Contact Enrichment ✅ Bulk Email & Phone Finder — Match on ANY Field 🎯

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

Most enrichment tools demand one specific identifier — usually an email or a LinkedIn URL. Real lists are messier than that.

This Actor lets you match on any combination of 13 identity fields, so you can enrich the list you actually have instead of the one you wish you had. Give it a name and a company, or just a phone number, or an address — whatever you've got. More fields simply mean a more precise match.

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
Match fields	Any of 13, in any combination	Usually email or domain only
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?

Any combination of these — mix and match freely:

Field	Example
first_name	Jane
last_name	Doe
email	jane@acme.com
email_domain	acme.com
sha256_email	4d1a...
phone	+15555550123
personal_address	123 Main St
personal_city	Austin
personal_state	TX
personal_zip	78701
company_name	Acme Corp
company_domain	acme.com
linkedin_url	https://linkedin.com/in/janedoe

✨ Your existing column names usually just work. Full Name, Company, Work Email, Mobile, LinkedIn, Zip Code 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" },
    { "phone": "+15555550123" },
    { "Full Name": "Maria Garcia", "Company": "Globex" }
  ],
  "requireEmail": true
}

🕵️ What data do I get for each contact?

• 👤 Full name (first & last)
• 📧 Personal email(s) — all known, not just one
• 💼 Business email(s)
• 📞 Phone numbers — personal and business
• 🎯 Job title
• 🏢 Company, company domain, industry
• 📍 City, state, ZIP, address
• 🔗 LinkedIn URL

Output sample:

{
  "matched": true,
  "fullName": "Jane Doe",
  "email": "jane.doe@example.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",
  "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.

🎚️ Matching modes

• ALL fields (default) — a contact must match every field you supply. Precise, with few false positives. Best when your data is clean.
• ANY field (matchAny: true) — a contact matches if any single field matches. Great for recovering data from partial or slightly inaccurate records, but it can return unrelated people, so review before use.

💰 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
• 🎛️ maxResultsPerRecord caps how many alternates you'll accept per row

To protect your budget, a single overly broad filter (like company_domain alone, which can match hundreds of thousands of people) is refused with a clear message instead of billing you for ten random strangers. Add a name, or use a strong identifier such as email, phone, or LinkedIn URL.

💡 Tips for the best match rate

• More fields = better matching. A name alone is rarely enough; name + company or name + city works well.
• Strong identifiers match best — email, phone, LinkedIn URL, or postal address will pin down one specific person.
• LinkedIn URLs are canonicalized automatically, so www. and trailing-slash variants both match.
• Try ANY mode on records that fail in ALL mode — often one field in the source data is stale or misspelled.

❓ 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.