I went straight to metrics and engagement numbers, which felt safe but probably wasn't what they wanted.
Start by clarifying the goal of the improvement (e.g., increase meaningful engagement, reduce toxicity, or improve user experience) and define success metrics. Then, identify key user pain points through data or research, brainstorm potential features, prioritize based on impact and feasibility, and outline how you would measure and iterate.
Pro tip: Anchor your answer in a specific user segment and a measurable goal, and always tie features back to Meta's business objectives like meaningful interactions and time well spent.
Ask clarifying questions to understand the objective (e.g., improve engagement, reduce harmful content) and which user segment to focus on. Define what 'improvement' means in measurable terms.
Use data (e.g., engagement metrics, sentiment analysis) and user research to pinpoint key issues with the current comments feature, such as spam, toxicity, lack of context, or poor discoverability.
Generate a range of feature ideas addressing the pain points, then prioritize using a framework like RICE (Reach, Impact, Confidence, Effort) or impact vs. effort matrix.
Specify metrics to evaluate the chosen solution, such as increase in meaningful comments, reduction in reports, or improvement in user satisfaction scores. Include guardrail metrics to monitor unintended consequences.
Describe a high-level plan for A/B testing, rollout, and iteration based on results. Mention potential technical challenges and how to address them.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.