A practical guide to choosing structured data, matching it to visible content, and testing the result.
Schema markup is a standardized vocabulary (from Schema.org) that helps machines understand web content. Instead of relying on AI to guess what your content means, schema explicitly declares it.
AI has to guess this is a question and answer. It might parse it correctly, or it might not recognize the Q&A structure at all.
<script type="application/ld+json">
{
"@type": "FAQPage",
"mainEntity": [{
"@type": "Question",
"name": "Is Pagesmith free?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Yes, you can try Pagesmith free..."
}
}]
}
</script>The markup labels the page as FAQPage for consumers that support this type.
Structured fields can make page details explicit for supported consumers.
Schema can label an article, product, organization, question, or answer. The visible content still has to support those labels.
Supported consumers can read fields such as author, date, price, or availability without inferring them from page layout.
Schema can connect publication dates, authors, organizations, and other entities when those details are present on the page.
Start with types that accurately describe the page and are supported by the search feature you want.
Use FAQPage only when the page meets the consumer's current eligibility rules and the questions and answers are visible to users.
{
"@type": "FAQPage",
"mainEntity": [{
"@type": "Question",
"name": "Your question here?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Your answer here."
}
}]
}Provides context for blog posts and news content: headline, author, publication date, and publisher. Helps AI assess recency and authority.
{
"@type": "Article",
"headline": "Your article title",
"author": {"@type": "Person", "name": "Author Name"},
"datePublished": "2025-01-14",
"publisher": {"@type": "Organization", "name": "Your Company"}
}Perfect for tutorials and step-by-step guides. Structures your instructions in a way AI can easily parse and present as numbered steps.
{
"@type": "HowTo",
"name": "How to do something",
"step": [
{"@type": "HowToStep", "name": "Step 1", "text": "First step details"},
{"@type": "HowToStep", "name": "Step 2", "text": "Second step details"}
]
}Establishes your brand identity. Connects your content to your organization for brand recognition in AI responses and knowledge panels.
{
"@type": "Organization",
"name": "Your Company",
"url": "https://yoursite.com",
"logo": "https://yoursite.com/logo.png",
"sameAs": ["https://twitter.com/yourcompany"]
}Step-by-step guide to implementing schema on your site.
Audit your site and categorize content: FAQ sections, blog articles, tutorials, product pages, company information. Each type needs appropriate schema.
JSON-LD (JavaScript Object Notation for Linked Data) is the recommended format. Add a script tag with type="application/ld+json" containing your structured data.
JSON-LD can go in the <head> or <body> of your HTML. Head placement is cleaner; body placement works for dynamically generated content.
Use Google's Rich Results Test (search.google.com/test/rich-results) or Schema.org's validator. Fix errors and warnings that apply to the search feature you want to support.
Pagesmith can generate structured data from the page content and settings. Review it when the page or search engine requirements change.
Every FAQ section automatically includes proper schema markup.
Blog posts and content pages get Article schema with proper metadata.
Site-wide organization schema establishes your brand identity.
Structured fields stay tied to the content you manage in Pagesmith.
<script type="application/ld+json">
[
{
"@type": "FAQPage",
"mainEntity": [
{
"@type": "Question",
"name": "What is Pagesmith?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Pagesmith is an AI..."
}
}
]
},
{
"@type": "Article",
"headline": "...",
"author": {...},
"publisher": {"@id": "#org"}
},
{
"@type": "Organization",
"@id": "#org",
"name": "Your Company",
"url": "https://..."
}
]
</script>Build a site with supported structured data where it fits. Review the visible content and markup together before publishing.
Schema markup is structured data that describes visible page content in a standard format. Search engines can use supported types to understand page details and determine eligibility for some search features. It does not guarantee an AI citation or rich result.
Use the most specific supported type that matches the visible content, such as Article, Product, Organization, or FAQPage where Google's eligibility rules allow it. Do not add a type only because it sounds relevant. Check each search engine's current documentation before implementation.
No. Google says no special schema is required for its AI search features, and OpenAI does not publish a required ChatGPT schema format. Accurate structured data can still support standard search features and make explicit page details easier for machines to read.
You can write JSON-LD manually, use a CMS plugin, or generate it from page data. Pagesmith can generate supported structured data for relevant page types. Review the result whenever visible content, product details, authorship, or eligibility rules change.
Use Google's Rich Results Test for Google-supported features and Schema.org's validator for vocabulary and syntax checks. A valid result does not guarantee a rich result, ranking, or AI citation. The markup must also match the visible page.