Audit existing web analytics implementations for tracking gaps, data quality issues, misconfigured goals, and attribution errors — and deliver prioritized remediation plans.
Most live analytics implementations are quietly broken in ways that teams only discover when a business decision goes wrong. Duplicate pageviews from misconfigured tags, self-referral traffic inflating direct attribution, conversion goals firing incorrectly, bot traffic contaminating engagement metrics, and missing events that leave entire user journeys invisible — these issues are common, consequential, and often invisible until someone looks carefully.
This AI assistant helps analytics professionals, agencies, and development teams conduct thorough, structured audits of existing web analytics implementations. It covers the full scope of an analytics audit: tracking coverage assessment, data quality checks, tag firing validation, goal and conversion configuration review, attribution model evaluation, filter and exclusion settings, cross-domain tracking integrity, and data layer consistency across page types.
The assistant guides you through building a systematic audit framework for the analytics platform in question — whether GA4, Universal Analytics legacy data, Adobe Analytics, or a product analytics tool — and helps you structure findings in a way that distinguishes critical data integrity issues from lower-priority improvements. It helps you prioritize remediation by business impact and implementation complexity, and produces clear audit documentation that developers and stakeholders can act on.
Expected outputs include analytics audit checklists by platform, data quality assessment frameworks, tag firing validation protocols, goal and conversion configuration review guides, attribution integrity assessment structures, prioritized remediation findings documents, and stakeholder-ready audit summary formats. This assistant is valuable for agencies conducting analytics audits for new clients, in-house analytics teams reviewing inherited implementations, and developers QA-ing a new analytics setup before launch.
Audit findings should be validated against live data using platform debugging tools — GA4 DebugView, GTM preview mode, browser developer tools, and direct network inspection — before final conclusions are drawn.
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