Validating structured data means checking that your schema is written correctly, matches the page content, and can actually be understood by search engines and AI engines. If the markup is broken, missing key fields, or saying something different from what's visible on the page, it's not helping your AEO. It's just sitting there looking important.
A lot of people add schema to a page and then move on. Sadly, that's not how it works. Even small errors can stop search engines from reading the markup correctly. And if AI engines can't trust the schema, it becomes far less useful as a signal for citations.
What validation catches
- Missing required fields that make the schema incomplete
- Broken JSON-LD syntax that stops the whole block from parsing
- Invalid schema types that don't match the page content
- Mismatches between visible content and what the schema claims
- Warnings that could weaken the page even if they're not technically fatal
Validation is how you make sure your structured data is doing the job you think it's doing.
The two tools you need
Checks whether your page is eligible for supported rich results in Google and whether Google can read the structured data properly.
- Shows detected schema items clearly
- Highlights errors and warnings in plain language
- Lets you test both the live URL and a pasted code snippet
- Especially useful for FAQ, Article, Breadcrumb, and other rich result types
The broader validation tool. Checks whether your schema follows schema.org rules, even for types beyond Google's narrow rich result support.
- Validates the schema structure itself against schema.org definitions
- Great for checking Organisation, Person, and other entity-focused markup
- Covers types and properties that Google's tool doesn't test
If you're serious about AEO, use both. Google Rich Results Test tells you what Google recognises. Schema Markup Validator tells you whether the schema itself makes sense.
What to check and in what order
1. Check that the schema is being detected at all
Paste in the live URL or the code snippet and see whether the tool finds the structured data. If it finds nothing, the code may not be on the page correctly, JavaScript may be loading it badly, or the markup may be broken at the syntax level.
2. Fix errors before warnings
Errors are the serious problems. They can stop the schema from working at all. Common errors include invalid JSON syntax, missing brackets or commas, using the wrong property for the schema type, or putting text where a URL should be. Fix these first, then address warnings.
3. Check that the schema matches the visible page
This one matters more than most people realise. If your FAQ schema says one thing and the visible FAQ says something different, that's a trust problem. If your Article schema says a page was updated yesterday but the visible page shows no sign of it, that's sloppy. Schema should support the visible content, not invent a parallel universe.
4. Check required and recommended fields
Different schema types have different expectations. Article schema usually needs a headline, author, datePublished, and publisher. FAQPage schema needs real visible questions and answers that match what's in the markup. BreadcrumbList should reflect the actual page path. Missing recommended fields don't always break the markup, but they make it weaker.
5. Always validate the live URL, not just the code snippet
Plenty of people validate a neat code sample and then forget to test the live page. Your CMS might alter the output. A plugin could strip something out. JavaScript could fail. Always test the live URL too, because the live page is what AI engines actually see.