Structured Data & Schema for AI

Q: Why does structured data matter for AI models?

Schema markup helps AI models parse relationships (who, what, where, when) with less ambiguity. It makes your content more machine-readable, allowing LLMs to accurately extract and cite your information.

Q: Which schema types are most valuable for AI visibility?

The most valuable schema types are FAQPage/QAPage, Article/NewsArticle, Product, Organization, and HowTo. These directly map to common user queries and AI answer formats.

Q: How do I implement structured data?

Use JSON-LD format placed in your page's or . Validate with Google's Rich Results Test. Optiview automatically checks for syntax, completeness, and relevance to your core topics.

Why does structured data matter for AI models?

Structured data (schema markup) helps AI models parse relationships with precision.

When you add schema, you're explicitly telling machines:

Who wrote or published the content (Organization, Person)
What the content is about (Article, Product, FAQ)
Where things are located (Place, LocalBusiness)
When events occur or content was published (datePublished, Event)
How to do something (HowTo steps)

Without schema, AI models must guess these relationships from unstructured HTML. With it, they can extract and cite your information with confidence.

Real impact: Sites with comprehensive schema markup get cited 2-3x more frequently in our tests, particularly for factual queries where accuracy matters.

Which schema types are most valuable for AI visibility?

Not all schema types are equally valuable. Focus on these high-impact types first:

1. FAQPage / QAPage

Impact: VERY HIGH — Directly maps to how users query AI assistants

Use when: Your page answers specific questions. AI models heavily favor Q&A formatted content for citation.

2. Organization

Impact: HIGH — Establishes brand authority and trust signals

Use when: Describing your company. Include logo, social profiles (sameAs), and official name. Essential for entity recognition.

3. Article / NewsArticle

Impact: HIGH — Helps AI identify authoritative content

Use when: Publishing blog posts, guides, or news. Include author, datePublished, and headline.

4. Product

Impact: HIGH — Critical for e-commerce and product recommendations

Use when: Selling products. Include offers, reviews, and aggregateRating for maximum visibility in AI shopping recommendations.

5. HowTo

Impact: MEDIUM-HIGH — Excellent for procedural content

Use when: Providing step-by-step instructions. AI models cite HowTo schema when users ask "how to" questions.

Pro tip: Combine multiple schemas on the same page using @graph. Example: An article page can have both Article and Organization schema.

How do I implement structured data?

Use JSON-LD format (not Microdata or RDFa). It's what AI models prefer and what Google recommends.

Where to place it: In your page's <head> or anywhere in the <body>:

{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is AI Visibility?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "AI Visibility refers to how often and how accurately AI systems reference your brand, products, or content when generating answers for users."
      }
    }
  ]
}

Validation: Use Google's Rich Results Test to check syntax and completeness.

What Optiview checks:

Presence of schema on each page
JSON-LD syntax validity
Schema completeness (all required fields)
Relevance to page content
Entity graph connections (Organization → Product → Review)

Can I use AI-generated schema?

Yes, but verify carefully. LLMs like ChatGPT can generate schema quickly, but they often make subtle errors:

Wrong property nesting (e.g., putting author at the wrong level)
Missing required fields
Using deprecated properties
Inconsistent URLs (mixing http/https or www/non-www)

Best practice: Generate with AI, then validate with Google's tool and test in Optiview before deploying site-wide.

Example: Organization Schema

This is the single most important schema for establishing brand authority:

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Optiview",
  "url": "https://optiview.ai",
  "logo": "https://optiview.ai/logo.png",
  "description": "AI Visibility intelligence platform",
  "sameAs": [
    "https://twitter.com/optiview",
    "https://linkedin.com/company/optiview"
  ],
  "contactPoint": {
    "@type": "ContactPoint",
    "contactType": "customer support",
    "url": "https://optiview.ai/contact"
  }
}

Why this matters: The sameAs array links your brand across platforms, helping AI models understand you're the same entity mentioned in social media, news, etc.

Common mistakes to avoid

Mixing schema formats: Don't use JSON-LD, Microdata, and RDFa on the same page. Stick to JSON-LD only.
Duplicate schemas: Don't add the same schema type twice (e.g., two Organization schemas). Use @graph if you need multiple.
Missing required fields: Each schema type has required properties. Check schema.org for the official spec.
Schema-content mismatch: Don't add FAQ schema if there are no FAQs on the page. AI models penalize misleading markup.
Not updating schema: If you change a product name or company logo, update your schema too. Stale data confuses AI models.

Structured Data & Schema