attentioninsight.com

What is Attention Insight?

Attention Insight is an AI-powered visual attention analytics platform. It predicts where people will look when they view a website, ad, product image or short video, generating attention heatmaps and related metrics in seconds rather than running a traditional eye-tracking study.

What it does

The core idea is pre-launch testing. You upload a design or clip, and the platform produces outputs such as an attention heatmap, clarity score, focus score, percentage of attention per element, contrast map and AI recommendations. The page positions this around three goals: validating concepts, fixing attention errors and defending design decisions with data.

Who it is for

The site names designers and marketers as its main audiences, with use cases spanning the design workflow. Two broad scenarios stand out:

• Designers and agencies who need to justify choices to clients or stakeholders, replacing subjective feedback like "make the logo bigger" with shareable reports and attention percentages.
• Marketers and conversion teams who want to check whether a CTA, headline or key visual actually draws the eye before spending on traffic.

How it compares to alternatives

The trade-off is that predictions are modelled estimates, not observed human behaviour, so they are strongest for directional decisions and weakest as a substitute for real conversion testing.

Practical next step

Pick one live page or ad with a clear primary action, generate a heatmap, and check whether the CTA and headline rank among the highest-attention elements. If they do not, adjust hierarchy and re-test before committing budget. For official details on plans and the free trial, see Attention Insight.

How can Attention Insight help me get stakeholder approval for my design decisions?

Attention Insight helps you replace opinion-based design debates with predicted attention data. You upload a design, ad, product shot or short video, and the platform generates an AI attention heatmap plus metrics such as Percentage of Attention, Clarity Score, Focus Score and a Contrast map. The practical value for stakeholder approval is that you can show where the eye is predicted to land, rather than argue that a layout "feels" right.

How it supports the approval conversation

• Make the key element measurable. Instead of saying "the CTA should stand out," you can show the predicted share of attention on the CTA versus the headline or hero image.
• Compare options side by side. Test two or three variations of the same layout and present which one directs more attention to the priority element. This turns a subjective preference into a choice between documented outcomes.
• Answer vague feedback with specifics. Comments like "make the logo bigger" or "it feels confusing" can be checked against the heatmap and focus metrics before you commit to changes.
• Share the evidence. Reports and shareable analysis links let stakeholders review the same visuals without needing a walkthrough from you.
• Use it before launch. Because results arrive in seconds rather than after a weeks-long eye-tracking study, the data is available while decisions are still open.

A concrete scenario

Suppose a client wants the logo enlarged and the headline moved. You run the current design and a revised version, then present both heatmaps. If the revised version pulls attention away from the CTA, you have a defensible reason to keep the original hierarchy — or to negotiate a smaller logo. The conversation shifts from taste to trade-offs.

Where it fits and where it doesn't

Attention Insight is strongest for visual hierarchy questions: which element gets noticed first, whether a CTA is being overlooked, and how a layout compares with a competitor's. It predicts attention, not comprehension, brand recall or conversion. A heatmap is evidence about visibility, not proof that a design will perform commercially. Treat it as one input alongside usability testing and analytics.

Next step

Pick one live design decision that is currently stuck in review. Run the current version and one alternative, then bring the heatmap and Percentage of Attention figures to the next stakeholder meeting. If you need a broader benchmark, Nielsen Norman Group publishes free guidance on visual hierarchy and attention that can frame the discussion.

How do I use Attention Insight's AI heatmaps to optimize my website before launch?

Attention Insight predicts where people will look on a design using AI trained on eye-tracking data, so you can test a page before it goes live. The workflow is: upload a visual (website mockup, ad, product shot or short clip), generate the attention report, then compare what the model highlights against what you actually want users to see first.

A practical pre-launch sequence

1. Define the priority order first. Before uploading anything, write down what a visitor must notice in the first few seconds: usually the headline, the primary CTA, the price or key visual. This list is your benchmark; without it, a heatmap is just a colourful picture.
2. Upload the full-page design or above-the-fold crop. The page evidence describes instant metrics including an attention heatmap, clarity score, focus score, percentage of attention per element, a contrast map and AI recommendations. Treat the percentage-of-attention figure as the most decision-friendly number, because it tells you how much of the predicted gaze lands on a specific object rather than on the page as a whole.
3. Check the CTA against its competition. If your button is drawing less attention than a decorative image or a secondary link, that is a hierarchy problem, not a colour problem. Move it, increase its contrast, or reduce the visual weight of whatever is stealing focus.
4. Run variations side by side. The page positions comparison as a core use case: test two hero layouts, two headline sizes, or a version with and without a promotional banner, and pick the one where attention matches your priority order.
5. Read the clarity and focus scores as diagnostics, not grades. A low clarity score usually points to competing elements or a busy background; a low focus score suggests attention is scattered rather than concentrated. Use them to locate the problem area, then fix it and re-run.
6. Check the contrast map for accessibility-adjacent problems. Text that is hard to see is hard to click, and the contrast map flags elements that may not stand out enough against their surroundings.
7. Repeat on mobile and desktop crops separately. Attention distribution differs between a tall mobile layout and a wide desktop one, so a single analysis rarely covers both.

Where it fits and where it does not

The stakeholder-defence angle is worth taking seriously. The page quotes familiar objections such as "make the logo bigger" and "I'm not feeling it", and positions shareable reports and percentage-of-attention figures as the counter-argument. A concrete scenario: a marketing manager preparing a landing page for a campaign launch can run the design, screenshot the attention report, and show the Head of Growth that the CTA already holds the largest share of attention — or that it does not, and here is the revised version that fixes it.

Decision criteria

Use Attention Insight early, when changes are still cheap, and use it to narrow options rather than to crown a winner. A predicted heatmap cannot tell you whether the message is convincing or whether the form converts; it tells you whether the right elements are visible and dominant. Pair it with a small round of real user testing or post-launch analytics for the questions it cannot answer.

A sensible next step is to pick one page you are about to launch, write your priority order, and run two versions — current design and one adjusted CTA — to see whether the predicted attention shifts in the direction you intended. If you want a broader set of design references while doing this, Nielsen Norman Group publishes research on visual hierarchy and attention, and Baymard Institute covers e-commerce layout and CTA placement patterns.

What are the pricing plans and is there a free trial for Attention Insight?

Attention Insight offers a 14-day free trial with no credit card required, so you can test the platform before committing to a paid plan. The exact plan tiers and prices are listed on the company's billing page, which is the authoritative source for current numbers: Attention Insight Pricing.

What the trial actually lets you do

Based on the page's own description, a trial account gives you access to the core workflow: upload a design, ad, product shot or short clip, and get AI-predicted attention output. The metrics named on the page include:

• Attention Heatmap
• Clarity Score
• Focus Score
• Percentage of Attention
• Contrast map
• AI Recommendation

That combination matters more than the trial length. A 14-day window is enough to run a real comparison — for example, two versions of a landing page hero, or your ad against a competitor's — rather than just clicking around the interface.

How to decide whether a paid plan is worth it

Ask one question: will you use this repeatedly, or once? If you're a marketer or designer validating concepts before launch, the value comes from testing many variations over time, which favors a subscription. If you only need a single pre-launch sanity check, the trial may cover it.

A practical test during the trial: take a design you already have performance data for — a page with a known click-through rate — and see whether the predicted attention on your CTA matches reality. If it does, you have a reason to trust it on the next design. If it doesn't, you've learned that before paying.

Trade-offs to keep in mind

The page frames this as a way to "defend with data" and settle subjective debates like "make the logo bigger." That's a genuine benefit for client-facing work and stakeholder reviews. The limitation is that predictions are not observed human behavior — they're modeled from eye-tracking data. Treat the output as directional evidence to guide and prioritize decisions, not as a replacement for live A/B testing on your actual traffic.

If you want a second opinion on visual hierarchy before launch, tools like Hotjar or UsabilityHub approach the problem from the real-user side, which can complement predicted attention rather than duplicate it.

How does Attention Insight compare to traditional eye-tracking methods?

Attention Insight replaces the physical lab setup of traditional eye-tracking with AI prediction. Instead of recruiting participants, wiring them to hardware and booking a lab, you upload a design and get a heatmap in seconds. The trade-off is that you are getting a statistical prediction of where people likely look, not a recording of where specific people actually looked.

Where the two approaches diverge

What this means in practice

The page frames the core promise as validating concepts, fixing attention errors and defending decisions with data. That last point is the most concrete difference. A designer arguing with a stakeholder who says "make the logo bigger" can point to a Percentage of Attention figure rather than an opinion. Traditional eye-tracking can do this too, but rarely fast enough to sit inside a normal review cycle.

The page also positions competitor comparison as a workflow: analyze your design, analyze a rival's, and look for where attention is being wasted. That is a use case traditional labs handle poorly, because you would need to run separate studies for each stimulus.

Choosing between them

Pick AI prediction when the question is "does this layout direct attention to the CTA, headline or key visual, and which of these three variants does it better?" Pick traditional eye-tracking when the question is "why did users look there, what did they feel, and what did they miss entirely?" The two are complementary: use prediction for cheap, high-frequency screening, then spend lab budget only on the concepts that survive.

A practical next step is to test one live design and one competitor page on the same day and compare their attention distributions. If the difference is obvious without a lab, you have saved a study; if it is ambiguous, that ambiguity is your argument for running one.

Can Attention Insight be used to analyze videos and competitor designs?

Yes. Attention Insight supports both video analysis and competitor-design comparisons, according to its own page content.

Video and short-clip analysis

The site describes receiving feedback on "any design or short clip within seconds," with outputs that include an Attention Heatmap, Clarity Score, Focus Score, Percentage of Attention, Contrast map, and AI recommendations. For video, that means you're evaluating predicted attention on individual frames or short segments, not getting a full timeline edit or motion-tracking suite. A practical scenario: a marketer checks whether a product reveal in the first few seconds actually draws the eye before committing to paid distribution.

Competitor design comparison

The page explicitly lists comparing your results "with competitors" as a way to spot improvement opportunities. This is useful for benchmarking hierarchy and CTA prominence — for example, testing whether a rival's hero layout pulls more attention to the primary button than yours does.

What to weigh

Both rest on AI predictions trained on eye-tracking fixations rather than live eye-tracking studies, so treat results as directional pre-launch evidence.

Next step: run one of your own top-performing assets and the closest competitor asset through the same analysis, then compare Percentage of Attention on the primary CTA before deciding what to change.