Not All Data Is Created Equal
LLMs are trained on web content, but they don’t treat all content equally. Structured, machine-readable data is weighted more heavily than prose. Corroborated facts outrank uncorroborated ones. Clear entity definitions beat ambiguous descriptions.
Here are the five data structures that move the needle most when it comes to LLM discoverability.
1. Organization Schema (JSON-LD)
The Organization schema is the foundation. It tells every LLM the definitive facts about your business — your name, URL, description, contact points, social profiles, and founding details.
{
"@context": "https://schema.org",
"@type": "Organization",
"name": "Your Company",
"url": "https://example.com",
"description": "A precise, entity-rich description of what you do.",
"foundingDate": "2020",
"sameAs": [
"https://linkedin.com/company/yourcompany",
"https://twitter.com/yourcompany"
]
}
The sameAs property is particularly powerful — it links your entity to its representations across the web, helping LLMs consolidate all information about you into a single, coherent entity.
2. Product & Service Schemas
LLMs recommend products and services. If yours aren’t schema-marked, they’re flying blind when trying to describe what you offer.
Use Product or Service schemas for every offering, with detailed descriptions, pricing hints, and key features. Include offers, aggregateRating, and review sub-schemas where authentic data exists.
3. FAQ Schema
FAQ schema is one of the highest-leverage GEO investments. It lets you inject exact question-and-answer pairs directly into the machine-readable layer of your pages.
When an LLM is asked exactly the questions you’ve marked up, it has a clean, authoritative source to draw from — dramatically increasing the likelihood of accurate citation.
Structure your FAQs around real user questions you want to own in AI search.
4. HowTo & Article Schemas
For process-oriented content, HowTo schema gives LLMs a step-by-step structure they can parse and re-synthesize. For thought leadership, Article schema with author, datePublished, and about properties establishes authority and recency.
LLMs have a strong prior toward recent, attributed, structured content. These schemas check all three boxes.
5. Knowledge Graph Samelinks
Perhaps the most underrated: linking your entities to their Wikidata equivalents via sameAs. If your technology, industry, or product category has a Wikidata entry, linking to it anchors your brand in an LLM’s canonical knowledge base.
"sameAs": [
"https://www.wikidata.org/wiki/Q12345",
"https://en.wikipedia.org/wiki/Your_Industry"
]
This is how you become part of the LLM’s world — not a stranger it has to guess about.
Putting It Together
None of these work in isolation. GEO is a system: each schema reinforces the others, the cross-references build coherence, and the whole becomes greater than the sum of its parts.
The brands that implement all five — consistently, correctly, and across their entire digital footprint — are the ones LLMs cite by default.
Start with your Organization schema today. Then build outward.