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Product Management Root Cause Analysis Question: Investigating sudden increase in support tickets for aviation app

What caused the sudden spike in customer support tickets related to the Lilium App's flight planning feature?

Problem Solving Data Analysis Technical Understanding Aviation Technology Transportation
User Experience Root Cause Analysis Customer Support Aviation Apps Bug Investigation

Introduction

The sudden spike in customer support tickets related to the Lilium App's flight planning feature 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 implications for our product strategy.

I'll approach this problem by first clarifying the context, then ruling out external factors before diving deep into our product ecosystem. We'll break down the metric, gather relevant data, form hypotheses, and conduct a thorough root cause analysis. Finally, we'll develop a comprehensive plan to validate our findings and implement 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 there might be a recent update. Has there been any recent deployment or feature change to the flight planning module?

Why it matters: Recent changes often correlate with sudden spikes in support tickets. Expected answer: Yes, a minor update was pushed last week. Impact on approach: If confirmed, we'd focus on changes in that update.

  • Considering user segments, I'm curious about the distribution. Are these tickets coming from a specific user group or evenly spread across our user base?

Why it matters: Helps identify if it's a localized or widespread issue. Expected answer: Mostly from frequent flyers using complex routes. Impact on approach: We'd dive deeper into advanced features used by power users.

  • Thinking about the nature of the tickets, I wonder about the common themes. What are the top 3 issues being reported in these tickets?

Why it matters: Identifies specific pain points to address. Expected answer: Route optimization errors, saved routes disappearing, and integration issues with third-party weather services. Impact on approach: We'd prioritize investigating these specific areas of the feature.

  • Considering potential data anomalies, I'm wondering about our tracking systems. Have there been any changes to how we categorize or count support tickets recently?

Why it matters: Ensures we're not dealing with a measurement issue rather than a real problem. Expected answer: No changes to the ticketing system in the past 3 months. Impact on approach: If confirmed, we can trust the data and focus on actual user issues.

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