AEO Guide: Schema
Schema Markup for AI Retrievability
Schema markup allows you to provide structured data to search and AI crawlers so they can better “read” your content.
In This Article
Additional Resources
Pages that seem clear to humans can still be ambiguous to search engines. Schema markup reduces that ambiguity by clarifying what your content represents, such as page type, primary subject, or key facts. It adds structured data that labels entities, relationships, and intent in a format machines already recognize. Those signals help AI systems scan, classify, and retrieve your content with confidence.
These five schema types make the biggest difference in whether AI systems understand and cite your content.
Organization Schema
Organization schema establishes your brand as a recognized entity. An entity is how AI systems recognize and understand distinct people, places, organizations, or things across the web. This markup ties your content directly to your company and reinforces entity relationships.
Why It Matters for AI Retrievability
Organization schema establishes your brand as a recognized entity. Entities are how search engines and AI systems identify and distinguish people, places, organizations, and things across the web. This markup ties your content directly to your company, helping systems connect signals consistently and evaluate your brand as a credible source.
Where To Use Organization Schema
- Homepage
- About page
- Contact page
- Any page representing your company
Required Properties
- name: Your company name
- url: Your website URL
Recommended Properties
- logo: Company logo image
- contactPoint: Contact information
- sameAs: Links to official social profiles and verified listings
- description: Brief company description
Implementation Example
{
"@context": "https://schema.org",
"@type": "Organization",
"name": "Example",
"url": "https://example.com",
"logo": {
"@type": "ImageObject",
"url": "https://example.com/logo.png",
"width": 600,
"height": 60
},
"description": "Example is an B2B SaaS company that helps businesses improve data reporting and accuracty.",
"contactPoint": {
"@type": "ContactPoint",
"telephone": "+1-555-123-4567",
"contactType": "customer service",
"email": "sales@example.com"
},
"sameAs": [
"https://www.linkedin.com/company/example",
"https://twitter.com/example",
"https://www.facebook.com/example"
]
}
Common Implementation Mistakes
- Inconsistent company name formatting across pages and schema.
- Missing or broken logo URLs.
- Incomplete or outdated sameAs links.
- Using different organization names in article schema vs. organization schema.
Author Schema
Author schema links content to the people who wrote it and their credentials. This helps AI systems confirm the content came from real, qualified people.
Why It Matters for AI Retrievability
AI systems increasingly evaluate author credibility when determining which content to cite.
Where To Use Author Schema
- Author bio pages (standalone entity pages for each author)
- Team member profile pages
- Within article schema for blog posts and articles
Required Properties
- name: Author’s full name
- url: Link to author bio or profile page
Recommended Properties
- sameAs: Links to professional profiles (LinkedIn, professional websites)
- description: Author credentials and expertise
- jobTitle: Author’s role or title
- worksFor: Organization the author works for
Implementation Example for Author Bio Page
{
"@context": "https://schema.org",
"@type": "Person",
"name": "Jane Doe",
"url": "https://example.com/about/jane-doe",
"description": "Senior SEO Strategist specializing in enterprise technical SEO and AI-powered search optimization",
"jobTitle": "Senior SEO Strategist",
"worksFor": {
"@type": "Organization",
"name": "Example"
},
"sameAs": [
"https://www.linkedin.com/in/janedoe",
"https://twitter.com/janedoe"
]
}
Implementation Example Within Article Schema
"author": {
"@type": "Person",
"name": "Jane Doe",
"url": "https://example.com/about/jane-doe",
"sameAs": ["https://www.linkedin.com/in/janedoe"]
}
Common Implementation Mistakes
- Inconsistent author name formatting across articles (Jane Doe vs. J. Doe vs. Jane D.).
- Missing author bio pages or profile URLs.
- Generic author descriptions without expertise indicators.
- Broken or missing external profile links.
FAQ Schema
FAQ schema structures question-answer pairs in a format AI systems can easily extract and cite.
Why It Matters for AI Retrievability
AI search features and voice assistants often rely on structured question and answer data. FAQ schema makes your content easier to retrieve and reuse, increasing the likelihood your answers appear in AI-generated responses.
Where To Use FAQ Schema
- Dedicated FAQ pages
- Product or service help documentation
- Blog content organized as questions and answers
- Support center articles
Required Properties
- Question: The question being asked
- acceptedAnswer: The answer to that question
Implementation Example
{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [
{
"@type": "Question",
"name": "What is schema markup?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Schema markup is structured data code you add to web pages to help search engines and AI systems understand your content's meaning, context, and relationships."
}
},
{
"@type": "Question",
"name": "Why does schema matter for AI retrievability?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Schema provides explicit signals that help AI systems categorize, understand, and cite your content. Without structured data, AI systems must infer meaning from unstructured text, which reduces accuracy and citation likelihood."
}
}
]
}
Common Implementation Mistakes
- Writing statements instead of actual questions in the name field.
- Answers that reference other content without being self-contained.
- Including links within answer text that reduce extractability.
- Mixing FAQ schema with other schema types incorrectly.
HowTo Schema
HowTo schema structures procedural content into machine-readable steps.Â
Why It Matters for AI Retrievability
AI systems need explicit structure to understand sequences and processes. HowTo schema makes it easier to extract and present your instructions in generated responses.
Where To Use HowTo Schema
- Step-by-step tutorials and guides
- Instructional blog posts
- DIY and how-to content
- Process documentation
Required Properties
- name: Title of the how-to guide
- step: Array of HowToStep objects with name and text
Recommended Properties
- totalTime: Estimated time to complete
- tool: Tools or materials needed
- supply: Supplies required
- image: Visual aids for steps
Implementation Example
{
"@context": "https://schema.org",
"@type": "HowTo",
"name": "How to Implement Schema Markup",
"description": "Step-by-step guide for adding structured data to your website",
"totalTime": "PT30M",
"tool": [
{
"@type": "HowToTool",
"name": "Google Rich Results Test"
}
],
"step": [
{
"@type": "HowToStep",
"name": "Identify appropriate schema type",
"text": "Review your content and determine whether Article, FAQ, HowTo, or other schema types best fit your page's purpose.",
"image": "https://example.com/images/schema-identification.jpg"
},
{
"@type": "HowToStep",
"name": "Create JSON-LD markup",
"text": "Build your schema markup using JSON-LD format with all required properties for your chosen schema type.",
"image": "https://example.com/images/json-ld-creation.jpg"
},
{
"@type": "HowToStep",
"name": "Add markup to your page",
"text": "Insert the JSON-LD script into your page header, either manually or through your CMS.",
"image": "https://example.com/images/schema-implementation.jpg"
},
{
"@type": "HowToStep",
"name": "Validate your implementation",
"text": "Test your markup using Google's Rich Results Tool to ensure it's valid and includes all required properties.",
"image": "https://example.com/images/schema-validation.jpg"
}
]
}
Common Implementation Mistakes
- Steps that aren’t actionable or specific (avoid vague instructions like “do research”).
- Missing context that makes steps unclear without reading surrounding content.
- Improperly nested steps or sub-processes.
- Not including tools or time estimates when relevant.
Article Schema
Article schema provides AI systems with clear metadata about your content detailing who wrote it, when it was published, and what organization produced it.
Why It Matters for AI Retrievability
Article schema helps AI systems categorize your content correctly and associate it with your brand and authors.
Where To Use Article Schema
- Blog posts and editorial content
- News articles
- Research papers and whitepapers
- Thought leadership pieces
Required Properties
- headline: Your article title
- datePublished: Publication date in YYYY-MM-DD format
- author: Person or Organization who created the content
- publisher: Organization that published the content
- mainEntityOfPage: The page URL
Recommended Properties
- image: Featured image for the article
- dateModified: Last update date
- description: Brief article summary
Implementation Example
{
"@context": "https://schema.org",
"@type": "Article",
"headline": "Schema Markup for AI Retrievability",
"description": "Learn how different schema types improve your content's visibility in AI-powered search",
"image": "https://example.com/images/schema-guide.jpg",
"author": {
"@type": "Person",
"name": "Jane Doe",
"url": "https://example.com/about/jane-doe"
},
"publisher": {
"@type": "Organization",
"name": "Example",
"logo": {
"@type": "ImageObject",
"url": "https://example.com/logo.png"
}
},
"datePublished": "2025-10-01",
"dateModified": "2025-10-09",
"mainEntityOfPage": {
"@type": "WebPage",
"@id": "https://example.com/blog/schema-markup-ai-retrievability"
}
}
Common Implementation Mistakes
- Missing required fields like author or publisher.
- Incorrect date formats. Dates must adhere to the YYYY-MM-DD international standard.
- Inconsistent author names across different articles.
- Generic or missing article descriptions.
- Author or publisher names that don’t match your organization and author schema.
Testing Your Schema
Every time you add or edit schema, make sure to test it to uncover any potential issues. The process is simple.
- Go to Google’s Rich Results Test.
- Enter your page URL.
- Review the results for errors or warnings.
- Fix any missing required fields, invalid URLs, or formatting issues.
- Retest until you see green checkmarks.
You can also check previously implemented schema in your Google Search Console by navigating to the Enhancement reports in the left-hand menu.
Schema markup doesn’t guarantee citations, but it removes uncertainty from how systems interpret your content. When entities, authors, answers, and processes follow a consistent structure, AI systems can retrieve and reuse your content more reliably.
SEO Strategist
With 10 years of marketing and technical SEO experience, Heather Frantz helps our clients improve their search visibility with technical SEO recommendations focused on focused on solving complex site issues and unlocking sustainable organic growth.
Updated Jan 12, 2026
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