Reverse Email Lookup — Email to LinkedIn, Name & Company

$3.20 per 1,000 people found. An email we cannot match is a free row. You get the person behind the address: name, job title, employer, the LinkedIn profile URL and the full career record. Their other emails and phones are opt-in at $8 per 1,000 people who have one that works.

Paste a list of email addresses and get back who is behind each one, from a database of 800M+ professional profiles. Work and personal addresses both resolve.

This is a database lookup, not a live scrape: seconds per list, and a freshness stamp on every row.

Why this one

1. You pay only for found. Unmatched emails are free not_found rows, malformed ones free invalid rows.
2. The profile link is a column. profileUrl, location, countryCode, companyName sit at the top of every row, ready for a CRM import.
3. Your own address is never sold back. With contacts on, the email you looked up is removed from the answer, and the contacts price applies only when another working contact is on record.

Who is this for

• Inbound qualification: who just signed up with this address?
• CRM enrichment: turn an email-only list into titled, located contacts.
• Fraud and KYB screening: who is behind a free-mail address?

Input

{
  "emails": ["satya.nadella@microsoft.com"],
  "contacts": false,
  "mustHave": []
}

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 input email, aligned with your list. A real row:

{
  "_status": "found",
  "_input": { "email": "satya.nadella@microsoft.com" },
  "_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 }]
}

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

Pricing

Event	Price	When
Person found	$0.0032	matched email, full career row
Person found (with contacts)	$0.008	contacts on and another contact that reaches the person today
Not found / invalid / missing_required	$0	always free

Your free $5 Apify credit is about 1,560 found lookups.

FAQ

Work emails only? No, personal addresses resolve too.

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.

Which actor in this family?

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

Actor	Input → output
Profile Lookup	profile URL → full career profile
Reverse Email Lookup (this one)	email → person, profile URL and employer
Name to Profile	name + company domain → profile
Social Handle Lookup	GitHub, X/Twitter or Facebook handle → profile
Bulk People Enrichment	CSV of emails, URLs, handles or names → profiles
LinkedIn Email Finder	profile URL → email addresses on record
Work Email Finder	name + company domain → work email candidates
Company Employees	company domain → current staff
People Database Search	filters → people
Company Database Search	filters → 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.