Design decisions shouldn’t depend on gut feelings alone. The right data allows us to measure and prove every change we make. Cognitive load stands out as one of the most useful metrics – it shows how much mental effort a user needs to understand a design.
High cognitive load makes a layout feel messy, confusing, and hard to read. Users have to spend more time figuring it out, which affects engagement and makes the call to action (CTA) less effective. Low cognitive load creates a design that feels smooth, with information that’s easy to grasp, and a CTA that grabs attention.
The Attention Insight Visual Usability Checker plugin has a workflow called the Cognitive Load Score. This tool gives a numerical score and creates a heatmap that shows which parts of the design are causing cognitive effort. By pairing this with Iterative Testing, it becomes possible to pinpoint exactly what needs fixing and to confirm improvements with data.
In this process, specific objects like the heading (“Special Offer”) and the CTA button (“Order Now”) are selected before analysis, ensuring that results track the same focal points across every variation.
Analysis: Testing Steps
Step #1 - Baseline (V1/Original)
The initial analysis produced a Cognitive Load Score of 81, a number that indicates heavy effort for the user. The heatmap displayed concentrated yellow areas over the background image, confirming it was the main source of cognitive effort. The text block contributed additional weight.
A deeper look at the score revealed the key issues:
Detail Density: This made up almost half the total load resulting from an excess of small details, shapes, and an intense background.
Visual Entropy: The layout seemed disorganized.
Color Complexity: Too many clashing tones were present.
Attention Distribution: Focus was spread across elements.
In this baseline test, the heading captured only about 23.7% of visual attention, while the CTA button drew just 2.1%.
At this stage, the process shifted to Iterative Testing. This other workflow in the tool enables designers to modify the layout, monitor attention shifts, and reassess Cognitive Load at every step. By going through edits and reanalysis , the process becomes data-driven: rather than guessing, you validate each change.
Step #2a - First Iteration (V1 → V2) - Background Overlay & Typography Adjustments
In the initial round of changes the background image was darkened with an overlay. This change helped the text stand out more. Typography was also adjusted:
- Headings kept their Playfair Display font to maintain style.
- Body text was changed to Quicksand, which looks cleaner and reads better.
- Font sizes became uniform to improve consistency.
These updates led to a more relaxed visual flow and less clutter, while keeping the brand’s look intact.
Step #2b - First Iteration (V1 → V2) - Spacing & CTA Adjustments
The next refinement addressed spacing. The subheading got more line height, which made it easier to read. The CTA was enlarged, with more padding and white space.
In terms of results, the heading attention dropped slightly by 0.8% (22.9%), while the CTA remained steady at 2.1%.
Step #3 - Second Iteration (V2 → V3) - Final Layout Refinement
The final simplification swapped the full-page background for a smaller framed picture on a black backdrop. This change cut down a lot of the visual noise.
The outcomes were evident:
- Original design: 81
- Second version: 69
- Third version: 56
Alongside these score drops, heading visibility improved from ~22.9% to 32.2% (+9.3), while the CTA rose modestly from 2.1% to 3.1% (+1.0).
Heatmap analysis confirmed the edits made a difference by showing that both the heading and CTA gained more focus.
Application: Design Decisions
Action #1 - Simplify the Background First
The baseline review showed the background caused the biggest problem. The decision here is to fix the background as the first priority. Simplifying it will offer the best chance to make an impact. A guiding rule was also set at this stage: CTA visibility cannot drop.
This was validated by data – even with simplification, CTA percentages remained stable across all versions.
Action #2 - Balance Style and Legibility
To cut down on distractions, the background overlay was darkened and the typography adjusted. The design choice here is to:
- Pick unique fonts to give headings character.
- Choose a simple font for body text to make longer sections easier to read.
- Use the same font sizes throughout to keep things consistent.
This strikes a balance between style and improves readability. Typography adjustments have been shown to lessen mental effort and improve readability.
The plugin approved this decision. Using Quicksand in the body text reduced entropy, and Playfair Display headings maintained the brand’s identity.
Action #3 - Prioritize CTA Above All
Adjusting the spacing made the layout feel less busy. The downside – headings drawing a bit less focus – was worth it since the CTA stayed prominent. The decision is to prioritize CTA stability above minor shifts elsewhere.
This shows an important idea: the top priority should guide compromises.
Action #4 - Choose the Optimal Version
Replacing the full background image with a smaller framed version simplified the design dramatically. The results proved this right. The cognitive score went down from 81 to 69 to 56.
The heatmap showed users paid more attention to both the heading and the CTA. This confirmed that the new design guided people’s eyes more effectively.
The choice here is clear:
- Pick the version which is the most optimal.
- Share this with stakeholders as the most effective option because it combines the lowest cognitive load with the highest CTA visibility.
The iterative testing showed the final version reduced mental effort and improved visual clarity in the most important areas.
Final Takeaway
Breaking the process into challenges and solutions explains how decisions get driven by data.
- Challenges uncovered issues: background intensity, detail density, entropy, and color chaos.
- Solutions addressed them step by step: overlays, typography, spacing, and background simplification.
The heading focus improving by 9.3%, and the CTA increasing by 1%, shows how data use transforms design tweaks into clear results.
The outcome was a design that looks calmer, works better, and guides users more effectively. This is the value of combining Cognitive Load analysis with iterative testing: every improvement is proven, not guessed.
