I went straight to metrics and kind of skipped the 'why does this even exist' part, which I think hurt me.
Start by clarifying the goal of News Feed: to increase user engagement and retention by providing a personalized, algorithmic stream of content. Then, outline a framework that evaluates user value, business impact, and risks, using metrics and experiments to validate assumptions. Conclude with a recommendation based on data and strategic alignment.
Pro tip: Acknowledge the tension between algorithmic ranking and user control, and propose a phased rollout with guardrail metrics to mitigate potential backlash. Show that you understand Facebook's mission to connect people and the need to balance short-term engagement with long-term trust.
Identify key metrics such as DAU/MAU, time spent, retention, and content interactions. Also consider counter-metrics like user satisfaction and well-being.
Evaluate how News Feed solves user problems: discovery of relevant content, social connection, and personalized experience. Compare to existing alternatives like profiles and notifications.
Estimate effects on ad revenue, content distribution, and ecosystem health. Consider how algorithmic ranking might change publisher and advertiser behavior.
List potential risks: filter bubbles, privacy concerns, user backlash, and technical scalability. Propose mitigations like transparency controls and gradual rollout.
Plan A/B tests to measure impact on key metrics. Use holdout groups and long-term studies to detect unintended consequences.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.