US employers struggle to find workers to keep up with the economy’s recovery from the pandemic-caused recession. Although the job market is picking up all over the US, the unemployment rate still fell from 5.8% to 6.1% in May. Employers can close the labor gap is to utilize data from professional social networking sites like LinkedIn.
LinkedIn offers employers a wealth of information, from industry insights to data on competitors, jobs, and professionals. By extracting LinkedIn data, you can automate your recruitment process and find the best candidates that suit your needs.
What is LinkedIn Data Scraping?
The fastest way to extract large amounts of LinkedIn public data is through data scraping. A scraper tool can accumulate information from the site and then summarize it into a structured format to provide you with actionable insights. Anyone with a decent command of computer programming skills can develop a DIY scraper to extract LinkedIn data. However, you need to have solid technical skills as there is a vast amount of data, platform restrictions, and ethical considerations to navigate LinkedIn.
Unless you’re a data professional, it would be challenging to perform LinkedIn data scraping on your own. Although there has been a data scientist shortage in the last few years, the rise of remote arrangements now gives you more access to data scientists who can help you. Likewise, these scientists can now pursue business data analytics specialty tracks through distant learning.
Today, prestigious universities across the country are offering online courses on the subject. For example, an online master’s program in business data analytics teaches remote students to become adept at looking for trends, making decisions, identifying opportunities, combining operational data with analytical tools, and presenting complex information – such as data from LinkedIn scraping. In addition, they’re able to build proficiency in coding, machine learning, big data, data mining, and deep learning that can drive stronger business decisions.
If you’re unwilling to invest the time and effort to create your tools, it’s best to hire an expert who can effectively execute the data scraping functions you need. Companies offering professional scraping services can utilize various data points, data quality, and aggregation scales, so it’s essential to choose the right data partner to suit your organization. Two leading LinkedIn scrapers include:
Proxycurl is a LinkedIn scraping API designed for developers. It offers a LinkedIn Profile General Resolution Endpoint, Person Profile Endpoint, Company Profile Endpoint, and Job Profile Endpoint using LinkedIn URLs. The LinkDB PostgreSQL database also provides pre-crawled LinkedIn person profiles in the US and Singapore and LinkedIn company profiles globally.
Pros: The API crawls are dispatched on-demand and are made in real-time for the latest data. Proxycurl also crawls at scale, scraping about a million pages per day. In addition, it can crawl popular websites like LinkedIn by bypassing recaptchas and bot detection to parse raw data and deliver structured data.
Cons: There is limited functionality in running discovery searches and extracting profiles using search criteria.
People Data Labs
People Data Labs (PDL) offers a pre-collected data solution that provides datasets on people and companies. PDL features include an Enrichment API and Search API to generate matching profiles or filter pools of profiles to fit specific search criteria. In addition, their Data Licensing feature gives clients annual access to datasets, although these advanced functions are pay-as-you-go.
Pros: PDL offers large datasets on person profiles, so it’s a comprehensive solution. Its plug-and-play model allows for immediate consumption, but it would help to undergo an online data analyst course to understand better the data presented.
Cons: At $0.25 per match, it’s expensive to utilize PDL services, especially if you’re more interested in company profiles. The pre-collected database also compromises fresh data, while security issues — as experienced by the PDL data breach in 2019 — may compromise your data.
The Verdict: Proxycurl
As we compared before with regards to the global company profile dataset, Proxycurl remains the outstanding solution for quality, real-time data. In terms of understanding LinkedIn profiles, we strive to cultivate large datasets from active profiles and perform regular updates to keep everything fresh and easy to use.