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Extracting the Truth

Talking to humans. Learn the art of the 'Mom Test'—how to ask questions that reveal the truth, even when people want to be nice to you.

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Methods

Technical Specification //

Gathering user data.

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Users aren't experts in solutions; they are experts in their own problems.

1The Mom Test

Named after the idea that even your mom shouldn't be able to lie to you about your business idea. Focus on the user's past actions, not their future intentions.

2Sample Size Matters

For interviews, 5-8 people is often enough to see a pattern. For surveys, you need statistical significance. Don't make big pivots based on a survey of 10 people.

3The Power of Silence

In an interview, silence is a tool. If you wait after a user finishes speaking, they will often add a 'hidden gem' of information that they were initially going to skip.

4Step-by-Step Breakdown

Interviews and surveys are the primary tools for gathering qualitative and quantitative data. But if you ask the wrong questions, you'll get useless data.

In interviews, avoid leading questions. Don't ask 'Would you use this?'. Instead, ask 'Tell me about the last time you faced this problem.'

Surveys are for validation at scale. Use them to see if the patterns you found in interviews apply to a larger population.

Which of these is a 'Leading Question' that should be avoided in a user interview?

  • How do you currently solve this problem?
  • Don't you think our new dashboard looks much cleaner than the old one?
  • What was the most frustrating part of your last checkout experience?
  • Walk me through your daily routine.

When should you use a Survey instead of an Interview?

  • When you want to understand the emotional motivation of a single person
  • When you have identified a pattern and want to see how common it is across 500+ users
  • When you are in the very early discovery stage and don't know the problem yet
  • When you want to see a user's body language

Level Up 🚀

Advanced cheat sheets, SEO tricks, and interview prep for this topic.

Browser Support

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Accessibility (A11y)

1Inclusive Recruiting for Research

If you only recruit interview participants from your existing power-user email list, you systematically exclude users with disabilities, non-native speakers, and people who churned because the product wasn't accessible to them in the first place.

Recruit from: support tickets, churned users, accessibility-tool users, and non-English-speaking segments — not just your most engaged newsletter subscribers.

SEO Implications

  • 1

    Search Intent for 'User Research Methods'

    Readers searching for interview and survey guidance want concrete question examples they can copy, like 'Mom Test' phrasing and sample sizes. Articles with actual example questions and numbers outrank generic 'talk to your users' advice.

Best Practices

Ask About the Past, Not the Future

'Would you use this?' produces polite, unreliable answers. 'Tell me about the last time you ran into this problem' produces a real, specific story you can act on.

Pilot the Survey Before Sending It

Send your survey to 5 colleagues first. Ambiguous wording and leading scales are much cheaper to fix before 2,000 responses come back skewed.

Frequent Bugs

THE BUG

A survey question offers a biased scale (e.g., only positive options) or asks two things at once, making the responses impossible to interpret cleanly.

THE FIX

Use neutral, single-concept questions with a balanced scale, and pilot-test with a small group before sending the survey at scale.

Real-World Examples

Rewriting a Leading Interview Question

A PM drafts: 'Don't you think our new dashboard looks much cleaner than the old one?' before a round of user interviews.

Wrong: "Don't you think the new dashboard looks cleaner?"

Right: "Walk me through how you'd find last month's report using this dashboard." (then observe, don't prompt)

Interview Prep

Pascual Vila

Pascual Vila

Frontend Instructor // Code Syllabus

Common Pitfalls & Errors

The Error //

Asking leading or hypothetical questions

Wrong: "Would you pay for a faster checkout?" Right: "Tell me about the last time you abandoned a checkout. What happened?"

The Solution //

Questions like 'Would you use a feature that does X?' get polite, hypothetical yeses that rarely predict real behavior. Ask about specific past experiences instead, which are far harder to fake or exaggerate.

The Error //

Making a big product decision from a tiny, unrepresentative sample

Wrong: "3 out of 5 interviewees mentioned pricing, so we're rebuilding the pricing model." Right: "3 out of 5 interviewees mentioned pricing — let's survey the full user base to see how common this really is before committing."

The Solution //

5-8 interviews are enough to spot a qualitative pattern, but they are not enough to size a market or justify a major pivot. Treat interview findings as hypotheses to validate at scale with a survey or usage data before betting the roadmap on them.

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