Pinecrest Grocers: Trial-to-paid conversion Dropped 20%
Product Management
medium40 min0 submissionsGoogle
Scenario
You are the PM for Pinecrest Grocers's core grocery product.
Trial-to-paid conversion has fallen 20% over the past 14 days. The drop appears concentrated in iOS and is most pronounced in India.
Context that may or may not be relevant:
- A redesigned onboarding flow shipped 29 days ago to 72% of users
- Marketing paused a paid acquisition campaign 23 days ago
- A competitor launched a free tier last month
- The data team migrated the analytics pipeline 20 days ago
Your VP wants an answer by end of day and is already asking whether the redesign should be rolled back.
Supporting data
incident
- metric
- trial-to-paid conversion
- drop pct
- 20
- window days
- 14
- concentrated region
- India
- concentrated platform
- iOS
recent changes
- onboarding rollout pct
- 72
- onboarding redesign days ago
- 29
- competitor free tier launched
- last month
- paid campaign paused days ago
- 23
- analytics pipeline migrated days ago
- 20
Your task
Diagnose the drop. Provide:
- Analysis — how you would structure the investigation and which hypotheses you would test in what order.
- Risks — of acting too early, and of acting too late.
- Recommendation — your diagnostic sequence and what you would tell the VP today.
Be specific about the data cuts you would pull.
Ready to move forward? Up next: Bluepeak Logistics: Trial-to-paid conversion Dropped 25%Next question
How you'll be graded
100 points, 60% to pass.
- data analysis25
- recommendation25
- problem structuring25
- hypothesis generation25
Hint
Reveal suggested structure
- Is it real? Check instrumentation first — the pipeline migration is the cheapest hypothesis to eliminate and the most embarrassing to miss.
- Decompose the metric. For DAU: new + returning + resurrected − churned. Which component moved?
- Segment. Platform, region, cohort, acquisition channel, new vs existing users.
- Timeline. Does the drop align with a specific deploy, or is it gradual?
- Internal vs external. Internal changes are testable and reversible; external ones are not.
- Act on the evidence, with a rollback only if the evidence points there.