Full Answer

AI agents do not browse a product page the way a human does. They parse structured data — JSON-LD, Open Graph tags, schema.org markup — and extract the fields they need: price, availability, specifications, reviews, shipping. Everything outside those structured fields might as well not exist. A beautifully photographed product with rich marketing copy but incomplete schema markup loses to a plain listing with complete structured data every time an agent runs a comparison.

The 34% that agents cannot read is not random. It concentrates in the details that close sales: variant-level pricing (a size XL costs more, but the schema only lists the base price), shipping thresholds (free over a certain amount, but encoded in page logic rather than markup), return windows, and bundle pricing. These are exactly the fields an agent needs to make a purchase decision on behalf of a human, and their absence forces the agent to either skip the product or present incomplete information.

For WooCommerce stores, the fix is structural. Product schema needs to include every variant, every shipping rule, and every policy — not as rendered HTML, but as machine-readable markup that an agent can parse without rendering the page. Server-side data infrastructure makes this maintainable at scale. The full analysis of how server-side data captures what GA4 misses covers the measurement side of this problem.