LinkedIn has emerged as the world’s largest professional network with over 1 billion users, creating an unmatched repository of business data and potential leads. For companies seeking to extract this valuable information, LinkedIn scraping tools have become essential assets in their data collection arsenal.

In this guide, you’ll discover which LinkedIn data scrapers deliver actual results in 2025 based on our thorough analysis of both free and paid options.

Understanding LinkedIn Scraping: Basics and Legality

LinkedIn scraping extracts data automatically from LinkedIn profiles, company pages, and job listings. Think of it as a digital mining operation where specialized tools gather information that would require hours to collect manually. This data proves invaluable for businesses making data-driven decisions across different departments.

What is LinkedIn scraping?

LinkedIn scraping uses automated software or scripts to extract structured information from LinkedIn’s vast database systematically. Rather than manually browsing and copying information, these tools quickly collect and organize data from public profiles. The extracted information typically includes professional details, company information, and sometimes contact data.

Businesses turn to LinkedIn scraping for several key purposes:

1. Lead generation: Sales teams identify potential customers by extracting contact details and company information to create targeted prospect lists

2. Market research: Analysts study industry trends and market dynamics through profile data

3. Recruitment: HR departments find suitable candidates by extracting information based on experience, location, and industry

4. Competitive analysis: Companies gain insights into competitors’ activities and strategies

The value of LinkedIn data cannot be overstated. With nearly 1 billion users from over 200 countries, it serves as a treasure trove of professional information. This data helps businesses work smarter by automating repetitive tasks and providing actionable insights.

What Data to Scrape From LinkedIn

LinkedIn company page:

● LinkedIn page URL

● Company name

● “About” description

● Website URL

● Headquarters location

● Foundation year

● Company type

● Company size

● Industries it specializes in

● Showcase page URLs

● Affiliated companies

● Number of employees

LinkedIn profile:

● First name

● Last name

● Headline

● “About” section

● Job title

● Current company details

● Country

● Number of followers

● Industry

● Company LinkedIn URL

● Educational qualifications

● Skills

● Location

● Certifications

● Job positions history

● Honors

● Languages

Top 5 LinkedIn Scrapers

1. Thordata

use case

If you’re looking for versatility, Thordata should be your go-to LinkedIn scraping tool. While most scraping tools work on their own, Thordata specializes in providing proxies that allow you to scrape LinkedIn without facing geographic or IP blocking issues. This means that Thordata ensures your scraping activities are secure, private, and, most importantly, untraceable.

Speed: Thordata provides high-speed proxies that ensure fast data extraction.

Security: Using proxies protects your IP address from being banned by LinkedIn, giving you an extra layer of security when scraping.

Ease of integration: Thordata’s proxies are easy to set up and integrate with your LinkedIn scraping tools, ensuring smooth operation.

2. ScraperAPI

scraperapi

ScraperAPI stands out as a robust web scraping API designed to simplify data extraction from challenging websites like LinkedIn. It effectively tackles common scraping hurdles by managing proxy rotation, handling CAPTCHAs, and rendering JavaScript-heavy pages, ensuring a high success rate for your LinkedIn data collection. Whether you’re looking to extract LinkedIn profile data for lead generation, company information for market research, or job postings for recruitment, ScraperAPI provides a reliable and scalable solution. It minimizes the need for extensive proxy management or anti-bot bypass efforts on your end, allowing you to focus on utilizing the valuable data.

Key Advantages:

● Anti-Detection Features: Automatically handles proxy rotation, CAPTCHAs, and JavaScript rendering, making it ideal for bypassing LinkedIn’s sophisticated anti-scraping mechanisms.

● Scalability: Designed to handle large volumes of requests, enabling efficient and extensive data extraction from LinkedIn profiles and company pages.

● Ease of Use: Offers a straightforward API, simplifying integration into your existing data pipelines without requiring deep technical expertise in web scraping infrastructure.

3. LinkedIn Scraper (GitHub)

github

LinkedIn Scraper is a free and open-source Python library available on GitHub. With over 1.8k GitHub stars and thousands of monthly downloads, it represents the most popular Python LinkedIn scraping tool.

LinkedIn Scraper exposes an API to retrieve data from company or individual pages in Python. Behind the scenes, it uses Selenium to automate user interaction on LinkedIn pages.

4. Linked Helper

linked helper

Linked Helper is a desktop application for LinkedIn automation that also has data-scraping capabilities. Specifically, it provides a LinkedIn scraping tool to extract information from profiles of people and companies. This can retrieve phones, emails, message history, and more, download them in CSV format, and send them to a third-party service.

5. Dripify

dripify

Dripify is a LinkedIn automation and prospecting cloud platform that supports sales professionals in automating various tasks on LinkedIn. The service offers several features and tools, including a LinkedIn scraper. That allows users to retrieve email addresses, phone numbers, and more from LinkedIn profile pages and export the data to a CSV file.

How to Choose the Right LinkedIn Scraping Tool for Your Needs

Selecting the ideal LinkedIn scraping tool demands consideration of several key factors beyond basic functionality. Your specific requirements should drive this decision, as the right tool dramatically impacts your data extraction success.

Assessing your technical expertise level

Evaluate your technical capabilities honestly before selecting a tool. Browser extension LinkedIn scrapers like Data Miner and Web Scraper work perfectly for individuals or small teams without coding experience. Developers benefit from open-source GitHub projects that offer flexible, customizable options—these come free but require significant technical knowledge. If Python falls within your comfort zone, tools providing programmatic access deliver greater control over the scraping process.

Determining your data volume requirements

Quantify your data extraction needs precisely. LinkedIn’s security measures allow viewing only 50-80 profiles daily with a standard account. Need thousands of profiles? Enterprise-level tools with sophisticated anti-detection capabilities become necessary. Small projects with limited data requirements might find lightweight tools sufficient.

Evaluating integration needs with other systems

The flow of extracted data into your existing workflow matters significantly. Look for tools offering:

● Direct CRM integration that syncs lead generation data instantly

● Export formats like CSV, JSON, or Google Sheets compatibility

● Webhook connections to automate data workflows

Consider whether real-time data access or periodic batch exports better align with your operational requirements.

Balancing budget constraints with scraping goals

Weigh costs against expected returns carefully. One-time projects benefit from tools with free trials or pay-as-you-go options. Continuous lead generation often justifies subscription-based premium tools. Remember that “free” open-source options still incur costs through time investment and technical maintenance. For serious business users running outreach campaigns, the quality of extracted email verification often justifies premium pricing.

Conclusion

Important ethical boundaries exist as well. Creating fake accounts, using fake payment methods, or extracting private information crosses into illegal territory. When scraping personal data, you must comply with privacy laws such as GDPR in the EU or CCPA in the US.

If you’re looking to scale up your LinkedIn scraping operations and avoid the pitfalls of IP blocking and geographical restrictions, Thordata is a solid choice. Its seamless integration with various scraping tools, combined with high-speed proxies, makes it the go-to solution for serious LinkedIn data extraction.

Frequently asked questions

Is LinkedIn scraping legal?

Yes, LinkedIn scraping is legal as long as you comply with LinkedIn’s terms of service. However, it’s important to use proxies like Thordata to avoid violating LinkedIn’s anti-scraping measures.

Why should I use a proxy for LinkedIn scraping?

Using a proxy prevents LinkedIn from detecting and blocking your IP address. This allows you to scrape large amounts of data safely and securely, especially if you’re using tools like Thordata.

Can I scrape LinkedIn profiles for free?

Yes, there are free tools like DataMiner that offer basic scraping features. However, if you need advanced features, automation, or large-scale scraping, you may need to use a paid service like Phantombuster or Thordata.

About the author

Jenny Avery

Content Specialist

Jenny is a Content Specialist with a deep passion for digital technology and its impact on business growth. She has an eye for detail and a knack for creatively crafting insightful, results-focused content that educates and inspires. Her expertise lies in helping businesses and individuals navigate the ever-changing digital landscape.

The thordata Blog offers all its content in its original form and solely for informational intent. We do not offer any guarantees regarding the information found on the thordata Blog or any external sites that it may direct you to. It is essential that you seek legal counsel and thoroughly examine the specific terms of service of any website before engaging in any scraping endeavors, or obtain a scraping permit if required.