Introduction
The sudden 20% drop in ad fill rate for AppLovin Exchange last week is a critical issue that demands immediate attention. This metric directly impacts revenue and user experience, making it essential to identify and address the root cause promptly. I'll approach this analysis systematically, focusing on data-driven insights and considering both technical and business factors.
Framework overview
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Recent changes often correlate with performance shifts. Expected answer: Yes, there was a minor update to the ad serving algorithm. Impact on approach: If confirmed, I'd focus on the update's specifics and potential unintended consequences.
Why it matters: Uneven distribution could point to specific content or user segment issues. Expected answer: The drop is more pronounced in gaming apps. Impact on approach: I'd investigate gaming-specific factors and potential changes in user behavior or advertiser preferences.
Why it matters: Understanding which part of the equation changed helps narrow down potential causes. Expected answer: The number of ad requests has remained stable, but filled impressions have decreased. Impact on approach: I'd focus on factors affecting ad delivery and matching rather than user engagement.
Why it matters: Advertiser actions can directly impact fill rates. Expected answer: No major changes observed in overall advertiser behavior. Impact on approach: I'd shift focus to internal factors and platform performance issues.
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