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What is Google Analytics (GA4)?
Sean Dorje
Published
October 2, 2025
3 min read
What is Google Analytics (GA4)?
Google Analytics 4 (GA4) represents Google's next-generation analytics platform, fundamentally reshaping how businesses collect, analyze, and activate customer data across digital properties. Following the sunset of Universal Analytics with standard properties ceasing data processing on July 1, 2023, GA4 has become the default analytics solution for millions of organizations worldwide.
Why Google Analytics 4 Replaced Universal Analytics
The transition from Universal Analytics to GA4 marks more than a simple platform upgrade -- it represents a complete reimagining of web analytics for the privacy-first, AI-driven era. Google Analytics 4 replaced Universal Analytics as the next-generation measurement solution, with standard properties stopping processing on July 1, 2023, while 360 properties received extensions until July 1, 2024.
This shift addresses fundamental limitations in Universal Analytics' session-based architecture. Where UA tracked pageviews and sessions as primary units, GA4 adopts an event-driven model that captures every user interaction as a discrete event. This architectural change enables more granular tracking of user behavior across devices and platforms, providing marketers with unprecedented insight into the complete customer journey.
The timing of this transition aligns with broader industry changes. Privacy regulations like GDPR and CCPA have reshaped data collection practices, while the rise of cross-device usage demands unified measurement approaches. GA4's event-based architecture and built-in privacy controls position it as Google's answer to these evolving requirements, offering organizations a platform designed for long-term compliance and comprehensive measurement.
GA4 vs. Universal Analytics: Data Model, Metrics & Attribution
The differences between GA4 and Universal Analytics extend far beyond interface changes. GA4's event-driven model captures discrete interactions as individual events, abandoning UA's Category, Action, and Label structure entirely. Every interaction -- whether a pageview, scroll, or video play -- becomes an event with customizable parameters, providing flexibility that UA's rigid hit types never offered.
User metrics have been completely reimagined. GA4 introduces Active Users as the primary metric, moving beyond UA's Total Users focus. The platform replaces UA's Bounce Rate with Engagement Rate, a more nuanced metric considering time on site, conversion events, and pages viewed. This shift reflects modern user behavior where single-page applications and dynamic content make traditional bounce metrics increasingly meaningless.
Attribution modeling has evolved from UA's last-non-direct-click default to data-driven attribution as GA4's standard. This machine learning-powered approach distributes credit across multiple touchpoints based on their actual contribution to conversions, providing more accurate insights into marketing effectiveness. The simplified account structure -- eliminating Views in favor of Data Streams -- reduces complexity while maintaining flexibility through features like data filters and user permissions.
AI-Powered Features & New Reporting Capabilities in GA4
GA4's integration of artificial intelligence transforms raw data into actionable insights through multiple advanced features. Generated Insights appear directly within reports, providing plain-language explanations of data fluctuations before analysts even notice changes. These AI-powered summaries help teams quickly understand performance shifts without manual investigation.
The platform now supports seamless cost data import from Pinterest, Snap, and Reddit through direct integrations. Organizations linking Google Ads accounts see average improvements of 23% in conversions and 10% reduction in cost per conversion. Cross-channel cost import capabilities enable comprehensive ROAS analysis across all marketing investments, not just Google properties.
Annotations have returned to GA4 reports, allowing teams to mark key events and campaigns directly within the interface. Combined with the ability to copy reports between properties and enhanced measurement tracking that automatically captures scroll depth, outbound clicks, and video engagement, these features create a more collaborative and comprehensive analytics environment. The platform's AI features include predictive metrics, behavioral modeling, and automated anomaly detection, transforming GA4 from a reporting tool into a strategic intelligence platform.
Privacy, Consent Mode V2 & the 2025 Cookie Shake-Up
Privacy compliance has become central to GA4's architecture, with Consent Mode V2 representing Google's response to evolving regulations. Released in November 2023, Consent Mode V2 aligns with the Digital Markets Act and introduces parameters like ad_user_data and ad_personalization for granular consent management.
The platform operates in two distinct modes: Basic Mode only collects data from explicitly consenting users, while Advanced Mode gathers anonymized data from all visitors, adjusting based on consent status. This dual approach helps organizations maintain measurement capabilities while respecting user privacy choices. The Cypriot DPA fined companies €48,000 for GDPR breaches, highlighting the importance of proper implementation.
May 2025 brought an unexpected challenge when Google silently updated the GA4 cookie format from a simple dot-separated string to the complex GS2 format. "In early May 2025, Google quietly changed the format of a key Google Analytics 4 (GA4) cookie without prior notice," causing widespread tracking disruptions. This unannounced change broke tracking implementations across thousands of organizations, causing data collection failures and attribution issues. The Headway lawsuit proceeding for sharing personal data through Google Analytics underscores the legal risks of misconfigured privacy settings, with the California Attorney General securing a $1.55 million settlement from Healthline Media for CCPA violations.
Migrating to GA4: Step-by-Step Framework for 2025
Successful GA4 migration requires systematic planning and execution. Organizations should begin by creating new properties through the Setup Assistant, which guides configuration of essential features including Google Signals for cross-device tracking and enhanced measurement for automatic event collection.
The migration process involves several critical steps. First, establish your property and data stream structure -- deciding whether to combine web and app data or maintain separate properties. Enable Google Signals for remarketing capabilities and cross-device reporting. Configure key events (formerly conversions) to align with business objectives, ensuring proper tracking of critical user actions.
Data quality remains paramount for successful migration. Companies focusing on data cleanliness report significant improvements, with one client achieving 28% increase in paid media ROAS and 5.3x increase in paid social revenue through improved data hygiene. Essential preparation includes verifying conversion tracking, reviewing default channel groupings, confirming platform connections (Google Ads, Search Console), and establishing proper data filters to exclude internal traffic and bot activity.
Common Pitfalls: Silent Cookie Updates, Data Gaps & Lawsuits
The May 2025 cookie format change exemplifies the risks organizations face with third-party analytics dependencies. Google's unannounced update immediately impacted marketing, engineering, and data functions -- breaking custom tracking code, causing attribution anomalies, and disrupting backend integrations that parsed GA4 cookies directly.
Privacy violations represent another critical risk area. The CCPA lawsuit against Headway proceeded because the company failed to anonymize IP addresses in Google Analytics, exposing sensitive medical information. This case expanded CCPA enforcement beyond advertising to include website analytics, signaling broader liability for data collection practices.
Configuration errors compound these risks. Organizations frequently misconfigure consent mode, leading to data loss when users grant delayed consent. Session misattribution occurs when UTM parameters are lost due to improper consent mode setup. Without proper monitoring, these issues can persist undetected for months, corrupting historical data and undermining strategic decisions. Zero-click searches reaching 60% further complicate attribution, as traditional tracking methods fail to capture the full customer journey.
Advanced Use Cases: BigQuery ML, AutoML & LLM Segmentation
GA4's BigQuery integration unlocks advanced machine learning capabilities that extend far beyond standard reporting. Organizations can perform customer segmentation using K-Means clustering directly within BigQuery ML, then leverage Large Language Models for natural language cluster explanations -- eliminating the technical barriers that previously limited advanced analytics to data science teams.
Predictive analytics adoption has accelerated, with 61% of B2B marketers already using predictive analytics and another 26% planning adoption within the year. AutoML integration with GA4 enables custom machine learning models that identify high-value users, with documented cases showing 25% conversion increases alongside 30% ad spend reductions.
The platform's account structure supports enterprise-scale deployments through subproperties and roll-up properties in GA4 360. These features enable granular data governance while maintaining holistic views across business units. Integration with Vertex AI allows creation of remote models that seamlessly connect GA4 data with advanced ML capabilities, while 75% of new analytics content will be contextualized through generative AI by 2027.
Key Takeaways: Building a Future-Proof Analytics Stack
GA4 represents more than a platform migration -- it's a strategic imperative for maintaining measurement capabilities in an evolving digital landscape. The event-based architecture, AI-powered insights, and privacy-first design position organizations for long-term success, but realizing this potential requires careful implementation and ongoing optimization.
Successful GA4 deployment demands attention to both technical configuration and strategic alignment. Organizations must audit tracking implementations regularly, implement server-side tagging to buffer against client-side changes, and maintain robust first-party data strategies that reduce vendor dependencies. The rapid pace of change -- from silent cookie updates to evolving privacy regulations -- requires adaptive approaches and continuous monitoring.
Looking forward, the convergence of analytics and artificial intelligence will accelerate. AI-powered features transform how organizations understand and act on data, but the gap between insight and action remains a critical challenge. While GA4 provides the foundation for data collection and analysis, organizations need partners who can operationalize these insights effectively.
Ready to transform GA4 insights into measurable growth? Relixir's GEO platform automates the journey from analytics to action, ensuring your brand dominates AI search while competitors struggle with implementation. Request a demo today to see how Relixir closes the insight-to-action gap.
Frequently Asked Questions
What is GA4 and why did it replace Universal Analytics?
Google Analytics 4 (GA4) represents Google's next-generation analytics platform, fundamentally reshaping how businesses collect, analyze, and activate customer data across digital properties. Google Analytics 4 replaced Universal Analytics as the next-generation measurement solution, with standard properties stopping processing on July 1, 2023, while 360 properties received extensions until July 1, 2024.
How does GA4's data model differ from Universal Analytics?
Where UA tracked pageviews and sessions as primary units, GA4 adopts an event-driven model that captures every user interaction as a discrete event. Every interaction -- whether a pageview, scroll, or video play -- becomes an event with customizable parameters, providing flexibility that UA's rigid hit types never offered.
Which AI-powered features are available in GA4?
Generated Insights appear directly within reports, providing plain-language explanations of data fluctuations before analysts even notice changes. The platform's AI features include predictive metrics, behavioral modeling, and automated anomaly detection, transforming GA4 from a reporting tool into a strategic intelligence platform.
What is Consent Mode V2 and how does it work?
The platform operates in two distinct modes: Basic Mode only collects data from explicitly consenting users, while Advanced Mode gathers anonymized data from all visitors, adjusting based on consent status. This dual approach helps organizations maintain measurement capabilities while respecting user privacy choices.
What risks did the May 2025 GA4 cookie update introduce?
May 2025 brought an unexpected challenge when Google silently updated the GA4 cookie format from a simple dot-separated string to the complex GS2 format. This unannounced change broke tracking implementations across thousands of organizations, causing data collection failures and attribution issues.
How can Relixir help turn GA4 insights into measurable growth?
Relixir's GEO platform automates the journey from analytics to action, ensuring your brand dominates AI search while competitors struggle with implementation. Request a demo today to see how Relixir closes the insight-to-action gap.
Sources
https://nonprofitmegaphone.com/google-analytics-4-vs-universal-analytics/
https://infotrust.com/articles/how-to-use-ai-features-in-google-analytics/
https://iapp.org/news/a/cyprus-dpa-issues-fine-for-improper-cookie-use-on-adult-websites/
https://privado.ai/post/why-headway-was-sued-for-sharing-personal-data-with-google-analytics
https://chartis.io/our-thinking/prepare-for-2025-google-analytics
https://www.cardinalpath.com/blog/ai-driven-marketing-how-automl-powers-smarter-conversions-insights
