What is Structured Data?

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Structured data is a standardized format for labeling the content on a web page so search engines and AI systems can understand exactly what each piece of information means — that a number is a price, a string is a product name, a figure is a rating. Instead of leaving machines to guess from raw text, structured data explicitly tags it, using a shared vocabulary (most commonly Schema.org markup) written in a format like JSON-LD.

The point of structured data is machine readability. A page might clearly show a product, its price, stock status, and reviews to a human, but a search engine sees mostly undifferentiated text. Structured data removes the ambiguity — it tells Google “this is a Product, this is its Offer, this is its AggregateRating” — so the content can be indexed precisely and reused in richer ways.

Structured data unlocks two things in particular:

• Rich results — enhanced listings in Google (star ratings, prices, FAQs, breadcrumbs) that stand out and lift click-through
• AI citation — AI Overviews and assistants rely on structured identifiers to cross-reference and quote content accurately, so complete markup is now an AI-visibility play, not just a rich-results one

Common ecommerce schema types include Product, Offer, and AggregateRating on product pages, BreadcrumbList site-wide, and FAQPage on pages with genuine questions (Google tightened eligibility, so only use it for real Q&A). On Magento (Adobe Commerce), native Product schema often ships incomplete — missing GTIN, MPN, brand, or attached ratings — which is exactly the data AI engines use to identify products. Completing it is a high-value, and often overlooked, part of technical SEO and AI-search optimization.