Structured data
Definition
Structured data is standardized information added to web pages that helps search engines understand content more accurately. It uses a specific format, often schema markup, to label different elements such as reviews, products, events, articles, or FAQs. By applying structured data, website owners make their content machine-readable, improving how it is displayed in search results.
This data enables rich results, such as star ratings, event details, recipe previews, or product availability, which enhance visibility and click-through rates. For example, a recipe page with structured data can appear in Google’s recipe carousel with cooking time and ratings displayed, attracting more users than a plain text listing.
Advanced
Structured data is implemented using formats like JSON-LD (recommended by Google), Microdata, or RDFa. Schema.org provides the most widely accepted vocabulary for markup, covering a wide range of content types. When applied correctly, structured data does not directly increase rankings but improves how search engines interpret and present a page in SERPs.
Advanced implementations often involve mapping structured data to dynamic content systems, automating markup for large product catalogs, and validating code using tools like Google’s Rich Results Test. Structured data also plays a role in voice search and AI-driven search assistants, as it enables systems to extract precise answers from webpages. Errors or misuse, such as spammy markup, can result in penalties or loss of eligibility for rich results.
Why it matters
Use cases
Metrics
Issues
Example
An online electronics retailer adds structured data to product pages including price, availability, and customer ratings. As a result, Google displays these details in search results, making the retailer’s listings more attractive. The enhanced visibility leads to higher click-through rates and improved conversions compared to competitors without markup.