Structured Data Services (Schema)
Structured data is how you tell search engines exactly what your content means, not just what it says. Rather than relying on interpretation, you provide explicit signals using vocabulary defined by Schema.org. This enables rich results in Google and improves how AI retrieval systems understand and attribute your content.
Search engines are pattern matchers. Without structured data, they infer meaning from text, document structure, and context signals. With structured data, you provide explicit declarations: this is an organization, this is a service, this is a frequently asked question and its answer. The difference in retrieval accuracy and rich result eligibility is significant.
JSON-LD is Google’s recommended format for structured data, and the only format we implement. It lives in a script tag separate from your page content, which means it can be added, modified, and validated without touching your HTML. It is also the format most reliably parsed by AI retrieval systems alongside traditional search crawlers.
Schema types we implement
Organization and brand signals
Organization schema establishes your brand as a defined entity: legal name, URL, logo, contact information, and social profiles. This feeds the knowledge graph and makes your brand recognizable to both Google and AI systems that build entity models. For AI systems specifically, a well-defined Organization entity is one of the clearest signals that a brand is citable.
Service and product schema
Service and Product schema enables rich results including pricing, availability, and review aggregates. For service businesses, Service schema defines what you offer, where you offer it, and at what price range. For ecommerce, Product schema with AggregateRating and Offer sub-types enables the price and availability rich results that increase organic click-through rates. See our Ecommerce SEO service for platform-specific implementation.
FAQ and HowTo schema
FAQPage schema causes question-answer pairs to expand directly in Google search results, increasing the physical space your result occupies without additional ranking improvement required. HowTo schema enables step-by-step rich results for instructional content. Both also improve AI answer inclusion by providing explicitly structured question-answer pairs that RAG systems can retrieve and reuse.
Article and breadcrumb schema
Article schema signals publication date, author, and content type. BreadcrumbList schema tells search engines the hierarchical position of a page within the site structure and enables the breadcrumb display in search results. These are foundational schema types that should be present on all editorial and service pages.
All schema implementations are validated against Google’s Rich Results Test and the Schema.org validator before deployment. Invalid markup produces no benefit and can generate Search Console errors that suppress other structured data signals on the same page.
Related services
Frequently asked questions
Schema.org is a collaborative vocabulary for structured data on the web, developed by Google, Microsoft, Yahoo, and Yandex. It defines a common set of types and properties that can be used to describe entities on the web: organizations, people, products, events, articles, and more. Structured data using Schema.org vocabulary tells search engines and AI systems exactly what a piece of content represents, rather than leaving them to infer it from text.
JSON-LD is Google’s recommended format and the one we exclusively implement. It is placed in a script tag rather than embedded in HTML attributes, which makes it easier to manage, validate, and update independently of the page content. Microdata and RDFa are alternative formats that remain technically valid but are harder to maintain and less reliably parsed by modern AI systems.
Structured data does not directly improve rankings, but it does improve visibility and click-through rates through rich results, and it improves how accurately search engines and AI systems understand your content. FAQ rich results increase the physical size of your search result. Product rich results include pricing and availability information that increases click-through rates. Both indirectly affect rankings through improved user signals.
AI retrieval systems use structured data as explicit signals when building entity models and deciding what to include in generated answers. Organization schema makes your brand clearly identifiable as a distinct entity. FAQ schema provides explicitly structured question-answer pairs that RAG systems can retrieve and reuse. Article schema signals content type and authorship. Together these signals make your content more retrievable and more reliably attributed.