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Why structured data is decisive for AI
AI systems are not search engines that weigh keywords. They understand content, and structured data is the machine-readable language that makes this understanding possible. Schema.org Product markup tells an AI system directly: "This is a product, it is called X, costs Y, is available, and belongs to brand Z."
Without this structure, the AI has to analyze and interpret the text, which is error-prone, slow and often incomplete.
The most important Schema.org fields for products
| Field | Meaning | Priority |
|---|---|---|
| name | Product name | Required |
| brand | Brand name | Required |
| offers.price | Price in EUR | Required |
| offers.availability | Availability | Required |
| description | Product description | Recommended |
| category | Product category | Recommended |
| additionalProperty | Technical properties | Optional |
Example: minimal Product markup
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "Product",
"name": "My Product",
"brand": {"@type": "Brand", "name": "My Brand"},
"description": "Clear, factual description.",
"offers": {
"@type": "Offer",
"price": "49.99",
"priceCurrency": "EUR",
"availability": "https://schema.org/InStock"
}
}
</script>Frequently asked questions
What is Schema.org? +
Schema.org is an open vocabulary for structured data. JSON-LD markup with @type: Product tells AI systems exactly what a product is.
Which fields are required? +
Name, brand, price, availability and description are the minimum requirements. In addition: category, SKU and properties.
How without code? +
Feed-AI generates Schema.org markup automatically from the product data you enter, no programming needed.