What Is Schema Markup?
Schema Markup, also known as Structured Data, is data that you can add to your web page’s HTML code to explicitly define entities, properties, and relationships within your content. By doing so, it helps search engines and AI systems understand your website content with greater accuracy and context.
By defining entities, relationships, and meaning in a machine-readable format, schema markup helps improve visibility in search, qualify your pages for rich results, and strengthen how your brand is understood across AI-driven experiences.
Built using the Schema.org vocabulary, schema markup transforms your website from a collection of pages into a connected semantic data layer that search engines and AI can reliably interpret and trust.
Although LLMs and search engines use sophisticated machine learning algorithms, they do not process or interpret information in the same way humans do. What might seem simple to a person may be unintelligible to a computer. Schema Markup helps fill in the blanks for LLMs and search engines so that they know exactly what your page is about.
For instance, let’s say you have a product detail page with an image and description of a handsaw, along with the brand’s image in the header.
A person reading this would immediately realize that the handsaw is from the brand “Dewalt,” but it might be difficult for search engines to understand that explicitly. You can use Schema Markup to identify that the brand of handsaw on this page is “Dewalt” so that the search engines and AI interfaces can present this content for users searching phrases like “Dewalt handsaw.”
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What are the main SEO benefits of using Schema Markup?
1. Help search engines and AI understand your content
Schema markup helps search engines and AI systems better interpret your content by defining the entities, topics, and relationships on your website in a machine-readable format.
This clearer understanding can improve eligibility for rich results, strengthen visibility in AI-driven search experiences, and help your content appear more prominently for high-intent searches.
The impact is measurable. Schema App customers have seen significant gains in organic visibility and engagement through connected structured data. Organizations like Wells Fargo have used connected schema markup to help resolve AI search hallucinations and improve how their brand information is understood across search and AI experiences. Schema App’s own Schema Markup and Entity Linking implementation also drove a 19.72% increase in AI Overview visibility, demonstrating how connected entity relationships can improve discoverability in modern AI-powered search experiences.
As search evolves from keywords to entities and relationships, schema markup helps search engines and AI systems understand not just what is on a page, but how your content connects across your broader digital presence.
2. Build a semantic data layer for AI-driven search
Schema markup does more than describe individual pages. It connects your content into a structured, reusable semantic data layer (aka Content Knowledge Graph) that helps search engines and AI understand your brand, expertise, and relationships across your website.
This connected data foundation supports modern AI-driven discovery experiences, including AI Overviews and generative search, where visibility increasingly depends on how well machines understand your content, not just the keywords on the page.
By implementing connected schema markup at scale, organizations create a more reliable source of truth for search engines and AI systems, helping improve visibility, reduce ambiguity, and strengthen brand representation in the age of AI.
Gartner has also identified that knowledge graphs are a critical enabler for generative AI adoption, further highlighting Schema Markup’s fundamental role in AI advancements.
3. Achieve Rich Results
Implementing certain types of structured data can also enable search engines to display visually enhanced search results (aka rich results) instead of generic “plain blue link” results listings.
Rich results enhance standard search results by presenting additional information, such as a business location, images, product reviews, etc. Rich results are also referred to as enriched results or rich snippets, as they provide snippets of information about a page, brand, or business.
Example of a Product Rich Result
Example of a Review Snippet
Rich results are visually appealing and informative, making your listings stand out on the SERP and improving the overall search experience for users. By incorporating structured data, you cater to both customer needs and search engine algorithms, increasing your competitiveness in search results.
What Types of Schema Markup are there?
There are many different types of Schema Markup that you can incorporate into your online content. Some of the most commonly used markup types include:
- Reviews: This type is used to mark up reviews for products, services, or other items. It includes properties like the reviewer’s name, rating, and review text.
- Product: Product markup is used for e-commerce sites to describe specific products. It includes details such as name, description, price, availability, and more.
- Local Business: This markup type is ideal for businesses with physical locations. It includes properties like name, address, phone number, opening hours, and geographical coordinates.
- Person: Person markup is used to describe individuals, including properties such as name, job title, contact details, and social media profiles.
- Organization: Similar to local business markup but broader, organization markup can be used for any type of organization, including corporations, educational institutions, non-profits, etc. It includes details like name, logo, contact information, and social profiles.
- Event: Event markup is used for marking up events such as concerts, workshops, or conferences. It includes properties like event name, date, location, and ticket information.
- Media Objects (images, videos, audio): Markup for media objects like images, videos, or audio files. It can include properties such as caption, thumbnail URL, and duration.
- Creative Works (movies, books, music, TV series, recipes): This type covers a range of creative content, including movies, books, music, TV series, and recipes. It includes properties specific to each type, such as author, director, actors, duration, and ingredients for recipes.
Choosing the right schema type depends on the nature of your content. Each type comes with its own set of properties that you can use to provide detailed and structured information about the content on your webpage. You can view the full list of Types here and learn more about the Schema.org vocabulary here.
What is the recommended format for implementing Schema Markup?
The most commonly used formats for implementing structured data are JSON-LD, microdata, and RDFa. However, Google recommends using JSON-LD due to its readability for both humans and machines.
Implementing JSON-LD (JavaScript Object Notation for Linked Data) is easier than implementing other formats like microdata or RDFa, and you can seamlessly incorporate it within the HTML of your web pages. This format is favored for its simplicity and effectiveness in conveying structured data to search engines.
How to implement Schema Markup on your site
Manually generate your own code and paste it on your site
One way to implement Schema Markup is to do it manually using the following steps.
- Review Page Content: Examine each page on your site and identify what the page is mainly about.
- Choose Schema Types: Select the appropriate schema type and properties that best describe the content on your page.
- Write the JSON-LD: Create the Schema Markup in JSON-LD using the chosen schema types and properties.
- Embed JSON-LD in HTML: Incorporate the Schema Markup JSON-LD into the HTML of your webpage.
- Test Markup: Use tools like Google’s Rich Results Testing Tool (if you aim to achieve a rich result) or Schema.org’s Schema Markup Validator to validate and ensure correct implementation and desired results.
If you have the technological savvy to write the JSON-LD and can meticulously work through each page of your site’s content, this approach is a viable option.
However, the manual method of implementing Schema Markup is incredibly labor-intensive—especially if you have a huge website. Similarly, bringing in your own IT team to write and deploy the code can also be costly and time-consuming.
Use a Schema Markup Plugin
Instead of implementing the markup manually, you can opt to use a Schema Markup plugin to implement Schema Markup programmatically.
There are many Schema Markup plugins available for WordPress, Shopify and other CMSes that will allow you to add markup to your page programmatically. However, many Schema Markup plugins tend to be limiting in terms of the Schema type and properties you can leverage. You will also have little control over marking up each page.
Learn more about the pros and cons of using a Schema Markup plugin here.
Work with a Schema Markup Partner
Implementing Schema Markup at enterprise scale requires more than generating code. It requires a governed, connected semantic data layer that can evolve alongside your content, support AI-driven search, and remain accurate over time.
Schema App combines enterprise-ready semantic technology with a team of structured data experts to help organizations build, deploy, and manage Schema Markup at scale without creating additional dependency on internal development teams.
Our platform enables marketing and SEO teams to manage structured data more efficiently through flexible deployment options and connected entity modelling, while our expert services team helps ensure your markup aligns with your business goals, content strategy, and AI visibility objectives.
Rather than treating Schema Markup as a one-time SEO task, we help organizations build the structured foundation needed to improve search visibility, strengthen brand control, and support how AI systems understand their business.
Build a Stronger Foundation for Search and AI
As search evolves toward AI-driven discovery, schema markup is becoming foundational infrastructure for digital visibility and brand understanding.
Whether you manage schema markup internally or partner with a provider like Schema App, investing in connected structured data helps search engines and AI systems better understand, represent, and trust your content.
If you’re looking to build a scalable, AI-ready schema markup strategy, get in touch with Schema App.
Martha van Berkel is the co-founder and CEO of Schema App, a semantic technology company that helps enterprise brands control how they are represented in AI and search. By building a semantic data layer, Schema App enables organizations to improve visibility, protect their brand, and drive more efficient organic growth. She focuses on helping marketing teams navigate the shift from traditional SEO to AI-driven discovery by establishing a structured source of truth for their content.