Full Answer

Gartner (2023) found 80% of AI projects fail, with 70% of failures caused by data quality issues. For WooCommerce stores, data readiness has three layers: completeness (are all purchase events captured, including those from Safari and iOS users?), cleanliness (events are deduplicated, correctly attributed, and structured consistently), and history (12–24 months of data to establish seasonal and behavioral patterns). Server-side tracking addresses completeness by recovering the 30–40% of events that ad blockers and ITP restrictions hide from browser pixels. BigQuery is the long-term storage layer where clean events accumulate into an AI-ready dataset — one that's queryable, joinable with ad spend data, and usable by tools like Google's Vertex AI. Stores that begin this infrastructure now will have actionable training data when AI personalization becomes accessible to SMBs, rather than scrambling to catch up.