UI design is full of small decisions that feel big. Should the navigation be at the top or side? Should buttons be rounded or square? Should the layout be dense or spacious?
These decisions matter, but they're hard to make confidently without data. That's where UI A/B testing comes in.
When UI A/B Tests Are Useful (And When They're Not)
UI A/B tests are great for testing:
- Visual hierarchy: Which layout guides the eye better?
- Interaction patterns: Which button style gets more clicks?
- Information density: Which spacing feels more comfortable?
- Navigation patterns: Which menu structure is easier to use?
UI A/B tests are less useful for:
- Fundamental product decisions: Should this feature exist? (That's a product question, not a UI question.)
- Brand identity: Should we use this color palette? (That's a brand question, not a usability question.)
- Accessibility: Is this design accessible? (That's a compliance question, not a preference question.)
7 UI Experiments You Can Run This Week
1. Navigation Placement
Test: Top navigation bar vs. side navigation drawer.
Why it matters: Navigation placement affects how users explore your app. Top nav is more visible but takes horizontal space; side nav saves space but can be hidden.
Example: Test a horizontal top nav against a collapsible side drawer. See which one helps users find features faster.
2. Button Style
Test: Rounded buttons vs. square buttons, or filled buttons vs. outlined buttons.
Why it matters: Button style affects perceived importance and clickability. Rounded buttons feel friendlier; square buttons feel more professional.
Example: Test rounded primary buttons against square primary buttons. See which style gets more clicks.
3. Typography Hierarchy
Test: Larger headings vs. smaller headings, or different font weights for emphasis.
Why it matters: Typography hierarchy guides the eye. Stronger hierarchy makes content easier to scan; weaker hierarchy can feel more subtle.
Example: Test a bold, large heading against a lighter, smaller heading. See which one helps users understand the content faster.
4. Card Density
Test: Dense card layouts (more info, less spacing) vs. spacious card layouts (less info, more spacing).
Why it matters: Density affects scannability and perceived complexity. Dense layouts show more at once; spacious layouts feel calmer.
Example: Test a card with tight spacing and multiple elements against a card with generous spacing and fewer elements. See which one feels more usable.
5. Empty State Design
Test: Illustrative empty states vs. text-only empty states, or helpful empty states vs. minimal empty states.
Why it matters: Empty states set the tone for new users. Helpful empty states guide action; minimal empty states feel cleaner.
Example: Test an empty state with an illustration and clear CTA against a minimal empty state with just text. See which one encourages more action.
6. Form Field Style
Test: Outlined input fields vs. underlined input fields, or labels inside fields vs. labels above fields.
Why it matters: Form field style affects perceived complexity and completion rate. Some styles feel more modern; others feel more traditional.
Example: Test outlined input fields against underlined input fields. See which style feels more approachable and gets more completions.
7. Color Contrast
Test: High-contrast text (dark text on light background) vs. lower-contrast text (lighter text on light background).
Why it matters: Contrast affects readability and perceived hierarchy. High contrast is more readable but can feel harsh; lower contrast feels softer but can be harder to read.
Example: Test dark gray text (#292929) against lighter gray text (#525252) on a white background. See which one feels more readable and professional.
Tips to Run Clean Tests
Test One Variable at a Time
If you change the button style, the button color, and the button text all at once, you won't know which change caused the difference. Test one thing at a time.
Ask a Clear Question
Before you test, write down the question you're trying to answer: "Which button style gets more clicks?" or "Which layout is easier to scan?" This keeps you focused.
Get Enough Votes
Small sample sizes can be misleading. Aim for at least 20-30 votes per version to get reliable results. More is better, but 20-30 is a good minimum.
Test with Real Users
If possible, test with people who represent your actual audience. Designers will have different preferences than end users, so make sure your test audience matches your product audience.
The Bottom Line
UI A/B testing helps you make design decisions with data instead of guesswork. These 7 experiments are a great starting point—but the real value comes from building a habit of testing your UI assumptions.
Pick one experiment, run it this week, and use the results to inform your next design decision. Then pick another experiment and repeat.