Schema markup is code you add to a web page that tells search engines and AI systems what your content actually means — not just what it says. It uses a shared vocabulary from schema.org to label things like your business, your prices, your reviews, and your FAQs, so machines can read them with certainty instead of guessing.
A web page is written for people. Schema markup is a parallel layer written for machines — usually a small block of JSON-LD that says, in effect, "this is a LocalBusiness, its name is X, its rating is 4.8, here are its hours." Google, Bing, and the large language models behind AI search read that layer to understand your page with confidence. The payoff is two things: enhanced "rich results" in search (star ratings, FAQs, prices), and a much better chance of being understood — and cited — by AI.
Schema doesn't make your content better — it makes your content legible. That legibility shows up in three concrete ways, and all three compound over time as search shifts toward AI.
There are three ways to write structured data — JSON-LD, microdata, and RDFa — but in practice the decision is made for you. JSON-LD lives in a single script block, separate from your visible HTML, which makes it far easier to maintain, scale, and debug. It's the format Google explicitly recommends, and it's what I use on every build unless a platform genuinely forces otherwise. Microdata and RDFa tangle the markup into your HTML tags; avoid them unless you've inherited them.
Schema.org defines hundreds of types, but a handful cover the vast majority of real sites. The skill isn't knowing all of them — it's choosing the most specific type that fits, and connecting them so they reference each other.
Yes — but not the way people hope. Schema markup is not a direct ranking factor; adding it won't push you from position 8 to position 1 on its own. What it does is change how you appear and how confidently machines understand you. Rich results lift click-through. Clear entities improve relevance. And in AI search, well-structured facts are the difference between being summarized accurately and being skipped. For most sites I audit, it's one of the highest-leverage technical fixes still left on the table — precisely because so few competitors do it properly.
This is the part most guides still under-sell. AI Overviews, ChatGPT, and Perplexity synthesize answers from sources they trust, and structured data is how they read your business's facts, people, and relationships without guessing. It feeds the knowledge graphs those systems rely on. Marking up your entities — and linking them to public references like Wikipedia and Wikidata — is how you make your site easy to quote accurately. It's not a guarantee of a citation, but it stacks the odds, and right now almost nobody is doing it at a practitioner level.
You can hand-write JSON-LD, use a generator, or let a plugin emit it — but the failure modes are always the same. The single most important rule: only mark up content that's actually visible on the page. Inventing data you don't show is the fastest route to a manual penalty.
Get your schema done right →I write custom JSON-LD by hand, scale it across whole sites, and validate it end to end. If your structured data is missing, generic, or quietly broken, let's fix it.