What is Structured Data?
Definition
Structured data is information organized into an explicit format with defined fields and relationships. On websites, it can describe entities and page content in machine-readable forms such as JSON-LD using Schema.org.
How does Structured Data work?
Structured data replaces ambiguous free text with named fields and predictable relationships. A page might state a company name in a paragraph while also expressing it as the name property of an Organization.
A consuming system can parse those fields without inferring every relationship from prose. Websites commonly use Schema.org, but databases, feeds, and APIs also contain structured data that is not Schema.org markup.
- A vocabulary defines the meaning of available types and properties.
- A serialization determines how those values appear in code.
- A consumer decides which supported fields it actually uses.
Why does Structured Data matter for B2B SaaS?
SaaS purchasing involves distinguishing products, businesses, integrations, and documentation. Structured data can make relevant distinctions more explicit for compatible search systems.
It also encourages consistent facts across templates, such as an organization’s preferred name and official URL. Google requires applicable policies and feature requirements for supported search treatments.
Adding fields does not create expertise, establish independent reputation, or make a weak comparison page authoritative.
- Align company facts across the homepage and supporting pages.
- Keep product descriptions separate from organization identity.
- Treat eligibility for search features as different from actual display.
What is an example of Structured Data?
A documentation article can include an Article object with a headline, author, and publisher. Its publisher can reference the organization described elsewhere on the site.
The visible article should identify those same facts so readers can verify them. Another example is a customer-facing API response, although that response is not automatically a search enhancement simply because it is structured.
- Use real authors rather than invented expert identities.
- Update dates only when the underlying content justifies them.
- Connect related objects through stable identifiers where appropriate.
How do you improve or measure Structured Data?
Start with a clear purpose for each object and property. Validate syntax, vocabulary usage, and any applicable search feature requirements as distinct checks.
Inspect production HTML because a correct source template can still output broken markup. Search Console can report supported enhancements, but it does not report every Schema.org type. Evaluate business outcomes separately from the count of valid structured data items.
- Test representative URLs from each content template.
- Check whether structured facts match visible and current information.
- Document ownership so releases do not silently remove important objects.
Frequently asked questions about Structured Data
Is all JSON structured data useful for Google?
No. Google supports specific formats, types, and features. An arbitrary JSON object does not automatically qualify a page for a search enhancement.
Does structured data replace good writing?
No. It complements visible content rather than replacing it. Readers and search systems still need accessible, accurate explanations of the underlying subject.
Can valid structured data still be ignored?
Yes. Valid syntax is only one requirement. A consumer can ignore unsupported properties, and search systems do not guarantee display even for eligible pages.