You’re analyzing appointment behavior for a scheduling product. ## Table ### `appointments` - `appointment_id` (STRING, PK) - `user_id` (STRING) - `scheduled_start_ts` (TIMESTAMP, UTC) — when the appointment was scheduled to happen - `status` (STRING) — one of: `confirmed`, `cancelled`, `returned` - Assume each appointment appears once with its final status. ## Definitions - A user’s **first cancelled appointment** is the cancelled appointment with the earliest `scheduled_start_ts` for that user. - A **future returned/confirmed appointment** means any appointment for the same user with: - `scheduled_start_ts` strictly greater than the `scheduled_start_ts` of their first cancelled appointment, and - `status IN ('returned', 'confirmed')`. ## Task Write a SQL query to compute the **percentage of users whose first cancelled appointment is followed by _no_ future returned or confirmed appointment**. ### Output Return exactly one row with: - `percent_never_returned` (DECIMAL) — 100 * (number of qualifying users / number of users who have at least one cancelled appointment). ## Notes / Edge cases - Users with no cancelled appointments are excluded from the denominator. - If a user has a returned/confirmed appointment at the exact same timestamp as the first cancellation, do **not** count it as “future”.