A retail company redesigned their email template, moving the main CTA from the top to the bottom because "people need to read the content first." Click rates dropped 40%. When they looked at heat map data from their old template, the pattern was clear: most clicks happened in the top third of the email. Readers weren't scrolling to the bottom.
Heat mapping reveals how people actually interact with your emails, not how you think they should. It's the difference between designing based on assumptions and designing based on evidence.
How email heat maps work
Email heat maps aggregate click data across recipients to show which areas of an email receive the most engagement.
Every click is logged with its position—which link was clicked, where in the email it appeared. When you aggregate thousands of clicks, patterns emerge. Some areas are "hot" (many clicks); others are "cold" (few or no clicks).
The visualization typically uses color gradients. Red or orange indicates high click concentration. Yellow indicates moderate activity. Blue or no color indicates low activity. The result looks like a thermal image overlaid on your email.
Heat maps can show absolute click counts (how many people clicked each area) or relative engagement (what percentage of total clicks went to each area). Both views are useful for different purposes.
Most email analytics platforms offer heat mapping as a feature. If yours doesn't, third-party tools can add this capability by analyzing your click data.
What heat maps reveal
Heat map data answers questions that aggregate click rates can't.
Which links get clicked? If you have five links in an email, heat maps show the distribution. Maybe one link gets 60% of clicks while another gets 2%. That 2% link might not be worth including.
Does position matter? Heat maps often show that links higher in the email get more clicks, regardless of content. This "position bias" affects how you should structure emails.
Do images get clicks? If you have clickable images, heat maps show whether people click them. Some audiences click images readily; others ignore them. Your data tells you which.
How far do people scroll? By looking at click distribution down the email, you can infer how far people scroll. If nothing below the fold gets clicks, people aren't scrolling—or the content there isn't compelling.
Do multiple CTAs help or hurt? Heat maps show whether having multiple CTAs distributes clicks (potentially good) or dilutes them (potentially bad). The answer varies by email and audience.
Interpreting heat map data
Raw heat map visuals need interpretation to be actionable.
Context matters. A link with few clicks might be poorly placed, poorly worded, or simply less relevant to most recipients. Heat maps show what happened, not why.
Sample size affects reliability. Heat maps from 100 clicks are noisy; patterns might be random. Heat maps from 10,000 clicks show reliable patterns. Ensure sufficient data before drawing conclusions.
Email client rendering varies. Your email might look different in Gmail vs Outlook vs mobile. Heat maps typically aggregate across clients, but click patterns might differ by client. Some tools let you segment heat maps by email client.
Compare across campaigns. A single heat map shows one email's performance. Comparing heat maps across multiple emails reveals consistent patterns—maybe your audience always clicks the first link, regardless of content.
Using heat maps for optimization
Heat map insights should drive concrete improvements.
Optimize link placement based on where clicks concentrate. If the top of your email is hot and the bottom is cold, put important links at the top. Don't fight your audience's natural behavior.
Reduce or relocate underperforming links. If a link consistently gets minimal clicks across multiple emails, either move it to a hotter zone, make it more prominent, or remove it entirely.
Test layout changes informed by heat map data. If heat maps suggest people don't scroll, test shorter emails. If they suggest images don't get clicks, test text links instead. Use heat maps to generate hypotheses, then A/B test to validate.
Align content hierarchy with attention patterns. Put your most important content where heat maps show people actually look. Don't bury key messages in cold zones.
Heat maps and mobile
Mobile email reading creates specific heat map considerations.
Thumb zones matter on mobile. People hold phones differently, and some screen areas are easier to tap than others. Heat maps might show different patterns for mobile vs desktop readers.
Smaller screens concentrate attention. On mobile, there's less visible content at any moment, which can actually increase engagement with what's visible. But it also means content below the fold is even less likely to be seen.
Touch targets need adequate size. If heat maps show clicks scattered around a link rather than on it, the touch target might be too small. Mobile users need larger clickable areas.
Segment heat maps by device when possible. Mobile and desktop behavior often differs significantly. Aggregate heat maps might hide important device-specific patterns.
Limitations of heat maps
Heat maps are useful but not comprehensive.
They only show clicks, not attention. Someone might read your entire email carefully without clicking anything. Heat maps would show that email as having no engagement, which isn't accurate.
They can't show hover behavior. On desktop, users might hover over links without clicking. This interest isn't captured in click-based heat maps.
They don't explain why. Heat maps show that a link got few clicks but not whether it's because of placement, wording, relevance, or something else. You need to hypothesize and test.
They require sufficient volume. Low-volume senders might not generate enough clicks for meaningful heat map analysis. The patterns in small samples are often just noise.
Heat maps vs click maps
The terms are sometimes used interchangeably, but there can be distinctions.
Click maps show exactly where clicks occurred, often as dots or markers on the email. They're precise but can be cluttered with high click volumes.
Heat maps aggregate clicks into zones and show intensity through color gradients. They're better for seeing patterns but lose precision about exact click locations.
Some tools offer both views. Click maps help with detailed analysis of specific elements. Heat maps help with overall pattern recognition. Use whichever view answers your current question.
Building heat map analysis into your workflow
Regular heat map review improves email performance over time.
Review heat maps for major campaigns. Don't analyze every email, but do analyze important sends—product launches, major announcements, high-volume campaigns.
Look for consistent patterns across emails. If every email shows the same hot and cold zones, that's a template issue, not a content issue. Redesign the template to match actual behavior.
Use heat maps to inform A/B tests. Heat map insights generate hypotheses. A/B tests validate them. The combination is more powerful than either alone.
Share heat map insights with stakeholders. Visual heat maps communicate engagement patterns more effectively than tables of click rates. Use them to build understanding of email performance.
Frequently asked questions
How many clicks do I need for a useful heat map?
Generally, at least a few hundred clicks for basic patterns, and thousands for reliable insights. With fewer clicks, the patterns you see might be random noise rather than real behavior.
Do heat maps work for plain text emails?
Sort of. You can track which links get clicked, but without visual layout, the 'map' aspect is less meaningful. Heat maps are most useful for HTML emails with visual structure.
Can heat maps show where people look, not just click?
No. Email heat maps are based on click data. Eye-tracking studies can show where people look, but that requires specialized research, not standard email analytics.
Should I redesign my template based on one heat map?
No. Look at heat maps across multiple emails to identify consistent patterns. A single email might have unusual results due to specific content. Patterns that repeat across emails are more reliable.