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I Studied 100 Paywalls, Here's What I Found
Steven Cravotta breaks down RevenueCat's 339-page "State of Subscription Apps" report (115,000+ apps, \$16B+ revenue) plus a study of 100 top paywalls, into a research-backed paywall playbook: hard...
https://www.youtube.com/watch?v=y0f8-CSOJ58
I Studied 100 Paywalls, Here's What I Found

TL;DR

Steven Cravotta breaks down RevenueCat’s 339-page “State of Subscription Apps” report (115,000+ apps, $16B+ revenue) plus a study of 100 top paywalls, into a research-backed paywall playbook: hard paywalls convert 5x freemium, price as high as possible (high-priced apps earn 5.4x the LTV of low-priced), push the yearly plan with a free trial, and A/B test everything by volume, not time.

The data (RevenueCat report)

  • Hard paywalls convert ~5x better than freemium — the advantage shrinks over a year+, but most users don’t retain that long, so hard paywalls get your ROI back far faster. Worth the extra friction.
  • The window to win is closing — 55% of all cancellations happen on day zero. Deliver the aha moment fast.
  • ~50% of paid conversions happen on day zero (echoed by Aperture’s founder) — the day users care most. Don’t rely on them coming back to upgrade.
  • Price high. High-priced apps generate ~$36 median monthly LTV vs $6.67 for low-priced — 5.4x higher. Mid-priced sit at roughly half the high-priced figure.
  • Yearly plans monetize ~2x better than other plan durations in the first 14 days, holding the edge at day 60. Most successful apps offer two plans (yearly + monthly), with the free trial offered only on the yearly plan.
  • Geography matters: North America drives highest return on spend, then Asia-Pacific, then Western Europe.
  • The bottom 25% of apps shrank 33% YoY; only 4.6% of apps ever reach $10k/month — gap is driven by paywall/marketing tactics, not code quality.

Paywall design & positioning

  • Clarity over complexity / clarity over persuasion. The paywall is the single most important screen — the decision point. Don’t make users calculate or think.
  • Trial-timeline priming screens build trust: Duolingo and Cal AI show a “here’s what happens during your trial / we’ll remind you before it ends” screen before the real paywall (the reminder requires turning on push notifications — positive friction).
  • The holistic funnel: long onboarding primes the user → hard paywall converts. Studied apps (Cal AI, Duolingo, Cocoa Note $1M/mo note app) all run intro → long questionnaire → hard paywall.
  • Drip funnel: for the 70% who abandon, push a discount (30/50/70% off) to a discounted paywall to recover otherwise-lost value.

Always be testing

  • It’s about volume, not time — confidence comes from user count. Puff Count’s data: 196k users, 91% completed onboarding, 27% started trial; tens of thousands of views per paywall variant.
  • Scientific method — change one thing at a time. Test pricing first, then header wording, then reviews. Superwall uses Bayesian analysis.
  • Optimize the whole funnel sequentially: paywall → onboarding → marketing creatives — each individually.

Tools mentioned

RevenueCat (report + subscription engine), Superwall (paywall A/B testing), Mixpanel (onboarding event tracking), paywallscreens.com & ScreensDesign (competitor paywall/onboarding research), 99designs (paywall design contest).

What links here