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Scraping Substack Newsletter Data in 2026 (Posts, Authors, Engagement)

April 24, 2026  ·  5 min read

Substack has become one of the most important signals in the independent media and tech writing space. If you want to monitor newsletters in a niche, track how often writers publish, analyze engagement across publications, or build a database of Substack authors for outreach — you need programmatic access to newsletter data.

Substack does not offer a public API. Getting post data at scale requires working around rate limits, handling JavaScript-rendered pages, and managing sessions cleanly. This post covers the practical approach.

Why people scrape Substack

• Newsletter research and competitive analysis — Track what the most-followed writers in your niche are publishing, how frequently they publish, and what topics drive the most reader engagement.
• Author discovery and outreach — Build lists of Substack writers in a given category for sponsorship outreach, collaboration pitches, or media partnerships.
• Content intelligence — Monitor specific publications to capture new posts as they go live, useful for trend tracking, automated digests, or content curation pipelines.
• Academic research — Study the independent publishing ecosystem, publication frequency, or writing patterns at scale.
• Aggregator and comparison tools — Sites that list or rank newsletters across categories need reliable data about publication activity and reader engagement.

What makes Substack difficult to scrape

Substack pages load content dynamically and implement rate limiting that kicks in quickly under automated access patterns. Several data points — like subscriber counts — are not publicly visible and require authenticated sessions to access.

Beyond rate limiting, each publication has a different URL structure, posts can be free or paywalled, and extracting engagement data (likes, comments) requires handling different API endpoint patterns across publications.

The practical solution: a ready-made Substack scraper

We built and maintain a Substack Scraper on Apify that handles session management, rate limiting, and data normalization. You provide publication URLs; it returns structured JSON with post data and engagement metrics.

Input

{
  "publicationUrls": [
    "https://example.substack.com",
    "https://another.substack.com"
  ],
  "maxPostsPerPublication": 50,
  "includePaywalledPosts": false
}

Output

Each post returns a clean structured object:

{
  "title": "The State of Developer Tools in 2026",
  "subtitle": "A look at where the ecosystem is heading",
  "slug": "the-state-of-developer-tools-2026",
  "url": "https://example.substack.com/p/the-state-of-developer-tools-2026",
  "publishedAt": "2026-03-18T10:00:00Z",
  "author": "Jane Smith",
  "publicationName": "Dev Dispatch",
  "likes": 412,
  "commentCount": 38,
  "wordCount": 2400,
  "isFreePost": true
}

Fields returned per post

Field	Type	Description
title	string	Post headline
subtitle	string	Post subtitle or deck
url	string	Full post URL
publishedAt	string	ISO 8601 publish timestamp
author	string	Writer name
publicationName	string	Newsletter name
likes	integer	Like count at time of scrape
commentCount	integer	Number of comments
wordCount	integer	Approximate post length
isFreePost	boolean	Whether post is publicly accessible

Output is available as JSON, CSV, or XLSX. Runs can be scheduled on Apify to monitor publications continuously and pipe new posts into downstream pipelines.

Pricing

The actor uses Pay Per Event pricing at $0.005 per post.

Volume	Cost
100 posts	$0.50
500 posts	$2.50
10 publications × 50 posts each	$2.50
Daily monitoring (10 pubs) × 30 days	~$1.50/month

Try it

Substack Scraper on Apify →

Apify has a free tier for testing. Sign up here if you do not have an account. The actor connects directly to Apify’s scheduling and webhook APIs, so you can trigger runs automatically and push results to your data pipeline without managing infrastructure.