LinkedIn Profile Data by URL — Full Career, No Cookies ✅ avatar

LinkedIn Profile Data by URL — Full Career, No Cookies ✅

Pricing

from $3.20 / 1,000 profile founds

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LinkedIn Profile Data by URL — Full Career, No Cookies ✅

LinkedIn Profile Data by URL — Full Career, No Cookies ✅

Turn LinkedIn profile URLs into the complete career record — every position with dates and descriptions, education, skills, certifications, patents — for $3.20 per 1,000 found, or with emails and phones at $8 per 1,000 with a live contact. No cookies, no scraping. Misses are free.

Pricing

from $3.20 / 1,000 profile founds

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B2B Enrich Search

B2B Enrich Search

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5 hours ago

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$3.20 per 1,000 complete profiles. Not found costs $0. The standard row is the whole career record: every position with dates and descriptions, education, skills, certifications, patents and publications. Emails and phones are an opt-in tier at $8 per 1,000 people who have one that works.

Turn LinkedIn profile URLs into structured data. Paste links, bare handles or mobile URLs and get one row per profile, with the profile link, location and current employer in their own columns for spreadsheets.

This is a database lookup, not a live scrape: answers come back in seconds from a database of 800M+ professional profiles. No cookies, no login, no account risk.

Why this one

  1. The complete record at the standard price. Every position with its description, the whole education list, skills, languages, certifications, patents, publications, articles.
  2. You pay only for found. Unmatched URLs are free not_found rows, removed profiles free profile_removed rows.
  3. Contacts priced by whether they work. With contacts on you pay $8 per 1,000 only for people with a personal mailbox, an address at their current employer or a direct phone. An old work address alone is charged as a plain profile.

Who is this for

  • Sales and GTM teams enriching sign-ups and CRM contacts.
  • Recruiters turning sourced profile links into structured candidate data.
  • Data teams feeding scoring models with career histories.

Input

{
"profileUrls": ["satyanadella", "https://www.linkedin.com/in/williamhgates"],
"contacts": false,
"mustHave": []
}

Links, bare handles and mobile URLs all work; spellings of the same profile are looked up once.

Emails and phones: contacts

Turn on contacts to get the recorded email addresses and phone numbers with each profile. The best address and a phone are lifted into their own columns: email, emailType (work / personal), employerMatch, workEmails, personalEmails, emailCount, phone, phones.

You pay the contacts price, $8 per 1,000, only for a person with a contact that reaches them today:

  • a personal mailbox (gmail, outlook, ISP mail);
  • an address on the domain of their current employer;
  • a phone the service labels as direct (not a switchboard).

Everyone else is delivered at the $3.20 profile price, old work addresses included. The _tier column says which price each row was charged at. Phone labels arrive with the next data rebuild; until then numbers ship unlabelled and never earn the contacts price by themselves.

How often that is, measured on 30 September 2026 over 200 employed professionals per country: the contacts price applied to 53% of people in the US, 42% in India, 40% in France, 33% in the UK and 32% in Germany. Everyone else shipped at the lower price.

Only people who have what you need: mustHave

List what a person must have for you to pay: email, personalEmail, workEmail, currentWorkEmail, phone, github, twitter, facebook. A person who is found but lacks one comes back as a free missing_required row that says what was missing (and names nobody). Social links are checked on every run; the email and phone requirements need contacts on, and a run that asks for them without it is refused before anything is charged.

Output

One row per profile, aligned with your list. A real row:

{
"_status": "found",
"_input": { "profile": "satyanadella" },
"_freshness": "fresh_90d",
"profileUrl": "https://www.linkedin.com/in/satyanadella",
"location": "Redmond, Washington, United States",
"countryCode": "us",
"companyName": "Microsoft",
"companySlug": "microsoft",
"_view": "lite-v4",
"slug": "satyanadella",
"fullName": "Satya Nadella",
"headline": "Chairman and CEO at Microsoft",
"jobTitle": "Chairman and CEO",
"industry": "Software Development",
"connectionsCount": 500,
"seniority": { "totalExperienceYears": 12, "currentTenureYears": 12, "averageTenureYears": 7 },
"experience": {
"work": [
{ "title": "Chairman and CEO", "company": "Microsoft", "startDate": "2014-02-01", "endDate": null },
{ "title": "Member Board Of Trustees", "company": "University of Chicago", "startDate": "2018-01-01", "endDate": null }
]
},
"education": [
{ "school": "University of Wisconsin-Milwaukee", "degreeName": "Master’s Degree", "fieldOfStudy": "Computer Science" }
],
"contactInformation": {
"socialLinks": { "profileUrl": "https://www.linkedin.com/in/satyanadella", "twitterUrl": null, "githubUrl": null }
}
}

(trimmed for display: the row also carries every past position with its description, about, skills, languages, certifications, patents, publications and articles whenever the profile has them)

With contacts on, the same kind of row gains the contact columns (values below are made up):

{
"_status": "found",
"_tier": "contacts",
"fullName": "Jane Doe",
"companyName": "Acme",
"profileUrl": "https://www.linkedin.com/in/jane-doe-example",
"email": "jane.doe@acme.example",
"emailType": "work",
"employerMatch": true,
"workEmails": ["jane.doe@acme.example", "jdoe@oldjob.example"],
"personalEmails": ["jane.doe@example.com"],
"emailCount": 3,
"phone": "+15550100123",
"phones": [{ "number": "+15550100123", "sharedBy": 1, "companyLine": false }]
}

When the URL matched several records the row carries _matchCandidates.

The Output tab has three views: Overview, Career & education and Contacts & signals.

Pricing

EventPriceWhen
Profile found$0.0032matched URL, the complete career record
Profile found (with contacts)$0.008contacts on and a contact that reaches the person today
Not found / removed / missing_required$0always free

Your free $5 Apify credit is about 1,560 complete profiles.

FAQ

How fresh is the data? Every row carries a _freshness bucket (fresh_90d, updated_1y, older) and the record's exact updatedAt.

Is there a size limit? Up to 1,000 entries per run; the Actor paces itself and finishes in minutes. For bigger lists use Bulk People Enrichment.

What happens with a wrong or dead URL? A free row with _status: "not_found" or "profile_removed" and your input echoed, so the spreadsheet stays aligned.

Which actor in this family?

One database, ten doors. Misses are free on every one of them.

ActorInput → output
Profile Lookup (this one)profile URL → full career profile
Reverse Email Lookupemail → person, profile URL and employer
Name to Profilename + company domain → profile
Social Handle LookupGitHub, X/Twitter or Facebook handle → profile
Bulk People EnrichmentCSV of emails, URLs, handles or names → profiles
LinkedIn Email Finderprofile URL → email addresses on record
Work Email Findername + company domain → work email candidates
Company Employeescompany domain → current staff
People Database Searchfilters → people
Company Database Searchfilters → companies

Disclaimer

This Actor is an independent product. It is not affiliated with, endorsed by or sponsored by LinkedIn. It does not access, crawl or scrape any of them at run time: answers come from our own database of publicly available professional data, and the network names only describe the kind of data it covers. To have a person's data removed, open an issue on this Actor with only the profile link — nothing else is needed, and it is removed from every listing.