analytics

  • - BigQuery Scheduled Queries for GA4 Automated Reporting

    Raw GA4 event data sitting in BigQuery is only useful once it becomes clean, automated reporting tables. This guide covers how to set up BigQuery scheduled queries for GA4 — from timing and pricing to MERGE patterns and when to move to Dataform.

  • - GA4 Data Quality Monitoring with BigQuery SQL

    GA4 exports to BigQuery silently, and silently it can break. This guide gives you the SQL, architecture, and mental model to catch data quality issues before they corrupt your reports.

  • - GA4 Data Retention Workarounds with BigQuery

    GA4 deletes raw event data after 14 months maximum — but if you have BigQuery export enabled, that limit simply does not apply to you. Here is everything you need to know to keep your data, query it efficiently, and recover what you can if you started late.

  • - dbt for GA4 BigQuery: Transform Raw Exports into Clean Tables

    If your data stack spans multiple warehouses or your team already knows dbt, it is the right tool for transforming GA4's messy BigQuery export. This guide covers the Velir/dbt-ga4 package, building custom models from scratch, incremental loading, testing, and how dbt compares to Dataform for this specific use case.

  • - Dataform for GA4: Build Your First BigQuery Transformation Pipeline

    GA4's BigQuery export gives you raw, deeply nested event data. Every query requires UNNEST subqueries, every dashboard scans the full table, and every analyst writes the same boilerplate SQL. Dataform fixes this: transform once into clean, flat, partitioned tables, then query cheaply downstream. This guide walks through the complete pipeline, from flattening events to sessionization, incremental loading, and data quality testing.

  • - GA4 BigQuery Export Cost Optimization: A Practical Guide

    GA4's BigQuery export is free, until it isn't. Storage, query processing, and streaming ingestion costs add up silently. This guide breaks down exactly where the money goes, what realistic numbers look like for different traffic levels, and the concrete SQL optimizations that can cut your bill by 80%.

  • - How GA4 Counts Millions of Users with 12 Kilobytes: The HyperLogLog Algorithm

    GA4 reports 2.4 million unique users, but how does it count them without storing 2.4 million IDs? The answer is HyperLogLog, a probabilistic algorithm that trades perfect accuracy for radical efficiency. This is the story of how a clever mathematical trick powers modern analytics.

  • - AI-Powered Audience Segmentation: K-Means Clustering with GA4 and BigQuery

    Manual audience segments are arbitrary. "High-value customers" based on revenue thresholds miss behavioral nuance. K-means clustering discovers natural user groups from your data. This guide shows how to build behavioral clusters in BigQuery ML and export them to Google Ads for targeted campaigns.

  • - Automated Anomaly Detection for GA4 with BigQuery

    Traffic dropped 40% and no one noticed for three days. A tracking script broke and conversions vanished. Bot traffic inflated your metrics by 200%. These problems are preventable. This guide shows how to build automated anomaly detection using BigQuery ML and Cloud Functions to catch issues before they become disasters.

  • - Predicting Customer Value with BigQuery ML and GA4 Data

    Your GA4 data contains patterns that predict which users will convert, churn, or become high-value customers. BigQuery ML lets you build machine learning models using SQL, no Python required. This guide walks through building a purchase propensity model and using predictions for Google Ads audiences.

  • - Cross-Domain Tracking in GA4: Setup Without Data Loss

    When users move between your domains, GA4 treats them as new visitors by default—inflating user counts and breaking attribution. This guide covers proper cross-domain configuration in GA4 and GTM, troubleshooting self-referrals, handling payment gateways, and testing to ensure session continuity.

  • - GA4 Custom Dimensions & Metrics: When and How to Use Them

    GA4 default parameters cover most cases, but custom dimensions unlock business-specific insights. This practical guide explains when you actually need them, the three scope types (event, user, item), implementation via GTM, quota management, and real examples for ecommerce and lead generation sites.

  • - GA4 Debug Mode: Complete Troubleshooting Guide

    DebugView is essential for validating your GA4 implementation, but it often refuses to show data when you need it most. This practical guide covers all methods to enable debug mode, diagnose why events are not appearing, and fix the 18+ common issues that break DebugView.

  • - Fixing Direct Traffic Inflation in GA4 for Single Page Applications

    If your SPA built with Nuxt.js, Next.js, or React shows unusually high Direct traffic in GA4, the problem is likely that document.referrer doesn't update on client-side navigation. Learn how to fix this using GTM's History Change trigger and a custom page_referrer variable.