Genezio Logo
Technical

Structured Data for AI

Organized information formats that help AI engines better understand and represent your content. This includes schema markup, knowledge graphs, and API-accessible data.

Detailed Explanation

Structured Data for AI involves organizing your brand information in formats that AI engines can easily parse, understand, and reference. While AI models can process unstructured text, structured data provides clear, unambiguous information that reduces the risk of misinterpretation. This includes schema markup on your website (product schemas, organization schemas, FAQ schemas), knowledge graph entities (like Google Knowledge Graph or Wikidata), and API-accessible data that AI platforms can query. Structured data is particularly important for factual information like product specifications, pricing, company details, and relationships between entities. By providing structured data, you help AI engines accurately understand and represent your brand, reducing the risk of errors or omissions in AI-generated responses. It also makes your information more accessible to AI platforms that prioritize structured sources.

Examples

1

Implementing Product schema markup so AI engines can accurately extract your product features, pricing, and availability

2

Creating a comprehensive knowledge graph entry that defines your company, products, and relationships

3

Providing API access to your product catalog so AI platforms can query current, accurate information

Why It Matters

Structured Data for AI reduces ambiguity and improves accuracy in how AI engines represent your brand. It makes your information more accessible and trustworthy to AI systems, increasing the likelihood of accurate, favorable mentions in AI responses.

Want to improve your AI visibility?

Discover how your brand performs in AI conversations and get actionable insights to improve your presence across AI platforms.