# 11. Reviews, Trust & Safety

← Business Requirements

## (a) Business requirements #

- A customer can leave one review per completed booking (rating 1–5 + free text), tied to a verified, completed, on-platform booking.
- Moderation: reviews enter `pending_moderation` and are not public until approved by an admin (or an AI moderator). Aggregate nurse rating/counts are recomputed on every review status transition — publish, hide, reject, unpublish — so hiding a 1-star review never leaves a stale, inflated average.
- Low-rating alerting: a rating at or below a configurable threshold (default ≤ 2) with negative content automatically raises a `support_alerts` row for the support team to investigate.
- Incident handling: rapid-response protocols with immediate suspension on credible complaints; structured family check-ins and easy in-app concern flagging (the patient is not the sole information source); high-acuity cases routed only to appropriately verified nurses.

## (b) Iran-specific considerations #

- The buyers are vulnerable people cared for unobserved at home; a single incident can destroy a fragile, trust-first brand — so moderation, low-rating alerting, and immediate suspension are core, not optional.
- Verified-trust is the brand; reviews must be bound to real completed bookings to resist fake-review fraud (gig-marketplace fraud is ~2× elsewhere, mostly impersonation).

## (c) MVP vs DEFERRED #

- MVP: one-per-completed-booking customer reviews; moderation with full recompute-on-every-transition; low-rating `support_alerts`; manual incident suspension.
- DEFERRED: two-way (nurse-reviews-customer) double-blind reviews with timed reveal; structured review-tag aggregation (`review_tags_master` / `review_tag_links` modeled but a phase-2 nicety); a dedicated `incidents` entity; ML fraud scoring.

## (d) Supporting database entities #

`reviews` (moderation status, recompute triggers), `review_tags_master`, `review_tag_links`, `support_alerts` (low-rating, fraud-signal), `nurse_profiles` (denormalized aggregates), `audit_logs`.

> Related: Data model — Reviews & Records.

↑ Back to top