Contact Enrichment ✅ Bulk Email & Phone Finder — LinkedIn, Email or Phone 🎯

Enrich the list you already have. LinkedIn URLs but no emails? A column of phone numbers with no names? A half-finished CRM export? Send it in and get back ☎️ direct phone numbers, ✅ verified work emails, job titles, and company data — matched against a database of hundreds of millions of professional profiles.

A pay-as-you-go alternative to Apollo, ZoomInfo, Lusha, Clay, Seamless, Hunter, Dropcontact and Clearbit — no subscription, no seats, no export credits, no API key. You pay only for contacts actually found.

🧑‍💼 What does this Contact Enrichment Actor do?

Real lists are messy: some rows have a LinkedIn URL, some an email, some only a phone number. This Actor takes whichever identifier each row has — LinkedIn URL, email, phone, or name + company domain — finds the person, and then checks the match against the other columns you supplied (name, company, city, state) so you're never billed for the wrong person.

Export to CSV, Excel, or JSON, or push straight into your CRM.

⚖️ Why use this instead of Apollo, ZoomInfo, or Clay?

	This Actor	Apollo / ZoomInfo / Clay
Pricing	Pay per contact found	Monthly subscription + credits
Minimum spend	Cents	$50–$15,000+/year
Lookup by	LinkedIn URL, email, phone, or name + domain	Usually one fixed identifier
Failed matches	Free — you're never charged	Often burns a credit anyway
Setup	Click Start	Sales calls, seats, contracts
Export limits	None — it's your dataset	Credit-capped exports

🔑 What can I match on?

Each record needs one lookup identifier (strongest is tried first):

Lookup field	Example
linkedin_url	https://linkedin.com/in/janedoe
email	jane@acme.com
phone	+15555550123
first_name + last_name + company_domain	Jane, Doe, acme.com

Any of these extra fields verify the person found:

Verification field	Example
first_name / last_name	Jane / Doe
company_name	Acme Corp
company_domain / email_domain	acme.com
personal_city	Austin
personal_state	TX

✨ Your existing column names usually just work. Full Name, Company, Work Email, Mobile, LinkedIn, State and dozens more are recognized automatically. Anything unusual can be pointed at the right field with the Field mapping input. Extra columns are ignored — paste a whole CRM export without cleaning it up first.

📥 Example input

{
  "records": [
    { "first_name": "Jane", "last_name": "Doe", "company_domain": "acme.com" },
    { "linkedin_url": "https://linkedin.com/in/johnsmith", "Company": "Globex" },
    { "phone": "+15555550123" },
    { "Work Email": "maria@globex.com", "Full Name": "Maria Garcia" }
  ],
  "requireEmail": true
}

🕵️ What data do I get for each contact?

• 👤 Full name (first & last) and LinkedIn headline
• 💼 Verified work email — never pattern-guessed
• 📞 Direct / mobile phone (US numbers)
• 🎯 Job title (current role)
• 🏢 Company, company domain, company LinkedIn page
• 📍 City, state, country
• 🔗 LinkedIn URL

Output sample:

{
  "matched": true,
  "fullName": "Jane Doe",
  "email": "jdoe@acmecorp.com",
  "businessEmail": "jdoe@acmecorp.com",
  "phone": "+15550101234",
  "jobTitle": "VP of Marketing",
  "company": "Acme Corp",
  "companyDomain": "acmecorp.com",
  "linkedinUrl": "https://linkedin.com/in/janedoe",
  "city": "Austin",
  "state": "TX",
  "country": "US",
  "input": { "first_name": "Jane", "last_name": "Doe", "company_domain": "acme.com" }
}

Every row carries the input filter that produced it, so you can join results straight back onto your source list. Records that match nothing stay in the dataset with matched: false — you can see exactly what didn't resolve.

🎚️ Match verification

• On (default) — if the person found for a row's LinkedIn URL / email / phone contradicts another field you supplied (a different first name, a different company), the row is reported as matched: false and you are not charged. Fields the profile doesn't have are never held against it.
• Off (matchAny: true) — accept the person found for the identifier regardless of the other columns. Useful when your names or companies are stale (people change jobs).

💰 Pricing — you only pay for what you find

Pay-per-event: you're charged only for contacts actually returned.

• ❌ Input records that match nothing → free
• ✅ Set requireEmail: true → never pay for phone-only records
• ✅ Set requirePhone: true → never pay for email-only records
• 🎯 One row in, at most one contact out — no paying for "alternates"

Rows without a lookup identifier (e.g. only a company domain) are answered with a clear message, free, instead of guessing at strangers.

💡 Tips for the best match rate

• LinkedIn URL matches best, then work email, then phone.
• Any LinkedIn URL form works — www., no www., trailing slash or not.
• Add a name or company to have every match double-checked for free.
• Turn verification off for rows that fail on stale data — e.g. someone who has since changed companies.

❓ FAQ

Do I need an API key? No. Just Apify credits — everything else is handled for you.

What if a record doesn't match? It's returned with matched: false and an explanation, and you are not charged for it.

Can I run a whole CSV through this? Yes. Upload it as the records input; unrecognized columns are ignored, so most exports work as-is.

Is this GDPR/CCPA compliant to use? You are responsible for having a lawful basis for processing and contacting the people you enrich. Use it for legitimate B2B outreach and honor opt-outs.