How to Build a Newsletter Analytics Tracker with Python

Why Track Newsletter Metrics? Newsletters are a booming business. Platforms like Substack, Beehiiv, and ConvertKit host thousands of creators earning serious revenue. But comparing newsletter performance across platforms is nearly impossible without scraping. Lets build a tracker that monitors newsletter growth, engagement, and monetization signals. What We Track Subscriber counts (where public) Posting frequency and consistency Engagement signals (likes, comments, shares) Pricing tiers for paid newsletters Growth trajectory over time Setup pip install requests beautifulsoup4 pandas Newsletter platforms use dynamic rendering. ScraperAPI handles JavaScript-heavy pages. Scraping Substack Newsletters import requests from bs4 import BeautifulSoup import pandas as pd import re from datetime import datetime SCRAPER_API_KEY = " YOUR_KEY " def scrape_substack_profile ( newsletter_slug ): url = f " http://api.scraperapi.com?api_key= { SCRAPER_API_KEY } &url=https:// { newsletter_slug } .substac