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Product Management Root Cause Analysis Question: Investigating Discord mobile app message delivery failures

What's causing the sudden 30% increase in failed message deliveries on Discord's mobile app?

Problem Solving Data Analysis Technical Understanding Social Media Gaming Enterprise Communication
User Experience Messaging Platforms Root Cause Analysis Technical Troubleshooting Mobile App Performance

Introduction

The sudden 30% increase in failed message deliveries on Discord's mobile app is a critical issue that demands immediate attention. This problem directly impacts user experience and could lead to decreased engagement and potential user churn if not addressed promptly. I'll approach this analysis systematically, focusing on identifying the root cause, validating hypotheses, and developing both short-term fixes and long-term solutions.

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 this could be related to a recent app update. Has there been a new version release in the past week or two?

Why it matters: Recent changes often correlate with performance issues. Expected answer: Yes, a new version was released recently. Impact on approach: If confirmed, we'd focus on changes in that release.

  • Considering user segments, I'm curious if this issue is affecting all users equally. Are we seeing any patterns in terms of device types, operating systems, or geographical regions?

Why it matters: Helps narrow down potential technical or infrastructure-related causes. Expected answer: The issue is more prevalent on Android devices in certain regions. Impact on approach: We'd prioritize investigating Android-specific components and regional server performance.

  • Given the significant increase, I'm wondering about our monitoring systems. Have there been any changes to how we measure or define failed message deliveries?

Why it matters: Ensures we're dealing with a real issue and not a measurement anomaly. Expected answer: No changes to measurement systems or definitions. Impact on approach: Confirms the issue is real and not a data discrepancy.

  • Thinking about user behavior, has there been any significant change in usage patterns or message volume recently?

Why it matters: Unusual spikes in usage could strain system resources. Expected answer: Message volume has been relatively stable. Impact on approach: Rules out capacity issues as the primary cause.

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