Waterfall Contact Enrichment

Clay alternative — find anyone's business email, phone number, and social profiles from their name + company domain. Zero external API costs.

Cascades through 4 data sources until contact info is found:

1. Email pattern generation — 15+ common B2B email patterns (first.last, flast, etc.)
2. Website scraping — finds emails, phones, and social links on the company website
3. Email pattern detection — identifies the company's actual email format
4. Social profile discovery — generates likely LinkedIn, GitHub, and Twitter URLs

Each result includes a confidence score (0-100) and status: found, likely, or not_found.

Key features

• Zero external API costs — no Hunter, Clearbit, or ZoomInfo subscription needed
• Waterfall enrichment — cascades through multiple free sources for maximum coverage
• Email + phone + socials — full contact enrichment, not just email
• 15+ email patterns — covers first.last, firstlast, flast, f.last, last.first, and more
• SMTP verification (deep mode) — confirms the exact mailbox exists on the mail server
• Website scraping — leverages our Contact Scraper to find real data on company sites
• Pattern detection — detects the company's email format, then applies it to the person
• Per-domain caching — efficient for bulk lists (multiple people at the same company)
• Batch processing — configurable concurrency for speed

How the waterfall works

Input: {name, domain} → Source 1 → Source 2 → Source 3 → Source 4 → Best match

Source 1: Generate 15+ email candidates from person's name
Source 2: Scrape company website for real emails, phones, socials
Source 3: Detect company's email pattern, apply to person
Source 4: Generate likely social profile URLs

Cross-reference all sources → Score by confidence → Return best email

Why waterfall? Single sources miss 40-50% of emails. By combining multiple approaches, we boost match rates to 70-90%.

Example output

{
    "firstName": "Jan",
    "lastName": "Curn",
    "domain": "apify.com",
    "company": null,
    "email": "jan.curn@apify.com",
    "emailConfidence": 85,
    "emailSource": "pattern_detection",
    "phone": "+420 234 567 890",
    "phoneSource": "website",
    "socialProfiles": {
        "linkedin": "https://www.linkedin.com/in/jan-curn/",
        "github": "https://github.com/jancurn",
        "twitter": "https://twitter.com/jancurn"
    },
    "status": "found",
    "sources": {
        "patternGeneration": {
            "candidates": ["jan.curn@apify.com", "jan@apify.com", "jcurn@apify.com"],
            "topPattern": "first.last"
        },
        "websiteScraping": {
            "emailsFound": ["hello@apify.com"],
            "phonesFound": ["+420 234 567 890"],
            "socialsFound": ["linkedin.com/in/jancurn"]
        },
        "patternDetection": {
            "detectedPattern": "first.last",
            "patternConfidence": 85,
            "generatedEmail": "jan.curn@apify.com"
        }
    },
    "allCandidates": [
        {"email": "jan.curn@apify.com", "pattern": "first.last", "confidence": 85, "sources": ["pattern_generation", "pattern_detection"]},
        {"email": "jan@apify.com", "pattern": "first", "confidence": 65, "sources": ["pattern_generation"]}
    ],
    "domainValid": true,
    "mxHost": "aspmx.l.google.com",
    "verifiedAt": "2026-02-07T12:00:00.000Z"
}

Input

Field	Type	Default	Description
people	array of objects	required	Each: {firstName, lastName, domain} or {fullName, domain}. Optional: company
enrichFromWebsite	boolean	true	Scrape company website for real contact data (calls Contact Scraper)
detectPattern	boolean	true	Detect company's email pattern (calls Email Pattern Finder)
verificationLevel	enum	"standard"	standard (MX only) or deep (MX + SMTP)
smtpTimeout	integer (3-30)	10	SMTP timeout in seconds (deep mode)
maxConcurrency	integer (1-5)	3	Parallel person lookups

Person object format

Each person in the people array needs:

{"firstName": "Jan", "lastName": "Curn", "domain": "apify.com"}

Or with full name:

{"fullName": "Jan Curn", "domain": "apify.com"}

Optional fields: company (string) for display purposes.

Verification levels

Level	What it checks	Speed	Accuracy
Standard	MX records + pattern generation + website	~5-15s/person	~80%
Deep	+ SMTP verification + catch-all detection	~15-30s/person	~95%

Standard mode is recommended for most use cases. Deep mode connects to the mail server to verify each candidate individually.

Confidence scoring

Scenario	Score
Direct match on company website + SMTP confirmed	98
SMTP confirmed + not catch-all domain	95
Direct match found on company website	90
Pattern matches detected company email format	75-80
Most common pattern (first.last) + MX valid	70
Common pattern (first, flast) + MX valid	65
Less common pattern + MX valid	60
Catch-all domain (accepts all addresses)	50
Domain has no MX records	0

Status values

Status	Meaning	Confidence
found	High confidence email discovered	70-98
likely	Best guess, moderate confidence	40-69
not_found	Domain invalid or no viable candidates	0-39

Email patterns generated

The actor tries 15+ common B2B email patterns for each person:

Pattern	Example (Jan Curn)
first.last	jan.curn@domain.com
firstlast	jancurn@domain.com
first	jan@domain.com
flast	jcurn@domain.com
f.last	j.curn@domain.com
first_last	jan_curn@domain.com
first-last	jan-curn@domain.com
firstl	janc@domain.com
first.l	jan.c@domain.com
last.first	curn.jan@domain.com
lastfirst	curnjan@domain.com
last	curn@domain.com
last.f	curn.j@domain.com
lastf	curnj@domain.com
f_last	j_curn@domain.com

International names are transliterated automatically (e.g., Rene -> rene, Munoz -> munoz).

Use cases

• Sales prospecting — find decision-maker emails from a list of names + companies
• Lead enrichment — add contact details to CRM records with only name + domain
• Outreach campaigns — build verified email lists for cold outreach
• Recruiting — find candidate contact info from LinkedIn profiles (name + company)
• Market research — enrich company databases with key contact information
• PR & media — find journalist and editor emails at publications

Pipeline integration

Combine with our other B2B actors for a complete lead generation pipeline:

1. Google Maps Lead Enricher or B2B Lead Gen Suite — find businesses and basic contacts
2. Waterfall Contact Enrichment — find specific decision-maker emails
3. Bulk Email Verifier — verify deliverability before sending
4. HubSpot Lead Pusher — push enriched contacts to your CRM

Cost structure

The actor itself has minimal compute cost. When enrichFromWebsite and detectPattern are enabled, it calls two sub-actors:

• Website Contact Scraper — ~$0.001 per domain (one call per unique domain)
• Email Pattern Finder — ~$0.001 per domain (one call per unique domain)

Sub-actor results are cached per domain, so 50 people at the same company only trigger one sub-actor call.

Deep mode adds SMTP connections which take 2-10 seconds per candidate (rate-limited to protect mail servers).

API usage

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("ryanclinton/waterfall-contact-enrichment").call(
    run_input={
        "people": [
            {"firstName": "Jan", "lastName": "Curn", "domain": "apify.com"},
            {"firstName": "Elon", "lastName": "Musk", "domain": "tesla.com"},
        ],
        "enrichFromWebsite": True,
        "detectPattern": True,
        "verificationLevel": "standard",
    }
)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item['firstName']} {item['lastName']}: {item['email']} ({item['emailConfidence']}%)")

JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });
const run = await client.actor('ryanclinton/waterfall-contact-enrichment').call({
    people: [
        { firstName: 'Jan', lastName: 'Curn', domain: 'apify.com' },
        { firstName: 'Elon', lastName: 'Musk', domain: 'tesla.com' },
    ],
    enrichFromWebsite: true,
    detectPattern: true,
    verificationLevel: 'standard',
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach(item => {
    console.log(`${item.firstName} ${item.lastName}: ${item.email} (${item.emailConfidence}%)`);
});

How it works

1. Domain validation — DNS MX lookup confirms the domain can receive email
2. Pattern generation — creates 15+ email candidates from the person's name
3. Website scraping — calls our Contact Scraper to find real emails, phones, and social links on the company website
4. Pattern detection — calls our Email Pattern Finder to identify the company's email format (e.g., first.last@domain.com)
5. Cross-referencing — matches website-found emails against the person's name patterns
6. SMTP verification (deep mode) — connects to the mail server to verify the top candidates
7. Confidence scoring — scores each candidate based on all signals
8. Result ranking — returns the best email with confidence score, plus phone and social profiles

Limitations

• Website scraping requires the company to have publicly listed contact information
• SMTP verification (deep mode) may be blocked by some corporate mail servers
• Catch-all domains cannot be reliably verified (flagged as "unknown" with lower confidence)
• Social profile URLs are generated guesses unless found on the company website
• Phone numbers can only be found via website scraping (no phone pattern generation)
• Free-tier Apify accounts may hit memory limits when running sub-actors concurrently