Structured Data Extractor

Structured Data Extractor pulls schema.org JSON-LD and Open Graph data from any web page: organisation details (legal name, VAT ID, address, phone, email, social profiles) and products (name, SKU, GTIN, brand, price, availability, rating).

Best for: Merchant onboarding, product catalogue enrichment, price checks and SEO audits of structured data markup.

How to extract JSON-LD and schema.org data

1. Add page URLs to Page URLs (startUrls).
2. Turn on Include raw JSON-LD if you want the original blocks too.
3. Click Start and download organisation and product data per page.

How it works

Fetches each page with one normal HTTP GET (no JavaScript rendering, no crawling) and parses application/ld+json blocks (including @graph), Product and ProductGroup objects and Open Graph meta tags. Structured data is published by sites specifically for machines to read. Unreachable pages or bad URLs return ok: false and are not charged.

Output

url, pageTitle, schemaTypes, organization, productCount, products, openGraph, ok

Pricing (pay-per-event)

• page-extracted: $0.001 per result ($1 / 1,000). Platform usage is included; you pay only for results.
• Example: 10,000 pages cost $10.00.

Example input

{
  "startUrls": [
    {
      "url": "https://www.allbirds.co.uk/products/mens-tree-runners"
    },
    {
      "url": "https://www.apple.com/uk/"
    }
  ]
}

Example output

Values below are illustrative.

{
  "url": "https://www.apple.com/uk/",
  "pageTitle": "Apple (United Kingdom)",
  "schemaTypes": [
    "Organization",
    "WebSite"
  ],
  "organization": {
    "name": "Apple",
    "url": "https://www.apple.com/"
  },
  "productCount": 0,
  "products": [],
  "openGraph": {
    "title": "Apple (United Kingdom)"
  },
  "ok": true
}

Use it via API, schedules and integrations

Run it in Apify Console, or call it from your own code with the Apify API or the Python and JavaScript clients. Save an input as a task and add a schedule to run it regularly, and send results to Slack, email, webhooks, Zapier, Make or n8n with Apify integrations. AI agents can find and run it through the Apify MCP server.

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("sterlingverify/schema-org-extractor").call(run_input={"startUrls": [{"url": "https://www.apple.com/uk/"}]})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

FAQ

Does it render JavaScript or crawl sites?

No. It makes one normal HTTP GET per page and parses the markup the site publishes.

What if a page has no structured data?

You get the page with empty fields. Unreachable pages or bad URLs return ok: false and are not charged.

Disclaimer

Only data the site itself publishes in its markup is returned, so it can be missing or out of date. Respect each site's terms and robots rules and don't use it for high-volume scraping. Not affiliated with schema.org.

Related sterlingVerify tools

Part of the sterlingVerify UK payments, KYB and data toolkit on Apify Store:

• Payments Stack Detector: find which PSPs, wallets and BNPL a store uses
• Merchant Website Compliance Checker for Onboarding: onboarding review of a merchant's website
• SSL Certificate Expiry Monitor: bulk SSL certificate expiry checks and alerts