LinkedIn Company Scraper

LinkedIn Company Scraper lets you scrape LinkedIn company pages and export them to JSON, CSV or Excel: website, industry, company size, employees on LinkedIn, followers, founding year, headquarters address, every office location, specialties, description, logo, products, showcase pages and similar companies. Paste company URLs, page names or LinkedIn company IDs, press Start, and get one row per company. No LinkedIn account, no login and no cookies are needed.

What data can you extract from LinkedIn company pages?

Each company becomes one row with 30 fields:

Group	Fields
Identity	Name, LinkedIn page, page name, LinkedIn company ID, tagline, logo, cover image
About	Description, website, industry, size band, type (public, private, nonprofit), founding year, specialties, phone
Counters	Employees on LinkedIn, followers
Headquarters	Headquarters as shown, plus street, city, region, postal code and country
Locations	Every office address the company lists, with the primary one marked
Related pages	Affiliated companies, showcase pages and similar companies, each with name, URL, industry, location and logo
Products	Products listed on the page, with category and description

Use cases

• Lead enrichment: turn a list of company names or LinkedIn URLs into websites, sizes, industries and headquarters.
• Account-based marketing: segment target accounts by size, industry and country.
• Market mapping: follow "Similar pages" to find a company's competitors.
• Investor research: check employee counts and follower growth over time with a scheduled run.
• CRM cleanup: fill missing company fields from their LinkedIn page.

How to scrape LinkedIn company pages

1. Open LinkedIn Company Scraper on Apify and click Try for free.
2. In Companies, paste LinkedIn company URLs, page names or company IDs, one per line.
3. Click Start. 100 companies take about a minute.
4. Open the Output tab and download the results as JSON, CSV, Excel, XML or HTML, or fetch them with the Apify API.

Input

Field	What it does
Companies	https://www.linkedin.com/company/stripe/, stripe and 2135371 (Stripe's LinkedIn ID) all work. Showcase pages (/showcase/...) work too; university pages (/school/...) don't.
Max companies	Scrape only the first this-many companies of the list.

{
    "companies": ["https://www.linkedin.com/company/stripe/", "apify", "https://www.linkedin.com/showcase/stripe-support"]
}

Output

A row from a real run, with lists shortened:

{
    "universal_name": "stripe",
    "name": "Stripe",
    "url": "https://www.linkedin.com/company/stripe",
    "company_id": "2135371",
    "tagline": "Help increase the GDP of the internet.",
    "description": "Stripe builds programmable financial services. …",
    "website": "https://stripe.com",
    "industry": "Technology, Information and Internet",
    "company_size": "5,001-10,000 employees",
    "employees_count": 16694,
    "followers_count": 1776112,
    "founded_year": 2010,
    "headquarters": "South San Francisco, California",
    "company_type": "Privately Held",
    "hq_street": "354 Oyster Point Blvd",
    "hq_locality": "South San Francisco",
    "hq_region": "California",
    "hq_postal_code": "94080",
    "hq_country": "US",
    "locations": [
        {
            "address": "354 Oyster Point Blvd, South San Francisco, California 94080, US",
            "lines": ["354 Oyster Point Blvd", "South San Francisco, California 94080, US"],
            "description": "Primary",
            "is_primary": true,
            "maps_query": "354 Oyster Point Blvd South San Francisco 94080 California US"
        }
    ],
    "showcase_pages": [
        {
            "name": "Stripe Partner Ecosystem",
            "url": "https://www.linkedin.com/showcase/stripe-partner-ecosystem",
            "industry": "Internet Publishing",
            "location": "South San Francisco, California"
        }
    ],
    "similar_pages": [
        {
            "name": "Atlassian",
            "url": "https://www.linkedin.com/company/atlassian",
            "industry": "Software Development",
            "location": "Sydney, NSW"
        }
    ],
    "products": [
        {
            "name": "Stripe",
            "category": "Payment Processing Software",
            "url": "https://www.linkedin.com/products/stripe"
        }
    ],
    "input": "https://www.linkedin.com/company/stripe/",
    "scraping_time": "2026-10-19T19:09:12+00:00"
}

A few fields worth knowing:

• employees_count is the number of people with a LinkedIn profile at the company, not the official headcount. company_size is the band the company chose itself.
• universal_name is the company's name in its LinkedIn URL. Two inputs that lead to the same company (a URL and its ID, or a renamed company) give one row.
• Fields the company left empty on LinkedIn come back empty, for example founded_year or phone.

The Output tab has an Overview view. You can export the dataset to JSON, CSV, Excel, XML and HTML.

How much does it cost to scrape LinkedIn company pages?

LinkedIn Company Scraper uses pay-per-event pricing: you pay only for the companies you get.

• $2.50 per 1,000 companies on the Apify Free plan.
• Bronze, Silver and Gold Apify plans pay less: $2.20, $1.90 and $1.40 per 1,000 companies.
• Companies that fail are not results, so you are not charged for them.

The Apify Free plan's monthly credits let you try the scraper before you pay.

Integrations and API

You can run LinkedIn Company Scraper from your own code with the Apify API.

Python

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("keklik/linkedin-company-scraper").call(
    run_input={"companies": ["stripe", "apify"]}
)
for company in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(company["name"], company["website"], company["company_size"])

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('keklik/linkedin-company-scraper').call({
    companies: ['stripe', 'apify'],
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.map((c) => [c.name, c.website]));

You can also:

• Schedule runs to track employee and follower counts over time.
• Use webhooks to get notified, or trigger your own pipeline, when a run finishes.
• Connect the results to Make, Zapier, Google Sheets, Airbyte and other tools through Apify integrations.
• Give AI agents access through the Apify MCP server, so Claude, ChatGPT or Cursor can look up companies for you.

FAQ

Is it legal to scrape LinkedIn company pages?

This scraper collects only company pages that LinkedIn shows publicly to visitors who are not logged in. Company pages are business information, but check that your use follows the laws that apply to you. If you are unsure, ask a lawyer.

Do I need a LinkedIn account?

No. You don't need a LinkedIn account, a login or cookies, and the scraper never uses yours.

Can I use a LinkedIn company ID?

Yes, but only for companies with at least one open job on LinkedIn: the scraper finds the company's page through its jobs. For other companies, use the company URL or page name.

Why did some companies fail?

Companies that fail are listed, with the reason, in the FAILED record of the run's key-value store (open the run, then Storage, then Key-value store):

• invalid_input: not a LinkedIn company URL, page name or ID.
• not_found: no LinkedIn page has that name.
• company_id_not_found: the company ID has no open jobs, so its page can't be found. Use the company URL.
• school_page: university pages are not supported.
• blocked: LinkedIn refused every attempt. Run it again later.

Do I need to set up proxies?

No. There is nothing to configure.

Related scrapers

• LinkedIn Jobs Scraper: the jobs these companies are hiring for, with salaries and descriptions.
• Google Maps Leads Scraper: phone numbers, websites and emails of local businesses.

Support

Found a bug or missing a field? Open an issue in the Issues tab and we'll look at it. Need a custom LinkedIn scraper or data in a different format? Contact us through Apify and we'll build it for you.