Structured data is code you add to a web page that tells search engines exactly what your content means, not just what it says. It is the foundation of rich results in Google and a key signal for AI search tools that need to understand your site without guessing.
Search engines read the words on your pages. Structured data goes a step further: it tells them what those words represent. The difference between a search engine reading "4.9 stars, 47 reviews" and knowing it is a verified customer rating is structured data.
Structured data is added to the source code of a web page, usually as a block of JSON-LD inside a <script> tag. It is invisible to visitors but fully readable by Google, Bing, and AI search tools like ChatGPT and Perplexity.
The standard vocabulary is Schema.org, a shared dictionary of types and properties maintained by Google, Microsoft, Apple and others. When you use it, every major search engine can understand your markup in the same way.
Without structured data, Google infers meaning from your copy. With it, you state facts directly: this page describes a Product, its price is X, it has Y reviews, it is in stock. There is no inference required. This is more accurate, more reliable and more useful to the search engine.
Structured data is what allows your listing in Google to show star ratings, prices, event dates, FAQs, breadcrumbs and more. These enhanced formats, known as rich results, increase your visibility and click-through rate compared to a standard blue link. Schema Markup is the practice of implementing this code correctly.
Unstructured data is ordinary web content: paragraphs, headings, images and lists that a human can read and understand but a machine must interpret. Structured data is the opposite: it is formatted precisely so machines can parse it without needing to interpret meaning from context.
A review written in a paragraph is unstructured. The same review expressed as a Review schema object with explicit ratingValue, author and datePublished properties is structured. Google prefers the latter because there is no ambiguity.
Structured data does not influence rankings directly. What it does is give Google precise, machine-readable facts that feed into multiple systems: rich results, Knowledge Graph entries, AI-generated answers and more. Here is the path it travels.
A <script type="application/ld+json"> block describes the entity on the page using Schema.org vocabulary.
When Google crawls your page, it extracts and validates the structured data separately from the visible content.
Google checks that the required properties are present, the values match the live page content, and the schema type is eligible for rich results.
Valid, eligible markup can produce rich results in Google Search, inform Knowledge Graph entries, and feed AI search tools that cite your content.
Google has confirmed structured data does not directly boost your rankings. Its value is in eligibility for rich results and improved understanding of your content, both of which can improve click-through rates and visibility in AI search.
Google requires that structured data accurately reflects what is on the page. Marking up a rating that does not appear in the visible content, or inflating a price, violates Google's guidelines and can result in a manual action or loss of rich results eligibility. The markup and the content must be consistent.
The same structured data that helps Google display rich results also contributes to your Knowledge Graph entity record, your Local SEO signals through LocalBusiness schema, and the citations used by AI tools when they describe your business or content.
Schema.org lists hundreds of types. In practice, a relatively small number account for the vast majority of structured data used across the web. These are the types most likely to be relevant to a UK business and most likely to produce rich results in Google.
Describes a physical or local business: name, address, phone number, opening hours, geographic coordinates and service area. Essential for Local SEO and Google Business Profile alignment.
Identifies a named individual: their name, job title, employer, social profiles and areas of expertise. Important for author credibility on editorial content and for building a personal entity in the Knowledge Graph.
Describes a piece of written content: its headline, author, date published, date modified and featured image. Supports Google's author trust signals and is used by AI tools to understand who wrote the content and when.
Describes a product for sale: its name, description, brand, SKU, price, currency, availability and aggregate rating. One of the most commercially valuable schema types for eCommerce SEO and comparison surfaces.
Describes individual reviews or aggregated ratings for a product, service or business. When implemented correctly, star ratings and review counts appear directly in Google search results, significantly improving click-through rates.
Describes a page that contains a list of questions and answers. When Google chooses to show FAQ rich results, the questions expand directly in the search listing, occupying significantly more screen space and providing visible answers before the user clicks.
Describes an event with a name, start date, end date, location and organiser. Event schema is used by Google to surface events in dedicated event search results and Google Maps, and by AI tools to answer queries about what is happening where and when.
Describes the navigational path to a page within a site hierarchy. When implemented, Google replaces the raw URL in search results with a readable breadcrumb trail, which improves clarity for users and gives Google a clearer picture of your site structure.
HowTo schema describes step-by-step guides and can produce rich results with numbered steps shown directly in Google. SoftwareApplication schema is used for apps and SaaS tools to display ratings, pricing and platform support in search results.
Not every schema type produces a rich result. Google supports a specific, documented list of rich result types. Adding schema to a page is always beneficial for machine understanding, but the visual enhancements in search results only appear for the types Google has chosen to support. The full list is maintained at Google's Structured Data Search Gallery. Our Schema Markup service covers implementation, validation and monitoring across all supported types.
A standard search result shows a title, a URL and a short snippet. Structured data gives you the opportunity to replace that with something far more prominent. Here is what well-implemented schema can produce in Google Search.
AggregateRating schema allows your review score to appear directly below your title in Google, before a user even reads your snippet. This is one of the most visible CTR improvements available.
FAQPage schema can produce an expanded listing with three or four questions visible in the SERP itself, dramatically increasing the footprint of your result and providing immediate answers that build trust.
Product schema brings price, currency and stock availability into the SERP, helping your listing stand out in comparison searches and filtering out users who would immediately bounce due to price mismatch.
BreadcrumbList schema replaces the raw URL in your search listing with a readable path: Home › Services › SEO. This communicates site structure clearly to both users and Google, supporting Technical SEO best practice.
Organisation and LocalBusiness schema, combined with consistent entity signals across the web, contributes to your brand appearing in a Knowledge Panel on the right side of relevant search results, displaying your details at a glance.
Google's AI Overviews, ChatGPT, Perplexity and other AI tools all need to understand what your content is about before they can cite it. Structured data gives them the clearest possible signal. As AI search grows in importance alongside traditional results, structured data becomes more valuable, not less.
When an AI tool crawls your site, structured data gives it unambiguous facts: your business type, location, services, ratings and more. This reduces the chance of your content being misrepresented or omitted from AI-generated answers.
AI Overviews and conversational AI tools frequently pull question-and-answer pairs directly from FAQPage schema. Writing structured FAQ answers in complete, parseable sentences is one of the most practical ways to appear in AI-generated responses.
Organisation and LocalBusiness schema contribute to your entity record in the Knowledge Graph, which in turn influences how AI tools describe your brand across ChatGPT, Gemini, Perplexity and others. Consistent, accurate entity data reduces the risk of hallucinated or incomplete business descriptions.
Generative Engine Optimisation, or GEO, is the practice of optimising content to appear in AI-generated answers. Structured data is one of its primary technical pillars, alongside strong topical authority and clear, factual writing. Neglecting schema is one of the easiest ways to be invisible to AI tools.
Schema Markup on your site, combined with consistent entity signals across directories, social profiles and third-party mentions, is what builds a strong Knowledge Graph record for your business. The stronger your entity record, the more confidently AI tools and Google can describe you. Read our Knowledge Graph guide for the full picture.
Structured data can be written in three formats. Google recommends JSON-LD for all new implementations and uses it in all of its own documentation. Here is what each format means and how the implementation process works in practice.
A block of JSON placed inside a <script type="application/ld+json"> tag. Google's preferred format. The markup sits in the <head> or <body> and is completely separate from the visible HTML, making it easy to add, edit and maintain without touching the page design.
An older approach that embeds structured data attributes directly into HTML tags using itemscope, itemtype and itemprop attributes. The markup is woven into the visible HTML, which makes it harder to manage as content changes and increases the risk of errors when developers edit templates.
Resource Description Framework in Attributes. Like Microdata, it embeds markup attributes in the HTML. Originally developed for semantic web applications, it is still used by some enterprise content management systems and government websites but is not recommended for typical SEO implementations.
Check what schema is already in place. Use Google Search Console and the Rich Results Test to identify errors, missing types and opportunities.
Match schema types to your page templates: LocalBusiness on the homepage, Product on product pages, Article on blog posts, FAQPage on FAQ sections.
Produce valid JSON-LD blocks for each template. For large sites, implement dynamically using your CMS's template system so markup populates automatically with page data.
Use Google's Rich Results Test and Schema Markup Validator to confirm there are no errors. Check that all required properties are present for the rich result types you are targeting.
Use the Enhancements reports in Google Search Console to track rich result impressions, click-through rates and any validation errors that appear over time.
On WordPress, plugins like Rank Math and Yoast SEO handle basic JSON-LD automatically. On Shopify, a base layer of Product schema is generated by the platform. Neither covers every schema type your site needs, and both can produce errors on more complex page types. Our Schema Markup service covers the full audit, implementation, validation and monitoring process across any CMS or platform, ensuring your markup is correct and maintained as content changes.
Adding structured data to a page is only half the work. Validating it correctly, checking it produces no errors, and monitoring it over time as content changes is what keeps your rich results live. There are three tools that handle this, and they serve different purposes.
Google's primary tool for testing structured data. Enter a URL or paste code and it tells you which rich result types your markup is eligible for, what required properties are present, and what errors or warnings exist. Use this first.
search.google.com/test/rich-results →Validates your markup against the Schema.org specification rather than Google's rich results criteria. Useful for checking types that do not produce rich results but still need to be accurate, such as Organisation schema or custom types.
validator.schema.org →The Enhancements section of Search Console shows your rich result impressions, clicks and any validation errors across your whole site over time. This is the tool you use after launch, not at implementation. Errors here mean rich results have been lost or are at risk.
search.google.com/search-console →The Rich Results Test is the most practical tool for day-to-day structured data work. It tells you not just whether your markup is valid JSON, but whether it meets Google's requirements for rich result eligibility. Here is how to use it effectively.
The Enhancements section of Search Console shows a separate report for each rich result type detected on your site. Each report shows valid pages, pages with warnings, and pages with errors, alongside impression and click data for that rich result type. This is how you catch drift after launch.
Shows every page where a rich result type passed all required checks. A drop in this number means pages have developed errors, often due to a content or template change.
Lists pages with errors that prevent rich result eligibility. Each error links to the specific property causing the problem. Fix these first before addressing warnings.
Shows how often your rich results appeared in Google Search and how many clicks they received. Compare this to standard result performance in the Search Performance report to measure the CTR impact of your schema.
The right schema stack depends on what your site is and what it sells. A local service business and an eCommerce store need very different implementations. Select your business type below to see the schema types that matter most and why.
Plumbers, solicitors, accountants, tradespeople, agencies, clinics and anyone serving a defined geographic area. The goal is maximum visibility in local search results and Google Maps, and making your ratings and contact information appear without a click. Local SEO and schema work hand in hand here.
Use the most specific subtype available: MedicalBusiness, LegalService, HomeAndConstructionBusiness, etc. Include name, address, telephone, openingHoursSpecification, geo coordinates, priceRange and sameAs links to your Google Business Profile and social profiles.
Nest inside your LocalBusiness schema. Include ratingValue, reviewCount and bestRating. Only mark up ratings that appear visibly on the page. Verify that the rating displayed in your markup matches what users see.
Add a Service schema block on each individual service page describing what the service is, who it is for and the area it covers. Link it to your Organisation entity using the provider property.
Add FAQPage schema to any page that contains a genuine question-and-answer section. Write answers in complete, factual sentences of 40-60 words. Avoid questions that are purely commercial.
Any site selling products online, whether Shopify, WooCommerce, Magento or custom-built. Product schema is the highest commercial-value structured data available for eCommerce: it brings price, availability and ratings directly into search results, improving qualified traffic and reducing bounce. See our eCommerce SEO service for the full picture.
Every product page needs Product schema with name, description, image, sku and brand. Without it, you are ineligible for merchant rich results. Shopify generates a basic Product block automatically but it frequently omits required properties such as offers and brand.
The Offer object inside Product is what carries price, priceCurrency, availability and url. This is the property set that produces price and availability in search results. It must be updated in real time or via dynamic markup to avoid showing stale prices.
Nest AggregateRating inside the Product block for each product that has reviews. Include ratingValue and reviewCount. Only mark up reviews that are visible on the page. Review schema that does not reflect visible content violates Google's guidelines.
Every product and category page should carry a BreadcrumbList reflecting the full category path. This helps Google understand your taxonomy, improves the URL display in results, and supports internal linking equity flow through category hierarchies.
Agencies, consultancies, law firms, accountancy practices, marketing firms and any business selling services to other businesses. The schema priority here shifts away from product data toward entity credibility, thought leadership signals and Knowledge Graph presence. See our B2B SEO service for context on how this fits into a broader B2B strategy.
Place Organisation schema in the global site template so it appears on every page. Include name, url, logo, description, foundingDate, numberOfEmployees and sameAs links to LinkedIn, Crunchbase, Companies House and any Wikidata entry. This is your primary entity anchor.
Add Person schema on author pages and link it to every Article the individual has authored using the author property. Include jobTitle, worksFor (linked to your Organisation entity), sameAs to LinkedIn and any speaker profiles. This builds E-E-A-T signals for your content.
Every blog post, case study and guide should carry Article or BlogPosting schema with headline, author (linked to a Person entity), datePublished, dateModified and image. The dateModified property is important for Google to understand content freshness.
Add a Service schema block on each service page with name, description, provider (linked to your Organisation entity) and areaServed. This helps Google and AI tools understand what your business does without having to infer it from page copy.
Software tools, apps, platforms and any product where the deliverable is digital. SoftwareApplication schema enables app-specific rich results including ratings, pricing and platform support. Combined with strong Organisation and Article schema, it makes your product highly citable by AI tools comparing software options.
Include name, applicationCategory, operatingSystem, offers (with price), aggregateRating and screenshot. The applicationCategory property uses Google's defined list: BusinessApplication, FinanceApplication, EducationApplication and so on. Choose the closest match.
Global Organisation schema anchors your brand entity. Link to G2, Capterra, Crunchbase and ProductHunt profiles via sameAs. These third-party mentions reinforce your entity record across the Knowledge Graph and give AI tools more sources to reference when describing your product.
Add FAQPage schema to your pricing page, feature pages and any comparison pages. Users searching "X vs Y" and "does X do Z" queries in AI tools frequently get answers pulled from FAQ schema. This is where SaaS structured data pays off most visibly in AI search.
Add HowTo schema to your help docs, onboarding guides and tutorial content. Include step objects with name, text and image for each step. This makes your support content eligible for step-by-step rich results and increases the likelihood of it being cited in AI-generated how-to answers.
News sites, blogs, review publications, niche content sites and any site where the primary product is written content. The schema goal here is Top Stories eligibility, author credibility, and being cited accurately by AI tools. Freshness signals matter more here than in any other category.
Use Article for evergreen content and NewsArticle for timely news pieces. Always include headline, author (linked to a Person entity), datePublished, dateModified and a high-resolution image meeting Google's minimum dimensions. The dateModified field is critical for freshness scoring.
Create a dedicated author page for each contributor with Person schema including name, jobTitle, description, url, sameAs (LinkedIn, Twitter/X, personal site) and knowsAbout. Link every Article back to this entity via the author property. This is the primary E-E-A-T signal Google uses to evaluate content credibility.
If your site publishes product or service reviews with a rating, add Review schema with itemReviewed, reviewRating and author. This can produce star-rated review snippets in search results, significantly increasing click-through for review content competing in product research queries.
Add WebSite schema with a SearchAction property to indicate that your site has an internal search function. This can produce a Sitelinks Search Box in branded search results, allowing users to search your site directly from Google. Particularly valuable for content sites with large archives.
Answers written to be clear, accurate and useful whether you are reading them here or finding them quoted by an AI search tool.