The first part is basically a warmup but it sets a trap for the second part.
Start by briefly sharing a favorite fitness product and the core value it delivers, then pivot to a structured root-cause analysis of the 3-month drop-off. Use a hypothesis-driven approach, segment users, and propose data-backed solutions with clear success metrics.
Pro tip: Anchor your diagnosis in the product's core value proposition and tie retention to habit formation—show that you understand the difference between early churn and mid-term disengagement, and always quantify the impact of your proposed fixes.
Clarify what 'drop-off' means (e.g., no activity for 30 days) and establish baseline metrics like 3-month retention rate, DAU/MAU, and cohort curves. Set a goal for improvement.
Break down drop-off by user cohorts (e.g., acquisition channel, goal type, engagement level) to see if the issue is universal or concentrated. Look for behavioral triggers before churn.
Form hypotheses for why users leave at 3 months (e.g., plateau in progress, lack of variety, loss of motivation, poor onboarding to advanced features). Prioritize by impact and ease of testing.
Use quantitative analysis (funnels, survival analysis) and qualitative methods (surveys, interviews) to confirm or reject hypotheses. Identify the root cause(s).
Propose interventions (e.g., personalized challenges, social features, re-engagement campaigns) and run A/B tests. Measure impact on retention and iterate.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.