

Hard paywalls convert at 10.7%. Freemium converts at 2.1%. Case closed?
Not quite. If hard paywalls were universally better, 90% of App Store apps would not still be using freemium. The headline number hides a more important question: which model is right for your app — and how do you know if it is working?
Key Takeaways
RevenueCat's 2026 report (115,000+ apps, $16B in revenue) puts the gap in stark terms: hard paywalls convert at 10.7%, freemium at 2.1%. The top 10% of hard paywall apps reach 38.7%.
The numbers go beyond conversion rate. Hard paywall users generate 21% higher 1-year LTV and 8x higher Revenue Per Install at Day 14. After one year, retention between the two models is nearly identical — meaning hard paywalls get more revenue without sacrificing long-term retention.
Hard paywalls do not convert better — they filter harder. Users who hit a hard paywall and leave are never counted. The 10.7% conversion rate reflects the behavior of users who chose to stay despite the gate. That is survivorship bias, not proof of superiority.
Freemium tells a different story when you look at the timeline. 23% of freemium conversions happen 6+ weeks after download. These are users who would never have paid on Day 0 — they needed time with the product before committing. A hard paywall would have lost them entirely.
The real question is not which model has the higher conversion rate. It is which model captures the right users from your specific acquisition channels.


The user must subscribe before accessing any content. No free tier, no trial browsing, no limited access.
When it works: When core value is immediately clear. Headspace progressively tested locking content from 20% free down to 100% locked — and saw double-digit conversion lifts at each stage. Users encountered more paywall touchpoints, and the concept was familiar enough from Spotify and Netflix that friction was accepted.
The tradeoff: You lose every user who needs to experience the product before paying. For acquisition channels that bring discovery-driven users (TikTok, Instagram), hard paywalls can filter out users who would have converted after engagement.

The user accesses limited content for free. Premium features, advanced content, or extended usage requires a subscription. Variations include metered access (X free sessions/month), feature-gating (basic free, advanced paid), and time-limited trials.
When it works: When free usage builds a habit that makes premium compelling. Strava offers free GPS tracking and basic activity logging — but locks training plans, route planning, and detailed analytics behind a $11.99/month subscription. Users build a running habit with the free tier, then upgrade when they want deeper insights. Result: 180M registered users, $415M revenue in 2025.
The tradeoff: Requires more product complexity — you need to design both a free experience worth using and a premium experience worth paying for. If the free tier is too generous, users never upgrade. If too restrictive, it feels like a hard paywall with extra steps.


The core product is free. Premium features exist but are not required for the primary use case.
When it works: When free users generate value beyond their own subscription. Nike Training Club eliminated its $14.99/month premium tier entirely in 2020 — making all workouts free. The strategy: use the free app to build brand affinity and drive downstream sportswear revenue. MyFitnessPal uses freemium with 220M registered users and 30M+ monthly actives — monetizing through both premium subscriptions ($9.99/month) and the massive free user base.
The tradeoff: Conversion rates are low — 2.1% median. You need scale to make the economics work. And the algorithm learns from your largest user segment (free users), which can dilute ad signal quality if conversion events are not carefully managed.

Adapty's 2026 benchmark data reveals a pattern unique to Health & Fitness:
Fitness apps are great at getting users to pay. They are terrible at keeping them. This means the paywall model does not just affect initial conversion — it shapes the quality of the subscription cohort that enters. A hard paywall that converts 10% of high-intent users may produce better 12-month revenue than a soft paywall that converts 20% of mixed-intent users — because the hard paywall cohort renews.

Health & Fitness is the only app category where annual plans dominate revenue — 68% of H&F revenue comes from annual subscriptions (RevenueCat 2026). This is significant because:
The paywall model determines how quickly users reach the conversion moment. Hard paywalls force an immediate decision — which works for users arriving from high-intent channels (Search, ASO). Soft paywalls and freemium let users experience workouts first — which may convert more discovery-channel users (TikTok, Instagram) but delays the conversion window.
Which channels convert through your paywall — and which ones don't? See trial-to-subscription rates by channel with 15K free attributed installs.
There is no universally correct paywall model. But there are three factors that narrow the decision:
1. Time-to-value: How quickly does the user experience core value?
2. Network effects: Does user value increase with more users?
3. Revenue model: Is subscription the only revenue source?
Whichever model you choose, the decision is a hypothesis — not a conclusion. The same paywall performs differently across acquisition channels. A hard paywall might convert well for Google Search users (high intent) but poorly for TikTok users (discovery-driven). Without channel-level measurement, you are testing blind.
Paywall A/B tests run at the app level. But the results vary by acquisition channel:
This measurement requires an attribution system that connects paywall events to subscription outcomes at the channel level.
Core Plan tracks Start Trial and Subscribe as standard events with attribution across Meta, Google, Apple Search Ads, and TikTok. The Actuals Report breaks down trial-to-subscription conversion rates by channel — so you can see whether your paywall is converting differently across channels, not just in aggregate.
With native RevenueCat and Adapty integration via S2S, subscription events flow into the attribution system automatically. Before changing your paywall model, this data diagnoses which channels have the widest conversion gap. After the change, it validates whether the new model improved CPS across all channels or just some.

Hard, soft, or freemium — each model attracts a different user profile from each acquisition channel. The paywall that converts best in aggregate may be losing your highest-value channel. The paywall that looks worst overall may be your best performer on the channel that drives annual subscribers.
The only way to know is to measure the full funnel — install to trial to subscription — by channel.
See which channels convert through your paywall — and which ones don't. Start with 15K free attributed installs on Airbridge Core Plan.
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