Linkedin Company Employees Scraper

Linkedin Company Employees Scraper

Linkedin Company Employees Scraper is an Apify actor that discovers and extracts public employee profiles from LinkedIn company pages at scale. It solves the challenge of building a reliable, analysis-ready staff list by aggregating profile URLs and scraping public profile metadata. Ideal for marketers, developers, data analysts, and researchers, this LinkedIn company employees extractor helps you scrape LinkedIn company employees list for lead generation, recruitment research, and workforce analysis — enabling repeatable, automated B2B intelligence at scale.

What data / output can you get?

This LinkedIn staff list scraper returns structured JSON records for each discovered public profile. Below are the primary fields it produces:

Data type (field)	Description	Example value
company_url	Canonical company page URL associated with the profile (when detected)	https://www.linkedin.com/company/microsoft
profile_url	Final canonical LinkedIn profile URL	https://www.linkedin.com/in/john-doe-123456
fullname	Full display name extracted from the profile	John Doe
first_name	First name parsed from the display name	John
last_name	Last name parsed from the display name	Doe
headline	Public profile headline / role summary	Senior Software Engineer at Microsoft
public_identifier	Identifier extracted from URL (as matched), e.g., “/in/slug”	/in/john-doe-123456
profile_picture_url	Open Graph image or detected profile picture URL	https://media.licdn.com/...
location.full	Full location string (with optional geocoding enhancement)	Seattle, Washington, United States
location.city	City derived from profile content or geocoding	Seattle
location.country	Country derived from profile content or geocoding	United States
location.country_code	Two-letter ISO code (when resolvable)	US
is_creator	Flag placeholder (always false in public mode)	false
is_influencer	Flag placeholder (always false in public mode)	false
is_premium	Flag placeholder (always false in public mode)	false
created_timestamp	UNIX timestamp when the record was created	1712419200
show_follower_count	Static flag (true by default in this actor)	true
current_company	Best-current company name detected from profile links	Microsoft
companies_detected	Array of companies referenced on the profile	[{"name":"Microsoft","slug":"microsoft","url":"https://www.linkedin.com/company/microsoft"}]
personal_website	First external website found on the profile (non-LinkedIn)	https://johndoe.dev
recommendations_received	Array of received recommendations found on public sections	[{"text":"Great teammate.","author":"Jane Smith","author_url":"https://www.linkedin.com/in/jane-smith"}]
other_contact_details.course_links	Extracted LinkedIn Learning course links	["https://www.linkedin.com/learning/agile-foundations"]
contact_elements.profile_identity.profile_identifier	Session redirect or profile URL identifier	https://www.linkedin.com/in/john-doe-123456
contact_elements.learning_content.course_details	Structured course details if present	[{"title":"Agile Foundations","duration":"1h 20m","url":"...","image":"..."}]
contact_elements.platform.*	Footer/platform metadata discovered on the page	See JSON example
error	Error message for blocked/failed profiles (present only on errors)	HTTP 999

Notes:

• Results are stored in the Apify dataset and can be exported to CSV, JSON, or Excel.
• Bonus metadata includes nested “contact_elements” (identity, auth points, learning content, platform, language) and “companies_detected,” making it a useful LinkedIn company employee directory scraper for deeper analysis.

Key features

• 🔎 Dual-source discovery for robust coverage
  Combines company page crawling with Google search (site:linkedin.com/in) to uncover more employee profile URLs. This increases find rates when you scrape employees of a company on LinkedIn.

• 🧭 Automatic Residential proxying
  The actor auto-configures and uses Apify RESIDENTIAL proxies for all requests to reduce blocks and improve stability — ideal for a LinkedIn company workforce scraper.

• 🌍 Location enrichment with geocoding
  Extracts location strings from public HTML and enhances missing country info via OpenStreetMap geocoding for cleaner analytics.

• 📦 Bulk inputs & limits
  Feed multiple targets (URLs, slugs, keywords) via targets and control volume with maxEmployees to export LinkedIn company employees to CSV at scale.

• 🧱 No-login, public-only scraping
  Designed for public LinkedIn content without cookies or authentication. Safer and more reliable than brittle browser extensions.

• 🧾 Structured, nested output
  Returns rich profile metadata including companies_detected, recommendations_received, and contact_elements, ready for pipelines and dashboards.

• 🔗 API-friendly & automation-ready
  Use the Apify API to integrate with your data pipelines, CRMs, or BI tools. Great for developers building LinkedIn company employees extractor workflows.

• 🧰 Production-grade reliability
  Batched retries, HTTP 999 handling, and network resilience tuned for repeatable runs when you need a LinkedIn company employees data scraper you can trust.

How to use Linkedin Company Employees Scraper - step by step

1. Create or log into your Apify account.
2. Open the actor “linkedin-company-employees-scraper” on Apify.
3. Add your input under “targets” as a list of items:
   • Company URLs or slugs (e.g., https://www.linkedin.com/company/microsoft or microsoft)
   • Keywords (e.g., software engineer or google)
4. Set “maxEmployees” to control how many profiles to extract per company (1–1000; default 10).
5. (Optional) Configure “proxyConfiguration.” The actor will still auto-use RESIDENTIAL proxies for stability.
6. Start the run. The actor will crawl the company page(s), search Google for profiles, then scrape each public profile.
7. Monitor progress in logs. You’ll see discovery counts, retries, and any HTTP 999 or block notices.
8. Download results from the Dataset tab in your preferred format (CSV, JSON, or Excel).

Pro Tip: Trigger runs via the Apify API to schedule recurring exports and keep your LinkedIn company employee list download tool fully automated.

Use cases

Use case name	Description
Sales teams – B2B prospecting	Build decision-maker lists by exporting public profiles from target company pages with a LinkedIn company employees finder tool.
Recruitment research	Identify talent pools and current roles to accelerate sourcing and outreach with a LinkedIn staff data extractor.
Market & competitor analysis	Track headcount signals and roles distribution for workforce insights using a LinkedIn company headcount scraper approach.
Data enrichment & analytics	Append public profile metadata (names, headlines, locations) to internal records and measure segment coverage.
Academic & policy studies	Analyze public workforce structures regionally using structured, repeatable data from a LinkedIn employees list extractor.
API-driven pipelines	Feed cleaned JSON data to CRMs or BI stacks; perfect for dev teams automating a LinkedIn company employee directory scraper.

Why choose Linkedin Company Employees Scraper?

Built for precision and repeatability, this LinkedIn company employees scraper emphasizes stability, public-only data collection, and clean output.

• ⚡ Reliable dual-discovery: Crawls company pages and leverages Google to maximize employee URL discovery.
• 🌐 Geocoded locations: Enhances incomplete location strings for analytics-ready city/country codes.
• 🧩 Structured JSON: Returns deeply structured fields (companies_detected, recommendations_received, contact_elements) for downstream use.
• 📈 Scales with your needs: Bulk targets and per-company limits make it a LinkedIn employees list extractor you can grow with.
• 🔒 Safer than extensions: No login or cookies; avoids the fragility of browser automation tools.
• 💻 Developer-first: Easy to orchestrate via Apify API for CI/CD, ETL, and workflow automation.
• 🧠 Proxy-smart: Uses residential proxies for stability across requests to reduce blocking.

Bottom line: It’s a production-ready LinkedIn company employees extractor that outperforms manual workflows and one-off extensions.

Is it legal / ethical to use Linkedin Company Employees Scraper?

Yes — when used responsibly. This actor accesses only publicly available LinkedIn pages and does not authenticate or access private content.

Guidelines for compliant use:

• Scrape only public data that’s available without logging in.
• Respect LinkedIn’s terms of service and applicable data protection laws (e.g., GDPR/CCPA).
• Use results for legitimate purposes (research, analytics, prospecting) and avoid spam.
• Consult your legal team if you have edge cases or jurisdiction-specific requirements.

Input parameters & output format

Example JSON input

{
  "targets": [
    "https://www.linkedin.com/company/microsoft",
    "openai",
    "software engineer"
  ],
  "maxEmployees": 25,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}

Input fields

• targets (array of strings)
  Description: Bulk input: LinkedIn company URLs or slugs, profile usernames, or keywords. Can be URLs (e.g., “https://www.linkedin.com/company/microsoft”) or plain text (e.g., “microsoft”, “google”, “software engineer”).
  Required: Yes
  Default: None (prefill example provided in UI)

• maxEmployees (integer)
  Description: Maximum number of employee profiles to scrape per company. Range: 1–1000.
  Required: No
  Default: 10

• proxyConfiguration (object)
  Description: Default: No proxy. If blocked, fallback datacenter → residential; stick to residential thereafter.
  Required: No
  Default: {"useApifyProxy": false}
  Note: The actor auto-configures RESIDENTIAL proxies for all requests regardless of this setting to improve reliability.

Example JSON output

[
  {
    "company_url": "https://www.linkedin.com/company/microsoft",
    "profile_url": "https://www.linkedin.com/in/john-doe-123456",
    "fullname": "John Doe",
    "first_name": "John",
    "last_name": "Doe",
    "headline": "Senior Software Engineer at Microsoft",
    "public_identifier": "/in/john-doe-123456",
    "profile_picture_url": "https://media.licdn.com/dms/image/.../profile-displayphoto-shrink_200_200/0/...",
    "location": {
      "country": "United States",
      "city": "Seattle",
      "full": "Seattle, Washington, United States",
      "country_code": "US"
    },
    "is_creator": false,
    "is_influencer": false,
    "is_premium": false,
    "created_timestamp": 1712419200,
    "show_follower_count": true,
    "current_company": "Microsoft",
    "companies_detected": [
      {
        "name": "Microsoft",
        "slug": "microsoft",
        "url": "https://www.linkedin.com/company/microsoft"
      }
    ],
    "personal_website": "https://johndoe.dev",
    "recommendations_received": [
      {
        "text": "John is a great engineer and collaborator.",
        "author": "Jane Smith",
        "author_url": "https://www.linkedin.com/in/jane-smith"
      }
    ],
    "other_contact_details": {
      "course_links": [
        "https://www.linkedin.com/learning/agile-foundations"
      ]
    },
    "contact_elements": {
      "profile_identity": {
        "profile_identifier": "https://www.linkedin.com/in/john-doe-123456",
        "profile_picture": "https://media.licdn.com/dms/image/.../profile-displayphoto-shrink_200_200/0/...",
        "profile_name_display": "John Doe"
      },
      "auth_points": {
        "email_phone_input_present": false,
        "password_input_present": false,
        "login_form_action": ""
      },
      "learning_content": {
        "course_details": [
          {
            "title": "Agile Foundations",
            "duration": "1h 20m",
            "url": "https://www.linkedin.com/learning/agile-foundations",
            "image": "https://media.licdn.com/dms/image/.../image-shrink_200_200/0/..."
          }
        ],
        "course_titles": [
          "Agile Foundations"
        ],
        "all_courses_link": "https://www.linkedin.com/learning/"
      },
      "platform": {
        "corporate_logo_url": "",
        "copyright": "",
        "policy_links": [],
        "about_links": [],
        "privacy_links": [],
        "user_agreement_links": []
      },
      "language": {
        "selector_present": false,
        "locales": []
      }
    }
  },
  {
    "profile_url": "https://www.linkedin.com/in/jane-failed-999",
    "error": "HTTP 999",
    "created_timestamp": 1712419205
  }
]

Notes:

• On blocked/failed profiles, the record includes profile_url, error, and created_timestamp.
• Some nested lists (e.g., recommendations_received, companies_detected, learning_content) may be empty when those sections aren’t present on public pages.

FAQ

Do I need to log in or provide cookies to use this scraper?

No. The actor targets publicly available LinkedIn pages and works without login or cookies. It avoids private or authenticated content.

How many employee profiles can I scrape per company?

You control this via the maxEmployees input. The configurable range is 1–1000 per run, with a default of 10.

What data does the scraper return?

It returns structured fields such as company_url, profile_url, fullname, headline, location, and more, plus nested arrays like companies_detected and recommendations_received. See the Output Format section for a full example.

Can I use keywords instead of company URLs?

Yes. Pass keywords or company names in targets (e.g., “software engineer” or “google”). The actor will run a Google query (site:linkedin.com/in) to discover relevant public profile URLs.

Can I export results to CSV or Excel?

Yes. All results are written to the Apify dataset. From there, you can export to JSON, CSV, or Excel with one click or via the Apify API.

Does it support LinkedIn Sales Navigator or Recruiter?

This tool focuses on public LinkedIn pages without authentication. It does not log in to Sales Navigator or Recruiter; instead, it discovers public profiles via company pages and Google.

Which proxies are used during scraping?

The actor auto-configures Apify RESIDENTIAL proxies for all requests to improve stability and reduce blocking, regardless of the proxyConfiguration input.

Can I filter by job title or location before scraping?

Pre-scrape filters aren’t part of the current inputs. However, the output includes headline and location fields, so you can filter downstream in your workflow or data pipeline.

Closing CTA / Final thoughts

Linkedin Company Employees Scraper is built to reliably discover and extract public employee profile data from LinkedIn company pages at scale. With dual-source discovery, residential proxies, and structured outputs, it serves sales teams, recruiters, analysts, and developers who need a dependable LinkedIn company employees finder tool. Integrate via the Apify API to automate exports to your CRM or analytics stack, and start building a clean, compliant LinkedIn company employees list extractor pipeline today.