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Why You Can’t Always See Exact Session Counts for the Previous Day in GA4
If you’ve logged into GA4 in the morning and noticed that the previous day’s session count doesn’t look quite right, you’re not alone. This is a common GA4 behavior — not necessarily an “issue.” The Main Reason: Data Processing Latency GA4 does not process data in real time for standard reports.Here’s what you should know:
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Comparing Ecommerce Funnel Performance Across Campaigns and Product Categories in GA4 BigQuery
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
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How to Measure and Analyze Cart Abandonment with GA4 and BigQuery
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
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Calculating Conversion Rates at Each Step of the Ecommerce Funnel Using BigQuery SQL
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
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How to Query GA4 Ecommerce Events in BigQuery to Analyze Your Checkout Funnel
Understanding your e-commerce checkout funnel is key to improving conversions and sales. Google Analytics 4 (GA4) exports detailed event-level data to BigQuery. This lets you slice and dice every user interaction in your funnel. These interactions range from product views to purchases. In this post, I’ll walk you through the GA4 e-commerce event schema in
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Marketing Channel Performance in GA4: Tracking New vs. Returning Users
Understanding how different channels contribute to user acquisition vs. user retention is critical for optimizing spend and strategy. In GA4, while you get some visibility into user types, a more detailed analysis often requires BigQuery SQL. This guide walks you through: Why This Analysis Matters Most marketing teams ask: By breaking down New vs. Returning
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How to Track New vs. Returning Users in GA4 Using BigQuery
Understanding the difference between new and returning users is critical for marketers and analysts who care about user acquisition, retention, and behavior trends. While GA4 simplifies many things, it doesn’t directly provide an easy way to segment returning users—especially if you want to go beyond default reports. This deep dive walks you through how GA4
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Types of Users in GA4: Definitions & Key Considerations
Google Analytics 4 (GA4) offers a more flexible and event-based model than Universal Analytics, but it can be confusing when it comes to understanding user types. Here’s a breakdown of the main user types GA4 tracks, what they mean, and what you should consider when analyzing them. 1. Total Users 2. New Users 3. Returning
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