Confirm attribution after membership verification
epic-membership-recruitment-core-services-task-008 — Implement the confirmAttribution method in ReferralAttributionService. When the membership system signals that a referred new member's membership is fully verified, this method transitions the pending attribution record to confirmed status via the repository. Include guard logic to prevent double-confirmation and to handle cases where the attribution record no longer exists (e.g., was manually removed).
Acceptance Criteria
Technical Requirements
Execution Context
Tier 3 - 413 tasks
Can start after Tier 2 completes
Implementation Notes
Implement as a conditional PATCH to avoid the read-then-write antipattern. In Supabase Dart client: `supabase.from('attribution_records').update({'status': 'confirmed', 'confirmed_at': DateTime.now().toUtc().toIso8601String()}).eq('new_member_id', newMemberId).eq('status', 'pending')`. Check the count of affected rows in the response — if 0 rows updated, distinguish between 'already confirmed' and 'not found' by doing a follow-up read (this is the only acceptable use of read-then-write here, as a diagnostic step after a no-op update). After a successful update, call `publishMilestoneEvent(mentorId, MilestoneType.attributionConfirmed)` — resolve mentorId from the fetched record.
Return sealed class: ConfirmationResult (Confirmed, AlreadyConfirmed, NotFound).
Testing Requirements
Unit tests (flutter_test + Mockito): mock IRecruitmentAttributionRepository. Test: (1) pending record transitions to confirmed and confirmed_at is set; (2) already-confirmed record — repository update not called, AlreadyConfirmed returned; (3) no record for member — AttributionNotFound returned; (4) repository throws — exception propagates; (5) publishMilestoneEvent is called exactly once on success and zero times on AlreadyConfirmed/NotFound. Use argument captors to assert the PATCH payload contains status='confirmed' and a valid confirmed_at timestamp.
Confirmed registration events originate from the membership system (Dynamics portal for HLF), which may call back asynchronously with significant delay. If the attribution service only accepts synchronous confirmation at registration time, late callbacks will fail to match the originating referral code, resulting in under-counted conversions.
Mitigation & Contingency
Mitigation: Design the attribution confirmation path as a webhook endpoint (Supabase Edge Function) that accepts a referral_code + new_member_id pair at any time after click. The service matches by code string, not by session. Persist pending_signup events immediately at onboarding screen submission so there is always a record to upgrade to 'confirmed' when the webhook fires.
Contingency: If the membership system cannot reliably call the webhook, implement a polling reconciliation job (Supabase pg_cron, daily) that queries the membership system for recently registered members and back-fills any unmatched attribution records.
If confirmRegistration() is called more than once for the same new member (e.g., idempotency retry from the webhook), duplicate milestone events could be emitted, causing the badge system to award badges multiple times.
Mitigation & Contingency
Mitigation: Use a UNIQUE constraint on (referral_code_id, new_member_id) in the referral_events table for confirmed events. The confirmRegistration() method uses upsert semantics; milestone evaluation reads the confirmed count from the aggregation query rather than counting individual calls.
Contingency: If duplicate awards occur in production, the badge system should support idempotent award checks (query existing badges before awarding). Add a deduplication guard in BadgeCriteriaIntegration as a secondary defence.
Stakeholder review may expand attribution requirements mid-epic to include click-through tracking per channel (WhatsApp vs SMS vs email), which is not currently in scope but was mentioned in user story discussions. This would require schema changes in the foundation epic and delay delivery.
Mitigation & Contingency
Mitigation: Capture per-channel data in the device_metadata JSONB field from day one as an unstructured field (share_channel: 'whatsapp'). This preserves data without requiring a schema column, allowing structured querying to be added later without migrations.
Contingency: If channel-level analytics become a hard requirement during this epic, timebox the change to adding a nullable channel column to referral_events and a corresponding filter parameter on the aggregation query, deferring dashboard UI to a separate task.