I use heatmaps almost every week when assessing product pages that underperform. They’re one of those deceptively simple tools: a visual layer over your interface that instantly tells you where people look, click, and scroll — and, more importantly, where they don’t. In this piece I’ll walk you through a practical, repeatable workflow I use to prioritize fixes on low-converting product pages. No theory-only takeaways — just step-by-step actions you can apply today.
Why heatmaps matter (and what they won’t do for you)
Heatmaps are fantastic for turning abstract problems into concrete, visual signals. They help with:
- Discoverability issues: Are people finding the CTA or price?
- Content prioritisation: Which features, images or copy are actually getting attention?
- Experience leaks: Are users clicking non-clickable elements out of confusion?
They’re not a silver bullet. Heatmaps won’t tell you why users behave a certain way, nor will they replace session recordings, funnel analysis, or qualitative interviews. Think of them as a high-signal diagnostic tool that points you to the right experiments.
Choose the right heatmap type and tool
There are three heatmap types I care about:
- Click heatmaps — show where users click (or tap). Great for CTAs, interactive elements, and mistaken click patterns.
- Move/hover heatmaps — approximate attention on desktop where mouse movement correlates with gaze.
- Scroll heatmaps — show how far down the page users make it, which helps with content placement and hero-to-CTA alignment.
My go-to tools are Hotjar (simple and fast to deploy), FullStory (rich session replay + eventing), Crazy Egg (useful for A/B split heatmaps), and Microsoft Clarity (free, with robust scroll maps). Pick one that integrates with your stack and gives you the data retention and segmentation you need.
Set up heatmaps with intention
Don’t scatter heatmaps across all pages. For prioritization I target:
- High-traffic, low-converting product pages
- Top-of-funnel variants that feed your main product pages
- Pages with recent design changes or high drop-offs
When you create a heatmap, segment it by key dimensions — traffic source (paid vs organic), device type (mobile, tablet, desktop), and user intent where possible (new vs returning). A CTA that performs well on desktop might be invisible on mobile; segmentation reveals that nuance.
What I look for first — an inspection checklist
When a new heatmap arrives, I run through this checklist. It’s simple, repeatable, and helps me identify high-leverage fixes quickly.
| Signal | What it suggests | Likely fix |
|---|---|---|
| Low click density on primary CTA | CTA not visible, copy unclear, or broken | Increase contrast, change copy, move CTA above the fold |
| High clicks on non-clickable elements | Users expect interaction (misleading affordance) | Make element interactive OR remove affordance (e.g., faux buttons) |
| Sharp scroll drop-off before key content | Too much above-the-fold friction or poor preview | Shorten hero, add summary bullets, highlight price/value |
| Heat concentrated on irrelevant sections | Users focusing on wrong details | Reduce emphasis on non-essential content; promote critical info |
Prioritising fixes — a pragmatic framework
I prioritise fixes by combining three lenses: impact, effort, and confidence. A simple RICE-like filter works well here.
- Impact — How much will this change likely improve conversion? Heatmaps give directional impact: e.g., if 70% of users never see the CTA, making it visible likely has high impact.
- Effort — How much dev/design time? A button color change is low effort; a layout redesign is higher.
- Confidence — How certain are you the change will help? Use supporting evidence: analytics (bounce/exit rate), session recordings, and user feedback increase confidence.
Score each candidate fix (High / Medium / Low) across these axes and prioritise High Impact, Low Effort, High Confidence items first. Those are your quick wins.
Examples of high-leverage fixes I’ve shipped
Here are concrete patterns I’ve used after reading heatmaps:
- CTA visibility on mobile: Scroll maps showed most users stopping before the CTA. I moved a compact CTA bar into a sticky footer (same action, less real estate) and saw a measurable lift in clicks.
- Misleading images: Users clicked a decorative image thinking it would enlarge or change the product. Solution: make it interactive with a zoom/gallery or remove the clickable affordance.
- Long feature sections ignored: A heatmap revealed dense copy below the fold received almost no attention. I turned key features into a short, scannable bulleted list and pulled the price/CTA above it.
From insight to experiment
Once you’ve prioritized fixes, turn them into experiments with clear hypotheses. I follow this simple template:
- Hypothesis: If we [change], then [measurable outcome] will improve because [rationale from heatmap].
- Primary metric: usually conversion rate or click-through to cart.
- Secondary metrics: bounce rate, scroll depth, average session duration.
- Sample & duration: run until statistical significance or for at least 2-3 business cycles.
For example: “If we add a sticky CTA on mobile, then add-to-cart rate will increase by 10% because scroll maps show 65% of users never reach the main CTA.” Ship the change as an A/B test when possible — visual changes can be noisy if you rely only on pre/post comparisons.
Combine heatmaps with other evidence
Heatmaps are strongest when they corroborate other signals:
- Use session recordings to watch the moments leading up to confusing clicks.
- Correlate with analytics funnels to quantify drop-offs.
- Run 5–10 usability calls focusing on observed heatmap anomalies — qualitative context rapidly increases confidence.
Practical tips and pitfalls
Some practical lessons I’ve learned:
- Segment aggressively. Mobile and desktop heatmaps often tell different stories.
- Watch for sample bias. Low-traffic pages need longer collection windows; don’t act on heatmaps with only a handful of sessions.
- Refresh after changes. Heatmaps are time-sensitive — re-run them after any layout or copy change.
- Avoid overfitting. One odd recording can create misleading hotspots. Use aggregated views.
- Don’t chase aesthetics alone. Heatmap-driven decisions should always tie back to measurable business outcomes.
If you want, I can: suggest a checklist tailored to your product page template, help pick a heatmapping tool aligned with your stack, or review a heatmap screenshot and prioritise fixes with you. Say which page you’re working on (or paste a heatmap link) and we’ll triage it together.
