Schema Markup
Schema markup is structured vocabulary from schema.org that you add to a web page to label its content for machines, telling search engines and AI systems exactly what each element means so they can render rich results and recognise the page as a specific entity.
Plain HTML tells a browser how to display text, but it does not say whether a number is a price, a rating, or a phone number. Schema markup closes that gap by tagging content with agreed types and properties, usually written as JSON-LD in a script tag in the page head. Each type is a vocabulary with defined properties: a Product carries a name, a brand, an image, and an offers block; an Offer carries a price, a currency, and an availability state; a Review carries an author, a rating, and a body. The markup sits alongside the visible page rather than replacing it, so the same product description a shopper reads is also described in a form a machine can parse without guessing.
For a store, the types that earn the most are Product, Offer, Review, AggregateRating, Organization, BreadcrumbList, and FAQPage, each one mapping a piece of the page to a meaning a machine can act on. Consider a Shopify merchant selling a merino base layer at forty-nine pounds with two hundred and eleven reviews averaging 4.6 stars. Without markup, a crawler sees a heading, some paragraphs, and a star graphic it cannot read. With a Product block that nests an Offer (price 49.00, currency GBP, availability InStock) and an AggregateRating (ratingValue 4.6, reviewCount 211), the page states those facts plainly, and the listing becomes eligible to show the price and the star rating beneath the title.
The payoff is twofold. First, eligibility for rich results: star ratings, prices, and FAQ accordions in the search listing, which tend to draw more attention than a plain blue link. Second, clearer entity recognition, which increasingly feeds AI answer engines that summarise and cite sources rather than rank ten links. When ChatGPT, Perplexity, or Google AI Overviews assemble an answer about a product, structured data gives them clean, unambiguous facts to quote, so a price or a rating lifted into an answer is more likely to be yours and to be correct. This matters most for the specific, comparable claims those systems lean on: price, availability, and rating.
The rule that trips people up is the visible-content match: the markup must describe content a user can actually see on the page. Marking up reviews or ratings that are not present, or inflating the numbers, is against Google guidelines and can trigger a structured-data manual action that removes your rich results entirely. The honest discipline is to add the vocabulary to reflect what is already on the page, keep it in step when prices and review counts change, and validate it with the Rich Results Test before shipping. Markup does not guarantee a rich result; it makes the page eligible, and the search engine still decides whether to show one.