Metrics question
Suppose free-to-paid conversion rose 15% after recent pricing, paywall, and onboarding changes, but 30-day churn also rose. How would you determine whether Suno is acquiring lower-intent subscribers versus creating an activation or expectations problem, and what actions would you take based on that diagnosis?
- Suno
- Metrics
- Hard
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What this question tests
Ability to separate an acquisition quality problem from an activation or expectations problem using cohort and behavioral data.
How to approach it
- Segment the new cohort by which specific change drove their conversion, pricing, paywall messaging, or onboarding, to see if churn concentrates in one segment.
- Compare early product usage between the new higher churn cohort and historical cohorts, since low engagement in the first sessions points to an activation problem rather than low intent.
- Check if paywall or pricing messaging set expectations the product did not meet, for example promising a capability that underdelivered, which would show up as churn tied to specific complaint themes in support or cancellation surveys.
- Look at willingness to pay signals like plan tier chosen and price sensitivity, since lower intent users often pick the cheapest plan and show minimal usage before cancelling.
- Cross reference with cancellation survey text or exit feedback to distinguish this was not what I expected from I just was not using it enough.
- Based on the diagnosis, act specifically: if activation is the problem, invest in onboarding, if it is expectations, fix paywall messaging, if it is genuinely lower intent acquisition, consider tightening targeting or the offer.
What a strong answer includes
- Uses cohort and usage pattern comparisons rather than assuming which cause is responsible.
- Ties cancellation survey or support text into the diagnosis instead of relying on numbers alone.
- Distinguishes the three plausible causes, low intent, poor activation, mismatched expectations, with a specific test for each.
- Names the different fix for each diagnosis, showing the analysis drives action.
Common mistakes
- Assuming churn automatically means the new users were low intent without checking activation and expectations first.
- Looking only at aggregate churn rate without segmenting by which change drove the conversion.
Likely follow-up questions
- Which of pricing, paywall, or onboarding would you suspect first, and why?
- What would you do if all three causes showed up in different segments?
More metrics questions
- Suno’s mobile app has strong first-song generation, but only 18% of new creators make a second song within 7 days. How would you diagnose the drop-off, break down the funnel, choose the most important leading and lagging metrics, and prioritize the first product changes or experiments to improve retention?Suno · Metrics · Hard
- You're given Suno's consumer revenue funnel spanning acquisition landing page → paywall → checkout → activation → renewal/winback. How would you diagnose the highest-leverage opportunities across paywalls, purchase and upgrade flows, pricing, offers, and winback, and what framework would you use to prioritize the first three experiments?Suno · Metrics · Hard
- Design an A/B testing plan for Suno's click-to-purchase journey from paid acquisition landing page through subscription checkout. Which hypotheses would you test first, what primary and guardrail metrics would you use, and how would you avoid short-term revenue lifts that hurt user trust or downstream retention?Suno · Metrics · Hard
- A paywall experiment increases checkout conversion, but shifts users toward a cheaper plan and lowers retention. How would you evaluate that result within Suno's broader pricing and packaging system, and decide whether to ship, iterate, or roll it back?Suno · Metrics · Hard
- Suno launches a beta for team workspaces. Creation and weekly usage are strong, but very few accounts expand after the first month. How would you diagnose the problem, which metrics would you inspect first, and what product or go-to-market experiments would you run next?Suno · Metrics · Hard
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More questions from Suno
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