# Consent and Communication Preference Sync

Design a preference automation that keeps consent, subscription status, channel choices, and suppression rules consistent across systems.

## Prompt

You are a consent operations architect who specializes in preference synchronization, provenance, and privacy-safe communication controls.

Inputs:
1. Communication purposes, channels, brands, and regions: {{communication_context}}
2. Consent, objection, subscription, and preference sources: {{preference_sources}}
3. CRM, marketing, product, support, and messaging systems: {{systems}}
4. Legal bases, evidence, precedence, and retention rules: {{governance}}
5. Identity, latency, security, and exception constraints: {{constraints}}

Do the following:
1. Define a canonical preference and consent model covering person or account identity, purpose, channel, brand, region, status, source, timestamp, notice version, evidence, and expiry where applicable.
2. Establish precedence for opt-out, objection, opt-in, administrator settings, transactional necessity, local rules, and conflicting updates without treating every communication as marketing.
3. Design event ingestion, identity resolution, validation, propagation, acknowledgement, retry, reconciliation, and suppression behavior across all connected systems.
4. Specify double opt-in, bounced addresses, shared inboxes, minors, deleted accounts, merged records, delayed events, offline capture, and restoration from backups.
5. Produce the data model, precedence table, event contract, synchronization workflow, reconciliation report, user-facing confirmation copy, audit evidence, and failure tests. Do not infer consent from silence, service use, or unrelated preferences.

## Best for

Privacy, marketing operations, and engineering teams keeping communication choices consistent across fragmented customer systems.

## Compatible tools

- Claude
- ChatGPT

## How to use

- Define purposes separately from channels.
- List every source and destination system.
- Agree precedence rules with privacy owners.
- Test opt-out propagation before campaign use.

## Customization tips

- Use suppression-first behavior during uncertainty.
- Retain provenance and notice version.
- Handle merged identities explicitly.
- Reconcile actual destination state, not only sent events.

## Example input

Context: Consumer mobility app operating in Germany and Austria. Channels: email, push, SMS, and in-app messages for product updates, promotions, safety alerts, and receipts. Sources: app preference center, website forms, support requests, CRM imports, and email unsubscribe links. Systems: customer database, CRM, marketing automation, push provider, and SMS gateway. Constraints: marketing opt-outs propagate within five minutes, safety alerts remain separate, and double opt-in evidence is retained.

## Example output

The model stores preference by purpose and channel rather than one global marketing flag. A marketing objection overrides later imported subscriptions unless a new valid opt-in is recorded. Receipts and safety alerts remain separately governed. Every change carries source, notice version, timestamp, and evidence; failed propagation places the destination on a suppression-first exception queue. Nightly reconciliation detects systems that silently diverged.