My first instinct was to just say yes, 10% lift sounds good, ship it.
Start by clarifying the goal and constraints, then evaluate the algorithm update against key metrics beyond matches, such as user engagement, retention, and monetization. Propose a structured testing plan to validate the 10% lift and assess potential risks before making a launch decision.
Pro tip: Always consider second-order effects: an increase in matches might not translate to meaningful conversations or dates, and could even harm user experience if it leads to lower-quality matches. Emphasize the importance of measuring downstream metrics and guardrails.
Ask clarifying questions to understand the goal (e.g., increase matches vs. meaningful connections), timeline, resources, and any strategic priorities for Facebook Dating.
Identify primary metrics (e.g., matches, conversations, dates) and guardrail metrics (e.g., user satisfaction, retention, reports) to ensure the update doesn't negatively impact the ecosystem.
Assess the credibility of the 10% projection: review the methodology, sample size, and potential biases. Consider if the lift is statistically significant and practically meaningful.
Propose an A/B test to validate the update in a controlled environment, measuring both primary and guardrail metrics. Determine sample size, duration, and success criteria.
Based on experiment results, decide whether to launch, iterate, or abandon. Consider a phased rollout to monitor long-term effects and gather user feedback.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.