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"), /company/, /school/ or /showcase/ URLs (any country subdomain), or plain company names / website domains (matched to a LinkedIn slug; check linkedin_url and the resolved_from_input: row warning).
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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When a company returns no row

You are charged only for rows that are delivered. Inputs that return no row are reported, never dropped silently:

• Not found — LinkedIn has no public page for that slug/name (confirmed on two separate sessions). Listed in the run log (NOT FOUND ...), in the run status message, and in the OUTPUT record under notFound / results with a hint.
• Temporarily unreachable — LinkedIn blocked or the proxy failed on every retry. Each company is retried on fresh proxy sessions first. If a run delivers nothing because of this it ends as Failed with a message (not as an empty Succeeded run); re-run those inputs.
• Not a company page / numeric id — e.g. a person profile URL, or a numeric company id (LinkedIn only shows those after login; use the slug). Listed in OUTPUT.results with status: invalid_input.

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)

Rate this Actor

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Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as USAGE_STATS in your own Apify key-value store, so you can see the exact record created for your run.

Set disableUsageStats to true in the input to opt out. Nothing is sent then; your USAGE_STATS record only says that statistics were disabled.

Only these fields are recorded:

• schema version, Actor name and build number;
• UTC start and finish hour (not a precise timestamp);
• run duration, number of results and time to the first result, each as a coarse range;
• whether the result was empty, the end status, and an error type from a fixed list;
• memory setting and counts of charged events;
• names of the input fields you set, never their values;
• the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same disableUsageStats: true input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

• the result limit you asked for (a range, when the input has one) and what share of it was delivered;
• results delivered per input item you listed (a range);
• output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
• how the run was started (console, API, schedule, webhook, another Actor);
• how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
• if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
• a short code made from the names of the input fields you set, never their values.

Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and disableUsageStats: true turns it off.