Conduit Digital

Glossary

Structured Data

Last updated September 2026

Structured data is standardized code, most commonly Schema.org markup in JSON-LD format, added to a webpage to label its content explicitly for machines: this is a product, this is its price, this is a review, this is an FAQ. It is how search engines and AI systems parse a page's meaning with certainty instead of inference.

Structured data does not change what a human visitor sees. It labels the same content for machines reading the page, so a search engine can display rich results and an AI system can extract a clean fact instead of guessing from surrounding prose.

01

What structured data actually does

JSON-LD is the dominant recommended format now, replacing older approaches like microdata and RDFa in most modern implementations. The markup sits separately in the page code and describes entities, attributes, and relationships in a format search and AI systems can parse directly.

02

Common schema types agencies use

  1. 01

    Organization and LocalBusiness, for entity basics

  2. 02

    Product and Review, for ecommerce rich results

  3. 03

    FAQPage and HowTo, for question-and-answer content

  4. 04

    Article and BreadcrumbList, for content and site structure

  5. 05

    DefinedTerm, for glossary and definition content

03

Why it's foundational to AEO and GEO

An AI system extracting an answer trusts a clearly labeled fact more readily than one it has to infer from paragraph text. Structured data is the most direct lever a site controls for machine-readability, more direct than writing style or backlinks alone.

Conduit adds relevant schema as a standard part of technical SEO builds, not an optional upsell, treating it as baseline infrastructure the same way clean HTML or a sitemap is baseline.

04

A common misconception

Adding a schema plugin and calling structured data done is one of the more common half-measures agencies inherit from a previous vendor. A site can have FAQPage markup on every blog post while the actual page content buries the answer three paragraphs deep, or Organization schema listing a phone number that does not match what appears on the page itself. Structured data has to describe what is actually, visibly true on the page, not what a template auto-generates. Google and AI systems that catch a mismatch between marked-up data and on-page content do not just ignore the bad markup, they can discount the trustworthiness of the whole page's structured data going forward, which makes a sloppy implementation worse than no implementation at all. A quick audit before assuming schema is handled: pull the page into Google's Rich Results Test and confirm the markup matches the visible content field for field, not just that it validates without errors.

FAQ

Questions agencies ask

Does structured data improve rankings directly?

Google has stated it is not a direct ranking factor on its own, but it enables rich results and improves machine parsing, both of which influence click-through rate and AI citation, so the practical effect on visibility is real even if indirect.

Do I need structured data if my content already reads clearly?

Reading clearly to a human and being unambiguous to a machine parser are different problems. Structured data removes any need for a machine to infer, which matters more as AI-driven answers become a bigger share of discovery.