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LinkedIn Profile Details Scraper

Pricing

from $2.72 / 1,000 profiles

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LinkedIn Profile Details Scraper

LinkedIn Profile Details Scraper

Scrape LinkedIn profile details in bulk from profile URLs, no login or cookies: headline, current title and company, location, about, followers, experience with dates, education, skills, certifications and languages. One row per profile; hidden profiles are free error rows.

Pricing

from $2.72 / 1,000 profiles

Rating

5.0

(3)

Developer

BlueskyScraper

BlueskyScraper

Maintained by Community

Actor stats

0

Bookmarked

11

Total users

9

Monthly active users

3 days ago

Last modified

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LinkedIn Profile Details Scraper turns a list of LinkedIn profile URLs into a clean table, without a login, cookies or an API key: name, headline, current company, location, about, followers and connections, education, recommendations, certifications, languages, website and photo β€” plus job title and full experience whenever LinkedIn shows them to logged-out visitors. $3.2 per 1,000 profiles, hidden profiles free.

What is LinkedIn Profile Details Scraper?

A bulk LinkedIn profile scraper for recruiters, sales teams and researchers who already have profile links β€” from a CRM, a Google Sheet, a search export β€” and need the data behind them. Paste the URLs (or slugs like satyanadella), press Start, export to Excel, CSV or JSON, or call it as a LinkedIn profile API from your code. No official LinkedIn API access is needed and your own LinkedIn account is never used.

Need the person's work e-mail too? Switch on πŸ“§ Find the work e-mail β€” the same row then carries an address with its confidence (see below), or use LinkedIn Profile Email Finder.

What data can LinkedIn Profile Details Scraper extract?

FieldExample
fullNameSatya Nadella
headlineChairman and CEO at Microsoft
titleChairman and CEO
company / companyLinkedinUrlMicrosoft / linkedin.com/company/microsoft
location / countryRedmond, Washington, United States / US
followers / connections12199041 / 500+
aboutAs chairman and CEO of Microsoft, I define my mission…
experiencetitle, company, start, end, current, duration
educationThe University of Chicago Booth School of Business, 1994–1996
certifications, languages, volunteering, publications, honorsAndAwards, organizations, skills, recommendationsas listed on the public profile
website, imageUrl, linkedinUrl, sluglinks

How often each profile field is filled

LinkedIn shows logged-out visitors a shorter profile than members see. Measured on 55 mixed profiles (3 October 2026):

Filled inProfile fields
Every profilefullName, headline (as in the page title β€” for 7 in 10 people that is their current company), location, country, followers, connections, imageUrl, linkedinUrl
Most profilescompany and companyLinkedinUrl (9 in 10), about (3 in 4), recommendations (7 in 10), education (6 in 10), website (5 in 10)
Some profilescertifications, honorsAndAwards, languages, volunteering, publications (1 in 4 to 1 in 3)
Few profilesjob title and full experience with titles and dates (about 1 in 5 β€” LinkedIn masks past employers for logged-out visitors), skills (about 1 in 8)

Added 5 October 2026 (checked on 7 public profiles): every role in the Experience section, including each role inside a company group (one long career went from 11 to 24 roles), with companyLogo and location; every school in the Education section with degree and fieldOfStudy (schools without dates used to be missing); city, region, countryCode; coverImageUrl, memberId, profileUrn; languageProficiencies, courses, projects, testScores, coursesTaught when the profile shows those sections. The exact connection count, Featured, interests and open-to-work / hiring flags are not shown to logged-out visitors, so they are not returned.

Added 5 October 2026 (round 2): similarProfiles β€” the "Other similar profiles" side rail of the public profile (LinkedIn's "People also viewed" as logged-out visitors see it): name, headline as the card shows it (usually the current company), location, followers, profile URL and photo of each person, 9–20 per profile (10 of 11 checked profiles show it). sameNameProfiles β€” "Others named …", when LinkedIn shows that rail (1 of 11). Same page, no extra request or charge.

An empty field means LinkedIn did not show it, not that the run failed.

πŸ’° How much does it cost to scrape LinkedIn profiles?

RowPrice
Profile$0.0032 β€” $3.2 per 1,000
Profile with e-mail (only with πŸ“§ on, and only when an e-mail is found)$0.008 β€” $8 per 1,000

No start fee, proxies included. Profiles that do not exist or that LinkedIn hides from logged-out visitors are free error rows. Apify's free plan ($5 of monthly credit) covers about 1,500 profiles a month. Paid Apify plans get tiered discounts automatically.

How to scrape LinkedIn profiles

  1. Click Try for free.
  2. Paste profile URLs or slugs into πŸ‘€ LinkedIn profiles, one per line β€” or link a Google Sheet / CSV in πŸ“„ URLs from a file or sheet.
  3. Optional: πŸ“° Add the person's latest posts (free) or πŸ“§ Find the work e-mail.
  4. Click Start and export the table.

⬇️ Input

{
"profileUrls": [
"https://www.linkedin.com/in/satyanadella",
"https://www.linkedin.com/in/jeffweiner08",
"justinwelsh"
],
"includePosts": false,
"findEmail": false
}

⬆️ Output

{
"type": "profile",
"fullName": "Satya Nadella",
"headline": "Chairman and CEO at Microsoft",
"title": "Chairman and CEO",
"company": "Microsoft",
"companyLinkedinUrl": "https://www.linkedin.com/company/microsoft",
"location": "Redmond, Washington, United States",
"country": "US",
"followers": 12199041,
"connections": "500+",
"about": "As chairman and CEO of Microsoft, I define my mission and that of my company as empowering every person and every organization on the planet to achieve more.",
"experience": [
{ "title": "Chairman and CEO", "company": "Microsoft", "startDate": "Feb 2014", "endDate": null, "current": true, "duration": "12 years 9 months" },
{ "title": "Board Member", "company": "Starbucks", "startDate": "2017", "endDate": "2024", "current": false, "duration": "7 years" }
],
"education": [{ "school": "The University of Chicago Booth School of Business", "startDate": "1994", "endDate": "1996" }],
"linkedinUrl": "https://www.linkedin.com/in/satyanadella"
}

One row per profile. The Output tab has a Profiles view, a Work e-mails view and a view of the inputs that could not be read.

What LinkedIn shows without a login

This Actor reads the public pages LinkedIn serves to logged-out visitors and search engines β€” no account, no cookies, nothing that could get an account banned. That decides what is possible:

  • Hidden profiles. Some people hide their profile from logged-out visitors; LinkedIn then answers with a login wall or HTTP 999 for that profile from every address. On mixed lists about 1 in 4 or 5 profiles is refused on the first route. Those get one more try through an unblocking route, paid only from your run's own margin (never from a subsidy that would have to be priced in). Whatever still stays hidden comes back as a free error row saying so.
  • Recent posts only. A logged-out visitor sees a company's ~10 newest posts (median 9 on a 20-company check, 2 of 20 showed none) and a person's ~5–10 newest posts, quote-shares and reposts plus up to 10 articles. A page with fewer posts than you asked for adds one free notice row saying how many LinkedIn showed. There is no paging back to older posts without a login β€” use the Only posts not delivered before switch on a daily schedule to build a full history from now on.
  • Shortened surnames. A few profiles show the surname as an initial ("Diego C.") to logged-out visitors; the row says so.
  • No private data. Phone numbers, connections lists and contact info behind the login are not read.

Pages that do not exist (HTTP 404) are free error rows too. A run in which LinkedIn refuses everything ends with error rows and no charge.

Use cases for LinkedIn profile data

Enrich a lead list

Add current company, location and follower count to the LinkedIn links already in your CRM.

Recruiting

Screen candidates' about text, education, certifications and recommendations in one sheet.

Influencer and creator research

Compare follower counts, headlines and badges of creators in a niche.

Keep a database fresh

Re-run the same list monthly and see who changed company.

Integrations and API

Use LinkedIn Profile Details Scraper like any Apify Actor:

  • API: start a run and read the dataset over HTTP β€” see the API tab for ready-made calls.
  • Python:
from apify_client import ApifyClient
client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("blueskyscraper/linkedin-profile-details-scraper").call(run_input={"profileUrls": ["https://www.linkedin.com/in/satyanadella", "https://www.linkedin.com/in/jeffweiner08", "https://www.linkedin.com/in/justinwelsh"]})
for row in client.dataset(run["defaultDatasetId"]).iterate_items():
print(row)
  • JavaScript:
import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('blueskyscraper/linkedin-profile-details-scraper').call({"profileUrls": ["https://www.linkedin.com/in/satyanadella", "https://www.linkedin.com/in/jeffweiner08", "https://www.linkedin.com/in/justinwelsh"]});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
  • No-code: Make, Zapier, n8n, Google Sheets, Airtable, Slack and webhooks through Apify integrations β€” send every finished run's rows wherever your team works.
  • AI agents (MCP): add the Actor to Claude, ChatGPT, Cursor or any MCP client through the Apify MCP server (https://mcp.apify.com) and ask for LinkedIn data in plain words.
  • Schedules: run it every day or week from the Schedules page; combine with Maximum results per run to cap the bill.

❓ FAQ

The Actor reads only pages that LinkedIn shows to anyone without an account. Scraping public data is generally lawful, but names, job titles and e-mails are personal data under laws such as the GDPR and CCPA: have a lawful reason to process them, keep them safe, and honour opt-outs. When in doubt, ask a lawyer.

Do I need a LinkedIn account, cookies or a proxy?

No. Nothing to log in to, no cookies to paste, no proxy to set up β€” your own LinkedIn account is never touched, so it cannot be restricted. Proxies are included in the price.

Can I use it with the Apify API?

Yes β€” every run can be started and read over the Apify API, from Python, JavaScript or any HTTP client. See Integrations and API above.

Can I use it through an MCP server?

Yes. Add it to the Apify MCP server (https://mcp.apify.com) and your AI assistant can call it directly.

Can I integrate it with other apps?

Yes: Make, Zapier, n8n, Google Sheets, Airtable, Slack and webhooks through Apify integrations.

Why did some pages come back as error rows?

Either the page does not exist (404), or LinkedIn hides it from logged-out visitors. Both are free β€” you pay only for rows with data. The error field says which.

Do I pay for errors, filtered-out posts or the start of a run?

No. There is no start fee; error rows and posts removed by your filters are never billed. Maximum results per run and Apify's Max cost per run are hard ceilings β€” when the cost limit is reached, the run stops by itself with everything written already paid for.

Why is the job title empty for many profiles?

LinkedIn shows the job title and dated experience to logged-out visitors for only about 1 in 5 profiles; for the rest it shows the current company, which is in company. The headline often carries the role as well.

Can I scrape thousands of profiles?

Yes. A run reads about 10–15 profiles a minute (LinkedIn dislikes bursts, so the pace is deliberate) and writes each row as soon as it is read. With the default one-hour run timeout that is several hundred profiles; for longer lists raise the timeout in the run options or split the list. Profiles not reached before the timeout are listed in the run's NOT_ATTEMPTED record and are not billed.

Your feedback

Something missing or wrong? Open an issue on the Issues tab β€” we read every one.

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