score | 5 named sub-metrics (CTA, headline, hierarchy, edge, clutter) |
| AI fix recommendations | General observations | Principle-based (Von Restorff, F-pattern, Z-pattern) with specific fixes |
| A/B pre-testing | Side-by-side visuals | Up to 5 variants with winner analysis |
| Platform-specific mockups | Generic image input | Meta Feed, Instagram Story, Google Display |
| Pricing floor | Paid plans, free trial | Self-serve, monthly, real free tier |
| Free tier | Limited / trial | 3 scans, no credit card |
| Time to insight | Seconds | Under 8 seconds |
| Primary use case | General UX and design attention | Digital ad creative pre-testing |
| Ideal team size | Designers, UX researchers | Performance marketers, growth teams, agencies |
Attention Insight feature descriptions based on publicly available product material; check their current pricing and features at attentioninsight.com.
When Attention Insight is the better choice
Attention Insight is a legitimately good tool in its category. Here's when it's the better pick over GazeIQ:
When GazeIQ is the better choice
If "ad creative" is 90%+ of what you're analyzing, GazeIQ's ad- specific layer makes a real difference in speed and decision quality:
Can you use both?
Yes — and for some teams it actually makes sense. We occasionally see design-led organizations where the UX team standardizes on Attention Insight for general design work while the performance marketing team uses GazeIQ specifically for Meta, Instagram, and Google Display creative pre-testing.
If you're picking between them for the first time, though, don't buy both. Decide whether your dominant workflow is ad creative pre-testing (pick GazeIQ) or general design/UX attention work (pick Attention Insight). The overlap is too large to pay for two saliency engines at once.
Frequently asked questions
What is Attention Insight?
Attention Insight is a saliency heatmap tool that uses deep-learning models trained on eye-tracking data to predict where viewers will look on an image or design. It's used across UX design, web design, and advertising, and is popular with designers who want an attention preview without running a live study.
How is GazeIQ different from Attention Insight?
Both use saliency models to predict attention, but GazeIQ is purpose-built for ad creatives while Attention Insight serves a broader set of design use cases. GazeIQ adds element-level scoring (CTA, headline, hierarchy, edge, clutter), named-principle recommendations (Von Restorff, F-pattern, Z-pattern), platform-specific mockups for Meta and Google Display, and A/B pre-testing for up to 5 variants.
Which tool is more accurate?
Both Attention Insight and GazeIQ use published saliency models that correlate strongly with lab-based eye tracking. GazeIQ runs on TranSalNet, which reports CC=0.907 on the SALICON benchmark — among the strongest scores published for static-image saliency. For ad-specific scenarios (where and how CTAs are rendered, edge crops on feed formats), GazeIQ's ad-tuned scoring layer gives more actionable output.
Can I analyze web pages or UX designs with GazeIQ?
GazeIQ will produce a saliency heatmap on any uploaded image, so you can use it on landing pages or UX screens. However, the Attention Score and sub-metrics are calibrated for ad creatives, and platform mockups target Meta Feed, Instagram Story, and Google Display. If most of your work is UX heatmaps across diverse formats, Attention Insight may be a better match.
What does GazeIQ's free tier include?
Three free scans, no credit card required. Each scan includes the full pipeline — heatmap, Attention Score 0–100, five sub-metrics, platform mockup, and AI recommendations grounded in named design principles.