LinkedIn Profile Scraper (Database) — profile data without scraping

$3.20 per 1,000 complete profiles — 20% under the busiest Actor on this shelf, and less than half what a search-plus-profile Actor costs for the same data. The standard output is the whole career record, not a teaser: every position with dates and descriptions, education, skills, certifications, accomplishments, publications and patents. Contact addresses are the only thing behind the paid tier.

Turn public LinkedIn profile URLs into structured data. Paste links, bare handles, or mobile URLs — get one clean row per profile.

This is a database lookup, not a live scrape. Results come back in seconds from a database of 1B+ professional profiles. No cookies, no login, no account risk, no per-profile browser session — by design.

What it costs against the shelf

The common way to buy this data is a search Actor that charges a page fee and then a per-profile fee on top. Priced per 1,000 profiles:

What you get	Typical shelf price	Here
Complete profile — full work history, education, skills	$4 per 1,000	$3.20 per 1,000
Complete profile + email addresses	$10 per 1,000	$8 per 1,000
The same data reached through a search Actor	~$8 / ~$14 per 1,000	$3.20 / $8
Profiles you asked for but we could not find	billed by some	$0
Run start fee	$0–$0.02 per run	$0.001 per run

(Read off the public Apify listings on 2026-09-18: $0.004 per profile and $0.01 with email search on the direct listing; $0.10 per 25-result page plus the same per-profile fee when you arrive through a search Actor. Those are the prices on the plans most buyers are on — the discounts published alongside them start at the higher subscription tiers. Ours is one flat price on every plan, free tier included.)

Why this one

1. Complete data at the standard price. Not a summary card — the full career record. Every position with its description, the whole education list, skills, languages, certifications, patents, publications, accomplishments, articles and interests.
2. You pay only for found. URLs we cannot match come back as free not_found rows. Removed profiles are free profile_removed rows. Empty input lines cost nothing. No charges for misses, ever.
3. Contacts when you want them. fullOutput: true adds work and personal email addresses, phone numbers, and up to 50 related profiles — still below what the shelf charges for a profile without any email.

Who is this for

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

Input

{
  "profileUrls": ["satyanadella"],
  "fullOutput": false
}

Different spellings of the same profile (mobile links, tracking parameters, bare handles) are folded together and looked up once.

What you get — the whole record at $0.0032, contacts at $0.008

Group	Standard (default, $0.0032/found)	fullOutput: true ($0.008/found)
Identity	full name, first/last, headline, photo, background image, profile slug	same
Current role	job title, employer name + slug (flat columns), dates, industry, employment type, job function	same
Career history	every position, past and present — titles, employers, dates, locations, descriptions	same
Education	complete list — schools, degrees, fields of study, dates, descriptions, grades, activities	same
Skills & languages	full skills list, languages with proficiency	same
Certifications	complete — name, authority, dates, license numbers, links	same
Accomplishments	projects, courses, honors, organizations, test scores	same
Publications & patents	included	same
Volunteer work	included	same
Articles & interests	included	same
Bio	full "about" text	same
Location	city, state, country (ISO code + full names)	same
Seniority signals	level, total experience years, tenure, decision-maker flag	same
Salary estimate	inferred min–max	same
Social links	professional profile URL, GitHub, Twitter/X, Facebook, website	same
Contacts	—	work + personal email addresses and phone numbers
Related profiles	—	up to 50 further people per profile
Honesty meta	_status, _freshness, updatedAt, _matchCandidates	same + per-section coverage map (_meta)

Two things stay out of the standard row on purpose: contact details, which are metered separately, and demographic attributes (birth date, gender), which only travel when the complete record is asked for explicitly.

Output — a real row

Every found row carries _status, _freshness plus the exact updatedAt timestamp, _fullData — a link to the complete document — and flat companyName / companySlug columns when a current position is on record. Misses are compact _status + _input rows that keep your spreadsheet aligned. A real row:

{
  "_status": "found",
  "_input": { "profile": "satyanadella" },
  "_freshness": "fresh_90d",
  "companyName": "Microsoft",
  "companySlug": "microsoft",
  "_view": "lite-v4",
  "fullName": "Satya Nadella",
  "headline": "Chairman and CEO at Microsoft",
  "jobTitle": "Chairman and CEO",
  "industry": "Software Development",
  "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.",
  "connectionsCount": 500,
  "followersCount": 12052722,
  "profileImageUrl": "https://assets.sputnik.io/pp/profilepic/7d36…",
  "location": { "city": "Redmond", "state": "WA", "country": "US", "countryFullName": "United States" },
  "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": "The University of Chicago Booth School of Business", "startDate": "1994-01-01", "endDate": "1996-12-31" },
    { "school": "University of Wisconsin-Milwaukee", "degreeName": "Master’s Degree", "fieldOfStudy": "Computer Science" },
    { "school": "Manipal Institute of Technology, Manipal", "degreeName": "Bachelor’s Degree", "fieldOfStudy": "Electrical Engineering" }
  ]
}

(trimmed for display — the row also carries slug, firstName/lastName, updatedAt, social links, and skills / languages / certifications / inferredSalary whenever the profile has them)

With fullOutput: true the same row becomes the complete document: every past position with descriptions, full education and certification detail, publications, patents, awards, projects, articles, related profiles, and the contact block (emails, phone numbers when on record).

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

Pricing

Event	Price	When
Profile found	$0.0032	matched URL — the complete career record
Profile found (with contacts)	$0.008	fullOutput: true — adds emails, phones, related profiles
Not found / removed	$0	always free

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

FAQ

How fresh is the data? Every row tells you: _freshness buckets (fresh_90d, updated_1y, older) plus the exact timestamp. For most enrichment flows a database answer beats waiting minutes for a live fetch that can fail.

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

What exactly does fullOutput add? Contact details — work and personal email addresses and phone numbers — plus up to 50 related profiles per person and the document's own coverage map. The career record itself (history, education, certifications, publications, patents, projects, articles) is already in the standard row. A standard row never carries contact data.

Is there a rate limit? The actor paces itself; a 1,000-URL run finishes in minutes. For 10,000+ rows use our Bulk People Enrichment (CSV) actor.

Is this compliant? The database holds public professional profile data. We honor removal requests — contact us via the Issues tab.

The family

Same engine, other doors: Reverse Email Lookup (email → person), Work Email Finder (name + domain → email), Company Employees Finder (domain → the whole roster), People/Company Database Search (filters → lists), Name-to-Profile (name + company → profile), Social Handle Lookup (dev/social handle → person), Bulk People Enrichment (CSV, 50k rows). One data core, one billing promise: misses are free.

Disclaimer

This Actor is an independent product and is not affiliated with, endorsed by, or sponsored by LinkedIn Corporation. It does not access, crawl, or scrape LinkedIn at run time — answers come from our own database of publicly available professional data; "LinkedIn" is used only to describe the kind of public profile data the database covers. Removal requests are honored via the Issues tab.