Scraping data from LinkedIn has become extremely difficult in the last few years – especially at Scale. Tools like Phantombuster can scrape hundreds of profiles a day – but how can you scale it up to tens of thousands a day for your ambitious projects? You may already try services like proxycurl, but more often than not, their data is outdated (scraped months ago).
Using Python, in 2018, I built the "one of its kind" system for large-volume LinkedIn scraping projects. The system allows me to
✅ extract LinkedIn profiles from LinkedIn searches (including work emails, standard or sales navigator searches)
✅ extract LinkedIn company profiles from LinkedIn searches (any volume, standard or sales navigator searches)
✅ Extract employees data of specific companies on LinkedIn (big companies? No problem!)
✅ Enrich contact lists with valuable data from LinkedIn
✅ Convert LinkedIn Sales Navigator URLs into regular/public URLs
People have used my service once use it again. Here’s what they said:
👍Cung is professional and highly capable. He can do things that many others will say are impossible. Worth every penny. Stop scrolling, and start hiring! – Mark
👍Cung is a master. Excellent skills, fantastic communicator, and an exceptionally talented engineer. If he can't do it, no body can. Highly recommend! – Spencer
👍Cung is just phenomenal! He is fast, reliable, accurate and needs only to be pointed to a project and set to go. He thinks on his feet, asks just the right questions and gets the job done. Just fantastic. Thank you Cung! – Peter Barry
Ready to get your LinkedIn data at scale? Let's connect.