// product data

All signals tagged with this topic

Oct 8

Why AI Agents Need Behavioral Product Data, Not Just Specs

As AI agents autonomously shop on behalf of customers, they expose a gap: traditional product databases (SKU, specs, dimensions) can't answer the contextual questions agents need to make good recommendations—why someone buys, when they use it, what problems it solves. Merchants who retrofit their data systems to include behavioral and situational attributes will capture agent-driven commerce. Those clinging to legacy catalogs risk invisibility in automated purchasing flows that increasingly mediate consumer choice.

theme-commerce Ecommerce AI adoption product data

Aug 11

AI Can't Find What It's Looking For on Most Product Pages

Source: Beet

Mirakl's research reveals a gap in e-commerce infrastructure: most product pages lack the structured data and metadata that LLMs need to process information reliably. This creates friction for retailers betting on AI-driven shopping agents—whether through their own platforms or third-party marketplaces—since agents that can't read product pages accurately can't complete transactions. The constraint is not AI capability but data standardization: retailers who invest in LLM-ready product pages now will capture early wins in agent commerce, while others risk invisibility to the next wave of shopping behavior.