What is schema markup (JSON-LD)? ================================ Schema markup is a small block of structured data that tells search engines and AI exactly what a page is about: this is a Product with this price, this is an Article by this author. SuperSchema writes it in JSON-LD, the format Google recommends, and it does not change how your page looks or slow it down. Category: Core Concepts | Last updated: 2026-07-07 Schema markup (also called structured data) is a small block of code that spells out what a page is about in a way machines can read without guessing. A human looking at your page sees a headline, a price, and a photo and understands "this is a product for sale." A machine sees a wall of HTML. Schema markup labels the important facts explicitly: this is a Product, its name is X, its price is Y, its rating is Z. SuperSchema writes that block for you in JSON-LD, the format Google recommends, and it never changes how your page looks or how fast it loads. The labels come from a shared, public vocabulary called schema.org, maintained by Google, Microsoft, and others. Because everyone agrees on the same terms (Product, Article, FAQPage, Organization, LocalBusiness, and hundreds more), a search engine or an AI assistant can read your markup and know exactly what each fact means, the same way it reads every other site that uses the vocabulary. A QUICK EXAMPLE Say you have a page for a recipe. A person reads the title and the ingredient list and understands it instantly. Structured data hands the same facts to a machine as clearly labeled data: { "@context": "https://schema.org", "@type": "Recipe", "name": "Classic Margherita Pizza", "author": { "@type": "Person", "name": "Jane Doe" }, "prepTime": "PT20M", "recipeIngredient": ["Flour", "Tomatoes", "Fresh mozzarella", "Basil"] } Nothing here is new information: it all comes straight from what is already on the page. The markup just states it plainly so a machine does not have to infer the recipe name, the author, or the prep time from the surrounding layout. WHY IT MATTERS FOR AI AND SEARCH Search engines and AI answer engines both work better when they are certain about your facts. When your page carries accurate schema, you make two things possible: Rich results in search: Google can show enhanced listings (star ratings, prices, FAQ dropdowns, recipe cards) instead of a plain blue link. These come from the structured data on your page. Accurate AI answers and citations: When an AI assistant like ChatGPT, Perplexity, or Google’s AI overviews answers a question, it is safer for it to state and cite a fact it can read explicitly than one it has to guess from raw HTML. Clear schema reduces the chance AI describes you wrong or reaches for a competitor instead. Note: Schema makes rich results and AI citations possible; it does not guarantee them. Search engines and AI systems decide what to show. Your job is to give them accurate, machine-readable facts so that when they do choose, they get you right. WHY JSON-LD, NOT MICRODATA There are a few ways to write structured data. The two you will hear about are JSON-LD and microdata. SuperSchema uses JSON-LD, and so does Google’s official guidance. The difference is where the data lives. JSON-LD: A single self-contained block of data, added inside a