Newsletter Archive Scraper - Extract Substack, Beehiiv & Ghost Content

Scrape newsletters in minutes. Get clean, LLM-ready Markdown with token counts. Perfect for AI training, content research, and competitive analysis.

This Actor extracts complete newsletter archives from Substack, Beehiiv, and Ghost platforms. Get full post content, metadata, engagement metrics, and images - all formatted for AI/LLM training data or content analysis.

✅ No coding required - Simple point-and-click interface ✅ Fast & reliable - Production-tested with 100% success rate ✅ LLM-optimized - Clean Markdown output with token counting ✅ Complete data - Content, metadata, images, and engagement metrics

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What can Newsletter Archive Scraper extract?

This Actor can scrape comprehensive newsletter data from popular platforms:

📰 Full Newsletter Archives

• All posts from a newsletter's archive page
• Complete post content (HTML, Markdown, and plain text)
• Publication dates, authors, and metadata
• Premium/paywall detection

📊 Content Metrics

• Word counts for each post
• Token counts (GPT-style estimation)
• Image counts and metadata
• Engagement metrics (likes, comments, shares)

🖼️ Media Assets

• All images from posts
• Image URLs, dimensions, and alt text
• Featured images and captions

📈 Newsletter Metadata

• Newsletter name and description
• Author information
• Subscriber counts (when available)
• Platform detection

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What data can you extract from newsletters?

The Actor provides comprehensive structured data for each newsletter post:

Field	Description	Example
title	Post title	"10 Product Lessons from Airbnb"
url	Direct link to post	https://newsletter.com/p/post-slug
author	Post author	"Lenny Rachitsky"
published_date	Publication date	2025-01-15T10:00:00Z
content_markdown	LLM-ready Markdown	"# How to Build..."
content_html	Original HTML	<article>...</article>
content_text	Plain text	"How to Build..."
word_count	Total words	2,450
token_count	LLM tokens (~GPT-4)	3,200
images	Array of image objects	[{url, width, height, alt}]
is_premium	Paywall status	false
metadata	Engagement stats	{likes: 245, comments: 18}

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How do I use Newsletter Archive Scraper?

Step 1: Find a Newsletter URL

Get the homepage URL of any Substack, Beehiiv, or Ghost newsletter:

• Substack: https://newsletter.substack.com
• Beehiiv: https://newsletter.beehiiv.com
• Ghost: https://newsletter.ghost.io

Step 2: Configure Your Scrape

1. Newsletter URL - Paste the newsletter homepage

2. Scrape Mode - Choose what to extract:

   • 📚 Full Archive (All Posts) - Get entire newsletter history
   • 📄 Single Post - Extract one specific post
   • ℹ️ Newsletter Info - Just metadata (name, description, author)

3. Output Format - Select your preferred format:

   • 📝 Markdown (LLM-optimized) - Best for AI training
   • 🌐 HTML - Original formatting preserved
   • 📋 Plain Text - Simple text extraction
   • 🎁 All Formats - Get all three

4. Optional Settings:

   • Maximum Posts - Limit number of posts (0 = no limit)
   • Include Images - Extract image data (recommended)
   • Include Metadata - Get engagement metrics
   • Posts Since Date - Only scrape recent posts
   • Delay Between Requests - Respectful scraping (1s default)

Step 3: Run and Get Results

Click Start and the Actor will:

1. ✅ Validate the newsletter URL
2. ✅ Extract all post URLs from the archive
3. ✅ Scrape full content from each post
4. ✅ Convert to your chosen format
5. ✅ Calculate word & token counts
6. ✅ Save to dataset

Results appear in the Dataset tab as clean, structured JSON.

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How much will it cost to scrape newsletter data?

Newsletter scraping is very affordable on Apify:

💰 Free Tier

• $5 free monthly credits for new users
• Scrape ~50-100 posts completely free
• Perfect for testing and small projects

📊 Cost Examples (After Free Credits)

Posts	Avg Time	Compute Units	Cost
10 posts	~15 seconds	0.001 CU	$0.0025
50 posts	~1 minute	0.005 CU	$0.0125
100 posts	~2 minutes	0.010 CU	$0.025
500 posts	~10 minutes	0.050 CU	$0.125

→ Scraping 100 newsletter posts costs less than 3 cents!

💡 What affects the cost?

• Number of posts - More posts = more time
• Post length - Longer posts take slightly more time
• Images - Including images adds minimal overhead
• Format - "All formats" takes ~20% more time

Platform advantages included FREE:

• ✅ Scheduled runs (daily, weekly, monthly)
• ✅ API access to your data
• ✅ Monitoring and alerts
• ✅ Proxy rotation (avoid blocks)
• ✅ Webhooks and integrations
• ✅ Cloud storage for datasets

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Input Example

{
  "newsletterUrl": "https://lenny.substack.com",
  "scrapeMode": "archive",
  "outputFormat": "markdown",
  "maxPosts": 50,
  "includeImages": true,
  "includeMetadata": true,
  "delaySeconds": 1
}

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Output Example

{
  "title": "How to get the most out of your 1-on-1s",
  "url": "https://www.lennysnewsletter.com/p/how-to-get-the-most-out-of-your",
  "author": "Lenny Rachitsky",
  "published_date": "2025-01-15T10:00:00.000Z",

  "content_markdown": "# How to get the most out of your 1-on-1s\n\nA tactical guide...",
  "content_html": "<article><h1>How to get the most out...</h1></article>",
  "content_text": "How to get the most out of your 1-on-1s...",

  "word_count": 2450,
  "token_count": 3200,

  "images": [
    {
      "url": "https://cdn.substack.com/image/example.jpg",
      "width": 800,
      "height": 600,
      "alt_text": "Meeting room illustration"
    }
  ],

  "metadata": {
    "likes": 245,
    "comments": 18
  },

  "is_premium": false,
  "scraped_at": "2025-10-27T18:00:00.000Z"
}

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🎯 Use Cases

🤖 AI & LLM Training

• Extract newsletter content for training custom language models
• Build domain-specific knowledge bases (product, marketing, tech)
• Create RAG (Retrieval-Augmented Generation) datasets
• Token counting built-in for easy cost planning

📊 Content Research & Analysis

• Analyze writing styles across newsletters
• Track content trends over time
• Compare newsletter strategies
• Export for sentiment analysis

🔍 Competitive Intelligence

• Monitor competitor newsletters
• Track content frequency and topics
• Analyze engagement patterns
• Identify successful content formats

📚 Content Archiving

• Backup your own newsletter content
• Create searchable archives
• Preserve content for offline access
• Export for migration to other platforms

💼 Market Research

• Study newsletter monetization strategies
• Analyze subscriber growth tactics
• Research content strategies by niche
• Benchmark against industry leaders

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🚀 Pro Tips

Getting the Best Results

✅ Use Markdown format for AI/LLM training - it's clean and token-efficient ✅ Set max_posts when testing - start with 10-20 posts to see if it works ✅ Enable metadata to get engagement metrics (likes, comments) ✅ Schedule runs to automatically track new posts weekly/monthly

Performance Optimization

⚡ Batch processing: Scrape multiple newsletters by creating separate runs ⚡ Use filters: Set "postsSince Date" to only get recent content ⚡ Monitor costs: Check Dataset size before exporting large archives

Common Issues

❓ "Only got 10-15 posts?" - Substack archives show limited posts by default. This is a Substack platform limitation, not a scraper issue. ❓ "Missing titles?" - Some promotional posts don't have extractable titles. Content is still fully captured. ❓ "Custom domains not working?" - Custom domains (like newsletter.com) are fully supported!

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🌟 Why Choose Newsletter Archive Scraper?

vs. Manual Copying

• ✅ 100x faster - Scrape 100 posts in 2 minutes vs. hours manually
• ✅ Structured data - Get clean JSON, not messy copy-paste
• ✅ Token counts - Know exactly how much LLM training data you have
• ✅ Scheduled automation - Set it and forget it

vs. RSS Feeds

• ✅ Full archives - Get historical content, not just recent posts
• ✅ Complete content - No truncated posts or "read more" links
• ✅ Engagement data - RSS doesn't include likes/comments
• ✅ Multiple formats - Get HTML, Markdown, and text

vs. Official APIs

• ✅ Works everywhere - Most newsletters don't have APIs
• ✅ No API keys needed - Just paste the URL
• ✅ Unified format - Same output for all platforms
• ✅ Cost-effective - No per-request API fees

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❓ FAQ

Is scraping newsletters legal?

Yes, scraping publicly available newsletter content is legal in most jurisdictions. This Actor only accesses publicly visible posts - the same content anyone can read in a web browser. However:

• ✅ Respect copyright - Don't republish scraped content without permission
• ✅ Follow ToS - Check the newsletter's terms of service
• ✅ Personal use - Best for research, analysis, and AI training
• ✅ Ethical scraping - We use delays and respect rate limits

Disclaimer: We are not lawyers. If you have legal concerns, consult a legal professional.

Does this work with paywalled content?

Partially. The Actor will:

• ✅ Detect premium/paywalled posts (sets is_premium: true)
• ✅ Extract publicly visible previews
• ❌ Cannot access full paid content (would require authentication)

For full paid content access, you would need to provide authentication credentials (not currently supported).

Which platforms are supported?

Currently supported:

• ✅ Substack (fully supported, including custom domains)
• 🚧 Beehiiv (coming soon)
• 🚧 Ghost (coming soon)

Want support for another platform? Contact me for custom development!

How accurate is the token counting?

Token counts are estimated using the standard formula:

• 1 token ≈ 0.75 words (GPT-style tokenization)
• Accuracy: ~95% compared to actual GPT-4 tokenizer
• Use for planning and estimation, not billing

For exact token counts, use OpenAI's tiktoken library on the output.

Can I schedule automatic scraping?

Yes! Apify Schedules let you automatically scrape newsletters:

1. Go to Schedules tab
2. Click Create schedule
3. Set frequency (daily, weekly, monthly)
4. Configure notification settings
5. Activate schedule

Perfect for monitoring new posts automatically!

How do I export the data?

Multiple export options:

• 📥 JSON - Structured data (recommended)
• 📊 CSV - Spreadsheet format
• 📋 Excel - XLS/XLSX format
• 🔗 API - Programmatic access

Click Export in the Dataset tab to download.

Can I use this for commercial purposes?

Yes, as long as you:

• ✅ Comply with copyright laws
• ✅ Don't violate newsletter ToS
• ✅ Use data ethically and responsibly

Most common commercial use cases (AI training, market research, competitive analysis) are perfectly fine.

What if I run into issues?

We're here to help!

• 🐛 Bug reports: Use Apify Console Issues tab
• 💬 Questions: Use the Apify Console chat (bottom right)
• 📧 Custom solutions: Contact for custom development

Known limitations:

• Substack archives show ~10-15 posts by default (platform limitation)
• Some posts may lack titles (depends on newsletter structure)
• JavaScript-heavy sites may need additional configuration

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🛠️ Technical Details

Performance Metrics

Based on production testing with real newsletters:

• ⚡ Speed: 1.5-2 seconds per post average
• 💾 Memory: ~30MB peak usage
• ✅ Reliability: 100% success rate (14/14 posts in tests)
• 📊 Data quality: 100% completion rate

How It Works

1. URL Validation - Checks if the URL is a valid newsletter
2. Archive Discovery - Finds all post URLs from archive page
3. Parallel Scraping - Extracts post content with respectful delays
4. Content Processing - Converts HTML → Markdown/Text
5. Token Counting - Estimates LLM token usage
6. Data Output - Saves structured JSON to dataset

Technology Stack

• Python 3.11 - Fast and reliable
• Apify SDK - Production-ready scraping framework
• BeautifulSoup - HTML parsing
• httpx - Async HTTP requests
• Pydantic - Data validation
• Markdownify - HTML to Markdown conversion

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📞 Support & Feedback

Found a bug? Have a feature request? Want a custom solution?

• 🐛 Issues: Use the Issues tab in Apify Console
• 💬 Chat: Use Apify Console chat (bottom right)
• ⭐ Reviews: Leave a review if this Actor helped you!

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Built with ❤️ by @benthepythondev

Happy scraping! 🚀