Structured data, or schema markup, is code you add to a page (using the schema.org vocabulary) that spells out what the content actually is: an FAQ, a how-to, a product, a company. It states the meaning outright instead of leaving a machine to infer it.
A person can tell from context that a block of text is a pricing FAQ or a set of steps. A machine has to guess, unless you label it, and labelling is what schema does. FAQPage says "these are questions and answers." Organization says "this is the company, and here's its name and description." HowTo says "these are steps, in order." The guesswork goes away, and instead of hoping a retrieval system untangles your FAQ from the surrounding prose, you hand it a clean version of exactly what each part means.
For a content team it's one of the few AEO levers that sits fully in your hands. Most of the work is soft, better writing and slowly earned authority, but schema is code you can ship this week. It won't carry a weak answer on its own, yet it comes close to mandatory. It makes your answers easier to pull, quote, and attribute, and the Organization markup feeds the knowledge graph that tells AI systems who you are as an entity.
Putting it in is mechanical. Pick the types that fit each page (FAQPage, HowTo, Product, Article, Organization), add them as JSON-LD in the head, keep the markup honest and in step with what's visible, and run it through a validator before it goes live. Mark up a pricing FAQ properly and you hand the engine a tidy list of question-and-answer pairs to lift. Leave it as plain paragraphs and the engine has to reverse-engineer the structure from your formatting, if it bothers at all.
Related terms
- Answer Engine Optimization (AEO): schema is one of its core levers
- Retrieval-Augmented Generation (RAG): parseable structure helps retrieval
- Knowledge Graph: what
Organizationand entity markup feed