An A/B test offers free users a limited-time trial of the paid plan to see whether it increases paid subscriptions and reduces churn.

Compute the signup (paid-conversion) rate for treatment vs. control and the percentage lift. 2. Test whether the lift is statistically significant (state your test, null/alt hypotheses, p-value or CI). 3. Calculate and compare cancel rates during the trial and after the first paid billing cycle. 4. Estimate net paid-subscriber change after 30 days and 60 days, incorporating both signups and cancels. 5. What additional metrics or user segments would you examine before recommending a full roll-out? 6. Summarize the experiment outcome and give a go / no-go recommendation with supporting numbers.

Standard A/B-testing framework: define metrics, check randomization, use proportion test or delta method, segment by tenure, bucketed time windows.

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