🚀 Ultra Fast LinkedIn Ads Library Scraper

Extract competitor intelligence and campaign insights at scale

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💡 Why scrape LinkedIn Ads Library?

LinkedIn's Ad Library holds millions of ads, but manual browsing is slow and incomplete. This scraper extracts structured data at scale so you can:

• → Track competitor campaigns in real time
• → Analyze ad performance and targeting strategies
• → Discover creative trends in your industry
• → Benchmark your campaigns against the market
• → Build comprehensive ad intelligence reports

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✨ Features

🔍 Flexible search

• ✓ Search by company/advertiser name
• ✓ Search by keyword
• ✓ Combine both for precise results
• ✓ Filter by single or multiple countries
• ✓ Custom date ranges or presets

Example (form-based):

{
  "company": "salesforce",
  "keyword": "crm software",
  "countries": ["US", "GB", "FR"],
  "dateOption": "last-30-days",
  "limit": 100
}

Example (direct URLs - batch processing):

{
  "limit": 100,
  "fetchDetails": false,
  "startUrls": [
    "https://www.linkedin.com/ad-library/search?accountOwner=bynder&dateOption=custom-date-range&startdate=2026-01-31&enddate=2026-02-01",
    "https://www.linkedin.com/ad-library/search?accountOwner=fantastic&keyword=sustainable&countries=AI,AQ,FR,GB,US&dateOption=custom-date-range&startdate=2026-01-31&enddate=2026-02-01"
  ]
}

⚡ Ultra-fast CheerioCrawler

CheerioCrawler ⚡

• Lightweight HTTP requests + HTML parsing (no browser overhead)
• Concurrent processing (3-4 requests simultaneously)
• 10-20x faster than browser-based scraping
• Processes 106 ads in ~1 minute 21 seconds

Performance modes 🚀

• Fast mode (fetchDetails=false): Basic ad data only - ~2 min for 1K ads
• Full mode (fetchDetails=true): Complete details - ~5-10 min for 1K ads (vs 84 min with browser)

📊 Rich data extraction

Basic data (always included):

• Ad ID and URL
• Headline and commentary
• Image/media URLs
• Advertiser information

Detailed data (optional):

• Ad type and format
• Impressions (when available)
• Targeting parameters
• Campaign duration and run dates
• Paying entity information

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🎯 Use cases

1. Competitive intelligence

Track competitor ad strategies, messaging, and creative approaches.

Input:

{"company": "hubspot", "countries": ["US", "GB"], "dateOption": "current-year", "fetchDetails": true, "limit": 200}

Output: Complete campaign analysis with targeting and performance data.

2. Industry research

Discover high-performing ad formats and messaging patterns.

Input:

{"keyword": "saas marketing", "dateOption": "last-30-days", "limit": 100}

Output: Recent SaaS marketing ads for content inspiration.

3. Regional analysis

Compare campaigns across different markets.

Input:

{"company": "microsoft", "countries": ["US", "FR", "DE", "ES"], "fetchDetails": true}

Output: Multi-region campaign comparison with targeting insights.

4. Performance benchmarking

Analyze impression ranges and targeting strategies.

Input:

{"keyword": "b2b software", "dateOption": "last-90-days", "fetchDetails": true, "limit": 500}

Output: Industry benchmarks for ad performance and targeting.

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🏗️ Architecture

┌─────────────────┐
│   Input URLs    │
│  or Form Params │
└────────┬────────┘
         │
         ▼
┌─────────────────┐
│ CheerioCrawler  │
│ (Concurrent)    │
└────────┬────────┘
         │
    ┌────┴────┐
    │         │
    ▼         ▼
┌────────┐ ┌──────────────────┐
│ List   │ │  Detail Pages     │
│ Pages  │ │  (Concurrent)     │
│ (HTML) │ │  (HTML Parsing)    │
└────────┘ └──────────────────┘
         │
         ▼
┌─────────────────┐
│  Extract Data   │
│  (Cheerio)      │
└────────┬────────┘
         │
         ▼
┌─────────────────┐
│  JSON/CSV       │
│  Output         │
└─────────────────┘

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📈 Performance

Speed comparison

Mode	1K Ads	Runtime	Improvement
Fast Mode fetchDetails=false	Basic data only	~2 minutes	10x faster
Full Mode fetchDetails=true	With details	~5-10 minutes	8-16x faster
Old Browser Mode	With details	~~~84 minutes~~	Baseline

Scalability

• ✓ Handles up to 100,000 ads per run
• ✓ Automatic pagination
• ✓ Rate limiting built-in
• ✓ Robust error handling and retries
• ✓ Performance estimates:
  • Fast mode: ~2 minutes per 1K ads (e.g., 10K ads ≈ ~20 minutes)
  • Full mode: ~5-10 minutes per 1K ads (e.g., 10K ads ≈ ~50-100 minutes)

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🎨 Sample output

JSON format

{
  "adId": "1071782994",
  "adUrl": "https://www.linkedin.com/ad-library/detail/1071782994",
  "headline": "Web scraping without the maintenance",
  "commentary": "Your agent can scrape Instagram, Google Maps...",
  "imageUrl": "https://media.licdn.com/dms/image/...",
  "adType": "Single Image Ad",
  "advertiser": "Apify",
  "advertiserUrl": "https://www.linkedin.com/company/10608457",
  "payingEntity": "Apify Technologies s.r.o.",
  "duration": "Dec 28, 2025 to Feb 1, 2026",
  "totalImpressions": "5k-10k",
  "targetingLanguage": "Targeting includes English",
  "targetingLocation": "Targeting includes European Economic Area...",
  "targetingParameters": "Audience(T:Yes,E:Yes)"
}

CSV export

Ready-to-analyze CSV with all fields for Excel, Google Sheets, or BI tools.

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🛠️ Technical highlights

• ✓ Built with TypeScript and CheerioCrawler (Apify SDK)
• ✓ Concurrent processing (3-4 requests simultaneously)
• ✓ Lightweight HTTP requests (no browser overhead)
• ✓ HTML parsing with Cheerio
• ✓ Supports direct URLs or form-based input
• ✓ Batch processing multiple searches
• ✓ Error handling with retries
• ✓ Respects LinkedIn rate limits
• ✓ Runs on Apify's infrastructure
• ✓ Optional LinkedIn session cookies (recommended to avoid rate limiting)

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🚦 Quick start

Prerequisites

1. LinkedIn session cookies (optional but recommended) - Set LINKEDIN_COOKIES environment variable
   • LinkedIn Ad Library is publicly accessible, but cookies help avoid rate limiting
   • Extract cookies from your browser after logging into LinkedIn
   • Format: cookie1=value1; cookie2=value2; ...

Get started on Apify

1. (Optional) Set LINKEDIN_COOKIES environment variable in Apify Actor settings for better reliability
2. Open the Actor on Apify
3. Configure your search parameters (form-based) OR provide startUrls array
4. Click Run
5. Download results as JSON or CSV

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🎯 Perfect for

• 📊 Marketing teams analyzing competitor strategies
• 📈 Data analysts researching ad performance trends
• 🔬 Researchers studying digital advertising patterns
• 🏢 Agencies building campaign intelligence reports
• 💻 Developers building ad intelligence tools
• 📱 Product managers benchmarking market positioning

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📚 Documentation

Input parameters

Parameter	Type	Required	Description
startUrls	array	No*	Array of LinkedIn search URLs for batch processing
company	string	No*	Company/advertiser name
keyword	string	No*	Search keyword
limit	number	No	Number of ads (1–100,000, default: 10). Performance: ~2 min/1K (fast) or ~5-10 min/1K (full)
fetchDetails	boolean	No	Fetch detailed info (default: false)
countries	array	No	Country codes (e.g., ["US", "FR"])
dateOption	string	No	Date filter (default: "last-30-days")
startdate	string	No	Custom start date (YYYY-MM-DD)
enddate	string	No	Custom end date (YYYY-MM-DD)

Note: Either startUrls OR (company OR keyword) must be provided.

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🔒 Privacy & compliance

• ✓ Respects LinkedIn's public Ad Library
• ✓ Optional LinkedIn session cookies (recommended to avoid rate limiting)
• ✓ Only accesses publicly available data
• ✓ Compliant with LinkedIn's Terms of Service
• ✓ Built-in rate limiting to prevent abuse
• ✓ Concurrent requests respect rate limits

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🌟 Why choose this scraper?

Feature	Description
Reliable	Production-grade error handling
Fast	Smart browser selection for optimal performance
Flexible	Multiple search and filter options
Complete	Optional detailed extraction
Structured	Clean JSON/CSV output
Scalable	Handles up to 1,000 ads per run

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🎉 Ready to unlock competitive intelligence?

Start scraping LinkedIn Ads Library today and gain valuable insights!

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🔄 Updates & support

• 🔄 Regular updates for LinkedIn changes
• 🔧 Active maintenance and bug fixes
• 📚 Community support and documentation