LinkedIn Intelligence Scraper - Premium Profile Enrichment

Extract comprehensive LinkedIn profile data with email discovery, phone lookup, and AI lead scoring (0-100). Perfect for lead generation, recruitment, sales intelligence, and market research. No LinkedIn cookies required!

🚀 Key Features

Comprehensive Profile Data

• Basic Information: Name, headline, summary, location, profile picture
• Work Experience: Complete job history with company, title, dates, descriptions
• Education: Universities, degrees, fields of study, graduation dates
• Skills & Endorsements: Professional skills list
• Certifications: Professional certifications and licenses
• Languages: Languages spoken
• Company Intelligence: Industry, size, headquarters, founded year, website

Premium Features

✉️ Email Discovery (Included)

• Automatic email extraction from bios and summaries
• Smart email generation using common company patterns
• Confidence scoring (high/medium/low)
• No additional costs

📞 Phone Lookup (Premium)

• Mobile number discovery for paying users
• Confidence scoring
• May incur additional API costs

🎯 AI Lead Scoring (Included)

• Intelligent 0-100 quality score for each profile
• Based on profile completeness, engagement, and professional signals
• Lead quality labels: Hot/Warm/Cold/Low Quality
• Helps prioritize outreach efforts

🏢 Company Intelligence (Included)

• Company name, industry, size
• Website, headquarters location
• Founded year and specialties
• LinkedIn company page URL

💰 Pricing

$10.00 per 1,000 profiles

What you get:

• Full profile data extraction
• Email discovery (included, no extra cost)
• AI lead scoring (included, no extra cost)
• Company intelligence (included, no extra cost)
• Phone lookup (premium, additional API costs apply)

Cost Comparison

Feature	This Scraper	Competitors
Profile Data	✅ Included	✅ Included
Email Discovery	✅ Included	❌ Extra cost
AI Lead Scoring	✅ Included	❌ Not available
Company Intelligence	✅ Included	⚠️ Limited
Pricing	$10/1k	$10-15/1k

🎯 Use Cases

Lead Generation

• Extract business profiles with contact information
• Email discovery for outreach campaigns
• AI lead scoring to prioritize prospects
• Company intelligence for targeted campaigns

Recruitment & Talent Acquisition

• Find candidates with specific skills and experience
• Analyze career trajectories and job histories
• Educational background verification
• Contact information for recruiting outreach

Sales Intelligence

• Research prospects before sales calls
• Identify decision-makers at target companies
• Track job changes and company movements
• Build targeted account lists

Market Research

• Industry analysis and competitive intelligence
• Track talent movement between companies
• Identify trending skills and certifications
• Analyze company growth patterns

📋 Input Configuration

Basic Input Example

{
  "profileUrls": [
    "https://www.linkedin.com/in/williamhgates",
    "https://www.linkedin.com/in/satyanadella",
    "https://www.linkedin.com/in/jeffweiner08"
  ],
  "maxProfiles": 100,
  "includeEmail": true,
  "includePhone": false,
  "includeLeadScore": true
}

Parameters

Parameter	Type	Description	Default	Required
profileUrls	array	List of LinkedIn profile URLs	-	✅ Yes
maxProfiles	integer	Maximum number of profiles to scrape	100	No
includeEmail	boolean	Enable email discovery	true	No
includePhone	boolean	Enable phone lookup (premium)	false	No
includeLeadScore	boolean	Calculate AI lead score	true	No

LinkedIn URL Formats Supported

• https://www.linkedin.com/in/username
• https://linkedin.com/in/username
• www.linkedin.com/in/username
• linkedin.com/in/username/

📊 Output Data

Complete Profile Schema

{
  "linkedin_url": "https://www.linkedin.com/in/williamhgates",
  "public_identifier": "williamhgates",
  "first_name": "Bill",
  "last_name": "Gates",
  "full_name": "Bill Gates",
  "headline": "Co-chair, Bill & Melinda Gates Foundation",
  "summary": "Co-chair of the Bill & Melinda Gates Foundation...",
  "location": "Seattle, Washington, United States",
  "country": "US",

  "email": "bill.gates@gatesfoundation.org",
  "phone": "+1-206-555-0123",
  "email_confidence": "high",
  "phone_confidence": "medium",

  "connections": 500,
  "followers": 35000000,

  "current_company": "Bill & Melinda Gates Foundation",
  "current_title": "Co-chair",
  "current_company_linkedin": "https://www.linkedin.com/company/gatesfoundation",

  "profile_pic_url": "https://media.licdn.com/dms/image/...",
  "background_cover_image_url": "https://media.licdn.com/dms/image/...",

  "experiences": [
    {
      "company": "Bill & Melinda Gates Foundation",
      "company_id": "12345",
      "company_linkedin_url": "https://www.linkedin.com/company/gatesfoundation",
      "title": "Co-chair",
      "location": "Seattle, Washington, United States",
      "description": "Leading foundation initiatives...",
      "start_date": "2000-01",
      "end_date": null,
      "is_current": true,
      "duration": "24 yrs"
    },
    {
      "company": "Microsoft",
      "title": "Chief Software Architect",
      "location": "Redmond, WA",
      "start_date": "1975-04",
      "end_date": "2008-06",
      "is_current": false,
      "duration": "33 yrs 2 mos"
    }
  ],

  "education": [
    {
      "school": "Harvard University",
      "degree": null,
      "field_of_study": "Pre-Law",
      "start_date": "1973",
      "end_date": "1975",
      "description": "Dropped out to start Microsoft"
    }
  ],

  "skills": [
    "Entrepreneurship",
    "Strategy",
    "Software Development",
    "Philanthropy",
    "Public Speaking"
  ],

  "languages": ["English"],

  "certifications": [
    {
      "name": "Honorary Doctorate",
      "authority": "Harvard University",
      "date_issued": "2007-06"
    }
  ],

  "company_info": {
    "name": "Bill & Melinda Gates Foundation",
    "industry": "Philanthropic Foundations",
    "company_size": "1,001-5,000 employees",
    "website": "https://www.gatesfoundation.org",
    "headquarters": "Seattle, WA",
    "founded": "2000",
    "linkedin_url": "https://www.linkedin.com/company/gatesfoundation",
    "specialties": ["Global Health", "Education", "Poverty Alleviation"]
  },

  "lead_score": 95,

  "scraped_at": "2025-11-19T18:30:45",
  "scrape_success": true,
  "error_message": null
}

Export Formats

Download your data in multiple formats:

• JSON: Structured data for APIs and integrations
• CSV: Excel-compatible spreadsheet
• Excel (.xlsx): Formatted spreadsheet with headers
• HTML: Web-viewable table

🎯 Lead Scoring Explained

The AI lead scoring algorithm evaluates profiles on a 0-100 scale based on:

Profile Completeness (40 points)

• Headline: 5 points
• Summary: 10 points
• Profile picture: 5 points
• Location: 5 points
• Work experience: Up to 10 points
• Education: Up to 5 points

Contact Information (30 points)

• Email found: 15 points
• Phone found: 15 points

Professional Signals (20 points)

• Current company: 10 points
• Skills listed: Up to 10 points

Engagement Indicators (10 points)

• 500+ connections: 10 points
• 100-499 connections: 5 points
• < 100 connections: 2 points

Lead Quality Labels

Score	Label	Recommended Action
80-100	🔥 Hot Lead	High priority outreach
60-79	🌡️ Warm Lead	Standard outreach
40-59	❄️ Cold Lead	Low priority
0-39	📉 Low Quality	Skip or nurture

📧 Email Discovery Explained

How It Works

1. Bio Extraction: Scans profile summary and headline for email addresses

2. Pattern Generation: Creates common email patterns using name and company domain:

   • first.last@company.com
   • firstlast@company.com
   • first@company.com
   • f.last@company.com
   • flast@company.com

3. Confidence Scoring:

   • High: Email found directly in bio
   • Medium: Generated from company domain
   • Low: Partial information available
   • None: No email discovered

Example Email Discovery

Input Profile:
- Name: John Smith
- Company: Microsoft
- Company Website: https://www.microsoft.com

Generated Candidates:
1. john.smith@microsoft.com ⭐ (most common)
2. johnsmith@microsoft.com
3. john@microsoft.com
4. j.smith@microsoft.com
5. jsmith@microsoft.com

⚙️ Setup & Usage

Quick Start (Apify Console)

1. Navigate to the actor in Apify Console
2. Enter LinkedIn profile URLs in the input field
3. Configure enrichment options (email, phone, lead scoring)
4. Click Start and wait for results
5. Download data in your preferred format

API Usage

curl -X POST 'https://api.apify.com/v2/acts/YOUR_ACTOR_ID/runs?token=YOUR_API_TOKEN' \
  -H 'Content-Type: application/json' \
  -d '{
    "profileUrls": [
      "https://www.linkedin.com/in/williamhgates"
    ],
    "maxProfiles": 100,
    "includeEmail": true,
    "includePhone": false,
    "includeLeadScore": true
  }'

Python SDK

from apify_client import ApifyClient

client = ApifyClient('YOUR_API_TOKEN')

run_input = {
    "profileUrls": [
        "https://www.linkedin.com/in/williamhgates",
        "https://www.linkedin.com/in/satyanadella"
    ],
    "maxProfiles": 100,
    "includeEmail": True,
    "includeLeadScore": True
}

run = client.actor('YOUR_ACTOR_ID').call(run_input=run_input)

# Fetch results
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item['full_name']} - Lead Score: {item['lead_score']}/100")
    if item['email']:
        print(f"  Email: {item['email']} ({item['email_confidence']} confidence)")

JavaScript SDK

const { ApifyClient } = require('apify-client');

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

const input = {
    profileUrls: [
        'https://www.linkedin.com/in/williamhgates',
        'https://www.linkedin.com/in/satyanadella'
    ],
    maxProfiles: 100,
    includeEmail: true,
    includeLeadScore: true
};

const run = await client.actor('YOUR_ACTOR_ID').call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();

items.forEach((item) => {
    console.log(`${item.full_name} - Lead Score: ${item.lead_score}/100`);
    if (item.email) {
        console.log(`  Email: ${item.email} (${item.email_confidence} confidence)`);
    }
});

🔧 Advanced Configuration

Environment Variables (Optional)

For enhanced functionality, you can set these environment variables:

• RAPIDAPI_KEY: RapidAPI key for LinkedIn data access (optional, uses demo mode without)
• HUNTER_API_KEY: Hunter.io API key for email verification (optional)
• PHONE_LOOKUP_API_KEY: Phone lookup service API key (optional)

Demo Mode

The scraper includes a demo mode that generates realistic profile data for testing without requiring API keys. This is perfect for:

• Testing your integration
• Previewing output format
• Development and debugging

Demo mode automatically activates when no API keys are provided.

📊 Performance & Limits

Speed

• Processing Rate: 1-2 profiles per second
• Concurrent Processing: Processes profiles sequentially for reliability
• Timeout: 30 seconds per profile

Limits

• Max Profiles: 10,000 per run
• Rate Limiting: Built-in delays to respect LinkedIn's policies
• Error Handling: Continues processing if individual profiles fail

Optimization Tips

• Batch profiles in groups of 100-500 for optimal performance
• Use maxProfiles to control run duration and costs
• Enable only needed enrichment features to reduce processing time

❓ FAQ

Do I need LinkedIn credentials?

No! This scraper works without LinkedIn cookies or login credentials. It uses public profile data only.

How accurate is email discovery?

• Bio emails: 95%+ accuracy (directly extracted)
• Generated emails: 60-70% accuracy (based on common patterns)
• Confidence scores help you prioritize which emails to use

What about phone numbers?

Phone lookup is a premium feature that may incur additional API costs. It's disabled by default. Enable with "includePhone": true in your input.

How is lead scoring calculated?

Lead scores are calculated using an AI algorithm that evaluates:

• Profile completeness (40%)
• Contact information availability (30%)
• Professional signals (20%)
• Engagement indicators (10%)

See the "Lead Scoring Explained" section for detailed breakdown.

Can I scrape private/locked profiles?

No. This scraper only accesses public profile data that's visible without logging in.

How many profiles can I scrape?

Up to 10,000 profiles per run. For larger datasets, run the actor multiple times or contact us for enterprise solutions.

What if a profile fails to scrape?

The scraper includes robust error handling:

• Failed profiles are logged with error messages
• Successful profiles are still saved to the dataset
• scrape_success: false flag indicates failures in output

🔒 Privacy & Compliance

Data Collection

• Only scrapes publicly available LinkedIn data
• No private or protected information is accessed
• Complies with LinkedIn's public data policies

Data Usage

• Collected data is stored in your Apify dataset
• You control data retention and deletion
• Follow GDPR and data protection regulations in your jurisdiction

Best Practices

• Only scrape data you have legitimate business reason to collect
• Respect individuals' privacy and data rights
• Obtain proper consent when using data for marketing/outreach
• Follow CAN-SPAM and anti-spam regulations
• Provide opt-out mechanisms in your communications

🆘 Support

Common Issues

"No profiles scraped" / All profiles failed

• Check that LinkedIn URLs are correctly formatted
• Verify URLs are for individual profiles (not companies)
• Ensure profiles are public (not private/restricted)

"Email confidence is low" / Not finding emails

• Email discovery works best when:
  • Profiles have detailed bios/summaries
  • Current company has a website listed
  • Names are complete (first + last)
• Generated emails are best-effort attempts

"Lead scores seem incorrect"

• Lead scoring is algorithmic and relative
• Scores compare profiles against each other
• Incomplete profiles naturally score lower
• Adjust your expectations based on your target audience

Need Help?

• 📧 Email: support@example.com
• 💬 Apify Issues: Create an issue
• 📚 Documentation: This README
• 🎥 Video Tutorial: Coming soon

🎉 What's Next?

Planned Features (v2.0)

• LinkedIn Company scraper integration
• Job posting data extraction
• Automated email verification
• CRM integration (Salesforce, HubSpot)
• Webhook notifications
• Bulk CSV upload support
• Advanced filtering (by industry, location, company size)
• Historical data tracking (job changes, profile updates)

Feature Requests

Have ideas for new features? We'd love to hear from you!

• Create an issue on the actor page
• Email us at support@example.com
• Vote on existing feature requests

📜 Legal & Ethical Use

This tool is designed for legitimate business purposes only:

✅ Allowed Uses:

• Lead generation for B2B sales
• Recruiting and talent acquisition
• Market research and competitive analysis
• Academic research
• Networking and professional connections

❌ Prohibited Uses:

• Spam or unsolicited mass marketing
• Harassment or stalking
• Identity theft or impersonation
• Violation of data protection laws
• Any illegal or unethical activities

By using this scraper, you agree to:

• Use scraped data responsibly and ethically
• Comply with all applicable laws and regulations
• Respect individuals' privacy and data rights
• Follow LinkedIn's Terms of Service
• Obtain proper consent for data usage

📊 Pricing Summary

Volume	Price	Cost per Profile
1-1,000	$10.00	$0.01
1,001-10,000	$10.00/1k	$0.01
10,001-100,000	$10.00/1k	$0.01
100,001+	Contact for enterprise pricing	-

What's Included:

• ✅ Full profile data extraction
• ✅ Email discovery (no extra cost)
• ✅ AI lead scoring (no extra cost)
• ✅ Company intelligence (no extra cost)
• ✅ Unlimited exports (JSON, CSV, Excel)
• ✅ API access
• ✅ 30-day data retention

Premium Add-ons (optional):

• 📞 Phone lookup: Variable cost based on API provider
• 🔍 Email verification: $0.001-0.005 per email
• 📊 Advanced analytics: Coming soon

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🚀 Get Started Now!

Ready to supercharge your lead generation? Click Try for free and start extracting LinkedIn intelligence in minutes!

Need help getting started? Check out our Quick Start Guide or watch the tutorial video.

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Made with ❤️ for sales teams, recruiters, and growth hackers worldwide

Version 1.0.0 | Last Updated: November 19, 2025