Analytics data ownership is the ability to control access, export useful records, enforce retention, and delete data when it is no longer needed. A vendor's use of cookies is a separate question: a cookieless tracker can still send data to a managed service, and a self-hosted service still needs an operator who can protect it.
Use this checklist to turn “we own the data” into requirements you can verify before choosing a platform. For a product shortlist, use the analytics platform comparison. For infrastructure responsibilities, use the self-hosted ownership guide.
1. Define which records you need to control
List the reports and underlying records your team needs: pageviews, custom events, campaign parameters, error details, or account-linked activity. A CSV containing daily totals is useful for a report archive, but it is not equivalent to an event-level export suitable for rebuilding a funnel.
For each record type, write down the required fields, timestamp precision, timezone, and identity rules. Record whether profile identifiers are customer-supplied, generated, or transformed. Keep sensitive fields out of analytics unless they are necessary for a defined purpose.
2. Test export with a small synthetic dataset
Create a test website and generate a known sequence: a visit, a signup, and one completed product action. Export the records through the supported dashboard or API workflow. Check the output against your expected sequence rather than assuming that an export button proves complete portability.
| Requirement | Evidence to request |
|---|---|
| Reporting continuity | An export with documented date boundaries, timezone, and metric definitions. |
| Event portability | The needed event names, properties, identifiers, and timestamps in a supported format. |
| Repeatable access | Documented pagination, permissions, rate limits, and plan restrictions. |
| Exit planning | A procedure and owner for retrieving the records before ending service. |
For Databuddy, start with the analytics query reference and test the specific outputs your reporting workflow needs. Query access does not by itself establish a full historical import path into another product.
3. Check retention and deletion separately
Ask how long active records, backups, exports, and logs remain available. Confirm which settings you control and which require support. Deleting a dashboard or revoking an API key is not the same operation as deleting stored analytics.
Document the procedure for a website deletion, a profile-related request where identification is used, and an organization exit. Include backup handling and the expected completion evidence. Do not promise immediate deletion from every storage layer without a documented mechanism.
4. Verify access boundaries
Use a second synthetic team member to check the permissions your organization needs. A contractor who can read a report should not automatically gain the ability to change collection settings or manage credentials.
Review API-key scopes, website access, organization roles, and credential rotation. See the API-key guide for Databuddy's scope model. Keep keys and raw exported records out of public documentation and source control.
5. Review hosting and subprocessors
Managed hosting transfers operational work to the provider; it does not establish that data never reaches infrastructure suppliers. Self-hosting gives you deployment control while making your team responsible for databases, backups, updates, and access.
Record the actual processing region, relevant subprocessors, contractual terms, and transfer arrangements. Review those facts for your deployment rather than relying on a general “full ownership” label. The security reference is a starting point for Databuddy's controls.
6. Keep cookieless collection distinct from ownership
Inspect cookies, localStorage, sessionStorage, requests, and event payloads. Databuddy avoids analytics cookies but uses browser storage; identification and custom properties can change the data being processed. The collection guide explains the configuration to review.
A cookieless label does not settle consent or data-protection requirements. CNIL's audience-measurement guidance describes conditional exemptions. Apply the rules relevant to your configuration and visitors.
Make ownership an acceptance test
Before rollout, keep the synthetic export, access results, retention settings, deletion procedure, and named owner in one review record. Revisit it when you enable identification, add a new event property, change hosting, or connect another service. That gives your team evidence it can use when the measurement workflow changes.