Schema markup is code you add to a web page to describe its content in a standardized, machine-readable way. It tells search engines and other tools exactly what a page is about: this is a product with this price, this is an article by this author, this is a business at this address.
People can usually understand a page just by reading it. Machines benefit from explicit labels. Schema markup provides those labels, which can make pages eligible for richer search results and helps search engines understand the entities on your site.
What is schema markup?
Schema markup is a type of structured data built on the schema.org vocabulary. According to its FAQ, schema.org is a collaboration between Google, Microsoft (Bing), Yahoo! and Yandex, created so websites could use one shared vocabulary instead of different formats for each search engine.
The vocabulary is large. As of October 2026, schema.org lists 826 types and 1,540 properties. Types describe what something is (Organization, Person, Product, Recipe, Event, Article). Properties describe its details (name, logo, price, author, startDate). Types are arranged in a hierarchy, so a Restaurant is a more specific kind of LocalBusiness, which is a kind of Organization.
Google defines structured data, in its introduction to structured data, as a standardized format for providing information about a page and classifying its content. Most structured data used for Google Search relies on schema.org vocabulary.
Why schema markup matters for search and AI
The most visible benefit is eligibility for rich results, the enhanced listings that can show review stars, prices, event dates, breadcrumbs and more. Google's structured data documentation shares case studies from publishers: Rotten Tomatoes measured a 25% higher click-through rate on pages with structured data, and Nestlé found pages showing as rich results had an 82% higher click-through rate than non-rich-result pages. Those are individual company results, not typical outcomes.
Schema also helps search engines understand who you are. Google says Organization markup helps it understand your organization and tell it apart from others, and that properties like logo can influence your knowledge panel. That makes schema a natural part of building a clear presence in the Knowledge Graph.
For AI search, the picture needs nuance. Google states in its guidance on AI features that there is no special schema.org markup required to appear in AI Overviews or AI Mode, and that structured data should match the visible text on the page. In other words, schema is not an AI shortcut. It is a clarity tool that supports accurate understanding of your content and business, which helps across search surfaces.
It is also important to know what schema does not do. Google's SEO Starter Guide frames structured data as making pages eligible for search features, not as a direct ranking boost. And eligibility is not a guarantee: valid markup can still go unused.
How schema markup works
Choose a format
Google supports three formats: JSON-LD, Microdata and RDFa. Google recommends JSON-LD because it sits in a separate script block rather than being woven into your visible HTML, which makes it easier to add, maintain and nest. All three are acceptable if implemented correctly.
Pick the right type and properties
Start with the most specific type that accurately describes the page's main content. A local plumber might use a Plumber type (a LocalBusiness subtype) on its homepage, Service markup on service pages and Article markup on blog posts. Then fill in the properties Google lists as required and recommended for that feature.
Connect entities with identifiers
Properties like sameAs link your entity to other pages that unambiguously identify it. Schema.org's sameAs definition gives examples like Wikipedia pages, Wikidata entries and official websites. For a business, this usually means your official social and directory profiles.
Validate and monitor
Google recommends testing markup with the Rich Results Test during development, then monitoring rich result reports and the URL Inspection tool in Search Console after launch. Templates and site changes can quietly break markup, so ongoing checks matter.
A schema markup example in practice
Imagine a hypothetical accounting firm with a homepage, a team page and a blog. A sensible setup might look like this:
- Homepage: an AccountingService (a LocalBusiness subtype) block with the firm's official name, URL, logo, address, phone, opening hours and sameAs links to its LinkedIn and Business Profile.
- Team page: Person markup for each partner, with name, job title and links to their professional profiles, connected to the firm through worksFor.
- Blog posts: Article markup with headline, author (linked to the partner's Person entity), publish date and modified date.
- Every page: BreadcrumbList markup that mirrors the site's navigation.
Every value matches what visitors can see on the page. Nothing claims reviews the firm doesn't display or services it doesn't offer. That consistency is what makes the markup trustworthy to search engines.
Schema markup best practices
- Start with your organization. Add Organization or LocalBusiness markup to your homepage or About page. Google says it doesn't need to appear on every page.
- Use JSON-LD. It is Google's recommended format and is the easiest to maintain.
- Mark up only what's visible. Google's structured data policies require markup to describe content users can see and to accurately reflect the page.
- Follow Google's feature docs, not just schema.org. Schema.org defines what's possible. Google's search gallery defines which properties it needs for each rich result.
- Be specific. Use the most specific accurate type, such as Dentist instead of LocalBusiness, or OnlineStore for an ecommerce site.
- Connect your entities. Link authors to articles, people to organizations and organizations to their official profiles through properties like author, worksFor and sameAs.
- Keep it current. Update markup when prices, hours, addresses or staff change, and check Search Console reports regularly.
- Review automated or AI-generated markup. Google's guidance on generative AI content says structured data needs the same review and validation as any other content.
Common mistakes and misconceptions
- "Schema improves rankings directly." Google describes structured data as making pages eligible for search features, not as a ranking boost.
- Marking up hidden or false information. Fake reviews, invisible content or misleading markup break Google's policies and can lead to a manual action that removes rich result eligibility.
- Relying on deprecated features. Google retires rich results over time. For example, Google's documentation updates log notes that FAQ rich results stopped appearing in Google Search starting May 7, 2026, and the FAQ documentation was later removed. FAQPage markup can still describe your content for other systems, but don't expect that display in Google.
- Assuming you need special schema for AI. Google says no special markup is needed for its AI features. Good, accurate markup still helps machines understand your content.
- Set-and-forget implementation. Theme updates, plugin conflicts and CMS migrations often break markup without anyone noticing.
Schema markup vs. structured data
People often use these terms interchangeably. Strictly, structured data is any standardized format for describing information, and schema markup is structured data that uses the schema.org vocabulary. Since nearly all structured data for search uses schema.org today, the difference rarely matters in practice.
How Butter approaches schema markup
At Butter, we treat schema markup as part of making a brand easy for machines to understand, not as a trick. Our GEO plan includes schema markup guidance alongside knowledge graph submissions, so clients get clear recommendations on which types to use, where to place them and how to connect their organization, people and content.
We usually start with Organization or LocalBusiness markup on the homepage, then add Article, Person, Product or Service markup where it accurately fits. We check that every value matches what's visible on the page, because mismatched markup undermines trust. On our GEO+SEO plan, we also handle technical SEO fixes, which includes catching markup that breaks during site changes. We're clear with clients that valid schema creates eligibility, not guarantees. You can see what's included on our pricing page.
Frequently asked questions
Does schema markup help with SEO rankings?
Google describes structured data as making pages eligible for rich results and other search features, not as a direct ranking factor. Rich results can make listings more noticeable, and Google's case studies show some sites saw higher click-through rates. Results vary by site and are never guaranteed.
What is the best format for schema markup?
Google recommends JSON-LD. It lives in a separate script block, so it is easier to add, update and nest than Microdata or RDFa. Google accepts all three formats as long as the markup is valid and correctly implemented.
Do I need schema markup to appear in AI Overviews?
No. Google says there is no special schema.org markup required to appear in AI Overviews or AI Mode. Pages must be indexed and eligible to show a snippet. Accurate structured data that matches your visible content is still a good practice for overall clarity.
How do I test my schema markup?
Use Google's Rich Results Test before publishing to check eligibility for specific features. After launch, monitor the rich result reports and URL Inspection tool in Search Console. The Schema Markup Validator is also useful for checking general schema.org syntax.