LinkedIn Company Lookup

Paste a list of LinkedIn companies. Get back structured JSON.

Followers, employee count, headquarters, industries, recent posts, similar companies, alumni insights — one record per company, ready to drop into a CRM, a dataset, or your own analysis.

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⚡ Why use this actor?

• Just paste — any format works. Full URLs, bare slugs, locale subdomains (uk.linkedin.com), /about and /jobs paths — all normalized for you. Mix them freely in one run.
• Batch-friendly. Up to 5 companies per run; lookups run in parallel.
• Failure-tolerant. One bad URL doesn't kill the run. Failed rows include an _error object with a machine-readable error_type so you can retry surgically.
• Honest about coverage. See the Data coverage section below — every field comes with a real fill-rate percentage so you know exactly what to expect before you spend a credit.
• Pay only for what works. You're billed per successful company; invalid URLs cost a fraction of a successful lookup, and server / network errors are free. See Pricing.

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🚀 Quick start

{ "slugs": ["openai", "anthropicresearch", "stripe"] }

That's it. You get one record per company in the dataset.

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📋 Input parameters

You must provide at least one of urls or slugs. They can be mixed. Up to 5 identifiers per run (combined across urls and slugs).

Parameter	Type	Description
urls	Array	Full LinkedIn company URLs, e.g. https://www.linkedin.com/company/ibm. Locale subdomains and trailing paths (/about, /jobs) are stripped.
slugs	Array	Just the slug, e.g. ibm, microsoft, openai. Pattern: ^[A-Za-z0-9._\-]+$.

Mixed input example

{
  "urls": [
    "https://www.linkedin.com/company/ibm",
    "https://uk.linkedin.com/company/microsoft/about/"
  ],
  "slugs": ["openai", "anthropicresearch"]
}

The two URLs above both normalize to canonical form, and any duplicates are removed automatically.

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📤 What you get back

One record per input company in the actor's default dataset. Each record carries the full LinkedIn profile shape (see the Dataset Schema tab for every field) plus two helper fields:

Field	Description
_input_url	The exact URL the actor sent for this row. Use it to correlate dataset rows back to your input list.
_error	Present only when the lookup failed. Inspect kind, status, and body to retry.

Successful record (truncated)

{
  "_input_url": "https://www.linkedin.com/company/ibm",
  "id": "ibm",
  "company_id": "1009",
  "name": "IBM",
  "url": "https://www.linkedin.com/company/ibm",
  "website": "https://www.ibm.com",
  "website_simplified": "ibm.com",
  "logo": "https://media.licdn.com/dms/image/...",
  "country_code": "US",
  "country_codes_array": ["US"],
  "headquarters": "Armonk, New York",
  "company_size": "10,001+ employees",
  "employees_in_linkedin": 421337,
  "followers": 19248301,
  "industries": "IT Services and IT Consulting",
  "organization_type": "Public Company",
  "founded": "1911",
  "specialties": "Cloud, Mobile, Cognitive, Security, ...",
  "about": "At IBM, we do more than work. We create...",
  "employees": [
    {"title": "Arvind Krishna", "subtitle": "Chairman and CEO at IBM", "link": "https://www.linkedin.com/in/...", "img": "..."}
  ],
  "similar": [
    {"title": "Microsoft", "subtitle": "Software Development", "location": "Redmond, WA", "Links": "https://www.linkedin.com/company/microsoft"}
  ],
  "updates": [
    {"title": "...", "text": "...", "post_url": "...", "likes_count": 1842, "comments_count": 73}
  ]
}

Failed record

{
  "_input_url": "https://www.linkedin.com/company/this-doesnt-exist-12345",
  "_error": {
    "kind": "http",
    "status": 404,
    "body": {
      "title": "Not found",
      "status": 404,
      "detail": "No LinkedIn company found for the provided URL.",
      "error_type": "not_found"
    }
  }
}

The error_type field is the canonical, machine-readable classifier:

error_type	HTTP	Meaning	Billed
not_found	404	URL parsed correctly but the company doesn't exist.	✓
invalid_input	400	URL malformed or wrong host.	—
upstream_unavailable	503	Upstream provider unreachable / transient. Safe to retry.	—
internal_error	500	Unexpected server error.	—

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📊 Data coverage

How often is each field actually populated? These percentages are measured over 2,358 real LinkedIn company records, covering a mix of public, private, large, and small companies.

✅ Always present (100% of records)

id · name · url · logo · image · description · company_id · company_size · employees_in_linkedin · followers

🟢 Almost always (>90%)

Field	Filled
industries	99.96%
similar[] (similar companies)	99.62%
organization_type	98.94%
about	98.05%
unformatted_about	98.05%
website / website_simplified	97.79%
employees[] (people preview)	97.58%
get_directions_url[]	91.56%
country_code / country_codes_array	91.31%
formatted_locations / locations[]	91.31%
headquarters	91.26%

🟡 Common (50–90%)

Field	Filled
updates[] (recent posts)	83.88%
slogan	72.82%
founded	64.93%
specialties	61.24%
additional_information	54.24%

🟠 Sometimes (10–50%)

Field	Filled
affiliated[] (related companies)	23.71%

🔴 Rare (<10%) — present mostly for venture-backed or public companies

Field	Filled
alumni / alumni_information[]	2.76%
crunchbase_url (when LinkedIn cross-links)	2.42%
funding (LinkedIn-shipped funding summary)	~2.4%
investors[]	~1.4%
stock_info	private companies → null

What does this mean for you? If your use case depends on funding, investors, or alumni_information, expect those fields on a small minority of companies — typically venture-backed startups and large enterprises. Identity, size, headquarters, posts, and similar-companies data are reliable across the board.

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🚀 Usage examples

Look up a single company

{ "slugs": ["openai"] }

Look up several companies by slug

{
  "slugs": ["stripe", "plaid", "ramp", "brex", "mercury"]
}

Mix full URLs and bare slugs in one run

{
  "urls": [
    "https://www.linkedin.com/company/ibm",
    "https://fr.linkedin.com/company/airbus/about/"
  ],
  "slugs": ["microsoft", "openai"]
}

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❓ FAQ

How long does a run take?

Each lookup typically completes in 30–60 s. A run of 5 companies in parallel lands in ~1 minute.

Why are some fields null?

LinkedIn data coverage varies per company. A small startup won't have alumni_information or funding. A privately-held firm won't have stock_info. See the Data coverage section for measured fill rates per field. Null = "LinkedIn doesn't expose this for this company" — not "the actor failed to map it."

Can I look up a personal LinkedIn profile?

No — this actor handles company pages only (/company/<slug>). Personal profiles (/in/<slug>) are not supported.

Why are some fields like Links capitalized inside similar[]?

That's how LinkedIn returns them. We preserve the upstream shape so existing parsers keep working.

How do I retry just the failures?

Filter the dataset for rows where _error is set, then feed the _input_url values back into a new run.

What happens if I pass the same URL twice?

Inputs are de-duplicated after canonicalization (urls and slugs both normalize to https://www.linkedin.com/company/<slug>), so you won't be charged twice for the same company in a single run.

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💰 Pricing

Pay-per-event — you're billed only for outcomes, not run-time:

Event	Charged when	Price
successful-lookup	Company successfully scraped and returned (HTTP 200).	$0.005 each
failed-lookup	URL is structurally valid but the company doesn't exist (404).	$0.002 each
Server / network errors (HTTP 5xx, timeouts)	—	not billed

Apify's standard apify-actor-start ($0.00005, ~one event per run at 128 MB) also applies.

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🔗 Related actors

Actor	Best for
Crunchbase Company Lookup	Resolve Crunchbase URLs into structured JSON.
Glassdoor Company Lookup	Resolve Glassdoor URLs into ratings + interviews.
ATS Jobs Search	Search jobs from 48 ATS platforms in one API call.

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🏢 About Jobo

Jobo provides job & company data infrastructure for developers, recruiters, and AI agents.

• Website: jobo.world
• Support: enrico@jobo.world