Structured Data
Structured data is machine-readable additional information you embed in your website's code to give content a clear meaning. Instead of letting search engines and AI systems guess what a text means, you tell them directly: this is a price, this an opening time, this a rating. That way content becomes unambiguously understandable and can be reliably processed further.
Why structured data matters
People recognize from context that "7 pm" is an opening time and "4.7 stars" is a rating. Machines initially see only strings of characters. Structured data supplies the meaning alongside: it marks which passage of text describes a product, a price, an address or a person. For classic search this decides whether you get rich results with stars, prices or FAQ dropdowns. For AI systems the benefit is even greater: a language model assembling answers prefers to draw on clearly marked facts, because it can attribute them unambiguously. Without this markup much is left to interpretation, and room for interpretation means errors or, quite simply, your content gets overlooked.
How structured data works
In practice you use a shared vocabulary called Schema.org. It defines types such as "Product", "Recipe", "Event" or "local business" with matching properties. You usually wrap this information in the JSON-LD format, a small block of data in the source code that stays invisible to visitors but is read by crawlers. An example: for an article you record the author, the publication date and the headline as named fields. Search engines and AI crawlers read out this block and instantly know what it is about, without having to interpret the running text. It is important that the marked-up information matches exactly what visitors actually see on the page. Otherwise it counts as deception.
Common mistakes
The classic mistake is marking up things that aren't visible on the page at all, such as invented ratings or prices. That gets penalized and costs trust. Just as common: outdated information that remains in the JSON-LD after a price change, while the page has long shown different figures. Contradictions between visible content and markup are almost worse than no markup at all, because they undermine your credibility. The wrong schema vocabulary is an issue too: marking a service as a product confuses the systems. So check your markup regularly with a testing tool and keep it in sync with the real content, especially for prices, dates and availability.
Relation to AI recommendations
AI assistants like ChatGPT, Perplexity or Google AI Overviews assemble answers from many sources and preferentially name facts they can attribute with confidence. Structured data provides exactly that confidence: it makes your core information unambiguous and citable. A language model that finds an opening-time or price detail as a cleanly marked-up field is more likely to reproduce it correctly than if it had to extract it from nested running text. This increases your chance of appearing in generated answers at all and being reproduced correctly. Structured data doesn't replace good content, but it is the technical bridge over which your facts travel reliably into AI answers. In GEO practice it is therefore part of the basic toolkit.
Example
Imagine a small bike shop that offers repairs. On the page, opening hours, address and customer reviews appear as normal text. If the owner adds structured data of the type "local business", they mark the address, phone number, opening hours and average rating as named fields. If someone asks an AI assistant "Where near me can I still get my bike repaired in the evening?", the system can read out the opening hours unambiguously and recommend the shop specifically. Without the markup it would have to guess the hours from the text, which often goes wrong.
Common questions
Do I need structured data if I already have good content?
Yes, because good content and structured data solve different jobs. The text convinces people, the markup makes your facts unambiguous for machines. Only together do they ensure that search engines and AI systems recognize and pass on your information correctly.
Is JSON-LD the same as structured data?
Not quite. Structured data is the concept of machine-readable markup. JSON-LD is one of several formats for implementing it, and today the recommended one. The vocabulary behind it usually comes from Schema.org, which defines the available types and properties.