What Is Schema Markup?
Schema markup is a form of structured data that you add to your web pages so that search engines and AI tools can understand the meaning behind your content, not just the words on the page. It uses a shared vocabulary defined at Schema.org, which describes hundreds of entity types such as organisations, products, articles, reviews, events, FAQs and local businesses.
In practice, schema markup is almost always written in JSON-LD (JavaScript Object Notation for Linked Data). This is a small block of code placed in the page that lists facts in a clean, machine-readable format, for example the name of your business, your star rating, your opening hours or the questions answered in an article. JSON-LD is the format Google recommends because it sits separately from your visible content and is easy to maintain.
Without schema markup, a search engine has to guess what a page is about from the raw text. With it, you are stating the facts plainly. A page might say in its markup that it is an Article, written by a named author, published on a given date, and that it answers three specific questions. This removes ambiguity and helps the page qualify for enhanced search features.
Why Schema Markup Matters
The most visible benefit is rich results. When a page carries valid schema, Google can show enhanced listings such as star ratings, FAQ drop-downs, breadcrumb trails, product prices and event dates directly in the search results. These richer listings take up more space, build trust and tend to earn a higher click-through rate than a plain blue link.
Schema markup has also become important for AI search. Engines like Google AI Overviews, ChatGPT and Perplexity rely on clear, structured signals to interpret a business and decide which sources to cite. When your facts are stated in clean structured data, an AI engine is far less likely to misread your offering and far more likely to reference you accurately. This is a core part of AI search optimisation and works hand in hand with strong SEO foundations.
It also supports the knowledge graph. Linking entities with schema helps search engines connect your business to its services, locations and people, which strengthens your overall topical authority over time.
How to Use Schema Markup
Start with the schema types that match your pages. A local service business should mark up its organisation and LocalBusiness details, service pages should use Service schema, articles should use Article schema, and any page with questions should add FAQPage markup. Most of our pages also include BreadcrumbList schema so the navigation path appears in search.
Keep your markup honest and consistent with what visitors actually see. Google penalises markup that describes content not present on the page, so never invent reviews or prices. After adding JSON-LD, validate it with the Rich Results Test and the Schema.org validator to confirm there are no errors before publishing.
Schema markup is a technical layer that rewards careful implementation. If you would like it done properly across your site, it forms part of our SEO services in South Africa and our AI search work. You can also read more in our guides on generative engine optimisation and answer engine optimisation.
How does schema markup help SEO?
Schema markup is structured data, usually written in JSON-LD, that labels the meaning of content so search engines understand it precisely: that a number is a review rating, a block is a set of FAQs, or an entity is a local business. It does not directly raise rankings, but it makes pages eligible for rich results such as star ratings, FAQ expanders and business panels, which increase visibility and click-through. It also strengthens how search engines and AI systems interpret entities and relationships on your site, which supports accurate representation in AI answers.
Common schema types and when to use them
Use Organization or LocalBusiness to describe the business itself, including name, address and contact details. Use Service for individual offerings, Article or BlogPosting for editorial content, Product for items, and FAQPage where a page genuinely shows a list of questions and answers. BreadcrumbList marks navigation paths, and AggregateRating carries a review score, which must describe your own entity and never a third party. Apply only the types that match visible content; marking up content a user cannot see, or attaching a rating to someone else's brand, breaches Google's guidelines.
FAQ
What is the difference between schema markup and structured data?
Structured data is the general concept of marking up content in a standard format. Schema markup specifically means using the Schema.org vocabulary, usually written in JSON-LD, to describe that content to search engines and AI tools.
Does schema markup help with AI search?
Yes. Clear schema markup gives AI engines like ChatGPT, Google AI Overviews and Perplexity structured, machine-readable facts about your business, which makes your content easier to interpret and cite accurately.
Do I need schema markup to appear in AI search?
No. Google has confirmed there is no special schema required for its generative AI features. Schema still matters for classic SEO and rich results, and it helps machines interpret your entities, but it is not a separate gate for AI visibility.
Can incorrect schema markup hurt my site?
Yes. Marking up content that is not visible on the page, or declaring a review rating for an entity that is not yours, violates Google's structured data guidelines and can trigger a manual action. Schema must always reflect genuine, visible page content.