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Product Management Root Cause Analysis Question: Investigating sudden ad revenue decrease in Duolingo's Android app

What's causing the sudden 30% decrease in ad revenue from Duolingo's Android app this month?

Data Analysis Problem Solving Monetization Strategy EdTech Mobile Advertising Language Learning
Root Cause Analysis Ad Revenue EdTech Mobile Apps Android

Introduction

A sudden 30% decrease in ad revenue from Duolingo's Android app this month is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term and long-term implications for the product and business.

I'll approach this problem by first clarifying key details, ruling out external factors, and then diving deep into the product, user journey, and metrics. From there, I'll form data-driven hypotheses, conduct root cause analysis, and propose validation methods and 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 a recent change. Has there been any significant update to the Android app in the past month?

Why it matters: Recent changes often correlate with sudden metric shifts. Expected answer: Yes, there was a major update. Impact on approach: If yes, we'd focus on changes in that update. If no, we'd look at external factors or gradual issues that reached a tipping point.

  • Considering the specificity to Android, I'm wondering about platform differences. Is this decrease unique to Android, or are we seeing similar trends on iOS?

Why it matters: Platform-specific issues require different solutions than global problems. Expected answer: The issue is Android-specific. Impact on approach: If Android-only, we'd focus on Android-specific factors. If across platforms, we'd consider broader issues affecting the entire product.

  • Given the magnitude of the decrease, I'm curious about user segments. Are we seeing this 30% decrease uniformly across all user types, or is it concentrated in specific segments?

Why it matters: Segment-specific issues may indicate targeted problems or changes in user behavior. Expected answer: The decrease is more pronounced in certain user segments. Impact on approach: If segment-specific, we'd dive into those segments' characteristics and recent changes. If uniform, we'd look at broader, systemic issues.

  • Considering potential measurement issues, has there been any change in how we track or calculate ad revenue recently?

Why it matters: Measurement changes can sometimes masquerade as performance issues. Expected answer: No changes in measurement. Impact on approach: If there were changes, we'd scrutinize the new measurement system. If not, we'd focus on actual performance factors.

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