Daily Active Users Dropped 5% - Diagnose It

What interviewers evaluate

• Do you clarify before diving in (define DAU, confirm it's real, the timeframe)?
• Do you rule out measurement/data issues first?
• Do you decompose systematically (segment by platform, geo, cohort, channel)?
• Do you separate internal causes (releases) from external (seasonality, competitors, outages)?
• Do you form testable hypotheses and propose how to confirm each?

A framework to structure your answer

1. Clarify - define DAU precisely, confirm magnitude and window, check if it's a sudden cliff or gradual decline.
2. Rule out data issues - logging/tracking change, a metric-definition change, or a reporting bug before assuming a real drop.
3. Internal vs external - did we ship a release, change onboarding/pricing? Or is it seasonality, a holiday, a competitor, or a platform/outage event?
4. Segment to localize - break the drop down by platform (iOS/Android/web), geography, new vs returning, acquisition channel, and feature. A uniform drop vs a concentrated one means very different things.
5. Form hypotheses - from where the drop concentrates, propose specific causes.
6. Confirm & act - validate the leading hypothesis with data/logs; propose a fix or mitigation.

Try structuring your own answer first, then reveal a strong worked example.

Common variants

• Conversion rate dropped 10% - what do you do?
• Revenue is flat but users are growing - why?
• Engagement is up but retention is down - explain.

Pitfalls to avoid

• Guessing a single cause immediately instead of structuring the investigation.
• Skipping the data-integrity check (often the actual culprit).
• Not segmenting - a 5% aggregate drop could be a 50% drop in one segment.
• Confusing internal causes with external ones.
• Stating hypotheses without saying how you'd confirm them.

Likely follow-ups

• You find it's only Android. What now?
• How would you prevent this from going unnoticed next time?
• The drop is real and external (a competitor launched). How do you respond?