JSON-LD

What JSON-LD is

JSON-LD is one of three ways to implement Schema.org structured data on a web page — the other two being Microdata and RDFa — and it's the format Google explicitly prefers and recommends. For AEO work specifically, JSON-LD is the standard choice, and there's rarely a good reason to reach for either of the alternatives on a new build.

Why JSON-LD wins over Microdata and RDFa

Separation from HTML is the first reason. JSON-LD lives inside a single <script> block, entirely separate from the visible page markup, which means schema can be added, edited, or removed without touching the page's visual structure at all — a developer can update the schema block without risking a layout break, and a content editor changing page copy won't accidentally corrupt the schema either.

Readability is the second. JSON-LD is plain JavaScript object notation, which is straightforward to write, review, and audit. Microdata, by contrast, requires attributes scattered across individual HTML elements throughout the page, which makes it far harder to spot errors or missing fields at a glance.

Dynamic injection is the third. JSON-LD can be added to a page through JavaScript — via Google Tag Manager, for instance — without requiring a server-side code change at all, which matters for teams that need to roll out schema changes fast without waiting on a full deployment cycle.

Basic JSON-LD structure

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "LocalBusiness",
  "name": "Business Name",
  "address": {...}
}
</script>

The @context line tells a parser which vocabulary to interpret the rest of the block against — almost always https://schema.org for this kind of markup. The @type line declares which schema type applies, and everything after that is the entity's actual attribute data.

Where JSON-LD fits alongside other schema types

A single page can carry more than one JSON-LD block, or one block with multiple types combined. A clinic's location page, for example, might combine LocalBusiness schema for the entity itself with FAQPage schema for a set of common questions, or HowTo schema if the page also walks through a process. All of these live in JSON-LD; the choice of JSON-LD as the delivery format is separate from the choice of which schema type to use.

Implementation in India

For Indian businesses running WordPress, which is still the most common CMS among small and mid-size local businesses, the Yoast SEO and Rank Math plugins generate JSON-LD automatically for LocalBusiness and FAQPage schema without requiring manual code. Businesses running on Laravel — the stack Angryturtle recommends and builds on for clients who want full control — implement JSON-LD through Blade template partials instead, which gives more precise control over exactly what data appears but requires a developer to maintain it rather than a plugin.

Neither approach is wrong; the choice comes down to whether the business has developer resources on hand or is relying on a WordPress plugin ecosystem to handle it automatically.

A common validation mistake

Adding a JSON-LD block that doesn't match the actual visible content on the page — declaring a phone number in schema that differs from the one printed on the page, for instance — creates exactly the kind of mismatch Google's quality systems are built to catch. Schema should always be validated against Google's Rich Results Test and checked line by line against the visible page content before publishing, not just checked for valid JSON syntax.

Why this matters for AI citation, not just search

AI systems parsing a page for grounding purposes lean on structured data specifically because it removes ambiguity — a JSON-LD block stating a clinic's address and hours directly is far easier for a model to extract accurately than the same information buried in a paragraph of marketing copy. Clean JSON-LD is one of the more reliable, low-effort levers a business has for improving its odds of accurate AI citation.

Related terms: Schema.org → · Structured data → · LocalBusiness schema → · FAQPage schema → · HowTo schema → · Grounding →

Example: A dermatology clinic's location page carries a JSON-LD block declaring a MedicalClinic type with address, phone, and hours. Search engines and AI systems parse this block directly to extract entity data, without needing to read or interpret the page's visible paragraph content at all.

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