On-Page Structure Types AI Search Engines Rely On
Structured data is the layer between your content and AI comprehension. Without it, AI engines are making educated guesses about what your content means. With it, you give them explicit, machine-readable facts they can cite with confidence.
Structured data is the layer between content and AI comprehension - without it, AI engines make educated guesses about what your content means, while with it, you provide explicit machine-readable facts across entity identification, content type, product, and navigation schemas.
Why AI engines depend on structured data
Natural language is ambiguous. A sentence like "We have been helping businesses grow since 2010" tells a human something meaningful - but an AI engine has to infer the entity (which company?), the activity (what kind of help?) and the date. Structured data resolves this ambiguity explicitly.
When you add Organisation schema that states your company name, founding date and industry, you give the AI engine verified facts rather than inferences. When you add Article schema that states the author and publication date, you give it attribution data rather than guesswork. Structured data converts implicit human-readable content into explicit machine-readable facts.
The full schema type reference for GEO
Entity identification schemas
- Organization - business identity, brand verification, sameAs profiles
- Person - author identity, credentials, professional profiles
- LocalBusiness - physical location, opening hours, NAP data
- Brand - standalone brand entity when separate from Organisation
Content type schemas
- Article - authored content with publication dates and attribution
- NewsArticle - journalistic content, particularly useful for publishers
- BlogPosting - blog content (subtype of Article)
- HowTo - step-by-step instructional content, highly citable by AI
- FAQPage - Q&A pairs directly quoted in AI answers
- QAPage - single question with multiple answers
Product and service schemas
- Product - commercial product with pricing, availability, reviews
- SoftwareApplication - SaaS and software products specifically
- Service - service offerings with description and provider
- Offer - pricing and availability data
- AggregateRating - composite review scores from multiple sources
- Review - individual review content
Navigation and structure schemas
- BreadcrumbList - hierarchical site structure
- WebSite - site-level information with SearchAction for sitelinks
- WebPage - general page type when no specific type applies
- SiteLinksSearchBox - enables search box in Google results
Implementation priority by site type
| Site type | Must-have schemas |
|---|---|
| Blog / content site | Organization, Article, FAQPage, Person (author), BreadcrumbList |
| Ecommerce | Organization, Product, AggregateRating, Review, BreadcrumbList |
| SaaS / software | Organization, SoftwareApplication, FAQPage, HowTo, AggregateRating |
| Local business | LocalBusiness, Organization, FAQPage, Review |
| Agency / service provider | Organization, Service, Person, FAQPage, Article |
Implementation tip: Use JSON-LD format (a script block in the page head) rather than microdata or RDFa. JSON-LD is easier to maintain, does not interfere with your HTML structure, and is the format recommended by Google and most AI engine documentation.
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Sources & Further Reading
Frequently Asked Questions
What is structured data?
Structured data is information formatted in a standardised way that machines can reliably read and interpret. On websites, it typically refers to Schema.org markup implemented as JSON-LD - code added to web pages that labels content types, entities and relationships in a machine-readable format.
What is the difference between schema markup and structured data?
Structured data is the broad concept of machine-readable, standardised information. Schema markup is the specific vocabulary (from Schema.org) used to label content types on websites. In practice, the terms are often used interchangeably.
Do I need structured data if I already have good content?
Yes. Even excellent content benefits significantly from structured data because it removes ambiguity. An AI engine reading your content has to infer what it means. Structured data tells it explicitly. Pages with matching structured data are significantly more likely to be correctly cited.
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