I started with the obvious stuff: is this a data pipeline issue or a real product signal?
Start by clarifying the metric definition and scope of the drop, then systematically rule out data/measurement issues before investigating product, infrastructure, and user behavior changes. Prioritize hypotheses by likelihood and impact, and propose concrete next steps for validation and mitigation.
Pro tip: Always check for data pipeline or logging issues first—many 'drops' are measurement artifacts. Also, segment the drop by platform, user cohort, and geography to quickly narrow down the root cause.
Define exactly what 'photo sharing' means (e.g., uploads, shares to feed, messages) and confirm the drop is real by checking data sources, logging, and dashboards for errors or delays.
Break down the metric by dimensions like platform (iOS/Android/Web), app version, user cohort, geography, and time to identify where the drop is concentrated.
Review recent deployments, experiments, configuration changes, and external events (e.g., holidays, outages) that coincide with the drop's onset.
Generate potential causes (e.g., bug in upload flow, backend latency, UI change, policy update) and validate them using logs, A/B tests, or user feedback.
Suggest immediate fixes (e.g., rollback, hotfix) and long-term monitoring to prevent recurrence, and define success metrics for recovery.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.