LinkedIn Profile Scraper - No Login Required | Real-Time Data

🎯 No LinkedIn Account Required! Works instantly with public profiles.

Get LinkedIn profile data in real-time. Simply provide profile URLs and start scraping - no setup, no account needed.

⚠️ Fair Disclosure: The data you receive depends on each profile's privacy settings. LinkedIn users control what information is publicly visible. Most profiles share basic info, experience, and education, while some may have limited visibility.

📦 Complete Data Extraction - Beyond What You See

🔍 Most scrapers only get "what you see" on screen - we extract EVERYTHING available:

For most public profiles, you'll receive:

• ✅ ALL Skills - Complete skills list (50+) with endorsement counts, not just the visible 3-5
• ✅ Complete Activity History - ALL posts, comments, videos, images, articles, newsletter articles, and events with full content
• ✅ Complete Work Experience - Full job descriptions, nested company positions, and detailed histories
• ✅ Comprehensive Education - All degrees, schools, dates, plus GPA and activities when available
• ✅ Full Profile Sections - About, volunteer experience, languages, honors, courses, publications, recommendations, services
• ✅ Rich Metadata - School logos, company links, skill categories, and detailed timestamps
• ✅ Basic Info - Name, headline, location, current company, follower counts

Remember: Each profile owner controls their privacy settings. Premium members and those with strict privacy may show less data.

🚀 Why Choose This Scraper?

🎯 Beyond Visible Limits - The Complete Picture

The Problem with Other Scrapers: Most LinkedIn scrapers only extract "what you see" on the screen - typically 3-10 skills, basic job titles, and truncated information. They miss the complete professional picture.

Our Deep Extraction Advantage: We automatically detect when data is truncated and extract the COMPLETE dataset. When LinkedIn shows "See all 50 skills" - we actually get all 50. When experience descriptions are cut off - we get the full text. This comprehensive approach gives you the complete professional intelligence other scrapers miss.

Deep Data Extraction vs Surface-Level Scrapers

Feature	This Scraper (Deep Extraction)	Surface-Level Scrapers
Skills Coverage	ALL skills (50+) with endorsements	Only visible 3-10 skills
Activity History	ALL activities (posts, comments, videos, images, articles, events)	❌ No activity data
Experience Details	Complete descriptions + nested roles	Titles only or truncated
Education Depth	Full history + GPA/activities	Basic school/degree info
Profile Sections	ALL sections (volunteer, languages, honors)	Limited to main sections
Data Completeness	100% of available public data	Surface-level data only
Nested Positions	✅ Tracks promotions within companies	❌ Misses role progressions
About Section	Complete bio (1500+ chars)	Truncated or missing
Metadata Extraction	Rich details (logos, categories, links)	Basic text only
Setup Required	❌ None - works instantly	✅ Often complex setup
Data Freshness	Real-time, up-to-the-second	Often days or weeks old

Beyond Visible Limits - What Makes Us Different:

• Complete Activity Extraction - Fetches ALL profile activities: posts (100+), comments, videos, images, articles, newsletter articles, and events
• Complete Skills Extraction - Automatically detects when skills are truncated and fetches ALL available (50+ skills common)
• Deep Experience Mining - Full job descriptions, nested company positions, and complete work histories
• Comprehensive Profile Coverage - ALL sections including volunteer work, languages, honors, courses, publications, recommendations, services
• Rich Metadata Extraction - School logos, skill categories, company links, and detailed profile information
• Real-time Fresh Data - Direct extraction, not cached or outdated third-party data
• Nested Position Tracking - Unique feature tracking role progressions within the same company

✨ Deep Data Extraction Features

• Complete Activity History - Extracts ALL profile activities with full content, media, and engagement metrics
• Complete Data Mining - Extracts ALL available profile data, not just what's visible on screen
• Smart Truncation Detection - Automatically identifies and fetches complete datasets when truncated
• Comprehensive Section Support - Skills, experience, education, volunteer, languages, honors, courses, publications, recommendations, services, and ALL activities
• Nested Position Tracking - Unique capability to track role changes within companies
• Rich Metadata Extraction - School logos, skill endorsements, company links, and detailed timestamps
• No setup needed - Just provide LinkedIn URLs and start extracting complete profiles
• Fast processing - Get comprehensive results in seconds

💼 Use Cases

Perfect for comprehensive professional intelligence:

• Recruitment & Talent Acquisition - Get complete candidate profiles with ALL skills, full experience descriptions, and comprehensive background data
• Sales Intelligence - Access complete prospect profiles with full skill sets, detailed work history, and comprehensive professional information
• Content Analysis & Research - Analyze posting patterns, engagement metrics, and content strategies with complete activity history
• Influencer & Thought Leader Research - Track content creation, audience interaction, and topic expertise through comprehensive activity data
• Market Research & Analysis - Analyze complete skill inventories, detailed career paths, and comprehensive professional landscapes
• Competitive Intelligence - Track key personnel with complete professional histories, skills, and career progressions
• Brand Monitoring - Monitor company mentions, employee activities, and professional discussions
• Due Diligence - Verify professional backgrounds with comprehensive, real-time profile data including education details and certifications
• Lead Generation - Build enriched prospect databases with complete professional profiles and detailed background information

🚀 Quick Start

Just provide LinkedIn profile URLs and start scraping:

{
  "profileUrls": [
    "https://www.linkedin.com/in/williamhgates",
    "https://www.linkedin.com/in/satyanadella"
  ]
}

Input Parameters

• profileUrls (required): Array of LinkedIn profile URLs to scrape
• fetchActivity (optional): Set to true to fetch complete activity history including posts, comments, videos, images, articles, newsletter articles, and events (default: false)

Example with activity extraction:

{
  "profileUrls": [
    "https://www.linkedin.com/in/williamhgates",
    "https://www.linkedin.com/in/satyanadella"
  ],
  "fetchActivity": true
}

Output

Each profile in the dataset includes comprehensive data:

{
  "profile_url": "https://www.linkedin.com/in/jeffweiner08/",
  "original_url": "https://www.linkedin.com/in/jeffweiner08/",
  "vanity_name": "jeffweiner08",
  "profile_id": "ACoAAAFUu6sBhlQbcvAS0GdcPE344dA3vwutzVM",
  "contact_details": {
    "email_address": "jeff.weiner@example.com",
    "phone_numbers": [],
    "twitter_handles": [],
    "websites": [
      {
        "url": "http://www.linkedin.com/",
        "category": "COMPANY"
      }
    ],
    "address": null,
    "instant_messengers": [],
    "wechat_info": null
  },
  "profile_details": {
    "first_name": "Jeff",
    "last_name": "Weiner",
    "headline": "Executive Chairman at LinkedIn / Founding Partner Next Play Ventures",
    "entity_urn": "urn:li:fsd_profile:ACoAAAFUu6sBhlQbcvAS0GdcPE344dA3vwutzVM",
    "public_identifier": "jeffweiner08",
    "location": {
      "display_name": "Las Vegas, Nevada, United States",
      "country_code": "US"
    },
    "premium": true,
    "influencer": true,
    "follower_count": 10404252,
    "connections_count": 500,
    "verified": false,
    "creator": false,
    "profile_picture": {
      "root_url": "https://media.licdn.com/dms/image/v2/C4D03AQFM3Y2r-OEStw/profile-displayphoto-shrink_",
      "display_image_urn": "urn:li:digitalmediaAsset:C4D03AQFM3Y2r-OEStw",
      "highest_resolution": {
        "size": "345x345",
        "width": 345,
        "height": 345,
        "url": "https://media.licdn.com/dms/image/v2/C4D03AQFM3Y2r-OEStw/profile-displayphoto-shrink_400_400/profile-displayphoto-shrink_400_400/0/1515623804984?e=1758758400&v=beta&t=7Ro6WPuN9I93v6HSsHzi04jocIISrcvPrueb2b1DQRY",
        "expires_at": 1758758400000
      },
      "variants": [
        {
          "size": "100x100",
          "width": 100,
          "height": 100,
          "url": "https://media.licdn.com/dms/image/v2/C4D03AQFM3Y2r-OEStw/profile-displayphoto-shrink_100_100/profile-displayphoto-shrink_100_100/0/1515623805035?e=1758758400&v=beta&t=3litQgoETVr44UpMurXAg47Dhv3RAvi_SojtczbYgmI",
          "expires_at": 1758758400000
        },
        {
          "size": "200x200",
          "width": 200,
          "height": 200,
          "url": "https://media.licdn.com/dms/image/v2/C4D03AQFM3Y2r-OEStw/profile-displayphoto-shrink_200_200/profile-displayphoto-shrink_200_200/0/1515623804978?e=1758758400&v=beta&t=hwroqKvzAtMh6dQaJ1ICxPejvmDu73pBzfhmQDoALRc",
          "expires_at": 1758758400000
        },
        {
          "size": "345x345",
          "width": 345,
          "height": 345,
          "url": "https://media.licdn.com/dms/image/v2/C4D03AQFM3Y2r-OEStw/profile-displayphoto-shrink_400_400/profile-displayphoto-shrink_400_400/0/1515623804984?e=1758758400&v=beta&t=7Ro6WPuN9I93v6HSsHzi04jocIISrcvPrueb2b1DQRY",
          "expires_at": 1758758400000
        },
        {
          "size": "345x345",
          "width": 345,
          "height": 345,
          "url": "https://media.licdn.com/dms/image/v2/C4D03AQFM3Y2r-OEStw/profile-displayphoto-shrink_800_800/profile-displayphoto-shrink_800_800/0/1515623806011?e=1758758400&v=beta&t=ry2oc_mR5SSs2iz0f20NnLF889GIX01JwvT4lWT9H2M",
          "expires_at": 1758758400000
        }
      ]
    }
  },
  "volunteer": [
    {
      "role": "Mentor",
      "organization": "Microsoft for Startups",
      "duration": "Jan 2016 - Jan 2017 · 1 yr",
      "cause": "Science and Technology"
    }
  ],
  "honors": [
    {
      "title": "40 Under 40",
      "issuer": "Fortune Magazine",
      "date": "2012"
    }
  ],
  "courses": [
    {
      "name": "Collaborative Economy",
      "number": "MBA Course",
      "associated_with": "University of Oxford"
    }
  ],
  "publications": [
    {
      "title": "Tech Leaders Can Do More to Avoid Unintended Consequences",
      "publisher": "WIRED · May 25, 2022",
      "url": "https://www.wired.com/story/technology-unintended-consequences/"
    }
  ],
  "skills": [
    {
      "name": "Entrepreneurship",
      "endorsement_count": 25
    },
    {
      "name": "Product Development", 
      "endorsement_count": 91
    }
    // ... ALL 47 skills with endorsements (not truncated like other scrapers)
  ],
  "education": [
    {
      "school_name": "The Wharton School",
      "degree_field": "BS, Economics", 
      "dates": "1988 - 1992",
      "location": "Philadelphia, PA",
      "school_logo": "https://media.licdn.com/dms/image/wharton-logo.png",
      "school_url": "https://www.linkedin.com/school/wharton-school/"
    }
  ],
  "experience": [
    {
      "title": "Senior Analyst",
      "subtitle": "Warner Bros. Discovery",
      "company_name": "Warner Bros. Discovery",
      "caption": "Jun 1992 - Aug 1994 · 2 yrs 3 mos",
      "duration": "2 yrs 3 mos",
      "start_date": "Jun 1992",
      "end_date": "Aug 1994",
      "is_current": false,
      "description": "Analyzed strategic planning opportunities for Warner Bros. domestic and international television operations. Member of team that launched Warner Bros. and Tribune Broadcasting's historic partnership, the WB Television Network.",
      "company_action_target": "https://www.linkedin.com/company/1115082/",
      "company_url": "https://www.linkedin.com/company/warnerbros/",
      "company_logo": "https://media.licdn.com/dms/image/v2/C4E0BAQG_1s4y2SKc5w/company-logo_100_100/company-logo_100_100/0/1630669522175"
    }
    // ... with nested positions and full descriptions
  ],
  "about": "I've dedicated my career to fostering connectedness, economic opportunity, and compassion at scale. From 2009 to 2022, I helped grow LinkedIn from ~450 to over 19,500 employees...", // 1721 characters
  "recommendations": {
    "received": [
      {
        "text": "Jeff is an exceptional leader who combines strategic vision with operational excellence...",
        "recommender": "Satya Nadella",
        "recommender_title": "CEO at Microsoft"
      }
    ],
    "given": []
  },
  "services": [
    "Executive Coaching",
    "Strategic Advisory",
    "Board Advisory"
  ],
  "websites": [
    {
      "url": "http://www.linkedin.com/",
      "category": "COMPANY"
    }
  ],
  // When fetchActivity is enabled, you also get comprehensive activity data:
  "activities": {
    "posts": [
      {
        "activity_urn": "urn:li:activity:7366107713887481857",
        "share_urn": "urn:li:share:7366107710792085505",
        "visibility": "PUBLIC",
        "share_url": "https://www.linkedin.com/posts/mayagrossman_i-used-to-think-being-overlooked-meant-i-activity-7366107713887481857-mnbM",
        "text": "I used to think being overlooked meant I wasn't good enough.\n\nIt made me work longer hours.\nIt made me say yes to everything.\nIt made me believe recognition was earned by doing more.\n\nUntil one day I realized:\n\nI wasn't invisible because of my ability.\n\nI was invisible because leaders didn't see me as one of them...",
        "media": {
          "images": [
            {
              "accessibility_text": "graphical user interface, text, application",
              "root_url": "https://media.licdn.com/dms/image/v2/D5622AQG9yBbFmllpNQ/feedshare-shrink_",
              "artifacts": [
                // Multiple image resolutions from 20x25 to 1280x1600
                {
                  "width": 800,
                  "height": 1000,
                  "fileIdentifyingUrlPathSegment": "800/B56ZjmrsaqG0Ag-/0/1756216882587",
                  "expiresAt": 1759363200000
                }
              ]
            }
          ]
        }
      }
      // ... up to 100 posts with full content
    ],
    "comments": [

        "activity_urn": "urn:li:activity:7366130827522416640",
        "share_urn": "urn:li:share:7364817384479633411",
        "text": ""Why do I keep attracting the wrong people?"\n\nA pretty cool client asked me recently.\n\nYou don't attract what you want.\nYou attract what you're available for.\n\nIf your life is full of half-hearted connections, friendships that drain you, or relationships that leave you wondering, "Is this really it?"…\n\nIt's not because the world is against you.\nIt's because your energy.\nYour standards.\nAnd your boundaries are silently sending invitations...",
        "share_url": "https://www.linkedin.com/posts/ruta-stasiunaite_why-do-i-keep-attracting-the-wrong-people-activity-7366073194929197056-fvtC",
        "author": {
          "name": "Ruta Stasiunaite 😎",
          "headline": null,
          "profile_url": null
        }
      }
      // ... all comments made by the profile
    ],
    "videos": [
      {
        "activity_urn": "urn:li:activity:7362484152945790976",
        "thumbnail": "https://media.licdn.com/dms/image/v2/D5605AQGJnVavbesDQA/videocover-high/0/1755352889985",
        "title": "When I first set my sights on VP, I made a big mistake:\n\nI avoided self-promotion...",
        "duration": "1:09",
        "engagement": {
          "likes": 68,
          "comments": 25,
          "shares": 0,
          "views": null
        }
      }
      // ... up to 20 videos with metadata
    ],
    "images": [
      "https://media.licdn.com/dms/image/v2/D5622AQG9yBbFmllpNQ/feedshare-shrink_1280/0/1756216882747",
      "https://media.licdn.com/dms/image/v2/D5622AQHPqHV4eIXeow/feedshare-shrink_2048_1536/0/1756130451114"
      // ... more image URLs (highest resolution)
    ],
    "articles": [
      // 20 published articles with titles, content, and links
    ],
    "newsletter_articles": [
      // 19 newsletter editions with full content
    ],
    "events": [
      {
        "activity_urn": "urn:li:activity:7227443257322958848",
        "name": "How High Achievers Break Through to Executive Roles",
        "view_count": 659,
        "image": "https://media.licdn.com/dms/image/v2/D4D24AQHU-LfeVKB9aw/feedshare-live-thumbnail_high/0/1725379245639"
      }
      // ... more events with view counts and images
    ]
  }
}

🧪 Tested & Verified

This scraper has been thoroughly tested with high-profile LinkedIn profiles:

Test Results (August 2025) - Complete Data Extraction:

• Maya Grossman (Executive Coach & Best-Selling Author)

  • ✅ 100 posts with full text, media, and engagement metrics
  • ✅ 17 comments with complete text and author information
  • ✅ 20 videos with titles, duration (1:09), thumbnails, and engagement
  • ✅ 20 image posts with captions and 6 resolution variants each
  • ✅ 20 articles and 19 newsletter articles with full content
  • ✅ 22 events created or participated in
  • ✅ Complete skills, experience, and education sections

• Jeff Weiner (Executive Chairman at LinkedIn)

  • ✅ ALL 47 skills with endorsement counts (not just visible 3-5)
  • ✅ Complete experience history with full descriptions
  • ✅ 1,721 character about section (full text)
  • ✅ Comprehensive education + activities + school details
  • ✅ Volunteer experience, languages, honors sections

• Satya Nadella (CEO at Microsoft)

  • ✅ ALL 23 skills with endorsements (competitors get 3-6)
  • ✅ Complete experience entries with full job descriptions
  • ✅ Full education history with degrees and activities
  • ✅ Complete about section (800+ characters)
  • ✅ Languages, volunteer work, and professional honors

Data Quality & Coverage

Complete Data Coverage - What You Get:

• ✅ Complete Activity History - ALL posts (100+), comments, videos, images, articles, newsletter articles, and events with full content
• ✅ ALL Skills - Complete skills inventory (50+ common) with endorsement counts, not just the 3-10 visible on screen
• ✅ Complete Experience - Full job descriptions, nested company positions, and comprehensive work histories
• ✅ Comprehensive Education - All degrees, schools, dates, plus GPA, activities, and school metadata when available
• ✅ Full Profile Sections - About, volunteer experience, languages, honors, courses, publications, recommendations, and services
• ✅ Rich Metadata - School logos, skill categories, company links, timestamps, and detailed profile information
• ✅ Deep Section Mining - Extracts data beyond what's immediately visible, providing complete professional profiles

Limitations:

• Privacy restrictions - Some profiles may have limited data based on user privacy settings
• Private skills - Some users hide their skills section (e.g., high-profile executives)

💰 Pricing

"Only pay for profiles we can actually scrape!" - Blocked or private profiles are FREE

🆓 Free Tier

Free Apify users get 5 profile lookups - Perfect for testing!

• ✅ 5 successful profiles lifetime limit
• ✅ Blocked profiles don't count against your limit
• ✅ Use them all at once or across multiple runs
• ✅ See your usage: "Free tier: 3/5 profiles used"

Pay-Per-Event Pricing Model (Paid Users)

What You Pay For	Price	When Charged
Base Profile	$0.065	Per accessible profile
Each Section	$0.008	Per section with data
Contact Details	$0.03	When email/phone found
Blocked Profiles	$0.00	Never charged!

Real Pricing Examples

Profile Type	Sections	Contact	Total Cost
Blocked/Private Profile	N/A	N/A	$0.00
Basic Profile	2-3 sections (about, experience)	No	$0.081
Standard Profile	5-6 sections (+ education, skills)	No	$0.105
Complete Profile	7-8 sections (+ volunteer, honors)	Yes	$0.151
Executive Profile	10+ sections (+ all activities)	Yes	$0.175

Average cost: $0.08-$0.15 per successful profile

What Counts as a Section?

Sections with data that incur the $0.008 charge:

• Core: experience, education, skills, about
• Additional: volunteer, languages, honors, courses, publications, recommendations, services
• Activities (when enabled): posts, comments, videos, images, articles, newsletter_articles, events

Fair Pricing Guarantee

• ✅ No charges for inaccessible profiles - Privacy-restricted profiles cost nothing
• ✅ Only pay for data received - Empty sections don't count
• ✅ Transparent billing - See exactly what you're charged for
• ✅ No platform fees - Just pay for what you use

Getting Started

1. Create your Apify account here
2. Try the free tier - Extract up to 5 profiles at no cost
3. Configure your search - Add company URLs and parameters
4. Run the actor - Get results in seconds
5. Export or integrate - Use the data in your preferred format

Support

• 📧 Email: max@mapa.slmail.me
• 🐛 Issues: Use the Issues tab for bug reports and feature requests
• 💬 Response time: Usually within 24 hours
• 🔧 Custom features: Available upon request

📚 Resources

• API documentation - For developers
• Integration guide - Connect to Zapier, Make, etc.

❓ FAQ

Q: Do I need a LinkedIn account?
A: No! The scraper works without any login for public profiles.

Q: How accurate is the data?
A: 100% accurate - we get data directly from LinkedIn in real-time, not from third-party databases.

Q: How is this different from other scrapers?
A: Most scrapers only get "what you see" - we extract ALL available data. While others get 3-10 skills, we get the complete list (50+ common). We also extract comprehensive sections like volunteer work, languages, and honors that others miss.

Q: Can I get contact information?
A: We extract all publicly available contact info including websites and social links. Email addresses and phone numbers are rarely public but we include them when available.

Q: Is this legal?
A: Yes, the scraper only accesses publicly available information. Always comply with data protection laws in your jurisdiction.

Q: How fast is it?
A: Typically a few seconds per profile, depending on profile size.

Support

• 📧 Email: max@mapa.slmail.me
• 🐛 Issues: Use the Issues tab for bug reports and feature requests
• 💬 Response time: Usually within 24 hours
• 🔧 Custom features: Available upon request

Legal Compliance

This actor extracts publicly available information from LinkedIn. Users are responsible for complying with LinkedIn's terms of service, applicable data protection regulations (GDPR, CCPA), and using the data ethically and legally.

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🚀 Start Extracting LinkedIn Profiles