This engagement centered on modernizing a legacy enterprise analytics stack without losing business-critical visibility. The challenge was to move toward cleaner, more governed tracking while keeping the organization operationally confident during the transition.
Challenge
The existing analytics environment was fragmented across platforms and event definitions.
Large event volumes and mixed implementation patterns made maintenance costly.
Privacy, consent, and downstream activation all needed to be preserved during migration.
Approach
Started by rationalizing event taxonomy against actual business journeys instead of legacy naming patterns.
Used GA4 and GTM as the core implementation layer with BigQuery-ready outputs in mind.
Considered privacy tooling and downstream activation from the start rather than bolting them on later.
Execution
Migrated Adobe Analytics and DTM patterns into a more maintainable GA4 + GTM architecture.
Collapsed 800+ noisy events into a clearer instrumentation model.
Supported activation and privacy integrations including Meta CAPI and OneTrust-friendly workflows.
Results
Created a more resilient analytics foundation for reporting and growth teams.
Reduced implementation complexity while increasing governance and clarity.
Improved downstream readiness for warehouse analysis and marketing activation.
Key Takeaways
Migration projects succeed when governance is treated as product design, not cleanup.
Better tracking often comes from simplification, not expansion.
Warehouse-readiness and privacy-readiness should be part of the same architecture conversation.