Metrics question
Figma's homepage is getting healthy traffic from design-related queries, but first-visit sign-up conversion is below target. What 3-5 experiments would you run across the homepage and sign-up flow, what hypothesis does each test, and how would you determine whether a result is a true win versus just shifting users downstream?
- Figma
- Metrics
- Hard
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What this question tests
Experimentation design: can you propose specific, hypothesis-driven tests across a funnel and reason about false wins from metric shifting rather than real improvement.
How to approach it
- Hypothesis 1: value clarity above the fold is weak, so test a headline and hero rewrite focused on the top design-related query intent driving traffic.
- Hypothesis 2: sign-up friction is too high for first-time visitors, so test reducing required fields or adding a Google/SSO option at the sign-up step.
- Hypothesis 3: visitors don't see the product before committing, so test adding an interactive or video preview before the sign-up wall.
- Hypothesis 4: the CTA is generic, so test outcome-specific CTA copy tied to the query intent that brought the visitor in, like 'start designing' versus 'try it free'.
- Hypothesis 5: mismatch between query intent and landing page, so test routing different query segments to tailored landing variants instead of one generic homepage.
What a strong answer includes
- Ties each test to a specific hypothesis about why conversion is low, rather than a generic list of things to A/B test.
- Explicitly checks for a true win versus shifted downstream metrics, for example verifying that sign-ups convert to activated users at the same or better rate, not just more raw sign-ups.
- Includes intent-based landing page routing, which is specific to Figma's stated traffic source (design-related queries).
Common mistakes
- Proposes generic button-color or headline tests with no hypothesis tied to the stated problem.
- Declares a win on sign-up rate alone without checking whether those sign-ups convert to real activated users downstream.
Likely follow-up questions
- How would you check that a sign-up lift is not just pulling in lower-intent users.
- How long would you run each test before calling a result significant.
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More questions from Figma
Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 2: Data fluency: SQL, logs, and reading the truth yourself
- Chapter 14: Get the job: the AI PM interview loop