Structured-data markup: making your catalog machine-readable.

Why it matters for AI

JSON-LD provides explicit labels for tools that consume it. It cannot make an unsupported claim reliable. Google's AI feature guidancesays no special AI schema is required. Treat markup as a maintained description of the business, alongside readable pages and source records.

The schemas product-and-quote B2B should use

• Organization. Who you are, logo, certifications, contact.
• Product / Offer. Products, attributes, and (where shown) price or price range.
• Service. The services you provide.
• FAQPage. Questions and answers that are actually visible; not a promise of a search feature or citation.
• Article. Guides and resources like this one.
• BreadcrumbList. Page hierarchy.

How to do it well

• Use JSON-LD in a <script type="application/ld+json"> block, it's the easiest to maintain.
• Mark up what's actually on the page, don't claim facts the human can't see (that breaks trust and guidelines).
• Keep it accurate and current, stale schema is worse than none.
• Validate before shipping (schema validators and rich-results testing).

Mini example (FAQ schema)

Illustrative syntax only; the lead time is fictional. Do not publish this block unless it matches an approved, visible answer on your own page.

{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [{
    "@type": "Question",
    "name": "What is your standard lead time?",
    "acceptedAnswer": { "@type": "Answer",
      "text": "10 business days for orders up to 5,000 units." }
  }]
}

Choose the type from the business fact

A defined manufactured item can be described with Product, while a machining capability may fit Service. Use Organization for the business identity and BreadcrumbList for the page hierarchy. Do not label every commercial landing page as a Product merely because it sells something.

For a quote-only item, do not invent a zero-dollar price or stock status to satisfy a validator. If a particular rich-result feature requires information you do not publish, the page may not qualify for that feature. Accurate, limited markup is preferable to a more complete but false offer.

Validate meaning as well as syntax

1. Parse the JSON and verify the selected types and properties against Schema.org.
2. Compare each attribute with the visible page and its approved source.
3. Check stable entity identifiers, canonical URLs, and referenced organization names.
4. For Google features, use the current supported structured-data documentation and Rich Results Test.
5. Recheck markup whenever the product, commercial terms, or source document changes.

A syntax check will not identify a certificate issued to a different facility or a lead time that no longer applies. Give each data source an owner. Store the review date internally, and show meaningful update dates to readers. Use the capability evidence checklist before turning copy into attributes.