Bluepeak Logistics: Trial-to-paid conversion Dropped 25%

Product Management
medium40 min0 submissions
BCG
Scenario

You are the PM for Bluepeak Logistics's core logistics product.

Trial-to-paid conversion has fallen 25% over the past 10 days. The drop appears concentrated in iOS and is most pronounced in the US.

Context that may or may not be relevant:

  • A redesigned onboarding flow shipped 28 days ago to 44% of users
  • Marketing paused a paid acquisition campaign 11 days ago
  • A competitor launched a free tier last month
  • The data team migrated the analytics pipeline 3 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
25
window days
10
concentrated region
the US
concentrated platform
iOS

recent changes

onboarding rollout pct
44
onboarding redesign days ago
28
competitor free tier launched
last month
paid campaign paused days ago
11
analytics pipeline migrated days ago
3
Your task

Diagnose the drop. Provide:

  1. Analysis — how you would structure the investigation and which hypotheses you would test in what order.
  2. Risks — of acting too early, and of acting too late.
  3. 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: Pallas Pharma: Weekly active teams Dropped 12%Next question
How you'll be graded

100 points, 60% to pass.

  • data analysis25
  • recommendation25
  • problem structuring25
  • hypothesis generation25
Hint
Reveal suggested structure
  1. Is it real? Check instrumentation first — the pipeline migration is the cheapest hypothesis to eliminate and the most embarrassing to miss.
  2. Decompose the metric. For DAU: new + returning + resurrected − churned. Which component moved?
  3. Segment. Platform, region, cohort, acquisition channel, new vs existing users.
  4. Timeline. Does the drop align with a specific deploy, or is it gradual?
  5. Internal vs external. Internal changes are testable and reversible; external ones are not.
  6. Act on the evidence, with a rollback only if the evidence points there.