Schema Markup
Structured data code added to web pages that helps search engines and AI systems understand the content's meaning, enabling rich search results.
Schema markup is structured data added to web pages using a standardised vocabulary (schema.org) that tells search engines and AI systems what the content means, not just what it says. It transforms vague HTML into precise, machine-readable information.
Why schema markup matters
Without schema markup, a search engine sees text on a page and must guess its meaning. Is "Apple" the fruit or the company? Is "4.5" a rating, a price, or a measurement? Schema markup removes the guessing by explicitly labelling content types and their properties.
How it works
Schema markup is added to HTML using one of three formats:
- JSON-LD (recommended): A JavaScript block added to the page header. Clean, easy to implement, and does not mix with HTML content.
- Microdata: Attributes added directly to HTML elements.
- RDFa: Another inline approach, less commonly used.
Common schema types
- Organization: Company name, logo, contact information, social profiles.
- Article: Headline, author, publication date, description.
- Product: Name, price, availability, reviews, ratings.
- FAQ: Questions and answers displayed directly in search results.
- HowTo: Step-by-step instructions with images and tools.
- Event: Date, location, performer, ticket availability.
- Person: Name, job title, affiliation, image.
Schema markup and AI
Schema markup is becoming increasingly important in the age of AI search. When AI assistants like Perplexity, ChatGPT with browsing, or Google's AI Overviews synthesise information from the web, schema markup helps them extract accurate, structured data from your pages. Well-marked-up content is more likely to be cited correctly.
Business impact
- Rich search results: Schema enables enhanced search listings with star ratings, prices, FAQs, and images β increasing click-through rates by 20-30%.
- Voice search: Structured data helps voice assistants answer questions using your content.
- AI citations: As AI search grows, schema markup increases the likelihood of your content being referenced.
Implementation
Most content management systems (WordPress, Shopify) offer schema markup plugins. For custom sites, Google's Structured Data Markup Helper and schema.org documentation guide implementation. Google's Rich Results Test validates your markup.
Why This Matters
Schema markup is an underused competitive advantage in search visibility. As AI-powered search becomes the norm, structured data determines whether your content is accurately understood and cited by AI systems. Implementing schema markup now prepares your web presence for both traditional and AI-driven discovery.
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This topic is covered in our lesson: AI and Content Strategy