This section explains how to overcome GA4’s reporting limits by using BigQuery SQL to accurately identify new and returning users, enabling better retention analysis and custom insights.
Session counts in GA4 often don’t match what you see in BigQuery exports. This is because GA4 constructs sessions using rules like inactivity timeouts, traffic source changes, and midnight splits. For analysts and marketers, this can lead to confusion in attribution, engagement tracking, and conversion reporting. In this post, we’ll break down session stitching, provide … 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
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
When Consent Mode is enabled in Google Analytics 4 (GA4), the way sessions are initiated, maintained, and reported changes significantly. This ensures compliance with privacy laws (like GDPR or CCPA), but also impacts how you interpret session data in BigQuery or the GA4 UI. Check Out Amazon Deals Discover top offers on books, gadgets & … Read more
Calculating the number of sessions in BigQuery GA4 provides immense flexibility and granularity. However, it can often lead to discrepancies when compared to the GA4 user interface (UI). Understanding these differences and how to mitigate them is key to accurate analysis. How to Calculate Sessions in BigQuery GA4 The most accurate and robust method to … Read more