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Product Management Root Cause Analysis Question: Investigating sudden drop in daily active users for a route planning app

Why has the number of daily active users for GoMetro's route planning feature dropped by 30% over the past week?

Data Analysis Problem-Solving User Behavior Understanding Transportation Mobile Apps Smart Cities
User Engagement Data Analysis Root Cause Analysis Transportation Apps

Introduction

The sudden 30% drop in daily active users for GoMetro's route planning feature over the past week is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term fixes and long-term strategic implications.

Framework overview

This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.

Step 1

Clarifying Questions (3 minutes)

  • Looking at the timing, I'm thinking there might be a recent change. Has there been any product update or feature release in the past 1-2 weeks?

Why it matters: Recent changes often correlate with sudden metric shifts. Expected answer: Yes, a minor UI update was released. Impact on approach: If yes, we'd focus on the update's impact; if no, we'd look at external factors.

  • Considering user segments, I'm curious about the distribution. Is the 30% drop uniform across all user groups or concentrated in specific segments?

Why it matters: Helps identify if it's a global issue or specific to certain users. Expected answer: The drop is more pronounced among casual users. Impact on approach: Segmented data would guide our investigation and solution design.

  • Given the feature's nature, I'm wondering about external factors. Have there been any significant changes in public transportation schedules or city infrastructure recently?

Why it matters: External changes could explain user behavior shifts. Expected answer: No major changes reported. Impact on approach: If yes, we'd consider adapting our feature; if no, we'd focus more on internal factors.

  • Thinking about data integrity, I want to confirm our metrics. Has there been any change in how we measure or define daily active users for this feature?

Why it matters: Ensures we're addressing a real issue, not a measurement anomaly. Expected answer: No changes in measurement. Impact on approach: If changed, we'd need to reassess the problem definition; if not, we proceed with our current understanding.

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