You need design validation. Should you run an A/B test or conduct user interviews?
The truth is, A/B testing vs user interviews isn't a choice between good and bad. They're different tools that answer different questions. A/B tests help you choose between options. Interviews help you understand why.
Use the wrong method, and you'll waste time getting answers that don't help you make decisions. Use the right method, and you'll get clear direction faster.
Here's how to pick the right method—and when to combine both.
A/B Testing vs User Interviews: The Core Difference
Before you choose a method, understand what each one does.
A/B Testing
What it is: You show two versions of a design to different people and measure which one performs better (or gets more votes). The winner has the higher conversion rate, click rate, or preference percentage.
What it answers: "Which version works better?" or "Which option should we choose?"
Example: You test two headlines side-by-side and see that Headline A gets 65% of votes while Headline B gets 35%. You choose Headline A.
User Interviews
What it is: You talk to users one-on-one about their experience, motivations, and mental models. You ask open-ended questions and listen for patterns.
What it answers: "Why do people think or act this way?" or "What's confusing or missing?"
Example: You interview users and discover that they don't understand your value proposition because you're using industry jargon they don't recognize. You rewrite it in plain language.
What each is best at:
- A/B testing: Choosing between options, settling debates, getting directional signals quickly, design validation when you have multiple good options.
- User interviews: Understanding motivations, discovering confusion points, uncovering edge cases, learning vocabulary and mental models, understanding emotional objections.
One helps you choose. The other helps you understand.
When A/B Testing Works Best (8 Examples)
A/B testing is perfect when you have two or more good options and need to know which one performs better. Here are 8 concrete examples:
1. Headline Clarity
Test: Two different headlines that communicate the same value proposition.
What you learn: Which headline helps people understand your offer faster and more accurately. You get data on which version is clearer, not just opinions.
2. CTA Copy
Test: "Start Free Trial" vs. "Get Started" vs. "Try It Free."
What you learn: Which button text motivates more clicks. Small copy changes can significantly impact conversion rates.
3. Hero Layout
Test: Image on left with text on right vs. image on right with text on left, or centered text vs. left-aligned text.
What you learn: Which layout guides attention better and creates the stronger first impression. Visual hierarchy matters for engagement.
4. Icon vs. Text Labels
Test: Navigation with icons only vs. icons + text labels.
What you learn: Which format helps users navigate faster and reduces confusion. Icons save space but can be ambiguous; text is clear but takes more room.
5. Pricing Layout
Test: Horizontal pricing cards vs. vertical pricing list, or 3 columns vs. 4 columns.
What you learn: Which layout makes pricing easier to compare and understand. Layout affects how people evaluate options.
6. Onboarding Step Wording
Test: "Step 1 of 3" vs. "1 of 3" vs. just a progress bar.
What you learn: Which format feels clearer and less overwhelming. Wording can affect perceived complexity and completion rates.
7. Button Hierarchy (Primary/Secondary)
Test: Primary button on left vs. primary button on right, or filled primary vs. outlined primary.
What you learn: Which visual treatment makes the primary action more obvious. Hierarchy affects click rates and conversion.
8. Trust Signals Placement
Test: Reviews above the fold vs. reviews below the fold, or security badges near the CTA vs. at the bottom.
What you learn: Which placement builds trust faster and reduces friction. Location matters for credibility signals.
A/B testing gives you data on which option performs better. It's perfect for design validation when you have multiple viable options.
When User Interviews Work Best (8 Examples)
User interviews are perfect when you need to understand motivations, mental models, or confusion points. Here are 8 interview-friendly topics:
1. What Users Believe the Product Is
Ask: "What do you think this product does?" or "If you had to explain this to a friend, what would you say?"
What you learn: Whether your messaging matches how people actually think about your product. Misalignment reveals communication gaps.
2. What They're Trying to Accomplish
Ask: "What are you trying to do here?" or "What's your goal when you visit this page?"
What you learn: The actual intent behind their actions, which might differ from what you assume. Understanding goals helps you design better workflows.
3. What Stops Them from Signing Up
Ask: "What would need to change for you to feel ready to sign up?" or "What's the biggest reason you'd hesitate?"
What you learn: Specific objections and blockers you need to address. Objections are fixable when you know what they are.
4. Vocabulary/Terminology Mismatch
Ask: "What do you call this?" or "How would you describe this feature?"
What you learn: Whether your language matches how users think. Terminology mismatches cause confusion and reduce trust.
5. Competitor Expectations
Ask: "What would you expect to see on a site like this?" or "How does this compare to [competitor]?"
What you learn: Industry conventions and expectations you might be missing. Violating expectations creates friction.
6. Emotional Objections (Trust, Risk)
Ask: "How does this make you feel?" or "Does this feel trustworthy? Why or why not?"
What you learn: The emotional barriers preventing action. Trust and risk concerns often block conversion more than logical concerns.
7. Workflow Context
Ask: "When would you use this?" or "How does this fit into your typical day?"
What you learn: The real-world context for how and when people use your product. Context reveals missing features or workflows.
8. Edge Cases / Needs You Didn't Anticipate
Ask: "What's missing that you'd expect to see?" or "What would make this more useful for you?"
What you learn: Needs, use cases, and features you didn't consider. Edge cases often reveal product gaps.
User interviews reveal the "why" behind behavior. They're perfect for understanding motivations and discovering what you're missing.
Choose the Right Method (A Simple Decision Framework)
Not sure which method to use? This framework will help.
If you need X → choose Y:
- "Choosing between two good options" → A/B test
- "Discovering what's confusing" → Interview
- "Understanding objections" → Interview
- "Settling a subjective debate" → A/B test
- "Learning vocabulary and mental models" → Interview
- "Getting directional design validation quickly" → A/B test
- "Finding edge cases and missing features" → Interview
- "Testing which visual treatment converts better" → A/B test
Don't do this (5 common mistakes):
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Using interviews to "vote" between two UIs: Interviews aren't for choosing between designs. People will tell you what they think you want to hear. Use A/B tests for choice.
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Running A/B tests when both versions are flawed: If both options are confusing or missing key elements, fix the underlying problems first (via interviews), then test.
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Changing multiple variables at once: If you test headline + layout + CTA all together, you won't know which change caused the difference. Test one variable at a time.
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Interviewing friends instead of target users: Friends are biased and don't represent your audience. Interview people who match your target users.
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Treating small sample results as truth: A/B tests with 10 votes aren't reliable. Interviews with 2 people aren't representative. Get enough data (20-30 minimum for tests, 5-8 minimum for interviews).
The rule of thumb: Use A/B tests for "which" questions. Use interviews for "why" questions.
The Best Workflow: Combine A/B Tests + Interviews
The best design validation workflow uses both methods in sequence. Here's how.
Phase 1: A/B Test (Fast Direction)
Run an A/B test to narrow choices and get a directional signal.
Example: You're testing two headline + hero layout combinations. You run an A/B test and get results: Version A gets 62% of votes, Version B gets 38%.
What you know: Version A is the winner (at least for this audience, at this time).
What you don't know: Why Version A wins, what's still confusing about it, or whether both versions are missing something important.
Phase 2: Interview 3-5 Target Users (Deep Understanding)
Interview users about the winning version to understand why it works and what still needs improvement.
Example: You interview 5 target users about Version A. You discover:
- Why it wins: People say the headline is clearer because it uses plain language instead of jargon.
- What's still confusing: Three people mention they're not sure what happens after they click the CTA. They want more clarity on next steps.
- What's missing: Two people mention they'd want to see social proof (reviews or testimonials) before signing up.
What you know: Why Version A is better, plus specific improvements to make it even stronger.
What you do: Keep Version A, add clearer next-step information, and add social proof above the CTA.
Why This Workflow Works
A/B tests are fast but shallow. They tell you which option wins, not why.
Interviews are slow but deep. They tell you why something works and what's still missing.
Combined, you get: Fast direction (from tests) plus deep understanding (from interviews) = better design decisions.
Use A/B tests to narrow choices. Use interviews to refine the winner.
What If You Don't Have Analytics or Traffic?
You don't need thousands of visitors to get useful design validation. Here's how to get directional signals even with low traffic.
Use Votes from Relevant Communities
Share your A/B test in design communities, relevant subreddits, or Slack groups. You can get 20-50 votes in hours, which is enough for directional design validation.
Example: Share a headline test in a design community. You get 30 votes. Headline A gets 70% of votes. That's a clear directional signal—not definitive proof, but strong enough to guide your decision.
Create Rapid Feedback Loops
Don't wait for perfect conditions. Run quick tests, get 20-30 votes, make a decision, then test the next variation. Multiple small tests beat one big test.
Example: Week 1, test two headlines (30 votes). Week 2, test two CTAs with the winning headline (30 votes). Week 3, test two layouts with the winning headline + CTA (30 votes). You've validated three decisions in three weeks.
Repeat Tests Over Time
Design validation isn't one-and-done. Test the same variations multiple times with different audiences to see if results are consistent.
Example: Test your headline in January, then again in March with a different sample. If results are similar, you can be more confident. If results differ, you might need to segment your audience or refine your messaging.
DesignPick is useful for directional design validation, especially in early stages. You can get votes from the design community quickly, test multiple variations rapidly, and iterate based on clear signals—even before you have production traffic.
You don't need perfect data. You need good enough data to make better decisions than guessing.
Ready to Test Your Designs?
When you're choosing between two designs, create an A/B test on DesignPick.
Upload both versions, share with the design community, and get real votes on which one works better. You'll have results in hours—fast enough to inform your next design decision.
Use A/B tests for "which" questions. Use interviews for "why" questions. Combine both for the best design validation workflow.
The Bottom Line
A/B testing vs user interviews isn't about picking one method forever. It's about using the right method for the right question.
- A/B tests answer "which": Which option performs better? Which version should we choose?
- Interviews answer "why": Why do people think this way? What's confusing or missing?
Use A/B tests when you need to choose between options. Use interviews when you need to understand motivations or discover problems. Combine both for the strongest design validation workflow.
Want more design validation strategies? Browse more posts on the blog.