Using Heatmaps on a SaaS Website

Heatmaps show where visitors click, how far they scroll and where they move their cursor on a page. For a SaaS website, heatmap analysis is one of the quickest ways to see how people actually interact with the pages that matter most, such as the homepage, the pricing page and the signup flow. Instead of debating in a meeting whether visitors notice the main call to action, you can look.

Heatmaps have a clear limit, though. They show what visitors do, not why they do it. Their value lies in revealing patterns worth investigating, which you then explain with other research and confirm with measurement. This article covers the types of heatmaps, which pages to analyze, what to look for, how to combine heatmaps with other data, and how to turn observations into changes you can measure.

Types of heatmaps

Click maps

Click maps show where visitors click on desktop or tap on mobile, with the most-clicked areas shown in warmer colors. They are useful for seeing whether your calls to action attract attention, for finding clicks on elements that are not actually clickable, and for spotting navigation items that almost nobody uses. A click map often settles arguments quickly, because it makes the distribution of attention visible at a glance.

Scroll maps

Scroll maps show how far down the page visitors get, usually as bands of color that cool as fewer people reach each depth. They help you understand how many visitors ever see a given section, which in turn helps you decide where to place calls to action, customer proof and key explanations. A section that only a small fraction of visitors reach cannot carry much of the page's persuasive work, however well it is written.

Move or attention maps

Move maps track cursor movement on desktop as a rough proxy for attention. They can be suggestive, but treat them with caution. People do not always look where their cursor is, and many leave the cursor parked while they read. Move maps are best used as a secondary signal alongside click and scroll data, never as a substitute for eye tracking.

Which pages are worth analyzing

Focus on pages that have meaningful traffic and a direct effect on the business. For most SaaS companies that means the homepage, the pricing page, the main landing pages for paid and organic campaigns, the signup and demo request pages, and any high-traffic blog posts that carry calls to action.

Low-traffic pages produce heatmaps that are too noisy to interpret. A click map built from a few dozen sessions mostly reflects the quirks of those individuals. It is better to study a few important pages properly than to collect thin data on every page of the site.

What to look for

Ignored calls to action

If the primary call to action gets few clicks while other elements on the page get many, something is competing with it. The button may be unclear, poorly placed, visually weak, or overshadowed by a secondary link that looks more inviting. Look at what visitors click instead, because that often tells you what they wanted. If they click "How it works" in the navigation rather than "Start free trial," they may not yet feel they understand the product well enough to try it.

Clicks on things that are not links

Visitors clicking on images, icons, feature names or text that does nothing are signaling that they expected more. Perhaps they wanted to enlarge a product screenshot, read more about a feature, or see what a particular icon represents. Consider making those elements interactive, linking them to more detail, or adding the information they were looking for directly on the page.

Navigation that pulls people away

Heavy clicks on the main navigation from a focused landing page can mean two things. Visitors may not be finding what they need on the page and are hunting elsewhere, or the navigation may simply be drawing them away from the conversion path. Recordings help tell these apart. If visitors explore and return, the page may be missing information. If they leave and never come back, the navigation may be a distraction worth reducing on that page.

Scroll drop-off

If most visitors never reach a key section, such as pricing details, testimonials or a comparison, that section is not doing much work. You can move it higher, tighten the content above it so people get there faster, or add a short summary near the top that points to it. Look for sharp drops in the scroll map, which often line up with a visual break that makes the page look finished, such as a large footer-like band or a wide image.

Pricing page behavior

The pricing page deserves particular attention, because clicks there reveal what buyers are uncertain about. Clicks on the monthly and annual toggle show interest in billing options. Clicks on feature tooltips show which features need explaining. Clicks on particular FAQ items show which questions matter most. If one FAQ question attracts a large share of clicks, its answer probably belongs more prominently on the page, perhaps directly on the plan cards.

Mobile versus desktop

Behavior on mobile often differs sharply from desktop. A layout that works well on a wide screen can push key content far down on a phone, and tap targets that are easy to hit with a mouse can be awkward with a thumb. Always analyze devices separately. Combining them produces an average that describes neither group accurately.

Combine heatmaps with other data

Heatmaps are most useful as part of a small research toolkit. Session recordings show individual journeys, including hesitation, repeated clicks and the moment someone leaves. Analytics funnels quantify how many visitors drop off between steps, so you know which pages to study. Short on-page surveys asking visitors what they were looking for, or what stopped them from signing up, add their own words. And user tests, where a few people complete a task while thinking aloud, let you hear their reasoning directly.

The combination is powerful. A heatmap might show that visitors ignore a section entirely. A recording might show that they scroll past it quickly, and a survey might reveal that they do not believe the claims in it. Each source adds a piece of the explanation.

How much data you need

Heatmaps need enough sessions to show reliable patterns. A few hundred visits per page and per device is a reasonable minimum for many sites, and more is better. Resist drawing conclusions from a handful of sessions, especially for small elements that only a few people would click anyway. If a page does not get enough traffic, either collect data over a longer period or rely more on recordings and user tests for that page.

Remember to reset or segment the data when the page changes. A heatmap that mixes sessions from before and after a redesign shows a blend of two different pages.

It also helps to segment by traffic source when you have the volume. Visitors arriving from a paid campaign, from organic search and from a newsletter often come with different levels of intent and different questions. A pricing page heatmap dominated by existing customers checking their plan will look very different from one dominated by first-time visitors. If your tool allows it, filter to the audience you are trying to understand before drawing conclusions.

Finally, set a fixed collection window before you look. Checking a heatmap after the first day and redesigning the page around it is the visual equivalent of stopping an A/B test early. Decide how many sessions or how many days you will collect, wait until you have them, and then review the page with the team in one sitting so everyone sees the same data.

A worked example (illustrative)

Consider a SaaS pricing page whose heatmap showed many clicks on a tooltip labeled "What counts as a user?" and relatively few clicks on the plan buttons. Session recordings showed visitors hovering between plans, opening that tooltip, and then leaving without choosing.

The team formed a hypothesis: visitors were unsure how users were counted, so they could not work out which plan they needed or what it would cost. They added a short, clear explanation of user counting directly on the plan cards and moved the related FAQ answer higher on the page. In the following weeks, plan selection improved, and the tooltip received fewer clicks because the answer was already visible.

Privacy and performance

Heatmap and recording tools capture visitor behavior, so configure them carefully. Use tools that mask sensitive fields, such as form inputs, by default, and check that masking actually works on your pages. Respect consent requirements in the regions you serve, which may mean loading the tool only after visitors agree. Check that the tool's script does not noticeably slow your pages, since a heavy script on the pricing page can cost more than the insights are worth. And do not record logged-in areas of your product without a careful privacy review, since those screens often contain customer data.

Turning insights into action

Each finding should become a small, testable change. Start by writing a hypothesis that explains the behavior, such as "visitors are unsure how users are counted." Make a change that addresses it. Measure the impact with analytics, or with an A/B test if you have enough traffic. Then check the heatmap again to see whether behavior shifted the way you expected. Writing the hypothesis down first keeps the team honest, because it makes clear what you expected to happen and whether it did.

Common mistakes

The most common mistake is analyzing low-traffic pages and reading meaning into noise. Mixing mobile and desktop data is close behind, producing averages that hide real problems on one device. Treating move maps as if they were eye tracking leads to overconfident conclusions about attention. Making changes without a hypothesis means you cannot tell whether a change worked or why. And ignoring privacy settings can expose sensitive information and create real legal and reputational risk.

The takeaway

Heatmaps are a fast, visual way to see how visitors interact with your SaaS website. Use them on high-impact pages with enough traffic, analyze mobile and desktop separately, combine them with recordings, analytics and surveys, and turn each observation into a hypothesis you can test and measure.