LinkedIn Scraper

LinkedIn Scraper extracts publicly available professional data from LinkedIn profile and company URLs. It captures names, job titles, companies, locations, profile URLs, skills, experience, education, and other visible business information.

Use it to build structured datasets for lead generation, sales prospecting, recruitment research, competitor research, and market analysis. You can also discover publicly visible company employees when that option is enabled.

🧩 What does LinkedIn Scraper do?

The LinkedIn Scraper extracts publicly available professional information from LinkedIn profile and company URLs. Instead of opening profiles one by one, we can provide multiple URLs and collect structured data in one run.

It works as a LinkedIn data scraper, LinkedIn profile scraper, and LinkedIn company data scraper for public pages. Depending on the page, extracted information can include names, job titles, companies, locations, profile URLs, skills, education, experience, and other visible professional details.

For agencies, recruiters, sales teams, and researchers, this turns manual LinkedIn data collection into a repeatable workflow. You can then use the resulting dataset for LinkedIn market research, competitor research, recruitment research, or B2B prospecting.

📊 What can LinkedIn Scraper extract?

The actor can extract different types of publicly available LinkedIn profile data, professional data, and company information.

Data type	Example fields
Profile information	Full name, first name, last name, headline, summary
Profile details	Profile URL, public identifier, profile ID
Location	Country, city, professional location
Professional information	Job title, current position, company affiliation
Experience	Current and previous positions, employment history
Education	School, education dates, educational background
Skills	Professional skills listed on the profile
Certifications	Publicly listed certifications
Languages	Languages listed on the profile
Company data	Company name, industry, website, LinkedIn URL
Company details	Company size, company location, company description
Engagement signals	Follower count and other publicly visible profile signals
Employee data	Publicly visible employees when company employee discovery is enabled

This makes the actor useful as a LinkedIn information scraper, LinkedIn professional data extractor, and LinkedIn profile data extraction tool.

🖼️ LinkedIn data extraction workflow

The basic workflow is simple: provide public LinkedIn profile or company URLs, configure optional employee discovery, and start the actor.

The scraper visits each supplied URL, reads the publicly available information, structures the fields, and returns the results as a dataset.

⚙️ Key Features of LinkedIn Scraper

The LinkedIn Scraper focuses on structured public professional data rather than requiring manual profile collection.

• 🔗 Profile and company URLs: Start with LinkedIn profile or company pages.

• 👤 Profile data extraction: Collect names, headlines, summaries, locations, and profile URLs.

• 🏢 Company data extraction: Extract company information available from public company pages.

• 🧑‍🤝‍🧑 Employee discovery: Optionally collect publicly visible employees from supported company pages.

• 💼 Professional information: Capture job titles, companies, experience, education, and skills.

• 🔎 Public data collection: Build datasets from publicly accessible information.

• 📊 Structured output: Receive organized records suitable for analysis and downstream workflows.

• ⚙️ Proxy configuration: Use supported proxy settings when additional scraping reliability is required.

• 🔄 Automation: Run repeated LinkedIn data extraction workflows without manually visiting every page.

• 🔌 API access: Connect the actor to your own applications and data pipelines through the platform API.

This gives you one workflow for LinkedIn scraping, LinkedIn profile scraping, LinkedIn company research, and LinkedIn data extraction.

🚀 How to use LinkedIn Scraper

Using the LinkedIn scraping tool starts with a list of profile or company URLs.

1. Add your LinkedIn URLs

Provide the public LinkedIn profile or company URLs you want to process.

For example:

{

  "startUrls": \[

    "https://www.linkedin.com/in/williamhgates"

  \]

}

You can add multiple URLs when you want to collect a larger LinkedIn dataset.

2. Enable employee discovery when needed

When a start URL points to a company page, you can enable Include Company Employees.

This allows the actor to discover publicly visible employees associated with that company's public employee panel.

3. Configure proxy settings

Proxy configuration is optional. The actor supports proxy settings for scraping reliability, including residential proxy routing through the available platform configuration.

4. Start the actor

Run the actor after entering your URLs and optional settings.

The scraper processes each URL and returns structured LinkedIn profile data, company information, and employee records when enabled.

5. Analyze your results

Once the run finishes, you can use the resulting dataset for LinkedIn data analysis, sales intelligence, recruitment research, market research, or other permitted business workflows.

🔄 How does LinkedIn Scraper work?

The LinkedIn Scraper works by taking public LinkedIn profile or company URLs as input and converting available page information into structured records.

1. Start with public URLs

We provide one or more LinkedIn profile or company URLs through startUrls.

2. Process each page

The actor visits the supplied pages and identifies supported public professional information.

3. Extract relevant fields

Depending on the page, it extracts information such as professional experience, job title, company affiliation, education information, skills, location information, profile headline, profile summary, and company details.

4. Discover company employees

When enabled, the actor can also collect publicly visible employees associated with a company page.

5. Return structured records

The extracted information is returned as structured data that can support LinkedIn data extraction, analysis, storage, or further automation.

This approach is useful when you want to scrape LinkedIn profiles, collect professional data, or build a structured research dataset without manually copying each profile.

📦 LinkedIn Scraper output format

The actor returns structured JSON records for scraped profiles and supported company-related data.

⬇️ Input

{

  "startUrls": \[

    "https://www.linkedin.com/in/williamhgates"

  \]

}

⬆️ Output

Here is a representative profile record:

{

  "full\_name": "William H. Gates",

  "first\_name": "William",

  "last\_name": "H. Gates",

  "headline": "Technology and philanthropy",

  "summary": "Co-founder and philanthropist...",

  "country": "United States of America",

  "city": "Seattle",

  "profile\_pic\_url": "https://example.com/profile.jpg",

  "follower\_count": 195000000,

  "public\_identifier": "williamhgates",

  "open\_to\_work": false,

  "show\_verification\_badge": false,

  "skills": \[

    "Leadership",

    "Software",

    "Philanthropy"

  \],

  "certifications": \[

    "Global Health Leadership Program"

  \],

  "experiences": \[

    {

      "title": "Co-chair",

      "company": "Microsoft",

      "company\_linkedin\_profile\_url": "https://www.linkedin.com/company/microsoft",

      "starts\_at": "1994"

    }

  \],

  "education": \[

    {

      "school": "Harvard University",

      "school\_linkedin\_profile\_url": "https://www.linkedin.com/school/harvard-university",

      "starts\_at": "1973",

      "ends\_at": "1975"

    }

  \],

  "background\_cover\_image\_url": "https://example.com/cover.jpg",

  "languages": \[

    "English"

  \],

  "personal\_emails": \[\],

  "personal\_numbers": \[\],

  "company\_name": "Microsoft",

  "company\_industry": "Technology",

  "company\_website": "https://www.microsoft.com",

  "company\_linkedin": "https://www.linkedin.com/company/microsoft",

  "company\_size": "N/A",

  "url": "https://www.linkedin.com/in/williamhgates",

  "id": "1",

  "error\_message": null,

  "status": "success"

}

The output can support a LinkedIn professional database, LinkedIn profile database, or internal research dataset.

🎯 Use Cases of LinkedIn Scraper

The LinkedIn Scraper fits workflows where public professional information must be collected at scale.

Lead generation

Sales teams can use structured profile information for LinkedIn lead generation, prospect research, and B2B prospecting.

It can support workflows involving a LinkedIn lead scraper, LinkedIn prospect finder, and LinkedIn sales intelligence.

Recruitment research

Recruiters can collect publicly available professional information to research candidates, roles, companies, and employment backgrounds.

Common workflows include LinkedIn recruiter scraper, recruitment research, hiring research, and LinkedIn employment data collection.

Company research

Company URLs can provide useful information for LinkedIn company research, business research, and competitive analysis.

This supports workflows such as LinkedIn company scraper, LinkedIn company profile scraper, and LinkedIn company data extraction.

Market research

Researchers can organize public professional information into datasets for LinkedIn market research, audience research, industry research, and competitor research.

Sales intelligence

Sales teams can combine public profile information with their existing systems to support LinkedIn sales research, account research, and prospecting workflows.

Business intelligence

Structured records can contribute to LinkedIn business intelligence, company databases, professional datasets, and broader data analysis projects.

Dataset creation

Researchers can use the output for LinkedIn dataset creation, professional networking data analysis, and research data collection.

💰 How much does LinkedIn Scraper cost?

LinkedIn Scraper starts at $4.99 per 1,000 results.

Your total cost depends on the number of records processed and the resources used during your actor runs. Larger datasets naturally require more processing than a small profile extraction task.

For a small research project, you can start with a limited number of URLs. For recurring workflows, the actor can support LinkedIn scraping automation and automated data collection.

⚖️ Is it legal to scrape LinkedIn?

Scraping legality depends on what data you collect, how you collect it, where you operate, and how you use the information.

This actor is designed to process publicly available information, but public availability does not automatically remove every legal or contractual restriction.

Before using extracted data, consider:

• LinkedIn's current Terms of Service.

• Applicable privacy and data-protection laws.

• Copyright and database-rights requirements.

• Rules governing commercial data collection.

• Your intended purpose for the collected information.

• Restrictions around personal or sensitive information.

• Requirements for storing, sharing, or contacting individuals.

For LinkedIn public data scraping, use responsible collection practices and only process information you are legally permitted to collect and use.

If your workflow involves personal data, consult appropriate legal counsel for your jurisdiction and use case.

🧾 LinkedIn Scraper input parameters

The actor accepts the following main inputs.

Parameter	Type	Required	Description
startUrls	Array	Yes	LinkedIn profile or company URLs to scrape
includeEmployees	Boolean	No	Finds publicly visible employees from supported company pages
proxyConfiguration	Object	No	Configures proxy routing for scraping reliability

🔗 Start URLs

startUrls accepts LinkedIn profile or company URLs.

You can provide one URL or multiple URLs depending on the size of your LinkedIn data collection task.

🧑‍🤝‍🧑 Include Company Employees

Set includeEmployees to true when you want publicly visible employees associated with a company page.

The resulting company record can include an employees array containing employee names, titles, and profile URLs.

⚙️ Proxy Configuration

Proxy configuration is optional and can route requests through supported proxy infrastructure.

This can help with reliability when processing larger LinkedIn scraping workloads.

⏳ During the Actor run

During an actor run, the scraper processes each supplied LinkedIn URL and extracts supported publicly available information.

I usually think of the process in three stages: URL processing, data extraction, and structured output.

First, the actor receives your profile or company URLs. It then processes each supported page and identifies available professional or company information.

For company pages, employee discovery runs only when the corresponding option is enabled. The actor then returns the collected records in a structured format.

If a URL cannot be processed successfully, the output can indicate an error status instead of silently treating the record as successful.

📝 Final Note

LinkedIn contains large amounts of publicly visible professional information, but manually collecting that information can become repetitive quickly.

With LinkedIn Scraper, we can turn profile and company URLs into structured datasets containing professional, company, and employee information.

Use the data responsibly, respect applicable rules, and focus your workflow on information you are permitted to collect and use.

❓ FAQ

What is LinkedIn Scraper?

LinkedIn Scraper is an automated LinkedIn data extraction tool that collects publicly available professional information from supported LinkedIn profile and company URLs.

What data can LinkedIn Scraper extract?

It can extract information such as names, headlines, summaries, locations, profile URLs, companies, job titles, experience, education, skills, certifications, languages, and available company information.

Can I scrape LinkedIn profiles?

Yes, the actor accepts public LinkedIn profile URLs through the startUrls input and extracts supported publicly available information.

Can I scrape LinkedIn company pages?

Yes. The actor accepts LinkedIn company URLs and can extract supported public company information.

Can it find company employees?

Yes. When Include Company Employees is enabled for a supported company URL, the actor can discover publicly visible employees associated with that company's public employee panel.

Is this a LinkedIn profile scraper?

Yes. It functions as a LinkedIn profile scraper, LinkedIn profile data scraper, and LinkedIn profile data extractor for supported public profile URLs.

Can I use LinkedIn Scraper for lead generation?

Yes, public professional data can support permitted LinkedIn lead generation, prospect research, sales research, and B2B prospecting workflows.

Can I use the output for recruitment?

Yes. The structured professional information can support recruitment research, hiring research, candidate research, and employment-data workflows, subject to applicable laws and platform rules.

Does it extract private LinkedIn information?

No. The actor is intended for publicly available information. It does not make private information publicly accessible.

Can I automate LinkedIn data extraction?

Yes. The actor can be integrated into automated workflows through its API, making it suitable for LinkedIn scraping automation, recurring data collection, and structured dataset generation.

Can I build a LinkedIn dataset with this actor?

Yes. Multiple supported URLs can be processed to create a structured LinkedIn dataset for research, analysis, or other permitted business purposes.

What is the difference between LinkedIn scraping and LinkedIn data extraction?

LinkedIn scraping refers to collecting information from LinkedIn pages, while LinkedIn data extraction focuses on turning that information into structured fields for analysis or storage.

Can I scrape LinkedIn search results with this actor?

This actor's documented input accepts profile and company URLs. It is not described here as a dedicated LinkedIn search-results scraper, so search-page scraping should not be assumed.

Does LinkedIn Scraper provide an API?

The actor can be run through the platform's API, allowing developers to integrate LinkedIn data extraction into applications and automated workflows.

What can I do with LinkedIn professional data?

Depending on your legal basis and intended use, professional data can support market research, competitor research, sales research, recruitment research, business intelligence, audience research, and dataset creation.