This is the kind of question where if you just say 'check the dashboard' you're already losing.
Start by clarifying the scope and definition of the metric, then systematically segment the revenue drop by dimensions like platform, region, user cohort, and ad product to isolate the source. Finally, validate hypotheses with data and consider external factors, ensuring you distinguish between correlation and causation.
Pro tip: Always quantify the impact of each potential cause and prioritize by magnitude; also, check for data pipeline issues early, as they can masquerade as real drops.
Confirm the exact definition of 'global ads revenue' (e.g., gross vs. net, includes all ad products) and verify the drop is real by checking data pipelines, logging, and reporting delays.
Break down revenue by key dimensions such as region, platform (iOS/Android/Web), ad product (feed, stories, reels), user demographics, and advertiser type to identify where the drop is concentrated.
Examine the ad delivery funnel: ad requests, fill rate, impressions, clicks, and conversion rates. Determine if the drop is due to fewer impressions, lower CPMs, or reduced demand.
Check for recent product changes, algorithm updates, policy changes, or bugs internally; externally, consider seasonality, macroeconomic trends, competitor actions, or ad platform outages.
Use statistical methods (e.g., A/B tests, causal inference) to confirm root causes and estimate their contribution to the revenue drop, then prioritize based on impact.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.