Does schema markup actually help your LLM visibility?


You’ve probably noticed that schema is suddenly showing up in every AI-SEO conversation. And if you’re like most technical SEOs, you’re wondering the same thing:

Is schema still as important now that LLMs pull answers differently than Google?
Or are we overestimating its impact on AI search visibility?

These questions were raised in one of our sessions of the SEO for LLMs course.

Let’s break this down.

The short version:
Schema still matters — but not for the reason most people think.

The longer version:

Right now, LLMs don’t parse schema the way Google does. They look at the raw HTML and primarily process what’s visible on the page.

In Crystal’s tests, she mentioned in the session, LLMs consistently picked up the on-page text but ignored schema-only information, even when crawling the correct URL.

So if schema doesn’t directly influence LLM parsing, why use it?

Because the real strategy is indirect:

Prioritize the schema that earns you rich results in Google.

Why?

Because LLMs pull heavily from search results (Google, Bing, etc.).
If your page shows up as a rich result, you increase the chances that:

  1. Your content appears in the LLM’s source set
  2. Your structured information influences how LLMs describe your entity, product, or content

That’s where schema plays its role — not through direct parsing, but through visibility amplification.

So what should you focus on?

  • Use schema types that grant rich results (reviews, recipes, products, etc.)
  • Skip the deep-dive 1,000-types-of-schema rabbit hole unless you have unlimited time
  • Keep everything in raw HTML, not just buried in JSON-LD
  • Make sure anything declared in your schema is also visible on the page

This is where your time pays off.

Let’s break this down clearly.

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