Privacy-aware marketing AI & customer data
Reduce exposure before using customer or CRM data with AI: classify, minimize, control access, document purpose, and verify vendor handling.
When to use it
Use before using customer records, support transcripts, CRM exports, lead lists, or behavioral data in an AI tool or automated marketing workflow.
What you need
- Data fields, source, purpose, audience, and intended model/vendor
- Access roles, retention/deletion controls, transfer locations, and contract terms available
- Applicable internal policy and review contact for the relevant market
Workflow
- 01
Map the flow
Record where the data originates, where it moves, who can access it, and what decisions use the output.
- 02
Minimize before transfer
Remove fields not needed for the task; avoid direct identifiers and sensitive details unless explicitly authorized and necessary.
- 03
Check the tool and terms
Verify retention, training use, access, deletion, subprocessors, region, and contractual controls from current vendor documentation.
- 04
Choose a safer method
Use synthetic or aggregated examples where possible; otherwise use approved environments, role controls, and documented safeguards.
- 05
Review output use
Check whether profiling, targeting, or automated decisions introduce additional review or notice requirements.
- 06
Record and govern
Log purpose, data categories, reviewer, vendor, retention, incident contact, and review date; test deletion and revoke access when no longer needed.
Output
A data-flow record, minimum-field dataset, vendor and purpose review, access/retention controls, and documented approval decision.
Boundaries
This framework does not determine legal basis or compliance. Requirements vary by jurisdiction, data, purpose, and vendor; get qualified privacy/legal review.
How it fits existing work
This is a data-handling framework, not a CRM integration or legal-compliance promise; it complements existing measurement and messaging playbooks.