Lead Enrichment Pipeline

One API call to turn a LinkedIn company URL into verified employee contacts with emails. No manual research, no tab switching, no copy pasting.

What It Does

You provide a LinkedIn company URL. The pipeline does the rest:

1. Scrapes employees from the company LinkedIn page (names, titles, profile URLs)
2. Enriches the company (industry, tech stack, domain, social profiles)
3. Generates candidate emails using 7 common corporate email patterns per person
4. Validates every email to confirm deliverability before you send

You get back a clean JSON array of enriched leads ready for outreach.

How It Works

flowchart TD
    A[User Input: LinkedIn Company URL] --> B[Step 1: LinkedIn Employee Scraper]
    B --> C{Title Filter Applied?}
    C -->|Yes| D[Filter by CEO, CTO, VP, etc.]
    C -->|No| E[Keep All Employees]
    D --> F[Step 2: Company Enrichment API]
    E --> F
    F --> G[Extract Domain + Company Intel]
    G --> H[Step 3: Email Pattern Generator]
    H --> I["Generate 7 patterns per person<br/>first.last@ / first@ / flast@ / etc."]
    I --> J[Step 4: Email Validator API]
    J --> K[Validate Each Candidate Email]
    K --> L[Step 5: Merge + Output]
    L --> M[Enriched Leads Dataset]

    style A fill:#e1f5fe
    style M fill:#c8e6c9
    style H fill:#fff3e0
    style I fill:#fff3e0

Quick Start

On Apify Console

1. Open the actor on Apify Store
2. Set the Company LinkedIn URL (e.g., https://www.linkedin.com/company/stripe)
3. Optionally set the Company Website for better enrichment
4. Optionally filter by Title Keywords like CEO, CTO, VP, Director
5. Click Start and wait for results

Via API

curl -X POST "https://api.apify.com/v2/acts/george.the.developer~lead-enrichment-pipeline/runs?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "companyUrl": "https://www.linkedin.com/company/stripe",
    "companyWebsite": "https://stripe.com",
    "maxEmployees": 10,
    "filterTitles": ["CEO", "CTO", "VP", "Director"],
    "validateEmails": true
  }'

Via Apify Client (Node.js)

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_TOKEN' });

const run = await client.actor('george.the.developer/lead-enrichment-pipeline').call({
    companyUrl: 'https://www.linkedin.com/company/stripe',
    companyWebsite: 'https://stripe.com',
    maxEmployees: 10,
    filterTitles: ['CEO', 'CTO', 'VP'],
    validateEmails: true,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Output Format

Each lead in the dataset looks like this:

{
    "fullName": "Patrick Collison",
    "firstName": "Patrick",
    "lastName": "Collison",
    "title": "CEO and Co-founder at Stripe",
    "linkedinUrl": "https://www.linkedin.com/in/patrickcollison/",
    "company": {
        "name": "Stripe",
        "domain": "stripe.com",
        "industry": "Financial Services",
        "description": "Financial infrastructure for the internet",
        "technologies": ["React", "Node.js", "Ruby"],
        "socialProfiles": {
            "linkedin": "https://www.linkedin.com/company/stripe",
            "twitter": "https://twitter.com/stripe"
        }
    },
    "emails": [
        {
            "email": "patrick@stripe.com",
            "valid": true,
            "score": 0.9
        },
        {
            "email": "patrick.collison@stripe.com",
            "valid": true,
            "score": 0.85
        },
        {
            "email": "pcollison@stripe.com",
            "valid": false,
            "score": 0.2
        }
    ],
    "enrichedAt": "2026-04-08T12:00:00.000Z"
}

Email Pattern Generation

The pipeline generates 7 common corporate email patterns for each employee:

Pattern	Example
first.last@domain	patrick.collison@stripe.com
first@domain	patrick@stripe.com
flast@domain	pcollison@stripe.com
firstl@domain	patrickc@stripe.com
last.first@domain	collison.patrick@stripe.com
first_last@domain	patrick_collison@stripe.com
last@domain	collison@stripe.com

Each pattern is then validated against the mail server to confirm deliverability.

Input Parameters

Parameter	Type	Required	Default	Description
companyUrl	string	Yes		LinkedIn company page URL
companyWebsite	string	No		Company website for enrichment
maxEmployees	integer	No	10	Max employees to extract (1 to 50)
filterTitles	string[]	No	[]	Only include matching title keywords
validateEmails	boolean	No	true	Validate discovered emails
apifyToken	string	No		Your Apify token for sub actor calls

Pricing

$0.03 per enriched lead via Pay Per Event.

This includes LinkedIn scraping, company enrichment, email generation, and email validation all in one call.

Comparison with alternatives

Service	Cost per lead	What you get
This pipeline	$0.03	LinkedIn profile + company intel + validated emails
Apollo.io	$0.10 to $0.50	Similar data, monthly subscription required
Hunter.io	$0.05 to $0.15	Email only, no LinkedIn scraping
Clearbit	$0.20 to $1.00	Company enrichment only
Manual research	$2 to $5/hr	Time intensive, error prone

Architecture

The pipeline orchestrates three existing Apify actors:

flowchart LR
    P[Lead Enrichment Pipeline] --> L[LinkedIn Employee Scraper]
    P --> E[Company Enrichment API]
    P --> V[Email Validator API]

    L -->|Employees| P
    E -->|Company Data + Domain| P
    V -->|Validation Results| P

    P --> G[Email Pattern Generator]
    G -->|Candidate Emails| V

    style P fill:#1565c0,color:#fff
    style G fill:#ff8f00,color:#fff

The email pattern generator is the core value. LinkedIn gives names but not emails. Company enrichment gives generic contact emails. The pattern generator bridges the gap by creating personalized candidate emails from names and the company domain, then validates each one.

Use Cases

• Sales prospecting: Find decision makers at target companies with verified emails
• Recruiting: Build candidate lists with contact information
• Market research: Map out team structures at competitor companies
• Partnership outreach: Find the right people to contact at potential partner companies
• Investor research: Identify key executives at portfolio companies

Tips for Best Results

• Always provide the company website when you know it. This improves enrichment accuracy.
• Use title filters to focus on decision makers and reduce costs.
• Set maxEmployees to a reasonable number. Start with 10 and increase if needed.
• The pipeline works best for companies with active LinkedIn presence.

Limitations

• LinkedIn scraping depends on publicly available profile data
• Email validation accuracy depends on the target mail server configuration
• Some mail servers block SMTP checks, resulting in lower confidence scores
• Rate limits apply to sub actor calls