What is Structured Data? — SimpleCrawl Glossary

Definition

Structured data is information organized in a predefined, machine-readable format that describes the content and meaning of a web page. It uses standardized vocabularies — most commonly Schema.org — to label content types like products, articles, recipes, events, and organizations so that search engines, AI systems, and other machines can understand the page beyond its raw HTML.

The most widely used structured data format on the web is JSON-LD (JavaScript Object Notation for Linked Data), embedded in a <script> tag within the page's HTML. Other formats include Microdata (HTML attributes) and RDFa (also attribute-based).

How Structured Data Works

Structured data bridges the gap between human-readable web pages and machine-readable information:

1. Vocabulary — Schema.org provides a shared vocabulary of "types" (like Product, Article, Person) and "properties" (like name, price, author). This standardization means all websites describe similar things in the same way.
2. Encoding — The structured data is embedded in the page's HTML using JSON-LD (most common), Microdata, or RDFa. JSON-LD is preferred because it sits in a separate <script> tag and doesn't mix with the HTML markup.
3. Consumption — Search engines (Google, Bing), social platforms (Facebook, Twitter), and AI systems read the structured data to understand page content. This powers rich search results, knowledge panels, and more.

A JSON-LD example for a product:

{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Wireless Headphones",
  "description": "Premium noise-canceling headphones",
  "price": "99.99",
  "priceCurrency": "USD",
  "brand": { "@type": "Brand", "name": "AudioTech" }
}

Google uses structured data to generate rich snippets — enhanced search results showing star ratings, prices, recipe times, FAQ answers, and other details directly in the SERP.

Structured Data in Web Scraping

Structured data is a goldmine for web scrapers because it provides clean, labeled information without the need for complex CSS selectors or fragile HTML parsing:

• Reliable extraction — Structured data follows a defined schema, making it predictable and consistent across pages. Unlike HTML layouts, structured data formats rarely change during site redesigns.
• Pre-labeled fields — Instead of writing selectors to find a product's price, name, and description scattered across the DOM, you can extract them directly from the JSON-LD with clear field names.
• Rich metadata — Structured data often includes information not visible on the page itself, such as canonical URLs, organization details, author information, and content relationships.
• Search result enrichment — Scraping structured data from search engine results pages gives you access to rich snippet data like ratings, prices, and availability.
• AI training data — Structured data provides high-quality, labeled datasets ideal for training machine learning models and populating knowledge graphs.

The combination of scraping visible page content and extracting embedded structured data gives you the most complete picture of any web page.

How SimpleCrawl Handles Structured Data

SimpleCrawl extracts and returns structured data as a first-class feature:

• Automatic JSON-LD extraction — SimpleCrawl detects and parses all JSON-LD blocks on a page, returning them as part of the API response alongside the page content.
• Schema-aware extraction — Define a target schema (e.g., Product, Article) and SimpleCrawl returns only the structured data matching that type.
• Structured output mode — Beyond extracting embedded structured data, SimpleCrawl can convert any page's content into structured JSON based on a schema you define — even when the page has no JSON-LD.
• Validation — SimpleCrawl validates extracted structured data against Schema.org specifications, flagging errors and missing required fields.
• Bulk extraction — Combine with SimpleCrawl's crawling capabilities to extract structured data from thousands of pages in a single job.

Whether you're building a product comparison engine, populating a knowledge graph, or creating training data for an LLM, SimpleCrawl makes structured data extraction effortless.

Related Terms

• HTML Parsing — Converting raw HTML into a queryable DOM tree
• Web Scraping — Automated data extraction from websites
• CSS Selectors — Patterns for targeting specific HTML elements
• RAG Pipeline — Retrieval-augmented generation for AI applications