After a Heatmap has collected enough Website activity, AIUNIFY Analytics converts that behavioral data into a visual representation of how visitors interact with the selected page.
The Heatmap viewer lets you analyze:
AIUNIFY Analytics overlays this behavioral information on the captured page Snapshot so you can relate visitor activity directly to the Website design.
The primary analysis workflow is:
Open Heatmap → Select Device → Select Clicks or Scrolls → Select Date Range → Identify Behavioral Patterns → Compare with Other Analytics → Take Action
To review a Heatmap:
The Heatmap viewer provides separate controls for Desktop, Tablet, Mobile, Clicks, and Scrolls.
Before interpreting the visualization, confirm:
The Heatmap view displays the tracked Website address beneath the Heatmap status.
This is important because similar landing pages may have completely different visitor behavior.
The Heatmap viewer combines two layers:
A captured representation of the Website page.
Aggregated:
or:
for the selected device and reporting period.
The Snapshot is reconstructed and the behavioral visualization is drawn directly over it.
Select:
Clicks
to see where visitors clicked on the page.
AIUNIFY Analytics records click data as:
The viewer then maps those points onto the dimensions of the page Snapshot.
The active Click Heatmap displays its total as:
%s clicks
For example:
348 clicks
The count reflects the Heatmap Click data included for the selected:
Heatmap + Device + Date Range.
AIUNIFY Analytics does not treat every displayed Heatmap point as equally important.
Each click position can carry a count, and the viewer weights the rendered Heatmap according to the highest recorded click concentration.
Operationally:
More visual intensity = more recorded click activity in that area relative to other areas of the same Heatmap.
A strong concentration around one area can indicate that many tracked clicks occurred near the same page element.
Examples could include:
The important question is not simply:
Where are visitors clicking?
but:
Are they clicking where the page was designed for them to click?
Suppose your landing page has:
Request Demo
near the top.
The Click Heatmap shows a strong concentration directly around that button.
That suggests the element is receiving substantial interaction relative to other areas of the page.
You can then compare that behavior with:
Goals
to determine whether the clicks are also leading to the desired Conversion outcome.
A heavily clicked element is not necessarily a successful business outcome.
For example:
Request Demo → 500 clicks
does not automatically mean:
500 Demo Requests Completed
Use:
to determine whether the interaction produced the intended result.
Suppose a major CTA is prominently displayed, but the Click Heatmap shows little activity around it.
Possible questions to investigate include:
The Scroll Heatmap can help answer the last question.
Click Heatmaps can also reveal activity on areas that were not intended to be primary interactive elements.
Examples might include repeated clicks on:
If an apparently non-interactive element receives significant clicking, visitors may be expecting it to perform an action.
That can become a Website-design opportunity.
Suppose a product image is not linked anywhere.
The Heatmap shows significant clicking on the image.
That may suggest visitors expect:
You could test making the image interactive and then compare subsequent behavior.
AIUNIFY Analytics stores Click locations as normalized horizontal and vertical coordinates and later scales them to the dimensions of the Heatmap Snapshot.
This allows click positions to be rendered appropriately against the captured page dimensions rather than relying only on one fixed screen coordinate system.
Because Click positions are displayed against the page Snapshot, the Snapshot should reasonably represent the page layout that visitors interacted with.
If the page is substantially redesigned but the old Snapshot remains, click positions may no longer visually correspond to the current layout.
When that happens:
Heatmaps → Actions → Retake snapshots
as described in Chapter 16.
Select:
Scrolls
to understand how far visitors progressed down the page.
AIUNIFY Analytics records a maximum Scroll percentage and organizes the data into levels from:
0% through 100%.
The displayed Scroll Heatmap then shows how many Pageviews reached progressively deeper areas of the page.
AIUNIFY Analytics analyzes Scroll Reach in 10% increments:
This gives you a structured way to see where visitor reach begins to decline.
The Scroll overlay uses the format:
[Scroll Level] • [Pageviews reaching level] out of [Total Pageviews] reached this level ([Percentage])
The exact interface language is:
“%1$s scroll level • %2$s out of %3$s pageviews reached this level (%4$s)”
For example:
50% scroll level • 400 out of 600 pageviews reached this level (66.67%)
Suppose the Heatmap displays:
10% → 1,000 Pageviews
20% → 920
30% → 820
40% → 700
50% → 550
60% → 400
70% → 275
80% → 180
90% → 110
100% → 60
This shows the gradual reduction in the number of Pageviews reaching deeper portions of the page.
The Scroll calculation asks whether the recorded maximum Scroll Depth reached at least a particular threshold.
For example:
A visit that reaches:
80%
also counts as having reached:
AIUNIFY Analytics calculates each threshold by counting records whose maximum Scroll is at least that deep.
For each Scroll Level, Analytics calculates:
Pageviews reaching that level ÷ Total applicable Heatmap Pageviews
and displays the resulting percentage.
This makes Scroll results easier to compare than using raw Pageview counts alone.
The Scroll overlay varies its visual intensity according to the relative number of Pageviews reaching each part of the page.
Areas reached by more Pageviews receive a stronger overlay, while deeper areas reached by fewer Pageviews become less intense.
Use the accompanying Scroll Level labels for exact interpretation rather than relying on visual intensity alone.
One of the most useful Heatmap observations is the point where visitor reach falls significantly.
For example:
40% → 82% of Pageviews
50% → 78%
60% → 44%
This indicates a substantial drop between the middle and 60% portion of the page.
You can then investigate what appears around that location.
A drop in Scroll Reach does not automatically mean the page is poorly designed.
Possible explanations include:
Interpret Scroll behavior alongside other Analytics data.
Suppose:
Only 20% of Pageviews reach 80% of the page
but your primary:
Request Quote
CTA is positioned at 85%.
That means a large portion of tracked Pageviews may never reach the CTA's location.
Possible actions include:
The upper portion of the page normally receives the greatest opportunity for visibility.
Use the early Scroll levels to determine whether visitors progress beyond the first section.
For example:
If:
90% reach 20%
but:
45% reach 30%
investigate what happens around the transition between those areas.
Scroll Heatmaps are especially useful on:
You can identify which sections remain within the journey as visitors move deeper down the page.
The strongest Heatmap analysis usually combines:
Scroll Reach
with:
Click Activity
Suppose a CTA has very few clicks.
There are at least two different possibilities:
Most visitors reach the CTA but do not click it.
Possible issue:
CTA appeal or messaging
Very few visitors reach the CTA.
Possible issue:
CTA placement or preceding content
Scrolls help distinguish those situations.
Suppose your CTA is located at approximately 70% of the page.
Scroll Heatmap:
70% reached by 25% of Pageviews
Click Heatmap:
CTA receives few clicks.
A reasonable investigation is:
The CTA may not be receiving enough exposure.
Now suppose:
70% reached by 80% of Pageviews
but the CTA still receives almost no clicks.
The investigation changes toward:
Select:
Desktop
to review the Desktop Snapshot and Desktop Heatmap activity.
The Device controls are independent, and AIUNIFY Analytics maintains a separate Desktop Snapshot.
Use Desktop results when evaluating the Website's larger-screen experience.
Select:
Tablet
to analyze Tablet-specific activity.
Because responsive Website layouts can change between Desktop and Tablet, do not assume the behavior will be identical.
The Tablet Heatmap uses its own Snapshot.
Select:
Mobile
to evaluate visitor interaction on the Mobile layout.
Mobile Heatmaps can be particularly useful because:
The Mobile Snapshot allows Click and Scroll behavior to be evaluated against that specific presentation.
Avoid making conclusions such as:
“Visitors do not click this button.”
when you have only reviewed Desktop.
A better process is:
Desktop → Clicks
Tablet → Clicks
Mobile → Clicks
and then compare.
A CTA may perform well on Desktop but poorly on Mobile because its position changes.
Suppose:
The CTA appears beside the main headline and receives strong click activity.
The responsive layout moves the CTA below several content blocks and it receives much less activity.
Next, review Mobile Scroll Reach.
If few Mobile visitors reach the CTA location, the issue may primarily be placement rather than the CTA itself.
For an important page:
This provides a much more complete behavioral picture than analyzing only one layout.
Heatmap results are date-sensitive.
The Heatmap viewer uses the selected Date Range when retrieving Click and Scroll data.
This allows you to analyze behavior during:
The Heatmap Date Range cannot precede the Heatmap's creation date.
The Heatmap's creation date acts as the minimum available date for the Heatmap viewer.
Therefore, creating a new Heatmap does not retroactively generate Heatmap behavior for periods before it existed.
Heatmaps become more valuable when you compare periods.
Example:
Before CTA redesign
After CTA redesign
Compare:
This helps determine whether the change altered visitor interaction.
If a page's structure changes substantially, historical behavior and the current Snapshot may no longer be visually compatible.
For major redesigns, use:
Retake snapshots
so new behavior can be interpreted against the updated page representation.
As explained in Chapter 16, AIUNIFY Analytics lets you clear Desktop, Tablet, and Mobile snapshots independently.
The Heatmap viewer calculates and displays the amount of behavioral data represented in the active visualization.
For Clicks, this is displayed as the number of:
Clicks
For Scrolls, the interface represents the applicable number of:
Pageviews.
Always consider the amount of underlying data before drawing strong conclusions.
A Heatmap with very little activity can be misleading.
For example:
5 clicks
may produce an apparent concentration, but it is a very small behavioral sample.
A Heatmap containing substantially more visitor activity generally provides a more stable picture of recurring behavior.
AIUNIFY Analytics reports the data count so you can consider that context.
A Heatmap tells you:
What was recorded
but not automatically:
Why the visitor did it.
For example, repeated clicking might represent:
Use additional Analytics tools to understand the context.
When a Heatmap identifies an unusual pattern, Session Replays can provide deeper context.
Example:
Heatmap finding:
Visitors repeatedly click a particular page area.
Then review applicable Replays to observe how individual Sessions interact with that portion of the Website.
Think of:
Heatmap → Detect Pattern
and:
Replay → Investigate Individual Behavior
For Advanced Tracking, Visitor Journeys can help explain broader behavior surrounding a page.
A useful investigative sequence is:
Heatmap identifies problem area
↓
Visitors / Sessions
↓
Session Events
↓
Replay when available
This moves from aggregate behavior toward individual Website journeys.
Heatmaps should also be compared with Goals.
For example:
A redesigned CTA may receive:
More clicks
but:
No improvement in Goal Conversions
That tells a different story than clicks alone.
The more meaningful business question becomes:
Did the behavioral improvement also improve the intended outcome?
Pageviews provides the broader traffic volume behind a Heatmap page.
For example:
10,000 Pageviews
with:
300 Heatmap clicks
provides a different context than:
500 Pageviews
with:
300 Heatmap clicks
Heatmap data should therefore be interpreted alongside overall Website traffic.
If a high-interest Heatmap area is an external CTA, compare it with:
Outbound clicks
For example:
Heatmap shows high interaction on:
Book Appointment
and Outbound Clicks shows strong activity toward:
booking.example
Together, these reports reinforce that visitors are actively using the external CTA.
Look for areas with concentrated Click activity.
Ask:
High-interest areas can reveal what visitors consider important.
Look for major page elements receiving little or no interaction.
Examples might include:
Then determine:
Were visitors exposed to it?
Use the Scroll Heatmap before concluding that the element itself is ineffective.
A false affordance occurs when something visually appears interactive even though it may not perform an action.
Heatmaps can help reveal this indirectly when users repeatedly click such an area.
Possible examples:
These patterns can guide usability improvements.
Look for sharp decreases between Scroll thresholds.
Example:
40% → 85%
50% → 80%
60% → 42%
Then inspect the content around the 50–60% region.
Questions include:
Scroll Heatmaps can show whether visitors are likely reaching important content.
Examples:
If an important section is far below the point reached by most Pageviews, consider whether its placement should change.
A practical way to read a long page is to divide it into business-purpose zones.
For example:
0–20%
Hero / primary offer
20–40%
Problem / benefits
40–60%
Features / proof
60–80%
Pricing / testimonials
80–100%
Final CTA / footer
Then compare Scroll Reach and Click behavior across those sections.
Suppose:
Strong CTA clicks.
Most visitors still scrolling.
Moderate decline.
Major drop-off before testimonials.
Very few visitors reach final CTA.
Potential test:
Move social proof and an additional CTA higher in the page.
After making the change, collect new Heatmap data and compare.
Suppose a Pricing page shows:
Possible business questions include:
Then compare the findings with Goals.
Suppose:
This can support investigation of:
Use Session Replays and Visitor Events for more precise individual behavior.
Suppose Mobile shows:
Desktop, however, shows:
This comparison suggests the Mobile layout itself deserves attention.
If the Heatmap displays:
We are still waiting for data
then the selected Device Type does not yet have a usable Snapshot.
The system states:
“The first visitor to open the heatmap page will create the initial snapshot.”
Check:
Possible explanations include:
Check all three Device versions and broaden the Date Range where appropriate.
Confirm:
Scroll visualization requires stored Scroll data for the selected Snapshot and Date Range.
If the behavioral overlay no longer corresponds to the visible page:
Snapshot alignment is especially important after major page redesigns.
This is not necessarily an error.
Desktop, Tablet, and Mobile use separate Snapshots because the Website layout can differ significantly across devices.
Investigate each layout independently before combining conclusions.
For each important page:
Use:
Heatmap
to identify behavior.
Then:
Goals
to measure outcome.
For example:
Heatmap finding:
Visitors see CTA but rarely click it.
Change:
Improve CTA wording and placement.
New Heatmap:
CTA clicks increase.
Goals:
Determine whether conversions also increase.
This creates:
Observe → Hypothesize → Change → Measure Behavior → Measure Conversion
For Mobile:
Before making decisions from Heatmap data, confirm:
Heatmap analysis can be summarized as:
Website Page
↓
Device Snapshot
↓
Visitor Behavior
↓
Where are visitors interacting?
↓
How far are visitors reaching?
↓
Desktop vs. Tablet vs. Mobile
↓
Pageviews + Goals + Outbound Clicks
↓
Visitor Journeys + Session Replays
↓
Change → Measure → Compare
You should now understand how to move from simply having a Heatmap to using it as an actual Website-optimization tool.
AIUNIFY Analytics Click Heatmaps use normalized click positions and weighted click counts to display concentrations of interaction over the captured page Snapshot.
Scroll Heatmaps divide the page into 10% reach levels, calculate how many applicable Pageviews reached each threshold, and display both the count and percentage directly on the page.
The strongest analysis comes from combining:
Clicks + Scrolls + Device Comparison + Date Range + Pageviews + Goals + Visitor Journeys + Session Replays
rather than interpreting a Heatmap in isolation.