Know how people will see your design, before they see it. Eyequant predicts where attention goes, what gets missed and what needs…
Sub-Category
Heatmap Tools
Directory of heatmap and click-tracking tools for seeing how visitors actually behave on a page, used to diagnose and fix poor conversion rates.
2 businesses
We uncover the user experience obstacles that cost your web business the most revenue. How much is your website leaving on the…
These tools capture what happens on a page after someone arrives — where they click, how far they scroll, where their cursor lingers, which elements they ignore entirely. A script sits on your site and turns that raw behaviour into visual overlays: click maps, scroll-depth reports, session recordings, sometimes AI-generated attention or gaze predictions modelled on real eye-tracking data. The output replaces guesswork with a picture of what a real visitor did on a specific page, which is a different kind of evidence than a conversion rate or bounce percentage on its own.
People start looking for this when a page isn't converting and the standard analytics can't say why. You can see that visitors land on a pricing page and leave, or that a form has a high drop-off rate, but not which field stopped them, whether they scrolled far enough to see the call to action, or whether a redesign quietly buried something that used to work. It also comes up when a team is arguing over a design decision with opinion instead of evidence, or when a new landing page has just gone live and someone wants proof it behaves as intended before more ad spend goes into it.
The main split is between tools that watch real visitors and tools that predict attention before a page has any traffic at all. Recording-based tools give you actual click maps, rage-click detection, and session replays, but they need a reasonable volume of visitors before the data means anything — a low-traffic page will just show noise. Predictive or AI-driven tools score a static design or mockup against models trained on real gaze data, which is useful pre-launch but is a simulation, not an observation, and quality depends on how well that model was validated.
Beyond that, compare how well a tool segments data by device, traffic source, or user type, whether it includes funnel or form-level drop-off analysis rather than just page-level clicks, how it handles privacy when recording sessions that touch personal or payment fields, and whether it's a standalone point tool or bundled into a wider CRO or testing platform you'd otherwise have to integrate separately.