Schema Generator
Generate valid JSON-LD structured data for eight of the most useful schema types. Built for teams optimising for both Google rich results and AI search citation.
Fields
Generated JSON-LD
{
"@context": "https://schema.org",
"@type": "Article"
}Validation warnings
- - Missing required field: Headline
- - Missing required field: Description
- - Missing required field: Image URL
- - Missing required field: Author name
- - Missing required field: Date published
- - Missing required field: Publisher name
- - Missing required field: Article URL
What is schema markup?
Schema markup is structured data you add to a webpage so that search engines and AI models can read it as fact rather than guessing from surrounding prose. It uses a shared vocabulary maintained by Google, Microsoft, Yahoo and Yandex at Schema.org, and the modern way to write it is a format called JSON-LD that lives inside a single script tag in the head of your page.
When a crawler reads a product page with Product schema attached, it learns the price, the availability, the SKU, the brand, and the average review score without having to parse the visual layout. When a model reads an article with Article schema, it learns the author, the publication date, the headline, and the primary image. That certainty is the difference between being cited in an AI Overview with your exact title and author, and being mentioned vaguely as one of several sources.
Structured data is also one of the few optimisation levers where the benefit accrues almost immediately. Unlike backlinks, content refreshes, or authority building, schema markup is parsed on the next crawl. A technically correct FAQPage block deployed on Monday can be powering richer AI answers by Wednesday.
Why schema matters for AI search
The shift from blue links to generative answers changes what visibility looks like. You no longer win by ranking in position three; you win by being the source a model quotes when it answers a question. Schema markup is how you hand that model the facts it needs to quote you confidently.
Entity certainty
AI models use structured data to confirm what an entity is, who it belongs to, and how it relates to other entities. This is the foundation of accurate citation.
Faster comprehension
Parsing a Product schema block is instant. Parsing unstructured HTML and inferring the same facts is expensive, and models skip pages that cost too much to understand.
Citation accuracy
When ChatGPT or Perplexity names you as a source, the author, publication date, and URL they use come from structured data. Wrong schema equals wrong citations.
Generative search platforms do not invent their answers. They retrieve pages, extract the facts they need, and present those facts with attribution. Every step in that pipeline benefits from structured data. The retrieval step prefers pages that clearly declare what they are about. The extraction step trusts declared facts more than inferred ones. The attribution step depends on knowing the author, the publisher, and the publication date with certainty.
This is why ClickedOn treats schema as a first-class deliverable on every AI SEO and GEO engagement. The brands that dominate AI citation in their category are the ones whose technical foundations made it trivially easy for a model to quote them accurately. If you want to be cited, start by being easy to cite.
The 8 schema types every business should use
Schema.org defines hundreds of types, but most businesses only need a handful to cover the full surface area of their site. These are the eight we implement first on every client project, and they are the eight the generator above supports.
Article
Blog posts, news articles, and editorial content. Powers author bylines, publication dates, and article rich results.
FAQPage
Lists of questions and answers on a page. Helps AI models surface your content as direct answers to user queries.
HowTo
Step-by-step instructional content. Enables how-to rich results in Google and structured answers in AI search.
Product
Ecommerce product pages with price, availability, and review data. Drives rich product snippets in search results.
LocalBusiness
Physical business locations with address, phone, hours, and service area. Critical for local SEO and map results.
Organization
Company-level markup with logo, social profiles, and contact details. Anchors your brand entity for AI models.
Event
Conferences, webinars, and scheduled events with date, venue, and ticket information. Drives event rich results.
Recipe
Recipes with ingredients, cook time, and nutrition data. One of the most mature rich result formats in Google.
How to install schema on your website
Installing schema markup is straightforward once you have the JSON-LD generated. The specific steps depend on your platform, but the principle is the same everywhere: wrap the JSON-LD in a script tag with type application/ld+json, and make sure it renders in every page load.
Generate your JSON-LD
Use the generator above. Pick the schema type that matches your page, fill in the required fields, and watch the live preview update on the right. When the warnings clear, copy the output.
Wrap it in a script tag
Your JSON-LD needs to live inside a script element with type="application/ld+json". The generator can copy the full script tag for you with a single click. Do not put the JSON inside a regular script type="text/javascript" tag, as crawlers will not parse it.
Add it to the page
On a static HTML site, paste the script tag inside the head. On Next.js, use a script tag with dangerouslySetInnerHTML in your page component, matching the pattern ClickedOn uses on every page of this site. On WordPress, use Rank Math, Yoast, or a header injection plugin. On Shopify, paste it into the theme.liquid head section.
Validate after deploy
Run the deployed URL through the Rich Results Test and the Schema.org Validator. Fix any errors immediately. Warnings are usually safe to ignore, but you should understand each one. Recheck after any significant template change.
Monitor in Search Console
Google Search Console has a Enhancements section that tracks how many pages carry valid schema of each type, along with any errors Google has detected during crawling. Check it weekly for the first month after deployment to catch template regressions.
Frequently asked questions
What is a schema generator?
A schema generator is a tool that creates valid JSON-LD structured data markup you can paste into the head of a webpage. It takes simple form inputs and outputs the machine-readable code Google, Bing, and AI models use to understand your content. The ClickedOn Schema Generator supports the eight schema types most commonly used for rich results and AI citation.
Do I need schema markup to rank in Google AI Overviews?
Schema markup is not strictly required to appear in AI Overviews, but it is one of the strongest comprehension signals available. Google's own documentation confirms that structured data helps its AI parse entities, relationships, and facts more reliably. Pages with clean Article, FAQPage, HowTo, or Product schema are more likely to be cited in generative answers than equivalent pages without it.
Which schema type should I use for my page?
Match the schema to the primary content type. A blog post uses Article. A services page with questions at the bottom uses FAQPage. A step-by-step guide uses HowTo. An ecommerce product page uses Product with Offer. A physical business location uses LocalBusiness. A company home page uses Organization. Pages can carry more than one schema block when the content genuinely fits multiple types.
Where do I put the JSON-LD code on my website?
Paste the generated JSON-LD inside a script tag with type application/ld+json, and place that script tag in the head or the body of the HTML. Google recommends the head for static pages and the body for content injected by JavaScript. On Next.js and React sites, use a script tag with dangerouslySetInnerHTML. On WordPress, use a plugin like Rank Math or paste it into a code injection field in your theme.
How do I validate my schema after generating it?
Use Google's Rich Results Test at search.google.com/test/rich-results or the Schema.org Validator at validator.schema.org. Both tools parse your JSON-LD and flag missing required properties, formatting errors, and enhancements that will unlock rich results. The Schema Generator also includes a built-in validation step that warns you about missing required fields before you copy the output.
Is schema markup a Google ranking factor?
Google has publicly stated that structured data is not a direct ranking factor, but it is a comprehension signal that enables rich results, and rich results measurably improve click-through rates. AI search platforms including ChatGPT, Perplexity, and Gemini also weigh structured data when deciding which sources to cite in their answers. The practical effect on visibility is significant even though the vocabulary Google uses avoids the word ranking.
Can one page have more than one schema type?
Yes. A single page commonly has Organization schema from the sitewide header, BreadcrumbList from the navigation, Article or Product schema for the primary content, and FAQPage schema for the FAQ section at the bottom. Each schema should be in its own script tag with type application/ld+json. Google and AI platforms will merge them into a single understanding of the page.
What is the difference between Schema.org and JSON-LD?
Schema.org is the shared vocabulary maintained by Google, Microsoft, Yahoo and Yandex that defines entities like Article, Product, Event and their properties. JSON-LD is one of three syntaxes for writing Schema.org markup; the other two are Microdata and RDFa. Google recommends JSON-LD because it lives in a single script tag in the head rather than being woven through the HTML. Our generator outputs JSON-LD exclusively.
Why does my FAQ schema not show rich results in Google?
Google significantly narrowed FAQ rich result eligibility in August 2023, and today only well-known authoritative sites and government health sources receive them. FAQPage schema is still valuable for AI citation, voice search, and future rich result changes, so keep it in place. The effort required is low and the markup continues to help AI models answer questions sourced from your pages.
Do I need a separate Organization schema on every page?
You only need a single Organization schema, and it should live on the home page or in a sitewide header injection. Every other page should reference the Organization via an @id pointer rather than duplicating the full schema. This keeps the data consistent and avoids confusing search engines with conflicting properties. Our Schema Generator outputs a standalone Organization block suited to a home page or about page.
Will structured data help me get cited in ChatGPT?
Schema markup is not a direct input to ChatGPT, but it dramatically improves the quality of the entity extraction pipeline that crawls and indexes web content for training and retrieval. Clean Article, Organization, and Person schemas mean the model receives accurate author, publication date, and source information. Pages with strong structured data are therefore more likely to be retrieved and cited when ChatGPT browses the web during a conversation.
Is this schema generator free?
Yes. The ClickedOn Schema Generator is completely free, with no sign up, no usage limits, and no watermark on the output. We built it because we needed a better tool for our own clients and decided to make it public. If you want full schema implementation across a large site, our SEO and GEO services deliver technical markup rollouts alongside strategy, content, and measurement.
Keep going
Schema is one piece of the AI search puzzle. Pair it with the rest of the ClickedOn AI SEO toolkit.
Need schema rolled out across your whole site?
We implement comprehensive JSON-LD markup as part of every SEO and GEO engagement, tied to measurable AI citation and search visibility gains.