Local Business Extractor (Apify Actor)

Give it any public business / venue page URL and get back clean, normalized LocalBusiness data — name, business type, contact details, full address with geo coordinates, opening hours, price range, and aggregate rating — pulled from schema.org LocalBusiness (and subtypes like Restaurant / Store) in JSON-LD and microdata. HTML-only (no headless browser) so it's fast and cheap. Ideal for local-business directories, lead lists, and store-locator / map datasets.

What it extracts

For each page it returns one flat record with:

• name, legal_name, business_type, description
• telephone, email, url, image
• Address: street_address, locality, region, postal_code, country, address_full
• Geo: latitude, longitude
• opening_hours[], price_range, founding_date, same_as[] (linked social/profile URLs)
• Ratings: rating_value, rating_best, rating_count

Plus control keys present on every row (ok and error alike, for clean buyer tables):

status, requested_url, final_url, http_status, redirected, found, complete, page_type, source, render_required, fields_found, error, extracted_at

Input

{ "startUrls": [{ "url": "https://example.com/locations/downtown" }], "maxConcurrency": 5, "maxPages": 100 }

maxPages capped at 200, maxConcurrency at 20 (cost guard).

Output — one STABLE record per URL (ok and error rows share the shape)

{
  "status": "ok",
  "requested_url": "https://example.com/locations/downtown",
  "final_url": "https://example.com/locations/downtown",
  "http_status": 200,
  "found": true,
  "complete": true,
  "page_type": "localbusiness",
  "source": "json-ld",
  "name": "Acme Coffee Downtown",
  "legal_name": "Acme Coffee LLC",
  "business_type": "CafeOrCoffeeShop",
  "description": "Specialty coffee in the heart of downtown.",
  "telephone": "+1-212-555-0100",
  "email": "hello@acmecoffee.example",
  "url": "https://acmecoffee.example",
  "image": "https://example.com/img/store.jpg",
  "street_address": "123 Main St",
  "locality": "New York",
  "region": "NY",
  "postal_code": "10001",
  "country": "US",
  "address_full": "123 Main St, New York, NY 10001, US",
  "latitude": 40.7128,
  "longitude": -74.006,
  "opening_hours": ["Mo-Fr 07:00-19:00", "Sa-Su 08:00-17:00"],
  "price_range": "$$",
  "rating_value": 4.6,
  "rating_best": 5,
  "rating_count": 312,
  "same_as": ["https://instagram.com/acmecoffee"],
  "fields_found": ["name", "telephone", "address_full", "rating_value"],
  "extracted_at": "2026-05-29T..."
}

found:false means no LocalBusiness markup was present (e.g. a JS-rendered locator widget). Failed fetches return the same keys with status:"error" + error.

Use cases

• Local-business directories — assemble structured listings (name, type, contact, hours, rating).
• Lead lists — pull public phone/email/address for businesses across a set of pages.
• Store-locator / map datasets — get geo coordinates + opening hours for mapping.

Notes / safety

• Reads only public schema.org business markup — facts-only, only contact details the page itself publicly publishes; no raw page bodies stored.
• SSRF-guarded (scheme + private/metadata IP block + redirect re-check), robots-respecting, rate-limited, cost-capped — all via the shared src/lib/actor_runner.js.
• HTML-only: client-rendered pages that inject business JSON via JS return found:false (no server-side markup to read). Core logic in src/extract.js (pure, unit-tested).

Run locally / test

npm install
npm test     # unit tests on the pure extractor (node:test)

Publish to Apify (account-holder's step)

$npm install -g apify-cli && apify login && apify push

Keep it free initially; enable pricing later via the adult account-holder once it shows repeat organic usage and clears a margin gate.