I went straight to engagement metrics and kind of forgot to define what 'discovery' even means first.
Start by clarifying what 'discovery features' means at Instagram (e.g., Explore, Reels, Search, suggested accounts) and the goal of discovery (help users find relevant content/creators they love). Then define success metrics across the user journey: engagement, satisfaction, and long-term retention, and propose how to measure them with A/B tests and guardrail metrics.
Pro tip: Anchor your metrics in Instagram's north star (time well spent) and emphasize that discovery success isn't just about clicks—it's about connecting users with content they value, which drives retention. Also, mention the importance of measuring both short-term engagement and long-term ecosystem health (e.g., creator diversity).
Define which discovery features you're measuring (e.g., Explore, Reels, Search, suggested accounts) and the intended user outcome (e.g., help users find new content/creators they love). Align with Instagram's mission and business goals.
Break down the discovery experience into stages: entry, browsing, consumption, and post-consumption actions (follow, like, share, save). Identify metrics for each stage.
Choose metrics that capture engagement (e.g., CTR, time spent, content consumed), satisfaction (e.g., likes, shares, follows), and retention (e.g., DAU/MAU, return rate). Include both leading and lagging indicators.
Propose A/B tests or holdout groups to isolate the feature's impact. Define primary and guardrail metrics (e.g., user reports, hide rate) to ensure no negative side effects.
Set up dashboards to track metrics over time, segment by user cohorts (new vs. existing, demographics), and use qualitative feedback to interpret results. Iterate based on learnings.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.