Implementation checklist
Cookieless Analytics Implementation Checklist: From Plan to QA
A complete cookieless analytics implementation checklist covering goals, privacy, events, installation, data quality, funnels, and launch QA.
A one-line script can install analytics, but it cannot define trustworthy measurement. This checklist turns installation into a controlled implementation with clear business questions, minimized data, and testable acceptance criteria.
Use it for a new site, a migration from GA4, or a repair of an analytics setup nobody trusts.
1. Define decisions before events
- Name the owner of the analytics setup
- Write the three questions the team needs answered weekly
- Choose one primary conversion and two supporting conversions
- Define the source of truth for revenue, signups, or leads
- Set an acceptable variance between analytics and backend totals
2. Complete the privacy review
- Document the collection purpose and legal basis
- List identifiers, IP handling, event fields, and subprocessors
- Set retention to the shortest useful period
- Confirm data location and deletion procedures
- Block personal data in URLs and event properties
- Update the privacy notice
- Ask qualified counsel whether consent is required for this exact setup
3. Create a small event dictionary
| Event | Trigger | Required properties | Owner |
|---|---|---|---|
| page_view | Route becomes visible | path, referrer | Engineering |
| signup_started | Form begins | source | Growth |
| signup_completed | Account is created | plan | Product |
| purchase | Payment succeeds | amount, currency, product | Revenue |
4. Install deliberately
- Load the script once on every public route
- Verify single-page app navigation creates one page view
- Use stable names for important buttons and links
- Track purchases from a trusted server-side confirmation when possible
- Preserve campaign parameters without storing unnecessary personal data
- Exclude internal and test traffic
5. Run launch QA
- Test direct, search, social, and campaign visits
- Test new and returning sessions
- Complete every conversion on desktop and mobile
- Check duplicate page views and events
- Test ad blockers and strict browser settings
- Confirm time zone and currency
- Compare a controlled set of test conversions with backend records
- Verify deletion and data-export procedures
6. Build the measurement loop
Define the expected journey, then compare it with observed event sequences. Automatic funnel detection can surface paths the tracking plan missed. Prioritize the largest meaningful drop-off, write a hypothesis, and choose a single success metric plus guardrails before launching an experiment.
- Review funnel volume and drop-off weekly
- Segment only when sample sizes remain useful
- Record experiment exposure before the outcome
- Wait for a pre-defined sample and duration
- Document decisions, including inconclusive tests
7. Keep the implementation healthy
- Assign an owner to each key event
- Add analytics QA to release checklists
- Review unknown events and properties monthly
- Reconcile conversions with source-of-truth data
- Audit access and retention quarterly
- Remove events that no longer support decisions
Definition of done
The setup is complete when a non-analyst can answer the agreed business questions, the key conversion matches backend records within the accepted range, privacy controls are documented, and a release test catches missing or duplicate events.
Put the guide into practice
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