Data Modeling for Attribution with Google Analytics 4 data скачать в хорошем качестве

Data Modeling for Attribution with Google Analytics 4 data

GA4 Data Modeling for Marketing Attribution in BigQuery I show why GA4-to-BigQuery users should move beyond ad hoc queries to purpose-built data modeling driven by a clear use case, using marketing attribution as the main example. I argue attribution is primarily a strategy problem, not solvable by a single “best” model or measurement tweak, and outline the core attribution ingredients: identity, touchpoints, and conversions. The session details anonymous (GA4 pseudo_id) vs identified users (user_id/email), how to raise identification rates, and how to stitch identities via journey mapping and a mapping table. It then covers touchpoint design (often session_start) and presents an activity-schema-based BigQuery architecture with lean staging tables, accounts/anon tables, identity resolution, touchpoints, attributed touchpoints, and an analytics layer combined with ad cost data. 00:00 Why Data Modeling Matters 01:25 From Ad Hoc Queries to Models 04:26 Pick a Use Case First 06:03 Attribution Layers Explained 07:24 Attribution Is Strategy 10:35 Attribution Data Ingredients 15:18 Identity Basics in GA4 15:58 Anonymous vs Known Users 19:57 User ID and Email Strategy 23:51 How You Identify Users Today 24:30 Identity Resolution Basics 26:41 Journey Mapping Workshop 28:03 Hashing and Passing IDs 29:53 Mapping Table Modeling 32:56 Filtering Touchpoints 34:52 Activity Schema Modeling 36:51 Boost Identification Rate 38:24 Touchpoint Design Choices 44:46 Attribution Architecture Blueprint 48:15 Wrap Up and Next Steps