LinkedIn Company Scraper — Exact Employee Count & Firmographics

Scrape LinkedIn public company pages for exact employee counts (not buckets), company type, size range, specialties, tagline, industry, full headquarters address, company description, website, founded year, funding rounds + investors, logo, and featured employee IDs. Optionally enrich featured employees with full person profiles.

No login required. No cookies. Scrapes only public data.

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What it does

For each LinkedIn company slug or URL you provide, the actor:

1. Fetches the public company home page (/company/{slug}/) — the only LinkedIn surface that is not auth-walled.
2. Parses the Organization node from <script type="application/ld+json"> for core firmographics (exact employee count, industry, HQ, website, founded year).
3. Reads the public about-us overview card for company type, size range, specialties, tagline, and funding history (rounds, last amount/date, investors, Crunchbase link).
4. Extracts featured employee public-profile IDs from trk=org-employees links.
5. Optionally enriches featured employees via a managed proxy (the enrichEmployees mode).
6. Outputs one flat row per company, charged as a single PPE event.

Auth-walled surfaces (NOT scraped)

• /company/{slug}/about/ → redirects to login
• /company/{slug}/people/ → redirects to login

Only the home page is public. This is documented to set accurate expectations.

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Edge: EXACT employee count

Every other LinkedIn company scraper returns employee buckets ("1001–5000") from the UI text. This actor reads numberOfEmployees.value from the structured Organization ld+json, which LinkedIn embeds with the exact integer (e.g. 231732).

The output field employee_count_source is labeled "ldjson_exact" so buyers know they are getting the real figure, not a range.

Competitors tested return the bucket string, wrong member counts, or null.

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Input

Field	Type	Description
companies	array	Slugs ("microsoft"), full /company/ URLs, or numeric IDs.
maxCompanies	integer	Max companies to scrape. 0 = all.
enrichEmployees	boolean	Enrich 1–4 featured employees with full profile data (default: false).
proxyConfiguration	object	Proxy settings. Defaults to Apify Residential (buyer-paid).

Example input:

{
  "companies": ["microsoft", "stripe", "openai", "https://www.linkedin.com/company/anthropic/"],
  "enrichEmployees": false
}

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Output schema (one row per company)

Field	Type	Notes
company_name	string	From ld+json
slug	string	Normalized slug
linkedin_url	string	Full company URL
tagline	string|null	Short company tagline (about-us card / og:description)
description	string	Company description
industry	string|null	Opportunistic HTML extraction
company_type	string|null	e.g. "Public Company", "Privately Held" (about-us card)
company_size	string|null	Employee range, e.g. "5,001-10,000 employees" (about-us card)
employee_count	integer|null	Exact count from ld+json (our edge)
employee_count_source	string|null	"ldjson_exact" or null
specialties	array	Company specialties / focus areas (about-us card)
website	string|null	Company website (decoded from the LinkedIn redirect)
hq_address	string|null	Flat formatted HQ address
hq	object	Structured: street, city, region, postal, country
logo_url	string|null	LinkedIn CDN logo URL
follower_count	integer|null	Extracted from page HTML
funding	object|null	Funding history: total rounds, last round type/date/amount, investors, Crunchbase URL
featured_employee_ids	array	Public profile IDs (1–4 per company)
featured_employees	array	Enriched person dicts (when enrichEmployees=true)
founded_year	integer|null	Opportunistic HTML extraction
scraped_at	string	ISO-8601 UTC timestamp
parse_source	string	"ldjson" or "html_fallback"
parse_confidence	float	0.0–1.0 quality signal
warnings	array	Machine-readable parse warnings

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enrichEmployees mode (hybrid)

When enrichEmployees: true, for each company the actor takes the featured_employee_ids (1–4 employees featured on the company home page) and fetches each profile via a managed proxy.

Each enriched employee includes:

{
  "full_name": "Reid Hoffman",
  "headline": "Co-Founder, LinkedIn...",
  "location": "United States, US",
  "current_title": "Co-Founder, Board Chair",
  "current_company": "Manas AI",
  "profile_url": "https://www.linkedin.com/in/reidhoffman",
  "photo_url": "https://media.licdn.com/...",
  "followers": 2767834
}

Honest limitation: This enriches only the 1–4 publicly-featured employees shown on the company home page — not the full roster. The full /people/ list requires authentication and is not accessible. Billing remains 1 charge per company (employees are embedded in the row, not separate rows).

Proxy infrastructure is handled automatically via your Apify Proxy configuration — no external credentials required.

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Proxy note

LinkedIn requires residential IPs — datacenter IPs typically receive HTTP 999 or a login redirect. The actor uses Apify Residential proxy (billed to your Apify account) by default, which provides the residential IP rotation LinkedIn expects. Configure via the proxyConfiguration input.

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parse_confidence

Every row includes a parse_confidence float (0.0–1.0). Values below 0.7 indicate structural drift — LinkedIn changed the page layout and the parser may have fallen back to HTML heuristics. Acts as an early warning system; watch it in aggregate across runs.

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Pricing

$0.00205 per company record ($2.05 / 1 000 companies). Pay only for the rows you get.

Scraping 1,000 companies costs approximately $2.05 in actor fees. Residential proxy usage is billed by Apify to your own account on top (typically a fraction of a cent per company). This undercuts the niche leader (≈$4 / 1 000 companies) while returning a richer flat row: exact-count integer (vs competitors' bucket strings), company type, size range, specialties, tagline, funding history, a structured hq object, parse_confidence, and optional featured-employee enrichment.

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Integrations

Built for sales and market-intelligence teams enriching firmographics with exact employee counts and company details from LinkedIn — the JSON/dataset output drops into the tools you already run, no glue code:

• n8n / Make / Zapier — trigger a run or pipe every new dataset item into 500+ apps (Google Sheets, Airtable, Slack, HubSpot, your database) with no code: n8n, Make, Zapier.
• Webhooks — fire your own endpoint the moment a run finishes, to push results straight into your pipeline (docs).
• MCP server — expose this actor as a tool to Claude, Cursor, or any MCP client so an AI agent can pull this data mid-conversation (guide).
• API & SDKs — fetch the dataset as JSON, CSV, or Excel through the Apify REST API or the Python / JS SDKs.

See all Apify integrations.

Legal

Scrapes public company pages only — no login, no authentication, no data behind a paywall. LinkedIn company pages are publicly accessible to any web browser.

Not affiliated with, endorsed by, or officially connected to LinkedIn Corporation.

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Competitors

Actor	Stars	Employee count	parse_confidence	Enrich
harvestapi/linkedin-company	4.7★	Bucket string	No	No
This actor	—	Exact integer	Yes	Yes (1–4)