30-Second Summary
What you'll learn from this article
- GA4 uses a completely different data model than Universal Analytics — event-based tracking.
- Identify drop-off points in your conversion funnel with customer journey analysis.
- Compare customer segment behaviors with cohort analysis.
- Identify high-value customers in advance with predictive audiences.
- Access raw data and perform advanced analytics with BigQuery integration.
Are you still leaving your marketing decisions to intuition? In the age of data-driven marketing, understanding and measuring customer behavior is no longer a luxury but a matter of survival. Google Analytics 4 has become the cornerstone of this understanding at the heart of digital marketing.
Google Analytics 4 (GA4) is the new standard for data-driven decision making in digital marketing. Unlike Universal Analytics, GA4 uses an event-based data model that tracks user journeys across devices and platforms. With UA's shutdown in 2024, GA4 is now the only option.
In this guide, you'll learn all dimensions of data-driven marketing from GA4 setup to advanced segment analysis, predictive metrics to BigQuery integration. When used correctly, GA4 can increase your marketing ROI by 30-50%.
What Is GA4 and Why Does It Matter?
Google Analytics 4 is Google's next-generation analytics platform. Replacing Universal Analytics, GA4 stands out with its event-based data model, cross-platform tracking, privacy-first approach, and machine learning capabilities.
GA4 vs Universal Analytics: While UA was session-based, GA4 is event-based. Every user interaction is recorded as an 'event' — page views, clicks, scrolls, video views, form submissions. This model offers more flexible and detailed analysis.
Why Is Migrating to GA4 Mandatory? Universal Analytics stopped collecting data on July 1, 2024. GA4 is now the only option. But this isn't just an obligation — it's an opportunity: GA4 offers more powerful features. Predictive analytics, cross-device tracking, advanced attribution models — all in GA4.
Privacy-First Approach: In a world of GDPR, CCPA, and cookie restrictions, GA4 fills data gaps with modeled data and machine learning. With consent mode, cookieless tracking, and first-party data focus, it's ready for the future.
GA4 Core Concepts and Metrics
Core concepts of GA4: Events (every interaction), Parameters (event details), User Properties (user characteristics), Conversions (goal completion). Key metrics: Engaged sessions, Engagement rate, Average engagement time.
Events and Parameters: In GA4, everything is an event. Automatically collected events: page_view, scroll, click, video_start, file_download. Enhanced measurement events: scroll depth, outbound clicks, site search. Custom events: Your own defined interactions. Parameters can be added to each event — like product_name, category, value.
New Engagement Metrics: Instead of bounce rate, there's 'Engaged sessions' and 'Engagement rate'. Engaged session: 10+ seconds, 1+ conversion, or 2+ page views. Engagement rate: Engaged sessions / Total sessions. These metrics better reflect actual user engagement.
Users and Sessions: GA4 has two types of users: Total users (all users) and Active users (default, engaged users). Sessions can now be tracked across devices. If a user starts on phone and continues on desktop, it can count as the same session.
GA4 Setup and Configuration
GA4 setup: Create property in Google Analytics, add data stream, implement tracking code (gtag.js or GTM). Enable enhanced measurement. Define conversions. Connect Google Ads and Search Console.
Basic Setup Steps: 1) Create a new GA4 property in Google Analytics. 2) Add web and/or App data stream. 3) Add tracking code to your site (gtag.js or Google Tag Manager). 4) Enable enhanced measurement (scroll, outbound clicks, video, file downloads). 5) Exclude your own IPs for internal traffic filtering.
Setup with Google Tag Manager: Using GTM is more flexible and powerful. Create GA4 Configuration tag, add Measurement ID. Create separate GA4 Event tags for custom events. Use data layer for dynamic parameter passing. Manage events without any code changes.
Defining Conversions: Mark important events as conversions: Purchase, form submission, registration, specific page visits. Go to Admin > Events > Conversions and 'Mark as conversion'. Maximum 30 conversions can be defined per property. For e-commerce, purchase event is automatic conversion.
Customer Behavior Analysis
Customer behavior analysis in GA4: Path exploration for user journeys, Funnel exploration for conversion funnels, Segment overlap for audience comparison, Cohort analysis for customer group analysis.
User Journey Analysis: Use Reports > Engagement > Pages and screens to see most visited pages. Use Explorations > Path exploration to analyze paths users take on your site. Where do they enter? Where do they drop off? Which path leads to conversion?
Funnel Exploration: Analyze your conversion funnel step by step. Explorations > Funnel exploration. Example: Homepage → Product page → Cart → Checkout → Purchase. How many users do you lose at each step? Which step has the biggest drop? Compare funnels by segment (mobile vs desktop, new vs returning).
Segment Analysis: Create user segments with the Audiences feature. Example segments: Purchased in last 7 days, cart abandoners, interested in specific category, high-value customers. Export these segments to Google Ads for remarketing. Use segment overlap to see which attributes overlap.
GA4 Advanced Features
GA4 advanced features: Predictive metrics (purchase probability, churn probability), BigQuery export (raw data access), Attribution modeling (data-driven attribution), Consent mode and modeled data.
Predictive Metrics: One of GA4's most powerful features. Purchase probability: User's likelihood of purchasing in the next 7 days. Churn probability: User's likelihood of not returning in the next 7 days. Revenue prediction: Expected revenue forecast. Create a 'high purchase probability' segment using these metrics and target them.
BigQuery Integration: GA4 offers free BigQuery export for raw data. Daily or streaming export options. Run advanced analyses with SQL. Create your own attribution models. Combine with other data sources (CRM, sales data). Apply machine learning models.
Data-Driven Attribution: GA4 uses data-driven attribution by default. The algorithm evaluates all touchpoints contributing to conversion. Legacy models like last-click, first-click, linear are also available. Compare different models with Model comparison report. Which channel/campaign actually contributes to conversion?
From Data to Action
Collecting data isn't enough, you need to take action. Use GA4 data for Google Ads optimization, site UX improvement, content strategy, and customer segmentation. Create regular reports and dashboards.
Google Ads Optimization: Import GA4 conversions to Google Ads. Use value-based conversions for smart bidding. Send GA4 audiences to Google Ads for remarketing. Optimize budget distribution with attribution reports. Calculate ROAS based on real attribution data.
Site and UX Improvement: Identify and improve high exit rate pages. Find bottlenecks with funnel analysis. Track page speed and Core Web Vitals data. Define baseline metrics for A/B tests. Compare mobile vs desktop performance.
Reporting and Dashboards: Create custom dashboards with Looker Studio (formerly Data Studio). Set up automated email reports (weekly/monthly). Define and track KPIs: Conversion rate, ROAS, CAC, LTV. Catch abnormal changes with anomaly detection. Present understandable reports to stakeholders — insights, not raw data.