
Linkedin Employees Scraper
Pricing
$39.00/month + usage

Linkedin Employees Scraper
Effortlessly gather LinkedIn URLs and names of employees in bulk. Ideal for HR and recruitment, this tool quickly provides essential contact information, simplifying talent search and networking opportunities.
2.6 (13)
Pricing
$39.00/month + usage
39
Monthly users
173
Runs succeeded
>99%
Response time
13 days
Last modified
2 days ago
The LinkedIn Employees Scraper is a high-speed, cost-effective tool for extracting employee information from company pages. It can gather data on up to 2000 employees in 60 seconds, including names, job titles, and locations. This versatile actor allows customizable searches across multiple companies, making it perfect for recruitment, lead generation, and market research.
🚀 New & Notable Features
- Filter by job titles: Option to filter results by specific job titles for targeted searches.
- Add custom job titles: Define custom titles to refine your searches further.
- Employee verification: Clearly see which employees are verified, enhancing data credibility.
- Alumni extraction: Extract alumni of any college.
- Lightning-fast scraping: Retrieve up to 500 employee results in just 60 seconds.
- Multi-company support: Scrape employee data from multiple company pages simultaneously.
- Flexible language options: Customize interface language and filter by employees' spoken languages.
- Customizable result limits: Specify how many employee results you want per company.
📋 Input Parameters
Field | Description | Example Input |
---|---|---|
companyUrls | Company URLs to scrape employees from. | ["https://www.linkedin.com/company/microsoft/", "https://www.linkedin.com/company/apple/"] |
designation | Search for specific job titles to filter results. Add predefined or custom titles. | ["CEO", "CFO", "Team Leader", "Manager", "President", "Lead"] |
maxResultsPerCompany | Maximum number of employee results to scrape per company. | 100 |
verifyEmployee | Toggle to enable employee verification. | true |
employeeCountryFilter | Restrict results to employees in specific countries. | ["US", "GB", "IN"] |
regionHint | Two-letter country code to indicate the primary region for search relevance. | "US" |
displayLanguage | Interface language for displaying LinkedIn employee profiles. | "en" |
employeeSpokenLanguage | Restrict search to employees speaking specific languages. | ["en", "fr", "de"] |
Sample Input
1{ 2 "companyUrls": [ 3 "https://www.linkedin.com/company/microsoft/", 4 "https://www.linkedin.com/company/apple/", 5 "https://www.linkedin.com/school/harvard-university/" 6 ], 7 "designation": [ 8 "CEO", 9 "CFO", 10 "Team Leader", 11 "Manager", 12 "President", 13 "Lead" 14 ], 15 "maxResultsPerCompany": 1000, 16 "verifyEmployee": true, 17 "employeeCountryFilter": ["US", "GB"], 18 "regionHint": "US", 19 "displayLanguage": "en", 20 "employeeSpokenLanguage": ["en"] 21}
🎥 Input Example
📊 Output Format
The actor returns a structured dataset with the following fields for each employee:
- Thumbnail: Employee's profile picture URL
- Name: Employee's full name
- Company: The company name
- Designation: Job title
- Link: URL to the employee's LinkedIn profile
- Followers: Number of followers
- Education: Educational background
- Experience: Work experience
- Location: Employee's location
- Verified: Indicator if the employee is verified (shown as ✅)
Example output:
Thumbnail | Name | Company | Designation | Link | Followers | Education | Experience | Location | Verified |
---|---|---|---|---|---|---|---|---|---|
[Image] | Amy Johnson | TechCorp | Chief Marketing Officer | https://www.linkedin.com/in/amyjohnson | 500+ | Stanford University | TechCorp | San Francisco, California | ✅ |
[Image] | David Williams | DataSphere | VP of Engineering | https://www.linkedin.com/in/davidwilliams | 2300 | MIT | DataSphere | Boston, Massachusetts | ✅ |
[Image] | Maria Garcia | CloudNine | Product Manager | https://www.linkedin.com/in/mariagarcia | 500+ | UC Berkeley | CloudNine | Seattle, Washington | ✅ |
[Image] | Robert Chen | Quantum AI | Technical Director | https://www.linkedin.com/in/robertchen | 1800 | University of Washington | Quantum AI | Austin, Texas | ✅ |
[Image] | Sarah Miller | TechCorp | Software Engineer | https://www.linkedin.com/in/sarahmiller | 650 | Harvard University | TechCorp | New York, NY | ✅ |
🎬 Output Example
⚡ Performance
- Scrapes up to 500 employee profiles in ~60 seconds
- Efficient and targeted data collection without compromising on detail
- Budget-friendly solution that delivers premium results at an affordable price
💡 Usage Tips
- Use the designation field: Specify standard or custom job titles for more precise results.
- Country and language filters: Narrow down candidates by country or spoken language for highly targeted outreach.
- Region hint: Improve relevance by setting the primary geographic focus of your search.
- Verification toggle: Enable employee verification to enhance data credibility.
- Display language: Set your preferred interface language for viewing results.
- Batch processing: Provide an array of company URLs for concurrent scraping.
📊 Use Cases
- Talent acquisition: Rapidly build candidate pools for recruitment.
- B2B lead generation: Identify and verify key decision-makers for sales outreach.
- Competitive analysis: Monitor competitor teams and strategic hires.
- Market research: Quickly survey employee distributions across multiple geographies and roles.
- Alumni extraction: Extract alumni of any college.
🔗 Other Actors you might want to check
🆘 Support
If you encounter any issues, have suggestions for improvements, or need assistance, please use the Issues tab on the actor's page. Our team actively monitors this section and will respond promptly.
We appreciate your feedback and will do our best to assist you with any concerns.
Pricing
Pricing model
RentalTo use this Actor, you have to pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period. You also pay for the Apify platform usage.
Free trial
1 day
Price
$39.00