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DoorDash·Product Manager·Onsite - Product Sense / Strategy·Intermediate

Intermediate
Jun 2026

Summary

DoorDash PM interview with a product analytics question about diagnosing a sudden drop in conversion on a third-party platform. Short and focused, just the one question from what I can tell.

Questions Asked (1)

Q1

OpenTable's conversion ratio dropped by 10% in a single day. What might be causing this?

Product Analytics & MetricsRoot Cause Analysis
Author's notes

I went straight to the funnel and started listing external causes before even asking what 'conversion' meant in this context.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the metric definition and scope (e.g., conversion ratio = bookings/visits, across all platforms or specific segments). Then systematically segment the data by time, user, platform, and geography to isolate the drop, and finally hypothesize potential causes across internal and external factors, validating with data.

Pro tip: Always quantify the impact and prioritize hypotheses by likelihood and ease of validation; this shows you can drive efficient root cause analysis under time pressure.

1. Clarify the metric and scope

Define exactly what 'conversion ratio' means (e.g., bookings per session, reservations per search) and confirm the time frame, platforms, and user segments affected.

2. Segment and localize the drop

Break down the metric by dimensions like device, geography, user type (new vs. returning), and time of day to identify where the drop is concentrated.

3. Generate hypotheses

Brainstorm potential causes across internal factors (e.g., product changes, bugs, pricing) and external factors (e.g., competitor actions, seasonality, macro events).

4. Validate and prioritize

Use data to test each hypothesis, starting with the most likely and easiest to check, and quantify the impact of each confirmed cause.

5. Recommend next steps

Propose immediate fixes or further investigations, and outline how to monitor the metric to prevent future drops.

Key Points to Mention

  • Metric definition: Ensure alignment on what conversion ratio means and its components.
  • Segmentation: Analyze by device, geography, user cohort, and traffic source to isolate the issue.
  • Internal factors: Recent product releases, A/B tests, pricing changes, or technical issues (e.g., site downtime, slow load times).
  • External factors: Competitor promotions, seasonality, holidays, or macro events affecting travel/dining behavior.
  • Data validation: Check for data pipeline errors or tracking issues that could falsely indicate a drop.
  • Prioritization: Focus on hypotheses with highest impact and fastest validation to drive actionable insights.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.