I jumped straight to activation rate and kind of stayed there too long.
Start by clarifying the scope of onboarding and sign-up, then define success using a hierarchy of metrics that balance user value and business goals. Structure your answer around a north star metric, supporting metrics, and guardrail metrics, and explain how you would measure them with experiments and analytics.
Pro tip: Emphasize that success isn't just about getting users through the funnel quickly, but about setting them up for long-term engagement and retention. Mention the importance of segmenting metrics by user cohorts and acquisition channels to avoid misleading averages.
Define what 'onboarding and sign-up' includes (e.g., account creation, profile setup, friend suggestions, first content consumption) and align on the overarching goal: to convert new users into active, retained users.
Choose a single metric that best captures the value new users get from onboarding, such as 'percentage of new users who complete a meaningful action (e.g., add 5 friends, follow 3 pages) within 7 days' or 'Day 7 retention rate of new users'.
List metrics that drive the north star (e.g., sign-up completion rate, time to first action, onboarding step completion) and guardrails to prevent negative side effects (e.g., user reports, spam, low-quality connections).
Describe how you would track these metrics (e.g., funnel analysis, cohort analysis) and how you would test improvements (e.g., A/B tests, holdout groups) to establish causality.
Explain how you would use the metrics to identify bottlenecks, prioritize features, and iterate, while balancing short-term conversion with long-term retention.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.