Glossary · workflow

Schema Markup (Structured Data)

Written by Luke Marinovic, Founder of UnderCurrent Automations · Melbourne

Published 13 May 2026 · Updated 13 May 2026

Schema markup is a shared vocabulary that tells search engines and AI tools what each element on a page is, not how to display it, but what it means, so the engine can extract clean facts, trigger rich results, and cite the page accurately.

Across UC's 146-article Australian corpus audit, 15% of audited sites shipped no JSON-LD schema at all, and among the rest only 24% included FAQPage and 9% LocalBusiness, the two types AI engines lift from most cleanly.

HTML tells a browser how to render. Schema tells the machine what it's looking at. A block of text that reads "Melbourne, VIC 3000" looks the same in HTML whether it's a postal address, a review location, or a line of body copy. Add an addressLocality property from the schema.org vocabulary and the ambiguity disappears. Schema.org was launched in 2011 by Google, Microsoft (Bing), Yahoo and Yandex as a shared standard: "a collection of shared vocabularies webmasters can use to mark up their pages in ways that can be understood by the major search engines." The formats are Microdata, RDFa, and JSON-LD. JSON-LD is the one Google recommends and the one you'll see in any modern implementation, a script block in the page head, separate from the HTML, clean to read and easy to validate.

Google's structured data documentation describes two uses: rich results (star ratings, FAQ dropdowns, sitelinks, breadcrumbs shown directly in search) and entity understanding (the machine building a confident model of what your business is, where it operates, and what it offers). Both matter, but entity understanding is the one that compounds. A Brisbane plumber's LocalBusiness block with a consistent name, address and phone, an Organization block with logo and sameAs links to LinkedIn and Google Business Profile, and a Service block naming the actual trades, these form a machine-readable identity card that every engine, including ChatGPT and Perplexity, can read and trust.

The visibility impact is real. According to Sixth City Marketing's schema research, pages with schema markup can see 20–40% higher click-through rates through rich results. That gap comes down to real estate, a FAQ dropdown or star rating dominates a plain blue link in the SERP.

The FAQ Schema type is one of the highest-leverage implementations for a service business: question-and-answer blocks marked up and ready for extraction by answer engines and AI Overviews. Schema implementation is a standard part of the technical layer we build in SEO & AI Visibility, because a page without it is harder for every engine to read cleanly, whether that engine is Googlebot or a language model compiling a citation list.

Frequently asked questions

Is schema markup the same as SEO?

Schema is one tool inside the SEO toolbox, not the whole thing. It helps search engines and AI tools understand what your content means, which improves eligibility for rich results and AI citations. But the page still needs to rank, be crawlable, and have genuine authority on the topic for schema to pay off.

Which schema types matter most for a service business?

LocalBusiness and Organization establish who you are and where you operate. Service describes what you offer. FAQPage marks up your question-and-answer blocks so they're eligible for rich results and AI extraction. BreadcrumbList signals your site structure. Those five do the most work for a typical service-business page.

Do AI engines actually use schema?

Yes. ChatGPT, Perplexity and Claude all parse structured data when it's present, using it to confirm entity identity, understand page type, and extract clean facts for citations. A page with a well-formed Organization block and consistent name, address and phone data is more likely to be cited accurately than a page where that information lives only in prose.

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