Feature Success Measurement Questions
Focuses on measuring the impact of a single feature or product change. Key skills include defining a primary success metric, selecting secondary and guardrail metrics to detect negative side effects, planning measurement windows that account for ramp up and stabilization, segmenting users to detect differential impacts, designing experiments or observational analyses, and creating dashboards and reports for monitoring. Also covers rollout strategies, conversion and funnel metrics related to the feature, and criteria for declaring success or rollback.
MediumTechnical
0 practiced
When reporting experiment results, when would you prefer confidence intervals over p-values? Describe how you would present both in a dashboard tile for product managers and executives, and how to interpret wide vs narrow intervals in the context of decision-making.
HardTechnical
0 practiced
You need to compute Kaplan–Meier survival curves for time-to-churn after a usage-limiting feature release using tables users(user_id, signup_date) and events(user_id, event_name, occurred_at). Describe the SQL steps or pseudo-SQL and the logic to handle censoring (users who haven't churned during observation), and how you'd present and interpret the survival curves for treatment vs control.
MediumTechnical
0 practiced
Given tables:users(user_id STRING, created_at TIMESTAMP)events(user_id STRING, event_name STRING, occurred_at TIMESTAMP)Write a SQL query to create weekly cohorts by signup_week and compute conversion to 'feature_used' within 14 days of signup. Output columns: cohort_week, cohort_start_date, users_in_cohort, converted_count, conversion_rate. Explain any assumptions about week boundaries and timezone handling.
MediumTechnical
0 practiced
Propose a staged rollout plan for a monetization feature (e.g., premium upsell) that balances learning and risk mitigation. Include percentage rollouts, canary regions or accounts, use of holdout groups for long-term measurement, monitoring cadence, and concrete rollback triggers.
MediumTechnical
0 practiced
A 'quick-buy' button increased early funnel clicks but did not increase completed purchases. List possible reasons for this leak (e.g., poor basket flow, pricing friction) and describe the analyses (SQL queries, session replays, funnel visualization) you would run to pinpoint where users drop out.
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