LinkedIn Scrapers are quite in demand in 2024. LinkedIn has the largest pool of corporates available today. So obviously, you can find many people on this platform who could have the same interests as yours. But websites like LinkedIn can serve you with data that can be used for selling goods and products.
LinkedIn has more than 800 million active users where people share their work experience, skills, and achievements daily. If you scrape and use this data wisely then you can generate a lot of leads for your business. Of course, this data can also be used for other purposes like finding the right candidate for the job or maybe enriching your own CRM.
In this article, we will talk about the best LinkedIn scrapers in the market. Using these scrapers you can scrape Linkedin at scale.
Advantages of using LinkedIn Scrapers Instead of Collecting Data Manually
- You will always stay anonymous. On each request, a new IP will be used to scrape a page. Your IP will always be hidden.
- The pricing will be less as compared to the official API.
- You can get parsed JSON as the output.
- 3rd Party APIs can be customized according to demands.
- 24*7 support is available.
Challenges of Scraping LinkedIn at Scale
If you have researched enough, you must by now know that there are tools with which you can scrape a few hundred profiles/jobs without any problem. These tools either use your LinkedIn Profile/LinkedIn Sales Navigator which makes them limited in terms of their abilities to extract data.
The main problem arises when you scrape LinkedIn at scale. We have discussed some of the challenges of scraping LinkedIn at Scale.
- Legal and Ethical Issues:
- User Agreement Violation: LinkedIn’s terms of service prohibit the scraping of their website. Engaging in this activity can result in legal action against the perpetrators.
- Privacy Concerns: Extracting user data without consent violates privacy norms and can lead to severe repercussions.
- Technical Challenges:
- Rate Limits: LinkedIn monitors and restricts frequent and massive data requests. An IP address can be temporarily banned if it makes too many requests in a short period.
- Dynamic Content Loading: LinkedIn uses AJAX and infinite scrolling to load content dynamically. Traditional scraping methods often fail to capture this kind of content.
- Complex Website Structure: LinkedIn’s DOM structure is intricate, and elements might not have consistent class or ID names. This can make the scraping process unstable.
- Captchas: LinkedIn employs captchas to deter automated bots, making scraping even more challenging.
- Cookies and Sessions: Managing sessions and cookies is necessary to mimic a real user browsing pattern and avoid detection.
- Maintenance Issues:
- Frequent Changes: LinkedIn, like other modern web platforms, frequently changes its user interface and underlying code. This means scrapers need constant updating to remain functional.
- Data Quality: Ensuring the scraped data’s accuracy, relevancy, and completeness can be challenging, especially at scale.
- Infrastructure and Costs:
- Large-scale Scraping: Scraping at scale requires a distributed system, proxy networks, and cloud infrastructure, increasing the complexity and costs.
- Data Storage: Storing vast amounts of scraped data efficiently and securely is another challenge.
- Anti-Scraping Mechanisms:
- Sophisticated Detection: LinkedIn employs sophisticated bot detection mechanisms. Mimicking human-like behavior becomes essential to avoid detection.
- Continuous Monitoring: Even if you successfully scrape data, LinkedIn monitors for suspicious activities and can block accounts or IP addresses.
Advantages of using LinkedIn Scrapers Instead of Collecting Data Manually
- You will always stay anonymous. On each request, a new IP will be used to scrape a page. Your IP will always be hidden.
- The pricing will be less as compared to the official API.
- You can get parsed JSON as the output.
- 3rd Party APIs can be customized according to demands.
- 24*7 support is available.
5 Best LinkedIn Scrapers [In 2024]
We will be judging these LinkedIn lead Scraper APIs based on 5 attributes.
- Scalability means how many pages you can scrape in a day.
- Pricing of the API. What is the cost of one API call?
- Developer-friendly refers to the ease with which a software engineer can use the service.
- Stability refers to how much load a service can handle or for how long the service is in the market.
- Data Quality refers to how old is the data.
Scrapingdogâs LinkedIn Scraper API
Scrapingdog offers a simple and easy-to-use LinkedIn Scraper API. This API can be used to scrape either a personâs profile or a company profile from Linkedin. Other than this Scrapingdog offers LinkedIn Jobs scraper to scrape job data from this platform.
Scalability
Well, you can scrape around 1 million profiles from Scrapingdog’s LinkedIn Scraping API be it for profile or jobs.
Pricing
The enterprise pack will cost $1k per month and you can scrape 110k profiles. Each profile will cost $0.009.
Developer Friendly
The documentation is self-explanatory and the user can test the API directly from the dashboard without setting up any coding environment.
Stability
Scrapingdog has been in the market for like 4 years now and has more than 200 users which proves its stability in scraping LinkedIn at scale.
Data Quality
They will scrape fresh data always.
Here’s a video that demonstrates how you can use the API to scrape data at scale.
Brightdata LinkedIn Scraper
Brightdata, along with its large proxy network also provides LinkedIn Scrapers.
Scalability
Their scalability is great but the error rate might go up due to disturbances in their proxy pool. Bright data goes down frequently.
Pricing
Their solution could be a little expensive. The per-profile cost is around $0.05.
Developer Friendly
The whole documentation is quite easy to read and there are request builders which can help you get started quickly.
Stability
No doubt Brightdata has the biggest proxy pool in the market but they frequently go down sometimes. But their overall their infrastructure is quite solid.
Data Quality
They will scrape fresh data always.
Read More: 5 Best Bright Data Alternatives for Web Scraping
Phantombuster
Phantombuster is another Linkedin scraper provider. Recently they have changed their messaging from web scraping services to lead generation services.
Scalability
Using Phantombuster you can only scrape 80 profiles in a day that too with your own credentials and cookies. This will lead to the blocking of your account. It cannot be used for mass scraping.
Pricing
Pricing is not clear for this service on their website.
Developer Friendly
No documentation is available on the website.
Stability
They are simply using your cookies to scrape the LinkedIn profile. This service is not at all stable because, after 50 profiles, LinkedIn will block your account and the cookies will no longer remain valid.
Data Quality
You will get fresh data.
People Data Labs
PDL provides data enrichment technology. You can use their APIs to find valuable insights for any prospect.
Scalability
PDL is designed for small projects. You cannot scrape thousands of profiles with it in a short time frame. So, the scalability is not great.
Pricing
It will cost you $0.28 per profile. This makes them very very costly.
Developer Friendly
The documentation is nice which makes them developer-friendly.
Stability
If you are ok with old data then it is stable otherwise stability is out of the park if you need live fresh data.
Data Quality
The data you get will be from an old database because they don’t scrape it fresh. They have data sources which they renew after some interval of time.
Coresignal
Coresignal is another great LinkedIn scraper. You can scrape a personâs profile as well as the company profile.
Scalability
They provide data from a purchased database. So, you cannot scrape live profiles. If you want to scrape live data then you will have data from the web except from Linkedin. So, this is not scalable.
Pricing
Their minimum pack will cost $800 but the number of credits you will get is not clear on the pricing page.
Developer Friendly
There is no documentation available on their website which makes this service difficult to use.
Stability
They have a large database of companies as well as people. This service is stable for someone who is ok with stale data, but not recommended for anyone who needs fresh data.
Data Quality
The data you get will be from an old database.
Final Verdict
We have compiled the aforementioned report considering various factors. This report is the result of a comprehensive analysis of each API. Although they may appear similar at first glance, further testing reveals that only a small number of APIs (one or two) are stable and suitable for production purposes.
Therefore, it is essential to evaluate the options based on your specific requirements and choose the most appropriate one from the given list.
