I went straight to engagement metrics and kind of dug myself into a hole.
Start by clarifying the goal of the personalized news feed—likely to maximize user engagement and satisfaction while balancing long-term retention. Then define a North Star metric and supporting metrics across user, product, and business dimensions, and outline how you would validate them through A/B testing and guardrail metrics.
Pro tip: Emphasize that metrics should be paired with counter-metrics to avoid optimizing for short-term engagement at the expense of user well-being or long-term trust, which is especially important at Meta given its scale and public scrutiny.
Ask questions to understand the feed's purpose, target users, and business goals (e.g., increase engagement, retention, or ad revenue). Confirm whether personalization is content-based, collaborative, or hybrid.
Choose a single metric that best captures the feed's success, such as Daily Active Users (DAU) or Time Spent per User, but justify why it aligns with long-term value.
Break down metrics into user engagement (CTR, likes, shares, comments), user satisfaction (surveys, sentiment), and business impact (ad revenue, retention). Include guardrail metrics like user reports or unfollows.
Propose A/B tests to compare personalized vs. non-personalized feeds, define success criteria, and consider long-term holdout groups to measure retention effects.
Set up dashboards to track metrics over time, segment by user cohorts, and establish a process to iterate on the algorithm based on results.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.