🔥 Linkedin Companies & Profiles Bulk Scraper

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👁 LinkedIn Premium Actor — by Bebity

🔁 Version 10 — Rebuilt 100% from scratch · June 2026

The entire scraper has been rewritten from A to Z. This is the tenth major version of Bebity's LinkedIn scraper — the whole scraping engine was thrown away and rebuilt from the ground up to talk directly to LinkedIn's modern interface (no brittle HTML scraping, no legacy glue). It is faster, far more reliable, and returns more complete data than any previous version.

This rebuild is final — done for good. The architecture is stable; from here we only add data and polish on top of it.

LinkedIn Premium Actor extracts complete, structured data from LinkedIn — both people profiles and company pages — from a simple list of search terms, names, or URLs. Give it keywords ("growth marketer"), full names ("Jane Doe"), or direct LinkedIn URLs, and get clean JSON back: identity, experience, education, skills, certifications, company size, locations, and more.

It is built for recruiters, sales teams, marketers, and data analysts who need reliable LinkedIn data at scale, without maintaining a scraper themselves.

What can LinkedIn Premium Actor do?

• 🔍 Search or direct lookup — pass a keyword/name to search, or a LinkedIn URL / /in/{slug} / /company/{slug} to fetch one exact profile or company.
• 📚 Bulk input — one list mixing search terms, names, and URLs. Each entry is routed automatically.
• 🌍 Location filter — narrow people searches by one or several locations (typed place names or raw LinkedIn geo IDs).
• 👤🏢 Profiles & companies — switch between people and company pages with a single field.
• 🧩 Pick your sections — choose exactly which profile sections to scrape (about, experience, skills, languages…) for faster, cheaper runs.
• 📦 Clean, consistent JSON — field names are harmonized across profiles and companies, every field documented below.

Together with the Apify platform, you also get scheduling, a full API, integrations (Make, Zapier, n8n…), monitoring, proxy rotation, and storage — all without writing infrastructure code.

What data can LinkedIn Premium Actor extract?

From a LinkedIn profile

From a LinkedIn company

How to scrape LinkedIn data — step by step

1. Open the actor and pick an Action: Profiles 👤 or Companies 🏢.
2. In Search terms, names or URLs, add your entries — e.g. growth marketer, Jane Doe, or https://www.linkedin.com/in/janedoe.
3. (Optional) Set a Limit per search term, add a Location filter, or restrict Profile data to scrape.
4. Click Start ▶️.
5. When the run finishes, download your results from the Output / Storage tab as JSON, CSV, Excel, or HTML, or pull them via the Apify API.

Input

The actor takes the following input. Open the Input tab for the interactive form, or pass JSON via the API.

Input example

{
"action":"get-profiles",
"keywords":[
"growth marketer",
"Jane Doe",
"https://www.linkedin.com/in/janedoe"
],
"limit":10,
"location":["Paris","United States"],
"profileFields":["about","experience","skills"]
}

Output

You can download the dataset produced by LinkedIn Premium Actor in any format — JSON, CSV, Excel, or HTML — or access it through the Apify API. Every field is documented in the actor's output schema, and the Console shows two clean table views: Profiles and Companies.

Profile output example

The example below is maximal — it shows every field the actor can return for a profile. A real run includes whichever sections the person has actually filled in, and whichever you requested via profileFields.

{
"vanityName":"janedoe",
"linkedinUrl":"https://www.linkedin.com/in/janedoe",
"firstName":"Jane",
"lastName":"Doe",
"headline":"Data & Cloud Architect",
"location":"Greater Toulouse Metropolitan Area",
"industry":"IT Services and IT Consulting",
"urn":"urn:li:member:123456789",
"summary":"Passionate about turning data into business value across cloud and BI projects.",
"profilePictureUrl":"https://media.licdn.com/dms/image/v2/EXAMPLE/profile-displayphoto-shrink_800_800/0/0000000000000",
"coverImageUrl":"https://media.licdn.com/dms/image/v2/EXAMPLE/profile-displaybackgroundimage-shrink_350_1400/0/0000000000000",
"followersCount":1261,
"connectionsCount":500,
"experience":[
{
"title":"Data & Cloud Architect",
"companyName":"Example Consulting",
"employmentType":"Full-time",
"startDate":"Jan 2021",
"endDate":"Present",
"duration":"5 yrs 6 mos",
"location":"Toulouse, France",
"description":"Lead data architecture and BI delivery for enterprise clients."
},
{
"title":"BI Engineer",
"companyName":"Example Corp",
"employmentType":"Full-time",
"startDate":"Jan 2008",
"endDate":"Dec 2020",
"duration":"12 yrs",
"location":"Toulouse, France"
}
],
"education":[
{
"schoolName":"Example University",
"degreeName":"Master's degree",
"fieldOfStudy":"Information Systems",
"startDate":"2005",
"endDate":"2006",
"activities":"Data science club, student association"
}
],
"certifications":[
{
"name":"AWS Certified Data Engineer - Associate",
"issuingOrganization":"Amazon Web Services (AWS)",
"issuedDate":"2025 · Expires Oct 2028"
}
],
"skills":["AWS","SQL","Apache Spark","Business Intelligence","Data Warehouse"],
"languages":[
{"name":"English","proficiency":"Full professional"},
{"name":"French","proficiency":"Native or bilingual"}
],
"volunteer":[
{"role":"Mentor","organization":"Example Nonprofit","dateRange":"2022 - Present","cause":"Education"}
],
"honors":[
{"title":"Employee of the Year","description":"Recognized for outstanding delivery."}
],
"organizations":[
{"name":"Example Data Association","role":"Board Member","dateRange":"2019 - 2023","description":"Community programs and events."}
],
"projects":[
{"name":"Real-time Analytics Platform","dateRange":"2023 - 2024","description":"Built a streaming analytics pipeline on AWS."}
]
}

Company output example

{
"vanityName":"examplesoftware",
"linkedinUrl":"https://www.linkedin.com/company/examplesoftware/",
"companyId":"12345678",
"name":"Example Software Inc.",
"tagline":"Turning ideas into tailored software.",
"description":"Example Software builds custom web, mobile and Web3 solutions for ambitious companies.",
"websiteUrl":"https://example.com",
"phone":{"number":"0600000000"},
"industry":"Computer Software",
"employeeCountRange":{"start":2,"end":10},
"foundedYear":2020,
"specialities":["software","web","mobile","scraping"],
"headquarter":{"city":"Paris","geographicArea":"France","postalCode":"92060","country":"FR"},
"locations":[
{"localizedName":"Paris","city":"Paris","country":"FR","latitude":48.88075,"longitude":2.275646,"headquarter":true}
],
"followersCount":333,
"logoUrl":"https://media.licdn.com/dms/image/v2/EXAMPLE/company-logo_400_400/0/0000000000000/example_logo",
"coverImageUrl":"https://media.licdn.com/dms/image/v2/EXAMPLE/image-scale_191_1128/0/0000000000000/example_cover",
"pageType":"COMPANY",
"verified":false,
"active":true,
"jobSearchUrl":"https://www.linkedin.com/jobs/search?f_C=12345678",
"callToAction":{"text":"Visit website","type":"VIEW_WEBSITE","url":"https://www.example.com"},
"hashtags":["software","development","web3"]
}

Note on field naming. Field names are now consistent across both output types: followersCount, coverImageUrl, and industry mean the same thing on a profile and on a company. Some fields are intentionally distinct because the concepts differ — a person has a profilePictureUrl and a summary, a company has a logoUrl and a description.

How much does it cost to scrape LinkedIn?

Web scraping cost depends on how much data you pull and which sections you request. A few tips to keep runs lean:

• Use the profileFields option to scrape only the sections you actually need — each section is one extra request, so fewer sections = faster and cheaper runs.
• Use direct URLs / slugs when you already know the exact profiles or companies — they skip search entirely.
• Keep limit sensible: limit × number of search terms is the upper bound on search rows.

Check the actor's pricing tab on Apify Store for the exact, up-to-date rate. You can run small test batches first to estimate the cost of a larger job.

Why run LinkedIn Premium Actor on Apify?

Your scraper plus the Apify platform is the complete package:

• API & integrations — call it from your code, or wire it to Make, Zapier, n8n, Google Sheets, and more.
• Scheduling & monitoring — run it on a cron, get alerts, keep history.
• Proxy rotation built in.
• Storage — datasets in JSON/CSV/Excel, served over API.

FAQ

Is it legal to scrape LinkedIn?

Our scrapers are ethical and do not extract any private user data, such as email addresses, gender, or location. They only extract what the user has chosen to share publicly. We therefore believe that our scrapers, when used for ethical purposes by Apify users, are safe. However, you should be aware that your results could contain personal data. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers.

What is the difference between a search and a direct lookup?

A search term (e.g. "growth marketer") returns up to limit results and can be narrowed by location. A direct lookup (a full LinkedIn URL or a /in/{slug} / /company/{slug} path) returns exactly one matching profile or company and ignores limit.

Why did my name get treated as a URL (or vice-versa)?

Entries are routed automatically: anything with a /in/ or /company/ marker (or a full URL) is a direct lookup; everything else is a search. A bare handle without that marker is treated as a search term.

Support & feedback

Your feedback matters — this actor evolves quickly. Want more fields, filters, or locations? Open the Issues tab on the actor's Apify Store page, or reach out to us directly. We ship improvements fast. 🚀

Made with ❤️ by Bebity