Google Analytics Migration - GA UA to GA4

A Migration of data platform applications from Google Analytics UA to GA4 version.

Overview

This project involves transitioning the data analytics infrastructure across the organization from the traditional Universal Analytics (UA) platform to the newer Google Analytics 4 (GA4) platform. This migration involves transferring existing data, configurations, and reporting setups from UA to GA4, ensuring a smooth transition while leveraging new capabilities and features offered by the GA4. The migration ensures continuity of analytics operations beyond the deprecation of Universal Analytics (UA) in July 2024, safeguarding access to essential data insights and analytics functionality.

Problem Statement

The UA version will cease to be operational after July 2024, necessitating a transition to GA4. Failing to migrate risks losing valuable data insights, hindering decision-making, and impacting the organization's ability to track and optimize performance effectively. GA4 is not backwards compatible with GA3. Thus, there was a critical need to ensure seamless integration and enhancement of the data platform and dependent applications to maintain continuity in data tracking, reporting, marketing processes, and product analysis post-migration. Each client was allocated a separate property in GA UA. However, clients with lower traffic volumes were exceeding the allowable limit for properties per account.

Solution

Migrated Google Analytics platform to GA4 using the new event driven architecture.
A single shared GA4 property for clients with considerably lesser traffic.
Enhanced Data platform integrations with GA using Google BigQuery.
Tableau and Looker Studio reports Migration to GA4
Data applications dependent on GA UA data, GA APIs and GA Google Sheet connectors migrated to GA4
A cookbook and training plan for the GA users.
Onboarding users to GA4 using a phased approach per team and deprecating GA3.

My Role

Collaborated with marketing, account management, product, architecture, storefront and data engineering and data insights teams to build an exhaustive roadmap to migrate from GA UA to GA4.
Led the Architecture and SF platform teams to migrate the GA Tag, Websites/Apps, and GA console setup by providing specifications, UAT plan and configurations.
Conducted validations to ensure GA4 data compares with GA UA. Documented reasoning for mismatches between basic metrics like Users, Sessions, Views, Events and Conversions.
Defined Account-Property structure for more than 600 clients, Event parameters, Goals/Conversions, Custom Dimensions and Metrics configurations and Filters for the migration.
Created a set of training documents and conducted online sessions to onboard marketing, product and account managers to GA4.
Created cookbooks and conducted sessions to guide the marketing and product teams to migrate applications to GA4.

Key Achievements

Migrated more than 600+ clients as part of the migration.
Reduced the number of properties used in GA3 by more than 95% by creating a shared property for a large number of clients.
Trained and onboarded around 30 members from Product, Marketing and Account management teams.

Challenges

Comparing metrics between GA4 and GA UA was one of the biggest challenges. The changes in the way users and sessions are counted caused a great deal of confusion in the initial validations. Leveraging the user explorer in GA console and event level data in Google Bigquery helped a lot to understand how metrics are computed in the new GA4 world and explaining almost all the differences.
Another big challenge was faced when traffic source attribution in GA4 did not match the one in GA UA. Exploring the documentation and identifying the new User, Session and event level traffic source attribution helped clear out the confusion. Realizing that Google Bigquery stores only the event level traffic source for GA4 instead of the session level traffic source in GA UA was an eye opener.

Learnings

Effective Collaboration: Working with cross-functional teams, including marketing, product, and engineering, reinforced the importance of clear communication and alignment of goals for successful project execution.
Stakeholder Training: Conducting training sessions for stakeholders underscored the importance of clear and concise communication tailored to the audience's needs.
Technical Expertise: Leading the migration process deepened my understanding of Google Analytics platforms and data architecture, enhancing my technical skills in data integration and analytics.
Problem-Solving Skills: Overcoming challenges such as metrics comparison, traffic source attribution and other similar ones, required innovative problem-solving and critical thinking, honing my ability to find solutions in complex situations.
Continuous Learning: The dynamic nature of technology necessitated continuous learning and adaptation, reinforcing the value of staying updated with the latest industry trends and developments.