Document Type: Framework
Status: Active
Authority: Data Brain
Parent: Data Brain Architecture
Applies To: All analytics audits, measurement reviews, and tracking validation processes across MWMS
Version: v1.0
Last Reviewed: 2026-04-23

Purpose

The Data Brain Analytics Audit Checklist defines the standardised execution process for conducting analytics audits across MWMS.

This page converts the Analytics Audit Framework into:

• repeatable audit steps
• structured validation checks
• consistent audit outputs
• actionable findings

The checklist ensures all audits are:

• complete
• consistent
• comparable
• decision-relevant

Core Principle

An audit is only valuable if:

• it is structured
• it is repeatable
• it produces actionable outputs

Unstructured audits produce inconsistent results.

Position in MWMS System

This checklist operates under:

• Data Brain Analytics Audit Framework
• Data Brain Measurement Quality Assurance Framework
• Data Brain Measurement Integrity Framework

This page is the execution layer of audit governance.

Audit Execution Flow

All audits must follow this sequence:

Step 1 — Define Audit Scope

Confirm:

• platform(s) being audited (GA4, GTM, Ads, etc.)
• environments (live, staging, subdomains)
• business objectives (conversion, lead, revenue, etc.)
• key metrics used for decisions

Step 2 — Business Alignment Check

Validate:

• primary conversions clearly defined
• key events mapped to user journey
• metrics aligned to business outcomes
• reporting used by decision-makers is correct

Step 3 — Implementation Audit

Check:

• tracking code present on all key pages
• GTM container functioning correctly
• no duplicate implementations
• no orphaned or unused tags
• correct property and stream setup

Step 4 — Event Validation

Validate all critical events:

• events fire when expected
• events do not fire incorrectly
• parameters exist and are correct
• values reflect real behaviour

Tools:

• GTM preview
• GA4 debug view
• data layer inspection

Step 5 — Duplicate Detection

Check for:

• duplicate page views
• duplicate conversions
• duplicate event firing

Indicators:

• inflated metrics
• abnormal ratios
• inconsistent counts

Step 6 — Missing Data Check

Validate:

• all key funnel steps are tracked
• no missing conversion events
• no gaps in user journey

Test:

• run full user journey manually
• compare expected vs actual events

Step 7 — Internal Traffic Check

Confirm:

• internal traffic excluded or flagged
• test traffic not polluting data

Step 8 — Source and Attribution Check

Validate:

• UTMs structured correctly
• unwanted referrals excluded
• source/medium classification correct
• channel grouping logical

Step 9 — Cross-Platform Validation

Compare:

• GA4 vs Ads platforms
• analytics vs backend / CRM

Check for:

• missing conversions
• inflated conversions
• attribution discrepancies

Step 10 — Data Integrity Review

Evaluate:

• data consistency across time
• ratio consistency (funnel logic)
• unexplained spikes or drops
• stability of signals

Step 11 — Privacy and Compliance Check

Confirm:

• cookie consent behaviour correct
• no tracking without consent where required
• no PII captured
• data retention settings appropriate

Step 12 — Monitoring Check

Confirm:

• alerts configured (GA4 insights or equivalent)
• anomaly detection active
• monitoring system in place

Audit Findings Classification

All findings must be classified:

• Critical → breaks data or decisions
• High → major distortion risk
• Medium → partial accuracy issue
• Low → optimisation opportunity

Audit Output Structure

Each audit must produce:

• Issue description
• Affected system
• Impact level
• Root cause
• Recommended fix
• Priority classification

Audit Completion Criteria

An audit is considered complete when:

• all checklist steps executed
• all findings documented
• priorities assigned
• fixes defined

Audit Frequency Guidelines

Minimum audit cadence:

• continuous monitoring → daily/weekly
• light audit → monthly
• full audit → quarterly
• triggered audit → after major changes

Audit Failure Conditions

An audit is invalid if:

• scope not defined
• key steps skipped
• validation not performed
• findings not classified
• outputs not actionable

Relationship to Other Frameworks

This checklist supports:

• Data Brain Analytics Audit Framework
• Data Brain Measurement Quality Assurance Framework
• Data Brain Measurement Integrity Framework
• Data Brain Data Trust Framework
• HeadOffice Audit Findings Prioritization Framework

Key Outcomes

When used correctly:

• audits become consistent
• issues are identified faster
• data quality improves
• decision risk reduces
• MWMS operates on validated measurement

Change Log

Version: v1.0
Date: 2026-04-23
Author: Data Brain

Change:
Initial creation of Analytics Audit Checklist as execution layer for Analytics Audit Framework.

Change Impact Declaration

Pages Created:
Data Brain Analytics Audit Checklist

Pages Updated:
None

Pages Deprecated:
None

Registries Requiring Update:
MWMS Architecture Registry

Canon Version Update Required:
No

Change Log Entry Required:
Yes