How to Scrape LinkedIn Company Data Without a Login

Enrich any list of companies with LinkedIn data: employee count, industry, headquarters, description, specialties, website, and top employee profiles. No LinkedIn account, no cookies, no browser automation. HTTP-only, so runs are fast and cost about $0.005 per company.

What data you get

Each run returns one dataset row per company. Fields come from LinkedIn's public guest company page, which does not require a login. The actor uses plain HTTP requests with no browser, so it processes each company in about one to two seconds.

{
  "company_id": "lead-001",
  "company_name": "Acme Corp",
  "linkedin_url": "https://www.linkedin.com/company/acme-corp",
  "employee_count": 5000,
  "employee_count_range": "1,001-5,000",
  "industry": "Software Development",
  "headquarters": "Munich, Bavaria",
  "description": "Acme Corp builds enterprise software for the manufacturing sector.",
  "specialties": ["ERP Integration", "Supply Chain Analytics"],
  "website": "https://www.acme-corp.example",
  "founded": "2015",
  "company_type": "Privately Held",
  "follower_count": 14200,
  "address": null,
  "employees": [],
  "posts": [],
  "error": null
}

Available fields

• employee_count: upper bound of the employee range shown on LinkedIn (for example, 5000 for "1,001-5,000").
• employee_count_range: raw range string as displayed on LinkedIn.
• industry: LinkedIn industry category.
• headquarters: city and region.
• description: full company description from the About section.
• specialties: list of specialties or focus areas.
• website: company website URL.
• founded: year founded.
• company_type: Privately Held, Public Company, etc.
• follower_count: LinkedIn follower count.
• employees: top visible employee profiles with name, title, and LinkedIn URL (requires includeEmployees: true).
• posts: up to 5 recent company updates with text and timestamp.
• error: null on success; a short message if the company could not be resolved.

Prerequisites

• A free Apify account. Sign up at the actor page. The free tier includes $5 of usage credit each month, which covers about 999 company lookups.
• A list of companies to enrich. LinkedIn URLs are fastest and most reliable. If you do not have LinkedIn URLs, the actor can search Google for the company page using only a company name and optional website domain.

STEP 1

Open the actor and sign up

1. Go to the NanoScrape LinkedIn Company Scraper on Apify.
2. Click Try for free. Sign up with Google or email. It takes about a minute.
3. Once signed in, the actor opens in Apify Console with the Input tab active.

Already have an Apify account? Just open the actor link and it drops you straight into the input editor.

STEP 2

Build your company list

In the Input tab, click JSON editor at the top right. Paste your list of companies in the format below. Each entry needs a company_id (your own key), a company_name, and either a linkedin_url or a website_domain:

{
  "companies": [
    {
      "company_id": "lead-001",
      "company_name": "Contoso Ltd",
      "linkedin_url": "https://www.linkedin.com/company/contoso"
    },
    {
      "company_id": "lead-002",
      "company_name": "Northwind Traders",
      "website_domain": "northwindtraders.example"
    }
  ],
  "includeEmployees": false
}

Tips for building the list:

• Use LinkedIn URLs whenever possible. The actor reads the company slug directly from the URL, which is faster and more reliable than a Google search.
• company_id is your own key. Use any string that ties the result back to your CRM row, spreadsheet ID, or database record.
• website_domain as fallback. When you do not have a LinkedIn URL, the actor searches Google for the company page. Adding the website domain improves search accuracy.
• Numeric LinkedIn IDs: if your CRM stores numeric-ID LinkedIn URLs (for example https://www.linkedin.com/company/19051), the actor tries a set of candidate slugs derived from the company name and domain. Rows that resolve this way include resolved_from_numeric_id: true in the output. Rows that cannot resolve come back with error: "numeric_id_unresolvable" and no charge.

Optional: include employee profiles

Set includeEmployees: true to also scrape the top visible employees from each company's People page. Use maxEmployeesPerCompany (1 to 50) and employeeTitleFilters to target specific roles:

{
  "companies": [
    {"company_id": "lead-001", "company_name": "Contoso", "linkedin_url": "https://www.linkedin.com/company/contoso"}
  ],
  "includeEmployees": true,
  "maxEmployeesPerCompany": 10,
  "employeeTitleFilters": ["CEO", "CTO", "Head of Engineering"]
}

Visibility note: LinkedIn shows a limited set of employees on the public guest People page, typically 5 to 10 profiles per company. The actor returns whatever LinkedIn exposes to an anonymous visitor. Employees with private profiles or who are not visible without a login will not appear.

STEP 3

Run the actor

Click Start at the top right. The actor processes companies in sequence. Each company takes about one to two seconds. A list of 100 companies typically completes in two to three minutes. Progress appears in the live log as each company resolves.

When the run finishes, the status changes to Succeeded. Click Results to preview the dataset. Each row represents one company. Rows with error: null resolved successfully; rows with an error value were not resolved and are not charged.

Running large batches: for batches of 1,000 or more companies, set requestDelay to 3000 or higher to avoid rate limiting. The default of 2000 ms works well for batches up to a few hundred companies.

Automate with n8n

To enrich a CRM export on a schedule (for example, enriching all new leads added each week), connect the actor to n8n using the verified Apify n8n node.

1. Open n8n and create a new workflow.
2. Add a Schedule Trigger node. Set the interval to once a week or another cadence that matches your CRM update frequency.
3. Add a Google Sheets (or CRM) node to read the current list of new companies.
4. Add an Apify node. Set Operation to Run an Actor and get dataset. Set Actor ID to santamaria-automations/linkedin-company-scraper.
5. In the Input JSON field, build the companies array dynamically from the previous node's output.
6. Add another Google Sheets node (or a CRM node) to write the enriched rows back.
7. Save and activate the workflow.

{
  "companies": [
    {
      "company_id": "{{ $json.crm_id }}",
      "company_name": "{{ $json.company_name }}",
      "linkedin_url": "{{ $json.linkedin_url }}"
    }
  ],
  "includeEmployees": false
}

This workflow runs weekly, reads new companies from a Google Sheet, enriches each one with LinkedIn data, and writes the results back. At $0.005 per company, enriching 200 new leads per week costs about $1 per week ($4 per month).

Common use cases

B2B lead enrichment

Your CRM has a company name and website but no LinkedIn data. Run a batch enrichment to fill in employee count, industry, and HQ for every row. Sort by employee count to focus outreach on companies in your target size range. The company_id field lets you match results back to your CRM records without manual lookups.

Sales intelligence: finding decision makers

Enable includeEmployees: true with title filters like ["VP Sales", "Head of Procurement", "CFO"]. The actor returns each matching employee's name, title, and LinkedIn profile URL. Route these directly into a sales sequence or cold-outreach tool.

Market research: segmenting by industry and size

Pull the LinkedIn profile for every company in a geographic area or sector, then group by industry and employee_count_range. This gives you a market map without a data subscription. Combine with Google Maps Scraper to add location density and contact info.

Competitive tracking

Track follower count and recent posts for a set of competitors over time. Run the actor weekly, store results in a spreadsheet, and chart follower_count over time. The posts field returns up to five recent company updates per run, so you can monitor what competitors are communicating publicly without checking their profiles manually.

What it costs

• Actor start: $0.001 per run (one-time flat fee, regardless of batch size).
• Per company enriched: $0.005 per company row returned. That is $5 per 1,000 companies.
• No monthly fees. No minimum spend.

10 companies                        = $0.051  ($0.001 start + $0.050)
100 companies                       = $0.501  ($0.001 + $0.500)
1,000 companies                     = $5.001  ($0.001 + $5.000)
Weekly enrichment, 200 leads/week   ~ $4.16/month

The Apify free tier includes $5 of usage credit each month. That covers up to 999 company lookups per month at no charge. Companies that fail to resolve (returned with an error value) are not charged.

FAQ

Related resources

• LinkedIn Company Scraper on Apify: Full actor documentation, input reference, and output field descriptions.
• Google Maps Scraper on Apify: Collect local business data at scale. Discover companies by location, then enrich them with LinkedIn data.
• Website Contact Extractor on Apify: LLM-powered extraction of decision-maker names, emails, and job titles from company websites.
• Website Email Scraper on Apify: Pull emails and phone numbers from company sites. Pairs with LinkedIn enrichment to build contact data.
• All NanoScrape tutorials: Step-by-step guides for every actor in the NanoScrape catalog.