LinkedIn Company Scraper

Get public company profiles from exact LinkedIn company URLs. Each result identifies the requested company before exporting its description, industry, website and audience metrics. Export to JSON, CSV or Excel, run on a schedule, call via API, or connect to Make, Zapier or n8n.

Enrich a known company list: use exact LinkedIn /company/ URLs; search by company name and personal /in/ profiles are outside this Actor. Free-plan result events cost $4 per 1,000 companies, plus the start event. Missing public fields remain null.

Quick start

Start with a tested example for verified company snapshots:

• Microsoft and GitHub company profiles with verified URLs

Open the example and choose Try for free to copy its input into your account. Check the input and set a maximum run charge before starting; Actor fees still follow the pricing below. When the run finishes, open the run's dataset and select the Overview view and download JSON for nested fields or CSV/Excel for a table.

Your goal	Input to use
Enrich a known employer list	Supply exact /company/ URLs
Compare later observations	Join by company_id, retaining scraped_at

The real output example shows the record shape. The Python workflow saves your own export to a local JSON file with a $0.05 maximum Actor charge.

What does this scraper extract?

The Actor reads the public company page directly, without a LinkedIn login, personal session cookies or another provider's API key. It checks the page's canonical URL, primary Organization record and company ID before returning a row. Related companies and organizations mentioned in posts are not accepted as the target.

The export contains company information that LinkedIn makes available to logged-out visitors. Public visibility varies. Missing optional fields remain null; the Actor does not guess an address, website or employee count. Company names and descriptions come from the source without rewriting or truncating the text.

Use this for company research, keeping a business directory current, enriching an existing list of company URLs, and comparing public company snapshots over time. It works well alongside a job feed when you already know which employer you want to research.

Input

Input	Default	Behavior
companyUrls	["https://www.linkedin.com/company/microsoft/"]	Exact public /company/ URLs. Names, personal profiles and fuzzy searches are rejected. Numeric company URLs are checked against the primary company ID.
maxResults	10	Maximum distinct verified companies to export.
proxyConfiguration	{"useApifyProxy": false}	Optional caller-selected proxy; direct requests are the default.

Example input

{
  "companyUrls": [
    "https://www.linkedin.com/company/microsoft/",
    "https://www.linkedin.com/company/github/"
  ],
  "maxResults": 2
}

Paste company URLs into companyUrls, choose a small result limit, and run. Canonical duplicates are removed before fetching. Numeric redirect URLs are rejected; use the named public company URL. A country-specific LinkedIn hostname is normalized to the public www hostname. Tracking query parameters do not create another company.

Names such as Microsoft, external websites, personal /in/ profiles, company search pages and /posts/ URLs are rejected. The Actor never turns these into a fuzzy company search. Supply a company's main /company/<slug>/ URL. A renamed slug that redirects to a different canonical company slug fails the identity check; update the input to the current canonical URL after checking it.

Example output

One complete record from a verified September 9, 2026 cloud run. Values and public media URLs can change or expire; this is a dated sample.

{
  "company_id": "1418841",
  "name": "GitHub",
  "url": "https://www.linkedin.com/company/github",
  "requested_url": "https://www.linkedin.com/company/github",
  "description": "As the global home for all developers, GitHub is the complete AI-powered developer platform to build, scale, and deliver secure software. Over 100 million people, including developers from 90 of the Fortune 100 companies, use GitHub to build amazing things together across 330+ million repositories. With all the collaborative features of GitHub, it has never been easier for individuals and teams to write faster, better code.\n",
  "industry": "Software Development",
  "website": "https://github.com",
  "headquarters": "San Francisco, CA",
  "address": {
    "type": "PostalAddress",
    "streetAddress": "88 Colin P Kelly Jr St",
    "addressLocality": "San Francisco",
    "addressRegion": "CA",
    "postalCode": "94107",
    "addressCountry": "US"
  },
  "company_size": "501-1,000 employees",
  "linkedin_employee_count": 6864,
  "followers": 6610616,
  "company_type": "Privately Held",
  "founded": "2008",
  "specialties": null,
  "logo_url": "https://media.licdn.com/dms/image/v2/D560BAQGxQRyEwD643g/company-logo_200_200/B56Z3045ErGgAI-/0/1777930048179/github_logo?e=2147483647&v=beta&t=VOSw99XrRMs2tz1Eqlkfz0kOuUlusjpBLk46CxqfeUI",
  "identity_verified": true,
  "scraped_at": "2026-09-09T19:39:11.312796+00:00"
}

All output fields:

Field	Meaning
company_id, name, url	Primary organization ID, displayed company name and canonical source URL.
requested_url, identity_verified	Normalized requested URL and a true value after the identity checks pass.
description	Full company description from the public Organization record.
industry, website	Public industry label and source-published website URL.
headquarters, address	Headquarters text and structured source address, when present.
company_size	LinkedIn's displayed company-size range, kept as text.
linkedin_employee_count	Count of LinkedIn-associated members in the source record, not independently verified workforce size.
followers	Public follower count when an exact number is available.
company_type, founded, specialties	Optional public company attributes; specialties remain source text.
logo_url, scraped_at	Source logo URL and UTC extraction timestamp.

Company-size ranges and associated-member counts can disagree. They describe different source metrics and are deliberately separate columns. An address may describe a headquarters rather than every operating location. A website is a link published on LinkedIn; this Actor does not crawl that website or verify its ownership independently.

The default dataset provides the rows, including an overview table. The SUMMARY record in the run's key-value store records requested and unique URLs, exported companies and the stop reason. The Output tab links to both. Source or storage failures mark the run failed; inspect any partial dataset and SUMMARY.failed_url before retrying a batch. Successfully written rows remain available.

Pricing and limits

On the Free plan, each exported company costs $0.004, equivalent to $4 per 1,000 companies, plus a $0.00005 start event at the default 512 MB. Bronze is $3.60/1,000, Silver $3.40, and Gold, Platinum and Diamond are $3.20/1,000 at the currently saved rates. The start event is $0.000045 on Bronze, $0.000040 on Silver, and $0.000035 on Gold, Platinum and Diamond. The Store pricing panel is authoritative.

A two-company Free-tier export at default memory is $0.00805 in Actor events. No email/contact add-on or third-party scraping subscription is required. An optional proxy can affect run costs; inspect the run usage and current Apify pricing. Use the maximum charge control as an additional budget bound. A spending cap can return fewer companies than requested.

Input is limited to 100 URLs per run and the default maximum output is ten companies. Requests run sequentially with bounded retries. Large batches or slow proxy routes may need a longer run timeout; splitting a list into small batches makes failed URLs easier to retry.

Python API workflow

Copy the first input JSON above into input.json and save this code as export.py. In a Python virtual environment, install apify-client with python -m pip install apify-client. Set APIFY_TOKEN to your own Apify token in your environment, then run python export.py. Keep the token out of source files and shared screenshots.

import json
import os
from decimal import Decimal
from pathlib import Path

from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("benthepythondev/linkedin-company-scraper").call(
    run_input=json.loads(Path("input.json").read_text(encoding="utf-8")),
    max_total_charge_usd=Decimal("0.05"),
    memory_mbytes=512,
    timeout_secs=300,
)
if not run or run["status"] != "SUCCEEDED":
    raise RuntimeError(f"Inspect the run before retrying: {run and run['id']}")

rows = list(client.dataset(run["defaultDatasetId"]).iterate_items())
Path("linkedin-companies.json").write_text(
    json.dumps(rows, ensure_ascii=False, indent=2), encoding="utf-8"
)
print(f"Saved {len(rows)} records from run {run['id']}")

This starts a run in your account, waits for completion and saves linkedin-companies.json. The $0.05 limit bounds Actor charges; it is not a promised bill or result count. Check the printed run ID and server log if the result is shorter than expected. If your client loses its connection, inspect the existing run in Console before starting another one. See the official Python client for other run options.

Use company_id for directory upserts, or keep ID plus scraped_at for history. Store company_size, linkedin_employee_count and followers separately: a reported size range, associated LinkedIn members and audience size measure different things. No employee list is included.

For recurring runs without writing a scheduler, copy a tested public Task into your account and attach an Apify Schedule to that copy. Keep its maximum-charge limit and avoid overlapping runs when using monitor state. The Python example above is also suitable for an existing scheduler; run it from the directory containing input.json and provide the token through that scheduler's secret settings.

FAQ

Does this search for companies by name? No. It verifies exact company URLs. This avoids silently returning a similarly named organization.

Can I scrape people or a company's employee list? No. The output describes the company. It does not enumerate employees, personal profiles or private information.

Does it need a LinkedIn account? No account is supplied to this Actor. A page that requires authentication or remains blocked cannot be exported through this public route.

Does a successful identity check verify every company claim? No. It verifies that the extracted source identity matches your input. LinkedIn's public fields may still be incomplete, outdated or self-reported.

Are emails and phone numbers included? This Actor has no invented contact discovery. It exports the company fields documented above. Use the published website with a separate contact extractor if your workflow needs public business contacts.

Why did a URL fail? Check that it is a main company URL and still publicly available. Blocked pages, mismatched identities and missing primary organization records fail clearly instead of becoming an empty successful export.

Can I schedule this? Yes. Use an Apify Task and schedule, then compare rows by company_id in your own database. This Actor exports current snapshots; it does not maintain a company-change history itself.

Can I export to a spreadsheet or API? Yes. The dataset supports JSON, CSV and Excel, and Apify exposes the dataset through its API. Nested address data is easiest to preserve in JSON.

How should I use the data? Follow applicable law, platform terms and your organization's data rules. Public availability does not grant unrestricted permission for every downstream use.

Related Actors

LinkedIn Jobs returns public job postings with descriptions and only-new monitoring. Facebook Pages extracts public organizational Page information and published contacts. Website Contact Extractor reads contact details from business websites.

Keywords: LinkedIn company scraper, company URLs, company profile data, business research, company industry, headquarters, company size, employee count, LinkedIn followers, company website, B2B data, organization ID, company enrichment, JSON export, CSV export, scheduled company data.