Linkedin Employees Scraper

# LinkedIn Employees Scraper 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 2,000 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. Unearth valuable networking opportunities by discovering potential connections within your target industries or companies. With this tool, you can identify employees who match your ideal criteria such as specific job titles, locations, or educational backgrounds across a wide range of organizations. By extracting detailed employee data, you can map out organizational structures, spot key decision-makers, and build targeted lists for outreach. Whether you're looking to expand your professional network, find new leads for business development, or connect with alumni from your university, it will empower you to uncover and approach the right people efficiently and strategically. ## 📄 What Can You Extract? - Name: Employee's full name - Designation: Job title - Company: The company name - Location: Employee's location - Link: URL to the employee's LinkedIn profile - Followers: Number of followers - Education: Educational background - Experience: Work experience - Thumbnail: Employee's profile picture URL ## 📘 How to Use Getting started is quick and painless even if you've never scraped data before: 1. Create a free Apify account. All you need is an email address. 2. Open the LinkedIn Employees Scraper on the Apify platform. 3. Add one or more LinkedIn company URLs (and optionally job titles and country filters). Make sure to use valid company URLs: - ✅ Valid: https://www.linkedin.com/company/example-inc./ - ❌ Invalid: https://www.linkedin.com/company/154XXX/ 4. Click "Start". The actor will visit each URL, find employees, and gather their data. 5. Download your dataset in JSON, CSV, Excel, or HTML or pipe it straight into your integrations via the API. ## ✨ Key Features - Lightning-Fast Scraping: Retrieve up to 2000 employee results in just 60 seconds. - Multi-Company Support: Scrape employee data from multiple company pages simultaneously. - 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. - Country Filtering: Filter employees by specific countries for targeted searches. - Alumni Extraction: Extract alumni of any college/University. - Customizable Result Limits: Specify how many employee results you want per company. ## ⌨️ Input Parameters | Field | Type | Description | Required | | -------------------- | ------- | ---------------------------------------------------------------------------------- | -------- | | companyUrls | Array | Company URLs to scrape employees from. | Yes | | designation | Array | Search for specific job titles to filter results. Add predefined or custom titles. | No | | maxResultsPerCompany | Integer | Maximum number of employee results to scrape per company. | Yes | | country | String | Restrict results to employees based in a specific country. | No | ### Sample Input json { "companyUrls": [ "https://www.linkedin.com/company/microsoft/", "https://www.linkedin.com/company/apple/", "https://www.linkedin.com/school/harvard-university/" ], "designation": [ "CEO", "CFO", "Team Leader", "Manager", "President", "Lead" ], "maxResultsPerCompany": 1000, "country": "US" } ## 📊 Output The actor returns a structured dataset with the following fields for each employee. ### Sample Output (JSON) json [ { "thumbnail": "[Image]", "name": "Amy ***", "company": "Tech***", "designation": "Chief ***", "link": "https://www.linkedin.com/in/***", "followers": "5***", "education": "Stanford University", "experience": "Tech***", "location": "San Francisco, California", "verified": "✅" }, { "thumbnail": "[Image]", "name": "David ***", "company": "Data***", "designation": "VP ***", "link": "https://www.linkedin.com/in/***", "followers": "2***", "education": "MIT", "experience": "Data***", "location": "Boston, Massachusetts", "verified": "✅" } ] ## 🎯 Use Cases - Talent Acquisition: Rapidly build candidate pools for recruitment. - Networking Opportunities: Discover potential connections within specific industries or companies. - 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. - Diversity & Inclusion Research: Analyze workforce diversity across different organizations. - Event Planning: Identify key industry leaders and influencers for conferences and events. - Academic Studies: Source data for research on employment trends and organizational structures. - Partnership Development: Spot potential collaborators within targeted sectors. ## 📌 Usage Tips - Use the designation field: Specify standard or custom job titles for more precise results. - Country filter: Narrow down candidates by country for highly targeted outreach. - Batch processing: Provide an array of company URLs for concurrent scraping. ## 🔌 Integrations LinkedIn Employees Scraper fits seamlessly into your data pipeline. Thanks to built-in integrations on the Apify platform, you can connect this actor with virtually any cloud service or web app. ### Popular integrations - Make (Integromat) – automate multi-step workflows with drag-and-drop scenarios. - Zapier – send data to 5,000+ apps without writing code. - Airbyte – sync datasets into your data warehouse. - Slack – push instant notifications to your team channels. - Google Sheets & Drive – store results in spreadsheets or cloud storage. - GitHub – commit scraped datasets directly to your repositories. - AWS S3 / Azure Blob Storage – archive large exports securely. ### Webhooks Set up webhooks to trigger an action whenever a specific event occurs – for example, receive an email or Slack alert whenever LinkedIn Employees Scraper successfully finishes a run. ## 🛠️ API Access Prefer to automate everything with code? The Apify REST API lets you manage, schedule, and run this actor programmatically – no clicks required. - Run & Schedule Actors: Kick-off a scrape on demand or set up a cron-like schedule. - Access Datasets: Stream results directly into your apps, data warehouse, or BI dashboards. - Monitor Runs: Track progress, error logs, and performance metrics in real time. - Version Control: Programmatically create new versions or roll back if needed. ### Client libraries Choose the SDK that fits your stack: | Language | Package | Install | | -------- | ------- | ------- | | Node.js | apify-client | npm install apify-client | | Python | apify-client | pip install apify-client | --- For complete API examples and detailed usage, visit the LinkedIn Employees Scraper API documentation. js // Example: Trigger a run with Node.js import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '<YOUR_API_TOKEN>' with your token const client = new ApifyClient({ token: '<YOUR_API_TOKEN>', }); // Prepare Actor input const input = { "companyUrls": [ "https://www.linkedin.com/company/microsoft" ], "designation": [], "maxResultsPerCompany": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("caprolok/linkedin-employees-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); ### MCP Quickstart You can use the Apify MCP Server in two ways: 1. Standard Input/Output (stdio): Ideal for local integrations and command-line tools such as the Claude for Desktop client. - Set MCP client server command to npx @apify/actors-mcp-server and environment variable APIFY_TOKEN to your Apify API token. - See npx @apify/actors-mcp-server --help for more options. 2. HTTPS Endpoint mcp.apify.com: Connect your MCP client by including Authorization: Bearer <APIFY_TOKEN> header in your requests. - Use https://mcp.apify.com for streamable transport. - Use https://mcp.apify.com/sse for legacy SSE transport. For more details, see the MCP API documentation. For full API details, visit the Apify API reference or open the API tab on this actor's Apify page for ready-made code snippets. ## 💬 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. ## 🔗 Related Scrapers