Introduction If you’ve started analyzing GA4 data in BigQuery, you’ve likely come across the field: It looks simple at first. However, in the context of Consent Mode, user stitching, and multi-touch attribution, its meaning and behavior deserve a deeper look. In this post, I’ll break down: Let’s get into it. What Is traffic_source.medium? In GA4 … Read more
Introduction Analyzing GA4 data in BigQuery can be incredibly powerful — but it’s easy to end up with slow, expensive queries as your logic grows. After writing complex GA4 SQL for things like session stitching and consent-aware attribution, I’ve learned some valuable techniques to keep things efficient, readable, and scalable. In this post, I’m sharing … Read more
Marketers often ask the big question: “Which channel really drives conversions?”With GA4 and BigQuery, you can move beyond guesswork and analyze attribution models directly in your data warehouse. In this post, we’ll show how to implement last-click attribution using SQL and compare it with GA4’s data-driven attribution (DDA) tables. This helps you evaluate channels side … Read more
Google Analytics 4 (GA4) has been evolving rapidly, but one hot topic in 2025 is data sampling. Many marketers and analysts are noticing that GA4 reports now apply sampling more aggressively than before, which can lead to inaccurate insights. This change is pushing professionals to rely more heavily on BigQuery for precise, unsampled data. In … Read more
Marketing teams constantly ask: “Which channel truly drives conversions?” GA4 provides user-level metrics and event data, but discrepancies between the GA4 interface and BigQuery exports can make attribution tricky. For example, Active Users or New Users may not match when you try to analyze traffic by campaign, source, or medium in BigQuery. This guide shows … Read more
If you’ve ever compared GA4 user metrics in the interface with BigQuery exports, you might have noticed discrepancies. For example, Active Users, New Users, or Total Users in the GA4 UI often don’t match what you calculate from the raw BigQuery data. Understanding why this happens is crucial for accurate reporting, marketing attribution, and data-driven … Read more
In this guide, we’ll walk you through SQL queries to calculate Active, New, and Returning Users, explore cross-device behavior, and share best practices for deduplication and segmentation. By the end, you’ll have a complete toolkit to analyze GA4 users in BigQuery with precision—perfect for building reports, dashboards, or feeding insights into your CRM or marketing … Read more
Yesterday’s post: How to Measure and Analyze Cart Abandonment with GA4 and BigQueryToday, we’ll go beyond a single funnel view and break down performance by campaign and by product category — so you can quickly see what’s driving the best conversion rates. Why This Matters Not all campaigns or product lines pull their weight.If you’re … Read more
Cart abandonment kills revenue. But with GA4 and BigQuery, you can do more than just spot it—you can uncover when users come back naturally, and when to target them effectively to win them back. Yesterday, we tackled Calculating Conversion Rates at Each Step of the Ecommerce Funnel Using BigQuery SQL.Today, let’s focus on cart abandoners—identifying … Read more
Yesterday, we explored how to query GA4 ecommerce events in BigQuery to analyze your checkout funnel.That post laid the foundation by showing how to pull funnel stage counts from GA4’s raw event data. Today, we’re going deeper.We’ll calculate conversion rates at each step of the ecommerce funnel, handle deduplication at both the user and session … Read more