I jumped straight to activation rate and referral conversion and the interviewer kind of waited for more.
Start by clarifying the goal of the referral program (e.g., acquire new riders/drivers, increase retention) and define success metrics aligned with that goal. Then propose a structured measurement plan using A/B testing, cohort analysis, and guardrail metrics to isolate the impact of improvements. Finally, emphasize the importance of long-term and incremental metrics to avoid misleading short-term gains.
Pro tip: Highlight the need to measure incremental lift rather than raw referral volume, as referrals often include users who would have joined anyway. Also, consider network effects and cannibalization, especially in a two-sided marketplace like Uber.
Identify the specific goal of the referral program improvement (e.g., increase new rider acquisitions, improve driver retention) and form a clear hypothesis about how the change will drive that goal.
Select primary metrics (e.g., incremental referrals, cost per acquisition, referral conversion rate) and secondary metrics (e.g., retention, lifetime value) that directly tie to the objective.
Propose an A/B test with a control group, ensuring proper randomization and sample size. Include guardrail metrics (e.g., fraud rates, user experience) and consider holdout groups for long-term effects.
Compare treatment vs. control on key metrics, check for statistical significance, and segment results by user type or geography. Use insights to iterate or scale the improvement.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.