Bulk LinkedIn & Email Enrichment — a CSV in, enriched profiles out

$3.20 per 1,000 resolved rows, $8 with the full 164-field document — the same price as the single lookups, with crash-safe resume on top. A delivered row is never re-billed, whatever the platform does to the run.

A CSV in, enriched LinkedIn profile rows out — built for the 10,000–50,000 row exports that are too big to paste into a lookup form.

Upload the file (or link it), and every row resolves by the strongest key it carries:

1. email address
2. profile URL
3. social handle (github / twitter / facebook)
4. full name — plus a company domain column when you have one

Bare names resolve only when exactly one profile carries the name. Namesakes come back as an honest, free refusal with the holder count — never a guess.

Built for big files

• Rows stream into your dataset as they resolve — no waiting for the end of the run to see results.
• Long runs survive platform server migrations: the actor checkpoints its progress and resumes where it left off instead of starting over.
• Ten consecutive service errors stop the run early instead of grinding through an outage on your time.

Input

{
  "csv": "email\nsatya.nadella@microsoft.com",
  "fullOutput": false
}

• csv — upload a file, paste rows, or link to a CSV file. Recognized columns: email, profile_url, github, twitter, facebook, full_name (or first_name + last_name), domain.
• fullOutput — deliver the complete profile document per resolved row (164 fields across 37 sections) at the full-profile rate, instead of the 60+ field summary card.

What you get — 60+ fields per resolved row, 164 with fullOutput

Group	Summary card (default, $0.0032/row)	Full document (fullOutput: true, $0.008/row)
Identity	full name, first/last, headline, photo, profile slug	same + background image
Current role	job title, employer name + slug (flat columns), position dates, industry	+ role descriptions, employment type, job function
Career history	current positions	every past position with dates and descriptions
Education & certifications	schools, degrees, fields of study, dates; cert names, authorities	+ descriptions, grades, license numbers
Skills, languages, bio	full skills list, languages, "about" text	same
Location & seniority	city/state/country, 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	—	email addresses and phone numbers when on record
Deep sections	—	publications, patents, awards, projects, articles, related profiles
Honesty meta	_status, _freshness, updatedAt; _matchCandidates when a key matched several people	same + per-section coverage map

Output

One row per input row, tagged with its record number (the header is record 1, the first data record is 2; a quoted cell containing a line break still counts as one record). A real resolved row:

Resolved rows carry the profile card plus flat companyName / companySlug columns when a current position is on record; free ambiguous rows carry _nameMatchCount, the honest namesake count.

{
  "_status": "found",
  "_input": { "row": 2, "email": "satya.nadella@microsoft.com" },
  "_freshness": "fresh_90d",
  "companyName": "Microsoft",
  "companySlug": "microsoft",
  "_view": "lite-v3",
  "fullName": "Satya Nadella",
  "headline": "Chairman and CEO at Microsoft",
  "jobTitle": "Chairman and CEO",
  "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.",
  "location": { "city": "Redmond", "state": "WA", "country": "US" },
  "seniority": { "totalExperienceYears": 12, "currentTenureYears": 12 },
  "experience": { "work": [ { "title": "Chairman and CEO", "company": "Microsoft", "startDate": "2014-02-01", "endDate": null } ] },
  "education": [ { "school": "University of Wisconsin-Milwaukee", "degreeName": "Master’s Degree", "fieldOfStudy": "Computer Science" } ]
}

(trimmed for display — the card also carries skills, languages, certifications, inferredSalary, social links and connection counts whenever the profile has them)

_status explains every non-match (ambiguous with the namesake count, not_found, invalid, profile_removed) — free rows, never dropped silently: your output CSV has the same accountability as your input.

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

Pricing — pay only for resolved rows

Event	Price	When
Row resolved (summary)	$0.0032	resolved to a profile, 60+ field row
Row resolved (full document)	$0.008	fullOutput: true, 164 fields / 37 sections
Unresolvable / malformed / namesake rows	$0	always free, with an explanation

A charge fires only after the row is already in your dataset.

The family

Same engine, other doors: Reverse Email Lookup (email → person), Profile Lookup (URL → profile), Work Email Finder (name + domain → email), Company Employees Finder (domain → roster), People/Company Database Search, Name-to-Profile (name + company → profile), Social Handle Lookup (dev/social handle → person). 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.