What Is Schema Markup?
Schema markup is a structured data vocabulary from schema.org that adds semantic meaning to your HTML. It is invisible to human visitors but tells AI exactly what each piece of content represents.
Organization schema identifies who you are. FAQPage schema marks verified questions and answers. Product schema includes GTINs, pricing, and reviews. Without schema, AI has to guess what your content means. A product name might be confused with a category label. A price might be mistaken for a model number. A testimonial might be read as editorial content. Schema removes that ambiguity entirely.
Why It Matters
- ChatGPT Shopping pulls product data from schema markup and Google Merchant Center. Without Product schema with GTINs and prices, your products are invisible to AI shopping. No schema means no shopping results, no matter how good your product pages are.
- Google AI Overviews heavily favor pages with schema. AI Overviews are appearing in 15%+ of searches and growing. Proper schema dramatically increases your chances of being featured in these results.
- Schema eliminates ambiguity. Without it, AI might confuse your product with a competitor's similarly named product. Schema makes the distinction explicit and machine-readable.
- AI models assign higher confidence scores to recommendations backed by structured data. When your information is schema-marked, AI can verify facts programmatically instead of inferring them from unstructured text. Your brand gets recommended with stronger language.
Our Process
- Schema Audit. We scan your existing website for current markup. Most sites have no schema, outdated schema, or incorrectly implemented schema. We document every gap and error so nothing gets missed during implementation.
- Organization Schema. We implement your company name, legal name, founding date, founders, address, contact points, social profiles, logo, and sameAs links connecting your profiles across the web. This tells AI exactly who you are and connects all your online presence into a single verified entity.
- FAQPage Schema. Every FAQ section on your site gets proper FAQPage markup. This tells AI "these are verified Q&A pairs," not just body text. AI heavily favors FAQ schema when looking for answers to user questions, making this one of the highest-impact schema types for AEO.
- Product/Service Schema. We implement detailed Product or Service markup with GTINs, pricing, availability, aggregate ratings, and review counts. This is critical for ChatGPT Shopping visibility. Without Product schema containing GTINs, your products cannot appear in AI shopping results.
- ItemList Schema. For comparison pages and catalogs, we add ItemList schema that explicitly ranks and orders your offerings. Structured ordering influences how AI presents your products when users ask comparison questions.
- Validation and Testing. All schema is validated using Google Rich Results Test and Schema.org validators. We then test your pages against real AI queries across multiple platforms to confirm they are correctly interpreting the markup. You get a full validation report.
What You Get
- Complete schema audit identifying gaps in your current implementation
- Organization schema connecting all your online profiles into a single verified entity
- FAQPage schema on every FAQ section across your site
- Product/Service schema with GTINs, pricing, and review data for ChatGPT Shopping visibility
- ItemList schema for comparison and catalog pages
- Validation report confirming all schema passes Google and schema.org tests
- Documentation for your team to maintain schema as content changes
Real-World Example
An e-commerce brand had 500 product pages but zero products appearing in ChatGPT Shopping results. Their schema was limited to basic Organization markup added years ago by a theme plugin.
We implemented Product schema with GTINs, pricing, availability, and AggregateRating on all product pages, plus FAQPage schema on their 30 FAQ entries. Within 5 weeks, 47 products were appearing in ChatGPT Shopping with star ratings and pricing. Their AI-referred revenue went from $0 to $18,000/month.
How This Connects
Schema Markup adds machine-readable meaning to the content you built in Layer 2 (Answer Hub) and Layer 3 (Brand Facts). The FAQ schema on your Answer Hub tells AI that those Q&A pairs are verified, not just body text. Product schema powers Layer 7 (AI Shopping). Organization schema ties everything together by telling AI that all these pages belong to the same verified entity.
Previous: Layer 4: Machine-Readable Data
Next: Layer 6: Third-Party Citation Building
Frequently Asked Questions
What types of schema markup matter most for AEO?
The four most impactful types are Organization (identifies who you are), FAQPage (marks verified Q&A), Product (enables AI shopping with GTINs and pricing), and ItemList (structures ranked lists and comparisons). Most businesses need all four to maximize AI visibility.
Does my website already have schema markup?
Many websites have basic schema added by CMS themes or plugins, but it is often incomplete or outdated. Common issues include missing FAQPage schema, Product schema without GTINs, and Organization schema with incomplete sameAs links. We audit your existing schema and fill the gaps.
Will schema markup affect how my website looks?
No. Schema markup is invisible to human visitors. It is embedded in your HTML source code and only read by search engines and AI models. Your website looks and functions exactly the same. The only visible change is improved AI recommendations and potentially richer search results.
What are GTINs and why do I need them for schema?
GTINs (Global Trade Item Numbers) are universal product identifiers like UPC or EAN codes. ChatGPT Shopping and Google Shopping require GTINs to match products across sources. Without GTINs in your Product schema, your products cannot appear in AI shopping results. If you sell physical products, GTINs are non-negotiable.
How do I know if my schema is working?
We validate all schema using Google's Rich Results Test and the Schema.org validator. Beyond validation, we test your pages against real AI queries to confirm platforms are correctly interpreting the markup. We provide a validation report and recommend re-testing quarterly.