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5 Best LinkedIn Sales Navigator Scrapers: How to Scrape Leads in 2022

Last Updated: January 16, 2022

We are going to recommend some of the best LinkedIn sales navigator scrapers that you can use to extract information about your leads.
LinkedIn Sales Navigator Scraper
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We are all aware at this point that LinkedIn is the leader when it comes to helping businesses and professionals build relationships within their niche, and network in general.

Apart from basic features that you have access to along with every other user, LinkedIn does offer some advanced features and tools that make the closing of deals and networking a lot easier.

LinkedIn Sales Navigator is one of these tools. The main goal of this app is to help you search for prospective customers.

However, it can do more than this because it can help you carry out other tasks including being able to close deals from the feature list.

In this article, we’re going to talk to you about how you can extract business leads and prospective customers and to do so, you have to be strategic about extracting the data yourself because the service is not going to offer you an API that is tailored to these needs.

As a result, we are going to recommend some of the best LinkedIn sales navigator scrapers that you can use to extract information about your leads.

We are also going to include a guide on how to create your own custom scraper for Sales Navigator if you know how to code.

Best LinkedIn Sales Navigator Scrapers

So, we have talked about how you can develop your own web scraper for Sales Navigator, but if you don’t know how to code, and you aren’t someone who wants to learn anytime soon, then we’ve got some great LinkedIn web scrapers that you can make the most of.

These services have already been made and developed by experts so that you don’t have to do anything except implement your own personal strategy with them. Let’s take a look.


Ophantom buster

Phantombuster is easily one of the best if you want to be able to scrape profile details of your prospective leads. The great news is that you won’t have to write any code to be able to use their features, and you can use this tool as a Chrome browser extension, which means that you can start to scrape profile information with only a few links.

Apart from scraping profiles, these guys can help you find information like email addresses, and even comes with a scheduler so that you can gather new information every day to increase your chances of success.

Their pricing begins at $30 a month, and they offer a free trial.



Octoparse is another one of the best web scrapers out there when it comes to LinkedIn Sales Navigator, and they are one of the best if you’re someone who doesn’t know how to code.

They are a visual web scraper, and they provide their clients with point and click interfaces, so that you can quickly identify the right data that you want to extract.

They don’t specify their features for any particular website, and we don’t think that you’re going to find it difficult to scrape your information.

Within just a few clicks, you can convert the profiles you’ve got on sales navigator into an easy-to-read spreadsheet. They even have a free trial for 14 days, which is really generous.

Their pricing begins at $75 a month, and they support both desktop and the cloud, so you don’t even have to download anything if you don’t want to.

LinkedIn Sales Navigator

Linkedin Sales Navigator

This is the extension version of LinkedIn Sales Navigator, and it can be used to scrape any profile that is visible, and while it isn’t a free tool, you can use it for free to test it out and decide whether it works for you before committing to a paid plan.

One thing that we really like about this tool is that it can help you with a multitude of advanced features including email finding.

This extension is only compatible with Chrome, and you can start to use it once you have downloaded it even if you don’t share your credit card details right away.

Its pricing begins at $47 a month, and there is a free trial, but there are limitations with this free trial. Just remember that it is only compatible with Chrome.



Parsehub is another excellent choice as a LinkedIn Navigator web scraper, because they’re going to make your life really easy when it comes to helping you scrape LinkedIn for information.

They are a relatively generic web scraper, which means that you aren’t going to pay much for their features, and a lot of them are free.

We say generic, because it is not specifically designed for scraping LinkedIn Sales Navigator, but it can help you scrape contact details of leads within the navigator.

The great news is that with this web scraper you don’t have to write any code to take advantage of it. All you need to do is locate the information and click on it.

Eva Boot

Eva Boot

Eva Boot is definitely a worthwhile scraper for Sales Navigator, and they say that they have specifically developed their features to help you extract information from LinkedIn Sales Navigator.

The good news is that it is completely compliant with LinkedIn, which means that you aren’t going to get your account banned when using them.

They help you extract information, and they can clean and enrich leads, just note that you will need to add your active LinkedIn Sales Navigator account to make the most of this tool.

It is a paid tool, but they do offer free credit to new users, and then from here, you gain access to monthly free credits.

Their pricing begins at $29 a month, and it is available through a web browser, so you don’t have to download anything.

Overview of Scraping LinkedIn Sales Navigator

As we mentioned above, there isn’t an API offered to you as a user of LinkedIn sales navigator that is going to let you extract all the data that you need.

Of course, this begs the question, how can you do so? The answer is really simple: by web scraping. This process involves using a bot, commonly known as a web scraper to extract information on a specific website in a way that is automated.

Because the process is automatic, you can send out a lot of requests at the same time, which means that you can collect all the necessary data that you need in a few minutes, depending on how much data you need.

One thing that you need to know about scraping sales navigator is that LinkedIn doesn’t support this because the number of requests that you will need to send to do it is unnatural, and their antispam system is going to block it.

This means that you need to be able to bypass the blocks to be able to scrape the leads that you are interested in. The good news is that it isn’t difficult to get around this, and the tools that we have talked about below can help you with this.

Scraping Sales Navigator with Python

This next section of the article has been written for those that know a little bit about coding. This means that if you don’t know how to code, you can move on to our next section where we recommend the best web scrapers that have already been developed so that you can use them alongside LinkedIn Sales Navigator.

When it comes to the programming language that we recommend you use, there are a number of different languages that are compatible with JavaScript and can send out HTTP requests.

For this specific guide, we are going to use language written in simple code by Python, because Python is one of the most popular, especially when it comes to beginner coders, because it can be easily understood.

Remember that you will need to bypass the antispam system with LinkedIn in order to successfully scrape your content.

This is more relevant if you want to develop your own custom scraper, because you need to think about this when you are coding, otherwise it is going to be rendered useless.

This is why you need to successfully integrate proxies into your script as well. We also suggest that you set random delays between your requests, so it doesn’t come across as suspicious.

Sample Code

The code below is going to show you how you can easily scrape LinkedIn Sales Navigator using Python.

from selenium import webdriver  # to  control the chrome browser

import time

from bs4 import BeautifulSoup  # to parse the page source

import pandas as pd  # to create csv file of scraped user details

from import Options


options = Options()

options.add_argument("user-data-dir=C:\\Users\\Alpha\\AppData\\Local\\Google\\Chrome\\User Data\\linkedin")

bro = webdriver.Chrome(chrome_options=options)  # creating chrome instance

record = []

print("ENTER THE FILENME WHERE LINKS ARE STORED")  # filename where the url of user to be scraped are stored

file_name_link = str(input())

file = open(file_name_link + ".txt", "r")

print("ENTER THE FILENAME TO STORE LEADS")  # filename to store the details of the users

file_name = str(input())

for i in file:


bro.implicitly_wait(15)  # wait until the page load fully


ss = bro.page_source  # getting page source from selenium

soup = BeautifulSoup(ss, 'html.parser')  # parsing the page source with a html parser of Beautiful Soup



names = soup.find("span", {"class": "profile-topcard-person-entity__name Sans-24px-black-90%-bold"})

name = names.text


name = "NO"


desination = soup.find("dd", {"class": "mt2"})

desgination = desination.text

designation = desination.text


designation = "NO"

contacts = soup.findAll("a", {

"class": "profile-topcard__contact-info-item-link inverse-link-on-a-light-background t-14"})


website = contacts[0].get("href")


website = "No"


twitter = contacts[1].get("href")


twitter = "No"

record.append((name, desgination, website, twitter, i))  # temporariy storing a user details in a list

Final Thoughts

As you can see, there are many different ways to generate leads for your business through LinkedIn and capitalize on LinkedIn’s existing tool.

A lot of these web scrapers come with free trials or free features so that you can make the most of them before you decide which one to work with over a long period of time.

You also have the option of developing your own web scraper, depending on your skill level when it comes to coding. Good luck!

Written by Jason Wise

Hi! I’m Jason. I tend to gravitate towards business and technology topics, with a deep interest in social media, privacy and crypto. I enjoy testing and reviewing products, so you’ll see a lot of that by me here on EarthWeb.