Marketing CDP Checklist for Growth Teams

A customer data platform may help when campaign, product, commerce, payment, and messaging records need to support the same decision or workflow. The useful question is not “Do we need a CDP?” It is “Which repeated data problem are we paying to solve?”

Start with the problem, required records, owners, and limits. Then compare products against that contract.

What to define before evaluating a platform

• The decision or workflow that needs better data
• The sources and exact objects or events required
• The stable identifiers available in each source
• The metric, currency, timezone, and attribution definitions
• The destination that needs the result
• Consent, retention, deletion, and access requirements
• The schedule and historical range the workflow needs

A five-step evaluation

1. Define the business event

Choose a small set of events tied to an observable business state, such as:

• Lead Qualified
• Trial Started
• Order Completed
• Subscription Renewed

For each event, document the owner, source, timestamp, stable event identifier, value, currency, and correction behavior.

2. Record each source contract

For every source, write down:

• Authentication and account scope
• Available fields and retained history
• API latency and rate limits
• Timezone and currency behavior
• Late, revised, deleted, or duplicated records

Do not assume similar-looking fields have the same meaning across tools.

3. Define identity rules

Prefer stable, consented identifiers such as an authenticated user ID or provider customer ID. Document when anonymous activity may be linked, how conflicts are handled, and which records must remain unmatched.

4. Build a reviewable conversion table

A useful conversion table usually records:

• Source event identifier and timestamp
• Customer or account identifier when available
• Campaign and click identifiers when captured
• Value, source currency, and reporting currency
• Attribution method and lookback settings
• Data-quality status and correction history

The table should make gaps and assumptions visible rather than hiding them behind a single total.

5. Test downstream delivery separately

If a compatible destination needs conversion events or customer groups, validate its schema, identity requirements, consent rules, deduplication support, rate limits, rejected records, and resulting platform match. Delivery does not guarantee that the destination accepts or uses every record.

Common failure modes

• Buying a platform before naming the repeated problem
• Treating field renaming as semantic standardization
• Matching customers without reliable identifiers or consent
• Hiding attribution assumptions in a dashboard
• Promising a fixed historical range without checking provider limits
• Treating a successful API response as proof that the destination used the data

Readiness test

Ask an owner to trace one important number from source record to mapping, calculation, report, and destination. If the path, assumptions, and gaps cannot be explained, fix that contract before expanding the workflow.