Full Answer

BigQuery ML can identify which visitors are likely to buy, which customers are at churn risk, and which products drive repeat purchases—using SQL you write directly in BigQuery. No separate ML platform required.

The critical dependency: these models need behavioral events, not just transaction records. ETL tools that sync WooCommerce orders provide purchase history but miss the 97-99% of sessions that never result in a sale. Without page views, add-to-cart events, and checkout steps, the model trains on buyer patterns alone—missing the behavioral signals that actually precede conversion.

Server-side event streaming routes the complete behavioral funnel to BigQuery in real-time: every page view, cart action, and checkout step. With this data, BigQuery ML can identify pre-purchase patterns and act on them.