As part of analyzing the same promotion experiment, you need SQL that handles users who churn and later resubscribe. Assume the following tables: 1. experiment_assignments - user_id BIGINT - variant STRING -- control or free_month - assigned_at TIMESTAMP This table already contains only users who qualified for the experiment, so you do not need to implement eligibility logic. 2. subscription_periods - user_id BIGINT - period_start_at TIMESTAMP - period_end_at TIMESTAMP NULL -- exclusive end time; NULL means the subscription is still active Each row represents one continuous subscription period. A user may appear in multiple rows if they churn and later resubscribe. Key relationship: experiment_assignments.user_id = subscription_periods.user_id. All timestamps are in UTC. For users assigned between 2025-01-01 00:00:00 UTC and 2025-01-31 23:59:59 UTC, write SQL that returns one row per assigned user with the following columns: - user_id - variant - converted_within_7d: 1 if the user starts any subscription in the interval [assigned_at, assigned_at + 7 days) - active_on_day_30: 1 if the user has an active subscription at exactly assigned_at + 30 days, even if they churned and resubscribed before day 30 - had_churn_and_return_before_day_30: 1 if the user has at least two distinct subscription periods with period_start_at < assigned_at + 30 days After producing the user-level result, explain how you would aggregate it to variant-level conversion and 30-day retention metrics.