"What's the best trading card marketplace" or "where do I buy quality hiking boots under $100" are prompts many people now ask an AI assistant instead of Google. A store that doesn't show up in those answers is losing a slice of product discovery that grows every month.
What's different from classic product SEO
- Product schema with price, availability and reviews in JSON-LD, not just in the visual markup — an LLM reads structured data, not CSS.
- Answer-first category pages: "The 5 best hiking boots under $100" works better as a citable structure than a plain product grid with no context.
- Consistency between catalog and external reviews: if Trustpilot/Google Reviews tell a different story than the one on your site, an engine synthesizing across sources will notice the gap.
An e-commerce-specific risk: client-side SPAs
Many modern e-commerce platforms render price, availability and schema via client-side JavaScript. AI crawlers, like most classic crawlers, often don't execute JavaScript: if schema.org is only injected after hydration, the engine sees it as empty. Check this with a scan.
Where to start
Scan your store for free to see what an AI engine actually sees, not what a browser with JavaScript enabled sees.