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SEO
10 mins read
SEO
10 mins read
The CausalFunnel Shopify App now includes a heatmap and user journey view that shows how real shoppers interact with every part of your store.
These visuals highlight where visitors click, how far they scroll, which elements they ignore, and the common paths they follow before adding to cart or exiting.
Instead of relying on assumptions, merchants get a clear picture of on-site behavior directly inside the same app they use for A/B testing and conversion tools.
This helps store owners make practical layout adjustments, fix drop-off points, and support higher conversions with evidence pulled from actual visitor activity.
Once you connect your store to the CausalFunnel Shopify App, the heatmap and user journey data starts collecting. The system begins tracking page activity and, after about three hours, you will see visual reports for each tracked URL. These reports show actual visitor behavior so you can make practical decisions about layout, copy, and calls to action.
What the main heatmap panel shows
Page Screenshot
A visual capture of the page used as the background for overlays. This helps you see exactly which part of the section visitors interacted with.
Clicks
Total number of clicks recorded on that page. The map uses hotspot intensity to show where clicks concentrate. High click counts on noninteractive elements flag a usability problem.
Moves
Mouse movement or pointer activity that shows where visitor attention drifts across the page. Heavy movement over an area that is not clickable suggests visitors expect interaction there.
Scroll
Percentage of page depth visitors reach. If 100 percent shows up, it means most visitors scrolled the full page. Low scroll depth on long product pages indicates key information sits below the fold.
Engagement
A composite measure based on clicks, moves, and time on page. This is useful to compare pages at a glance.
How to read the numbers and what they mean
A good sign the CTA is visible and convincing. If conversions remain low despite high clicks, confirm the click leads to the expected action.
Likely a confusion issue. People may expect a link or button where there is none. Consider making the element interactive or adjusting copy to reduce confusion.
Strong pointer movement but low clicks
Visitors are inspecting but hesitating. Test clearer affordances, stronger copy, or simpler choices in that area.
Low scroll for long pages
Important content is likely missing from most visitors. Move critical information higher or shorten the page.
Low engagement combined with high exits
Signals the page is not answering the visitor’s question. Use session playback or user journey paths to find where visitors leave.
Filters and how to use them
The app includes filters that let you isolate the exact audience segment you want to analyze. Apply filters one at a time or combine them for focused insight.
All Users or specific segments when available. Use this to compare new visitors versus returning shoppers.
Select the channel that brought the visitor. Comparing organic versus paid traffic often reveals differences in intent and patience.
Enter a referring website such as google.com or facebook.com and press Enter to see behavior for traffic coming from that source.
Filter by campaign data. Add the UTM Key for your campaign tag for example utm_source and its value for example google to view only visitors from a particular campaign. This is useful when you want to validate a landing page used for specific ads.
Practical workflows and examples
Filter by device type and run the click heatmap. If mobile visitors tap an image that looks clickable but is not, either make it clickable or change the visual cue so it no longer looks actionable.
After changing a product page layout, hit Update Screenshot, then compare clicks and scroll to the earlier version. Are clicks shifting to the new CTA? Is scroll depth improving?
Filter by UTM parameters to isolate campaign traffic. Check whether campaign visitors reach the call to action or drop off quickly. If they drop off, match the landing content to the ad message.
Use the moves and clicks overlays on cart and checkout pages. High pointer activity around a form field with little input suggests the field is confusing or validation is failing.
Device and time considerations
Action checklist after reviewing a heatmap
Reporting cadence and next steps
This feature puts direct behavior data inside the same interface you use for testing so you can move from insight to experiment quickly.
The User Journey feature gives a complete view of how visitors move through your store. Instead of looking at each page in isolation, this panel shows the actual paths users follow from entry to exit. It helps you understand where interest builds, where visitors hesitate, and where you lose them. Once your store is connected and tracking begins, the system starts mapping every movement across URLs, directories, and sections of your site.
At the top, you will see the total number of users recorded for the selected date. For example:
Each path represents a unique pattern of movement. A path might show users entering the home page, going to a product page, checking a collection, or dropping off. This makes it simple to identify the most common user flows and the flows that correlate with poor engagement.
The dashboard groups user behavior by directories so you can quickly understand where the bulk of the traffic moves.
Shows how many users reached any product URL and the number of unique paths taken inside product pages. If you see 20742 users and 153 paths, it means product content is a major pivot point but users navigate through it in many ways.
Lists static or custom pages such as About, FAQs, or guides. High path variation often signals inconsistent page structure.
Shows users entering collection level browsing. If path count is high but user volume is low, exploration is scattered and likely needs cleanup.
Captures visitors who used your store’s search bar. High search usage often means your navigation menus are not serving visitor needs.
Tracks visitors viewing account or login pages. This helps detect friction before checkout.
Shows blog traffic paths if your store includes articles.
Tracks users who reach the cart page. Low volume here with high product page volume often indicates hesitation or missing incentives.
These smaller paths help you find overlooked pages that still influence conversions.
Selecting a directory reveals all the URLs inside it so you can view user flow at the page level.
Page level analytics
When you click into any URL, the page analytics panel opens. This includes:
Total visitors who accessed the page in the selected period.
All recorded clicks on that page. Low clicks with high user count may indicate unclear direction.
How long visitors stayed. Useful for identifying interest or confusion.
Shows how far the typical visitor scrolls. A high value means most people see the entire page.
For example: Book button clicks. This helps you understand whether the call to action is being noticed and used.
A link to open the heatmap for that exact URL appears inside the panel. This keeps page level insights connected to visual behavior data.
Next Visited URLs
This shows where visitors went immediately after the selected page. For a home page, you may see:
/products → 20742
/pages → 7762
/collections → 482
/search → 480
/account → 437
These numbers show the distribution of user intent after landing. If product page traffic is strong but cart movement remains low, the issue likely lies inside the product page layout or offers.
Where users came from
If referral data is available, you will see the previous URLs visitors came from. This helps you understand whether the page is functioning as a landing page or simply a pass through.
The session insights panel shows:
This gives you a layered understanding of how different segments behave. For example, returning visitors may go deeper into collections while first time visitors may stay on products.
How to use User Journey data to improve your store
Look for high drop off points. If many users exit from a specific product page, run a heatmap review and consider an A B test for layout or pricing.
When a path consistently leads to strong engagement, simplify entry into that path from other key pages.
Use journey paths to identify which pages influence conversions most often and prioritize them for experiments.
If search paths are unusually high, improve navigation labels or surface popular categories earlier.
Scroll and time data help confirm whether visitors see the information you assume they see.
Once you understand the movement across your store, heatmap and A B testing together create a full cycle: identify behavior, diagnose the reason, test a better approach, and measure the result.
CausalFunnel’s Heatmap and User Journey tools give you a direct view of how visitors behave across your Shopify store. Instead of guessing what users see, click, or skip, you get hard data that highlights attention patterns, drop-off points, navigation choices, and the paths that lead to conversion.
When this insight is paired with your A/B testing workflow, every improvement becomes intentional rather than reactive. You can refine layouts, adjust messaging, strengthen product pages, and fix friction with confidence. Together, these tools create a continuous optimization loop that helps your store gain clarity on user behavior and steadily improve results over time.
Start using our A/B test platform now and unlock the hidden potential of your website traffic. Your success begins with giving users the personalized experiences they want.
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