How to use a LinkedIn scraper in 2025: THE Guide

Whether you’re in sales, marketing, business development, partnerships, or HR, it’s safe to assume that you use LinkedIn one way or the other, especially if you work in B2B. 

What started off as a simple social platform for professionals, LinkedIn has become one of the most powerful tools for networking, prospecting, and outreach in 2025. With over 900 million users, chances are that your target prospects, partners, or talents already have profiles on this social platform. 

Moreover, these profiles contain valuable information about prospects and their companies that sales and marketing teams can leverage to identify targeted leads, determine the best time and message to engage with them and explore potential ways to personalize communication. 

However, going through thousands of profiles and sourcing relevant prospect data manually can take ages, and that’s where LinkedIn scrapers come into play. 

In this article, we’ll take a closer look at how LinkedIn scraping works and how businesses can leverage this powerful tool to supercharge their prospecting and outreach efforts in 2025. 

LinkedIn scraping 101: What is it?

Let’s start with the basics—what is LinkedIn scraping? 

In essence, LinkedIn scraping involves automatically collecting structured information from personal profiles and company pages on LinkedIn.

To do this, businesses use various LinkedIn scrapers, which are different types of software designed to automatically extract relevant data from LinkedIn profiles, including job titles, company information (name, size, industry, revenue), and, most importantly—contact data like emails and phone numbers.

This way, businesses can significantly expand their contact lists with targeted prospects much quicker, increasing the audience for their sales and marketing efforts. 

There are myriad types of LinkedIn scrapers aimed at different levels of technical expertise and business needs, but all of them can be split into three main categories: 

• Cloud-based: These LinkedIn scrapers are built on APIs, hence requiring no software installation from the user’s end. They are quite hassle-free, suitable for large-scale scraping, and are usually accompanied by extra features such as data enrichment. 
• Browser-based: Such scrapers work through browser extensions and actually scrape the data in real time when users browse LinkedIn profiles. They are easy to install and use, and hence, teams of smaller sizes or individual sales/marketing professionals usually find them the most convenient.
• Desktop-based: Normally, these involve a certain level of coding, such as Python scripts. Users can tailor desktop-based scrapers to their exact business needs, which are often accompanied by extensive data extraction capabilities but also require technical skills to set up and maintain.

Regardless of which tool you use for scraping data, keep in mind that LinkedIn is a powerful B2B tool that can be leveraged in many ways to grow your brand, generate leads, and increase sales.

Why scrape data from LinkedIn?

LinkedIn is a real treasure trove of data insights about possible leads, clients, and even the competition. But what makes scraping data off LinkedIn totally worth it? Let’s break down the key reasons why so many businesses scrape LinkedIn data from relevant profiles:

How to use a LinkedIn sales navigator scraper?

Now that we’ve covered the basics, time to put theory into practice and explore how to scrape LinkedIn data with different types of software, depending on your business needs. 

Free LinkedIn scrapers

Unlike virtually every other form of B2B software, there are quite a few completely free LinkedIn scraping tools out there that can help businesses extract the ‘basic’ data such as job title, location, company size, company revenue, and most importantly—email and phone number.

These tools are more often than not Chrome extensions and are great for teams just starting or with tight budgets. 

Findy is a great example of a free LinkedIn scraper that operates with minimal effort—no coding skills, no setup, simply download the extension and let it run in the background:

The way tools like Findy work is extremely simple—as users browse through LinkedIn profiles, these extensions will automatically extract whatever information on prospects and their companies they can find. 

Some of the more advanced extensions like Findy will also validate your emails in real-time to ensure your bounce rates stay low, without harming your email deliverability. Afterward, simply export your scraped prospect and company data into a CSV file or manually add them to your Excel or CRM. 

While such tools may slightly lack in terms of advanced features compared to the paid alternatives that we’ll discuss below, If you’re simply looking to extract basic prospect data and contact info to build prospect lists for your outreach, look no further and save your money. 

Paid LinkedIn scrapers  

On the other hand, there’s also no shortage of paid tools out there to help businesses scrape LinkedIn data. 

After browsing through several of the ‘top’ paid options on the market, the features they mention that free Chrome extensions don’t offer are faster bulk extraction, at times more data points, integration capabilities with CRMs, and available customer support. 

However, such tools are usually expensive with many other unnecessary features that small teams simply do not require, so whether to opt for a paid LinkedIn scraper solely depends on your needs and budget. 

At the end of the day, if all you’re really looking for is a few hundred or thousand validated emails and basic data on prospect and company information of LinkedIn users, we’d highly recommend sticking with a free tool instead. 

Web LinkedIn scraping APIs  

Finally, it’s worth mentioning that a good chunk of such ‘advanced’ paid LinkedIn scrapers require minimum to expert-level coding skills, often operated on Python: 

Source: ScrapFly

So, if the image above gives you a bit of anxiety just looking at it like it does for me, such tools are probably not the best option for you, unless you have an IT professional on your team willing to help with LinkedIn scraping. 

In all fairness, they have the potential to extract huge chunks of more hidden data such as company metrics, but they are quite resource-consuming to install and maintain. While they may give more control over your LinkedIn scraping process, their use can be regarded as overkill for smaller teams.

So then we face a dilemma—code-requiring scrapers are too advanced to operate without an IT professional by your side but they do provide more advanced ‘hidden’ information, whereas no-code paid tools don’t offer those advanced scraping capabilities yet are quite costly. 

Where to scrape LinkedIn data for lead generation? 

Once you’ve decided to gear up with one of the LinkedIn scrapers we’ve discussed, here are the best ways to utilize them to build hyper-targeted prospect lists, be it for sales, marketing, BD, or HR activities: 

1. Sales Navigator → use this premium LinkedIn feature to leverage the numerous search filters, and then extract the contact info one by one or in bulk via your tool;   
2. Post likers and commenters → a neat trick is taking a look at those who’ve engaged with your company’s or industry-related posts, as that could signify potential interest from their side; 
3. Competitor’s followers → go for a stroll through your competitor’s accounts to scrape LinkedIn followers that could potentially be in the market for such a solution or an alternative now or in the future; 
4. Group members → LinkedIn has countless different groups where users with similar personal interests and professional attributes can network, share knowledge, and learn, so depending on your product, you could target relevant groups. 
5. Event attendees → when it comes to B2B virtual events such as webinars, conferences, and workshops, organizers will undoubtedly advertise them on LinkedIn; users that engage with such posts and ads are likely to be interested in your solution/expertise. 

Alright, now that you know where to grab LinkedIn data for leads, let’s jump into the top scraping tips for 2025 to make sure you’re doing it right and staying ahead!

What are the LinkedIn scraping best practices in 2025?

There are certain best practices everyone should follow when scraping LinkedIn data to stay legally and ethically in the green (more on that shortly):

• Stay compliant → pace your data-scraping efforts, do not scrape aggressively, and don’t use tools that promise to extract any private information beyond simple contact and company data to avoid raising any red flags by LinkedIn; 
• Enhance data usage → focus on quality over quantity when scraping LinkedIn data. In any case, targeted and relevant outreach will always bring in better results than the ‘spray and pray’ approach. 

At the end of the day, LinkedIn should be used for what it was designed to be—a place for professionals to network, connect with each other, and potentially engage in business. 

This is why it’s best to prioritize building up your personal LinkedIn profile, establishing your professional brand, engaging with valuable posts, and building relationships, which in turn will grow your social selling index.  

How to fuse LinkedIn data with outreach?

Now, in the context of best practices to make the most of your LinkedIn scraping efforts, the biggest recommendation involves integrating your chosen scraping tool with a reliable outreach tool to facilitate seamless data flow and automated engagement. 

This way, businesses can take the scraped data, merge it with their CRM or sales outreach software, and run automation campaigns in a matter of seconds, enabling them to take immediate action with the data scraped.

While most of those free Chrome extensions mentioned are standalone tools, they are virtually all created by such outreach suites. For instance, Findy seamlessly integrates with Reply.io to add extracted LinkedIn data directly to your sales campaigns with a click of a button: 

This way, after scraping data from prospects on LinkedIn, Reply.io users can right away add them to their multichannel outreach campaigns, now having the ability to engage with them not only through LinkedIn but also via email, cloud calls, WhatsApp, and more:

Moreover, given that Reply.io offers a native lead database with hundreds of millions of profiles, should your prospects already be in the database — Reply.io will automatically enrich their customer profiles with any extra data available.

The best part? 

With our brand new AI SDR agents, you won’t even have to worry about setting up these multichannel sequences or crafting messages—AI will do that for you. It will determine the best channels and timing to connect with your prospects (taking into account the reason for outreach and other details), generate hyper-personalized messages for each unique lead (based on available data points), and then handle responses on your behalf, all on autopilot. 

With these advanced AI features and automations, what starts off as simply browsing a LinkedIn profile can result in a new customer or partner acquired in a matter of a few clicks. Sounds too good to be true? Give Reply.io a free 2-week spin and see for yourself! 

Is LinkedIn scraping legal? 

Let’s address the big elephant in the room:

In short, it’s in the gray area. Here is what you should know:

• Technically speaking, mass scraping in and of itself is against LinkedIn’s terms of service. In practice, though, a lot of companies use scraping tools because the logic is public information should be public, and then again, LinkedIn is pretty imperfect in enforcement.
• Some of the more advanced, paid tools (especially those using code) at times access the more private information, which probably pushes the boundaries legally and ethically, whereas the more lightweight tools like free Chrome extensions generally scrape basic data, which offers more compliance with legal standards. 
• LinkedIn has certain connection requests, messaging, and extraction limits that businesses should follow to avoid the infamous LinkedIn ‘jail’. At times, users may be lucky enough to get a warning first: 

• If you’ve gone beyond the limits of LinkedIn scraping, you run the risk of getting your account restricted or, in the worst case, banned. Truth be told, I once got my account temporarily restricted for 24 hours when I was scraping emails of potential speakers to invite to our upcoming sales conference, but I learned my lesson and turned down the volume from then on. Years have passed since, and I haven’t witnessed any issues since. 
• While concrete information on the exact limits is impossible to find, the agreed consensus among LinkedIn specialists is that you can safely scrape LinkedIn data as long as you stay under 80 profiles per day on a free account and 150 profiles with a premium account. 

In summary, keep your LinkedIn scraping volume low and steady, prioritize quality over quantity, and leverage a reliable and most importantly compliant tool that doesn’t go out and beyond to export private information, follow the above-mentioned best practices, and you’ll be fine. 

The future of LinkedIn data scraping  

Scraping LinkedIn prospect and company information has become a critical tool for B2B businesses in 2025 given the growing importance of data in sales and marketing processes, and decision-making.

When leveraged correctly, businesses can leverage the number one professional social networking channel to find targeted prospects, partners, and talents. With modern technology, LinkedIn scraping tools seamlessly integrate with CRMs and outreach suites to facilitate data flow and automate the entire prospecting & outreach process, and data will only keep getting more important as time passes. 

The rise of AI has already made LinkedIn scraping smarter and more adaptive, and will undoubtedly get even more efficient very soon with more companies pushing the boundaries of leveraging these powerful algorithms for B2B processes. 

It’s also very important to remain legally and ethically above board at all times when scraping LinkedIn data—use reliable scraping tools responsibly, focus on data available publicly, and keep an eye for any changes in LinkedIn’s terms of service, which are most likely only going to get stricter in the near future.