JSON-LD

JSON-LD stands for 'JSON for Linked Data' — a way to express structured data using JSON syntax. The defining trait is that it lives in a separate `<script type="application/ld+json">` block, untouched by the visible HTML. It exists because the older alternatives, microdata and RDFa, mixed markup into HTML attributes and were brittle to maintain. Google explicitly recommends JSON-LD as the structured-data format of choice.

Mechanically it is a clean separation between content and semantic layer. The page body stays as is; the JSON-LD block expresses the page's meaning in Schema.org vocabulary. Engines and LLMs parse the block independently and extract facts from it. When body content changes, you only need to sync the JSON-LD, which keeps maintenance tractable and lets engineering and content teams divide work cleanly.

Day to day, marketers partner with engineering to apply JSON-LD on product, article, FAQ and event pages. The lift is small relative to the upside — better odds in AI citations and richer search result coverage. Useful KPIs are rich-result coverage and AI citation rate on tagged pages. Villion auto-diagnoses JSON-LD coverage across the site and prioritises the pages where it is missing first.

Compared with the alternatives the case is open and shut. Microdata and RDFa bake markup into HTML attributes, which is fragile and hard to keep in sync with design changes. JSON-LD lives in its own block, so design refactors do not break it. That operational simplicity is exactly why Google made it the recommended format.

Two common misreads. First, treating JSON-LD as a parallel marketing surface. If the JSON-LD describes something different from what the visible page says, you hurt yourself — structured data is a faithful summary, not an extra promo channel. Second, expecting JSON-LD alone to deliver GEO results. It is infrastructure that raises eligibility; you still need the content quality and authority signals to convert that eligibility into citations.

Sensible next steps: prioritise JSON-LD on core pages (product, article, FAQ, Organization), validate with Google's Rich Results Test and the Schema Markup Validator, audit body-vs-markup alignment regularly, and measure citation accuracy on price, rating and definition fields before and after rollout. In the GEO era, JSON-LD is the layer AI consults first when extracting facts — its value is rising, not falling.