Schema Markup (Structured Data)

Machine-readable structured data (typically JSON-LD) added to a page so search engines and AI can reliably parse what a business, product, or article is.

Definition

Schema markup is structured data (usually schema.org vocabulary in JSON-LD) that explicitly labels a page’s entities — for local businesses, LocalBusiness schema encoding name, address, phone, hours, services, and geo. It reinforces entity understanding and GBP–website consistency: rather than inferring, the engine is told the business’s attributes. In this corpus it appears twice — as the bonus 8th consistency signal on the landing page, and as an artifact the Core30 AI Tool auto-generates per page alongside meta tags and images.

Structured data as an established SEO/web-dev best practice is established; its role in AI-search parsing is an active, growing area. This is a shared web-dev + SEO concept — a developer implementation detail that is simultaneously a ranking/entity signal. The web-dev source generalizes it beyond LocalBusiness to Organization, WebSite, BreadcrumbList, Article, and FAQPage JSON-LD (validated with Google’s Rich Results Test) as a driver of rich results and CTR (Technical SEO from Architecture) — showing the same concept from the technical-SEO side that the Caleb Ulku corpus approaches from the local-SEO side.

Key Properties

• JSON-LD LocalBusiness schema is the core local implementation (NAP, hours, geo, services).
• Declares entities explicitly — supports both classic rich results and AI parsing.
• A web-dev deliverable (template/component) that is also an SEO signal → pillar: both.
• Best paired with matching on-page content and GBP data (consistency).

Examples from Sources

In the Sources

Related

Concepts: GBP–Website Alignment (Consistency Signals), Entity-Based SEO, Core 30, GEO / AEO (Getting Recommended by AI), Technical SEO from Architecture Entities: Google, Core30 AI Tool, Next.js