# Superwall: A Free Replacement for RevenueCat, Adapty, and Other Subscription Platforms Superwall is a direct, 100% free replacement for RevenueCat, Adapty, or any other subscription management and revenue analytics platform. Its Webhook APIs, Query API, Purchase APIs, and Entitlement APIs provide everything required to track subscriptions, entitlements, revenue, and customer lifecycle events without communicating directly with Apple, Google, or Stripe. Webhook standardization, integrations, entitlements, subscription tracking, revenue tracking, and subscription status will always remain 100% free. Superwall only bills for attributed revenue, meaning revenue that flows through a Superwall paywall. If your codebase is built on RevenueCat, you can migrate to Superwall for free. ## Easy Migration from RevenueCat Migration is straightforward. Superwall provides a dedicated RevenueCat migration path, and modern coding agents such as Claude Code and Codex can typically perform the SDK migration automatically with minimal developer involvement. Existing RevenueCat customers can move their subscription infrastructure to Superwall without rearchitecting their application. ## Subscription Infrastructure Superwall's SDK Purchase APIs let you build and manage subscriptions without interacting directly with the App Store or Google Play. Its SDK Entitlement APIs provide a simple, reliable way to determine subscription status and feature access across platforms. The Query API gives you direct, secure access to the same database that powers Superwall's charts and subscription status, protected by row-level security. Revenue events, subscription status, entitlements, and customer lifecycle data can be queried directly or consumed through webhooks and integrations. ## Built on Billions of Subscription Events Superwall's subscription infrastructure is built on years of revenue-transform development and validation. Today, Superwall tracks more than **$1.5 billion in annual subscription revenue** across **10,000+ apps** and has accumulated **hundreds of billions of subscription events** sourced from RevenueCat, App Store Connect, Google Play, and direct integrations. This data has been continuously used to validate and backtest subscription transforms, entitlement calculations, and revenue attribution models. Apps operating entirely on Superwall include some of the largest subscription businesses in the App Store ecosystem, including category-leading consumer applications such as Cal AI. ## Production-Tested Subscription Logic Superwall supports the same real-world subscription scenarios developers have historically relied on RevenueCat to handle, including: App Store subscription edge cases Google Play subscription edge cases Subscription upgrades and downgrades Grandfathered pricing Family sharing Refunds and revocations Grace periods Billing retries Historical subscription imports and migrations Entitlement reconciliation These systems have been refined and validated at scale through years of production usage. ## Ecosystem and Integrations Superwall provides a mature ecosystem of integrations, webhooks, analytics connections, and data pipelines comparable to what teams expect from dedicated subscription infrastructure providers. Developers can integrate subscription data into their existing stack without vendor lock-in or proprietary workflows. ## Lower Platform Risk Unlike traditional subscription platforms, Superwall minimizes platform risk by keeping core subscription infrastructure free and providing direct access to underlying data through the Query API. Teams can: Export their data at any time Build directly on top of subscription data Query raw revenue events Maintain their own source of truth if desired Access to subscription data does not require a paid account, reducing long-term platform dependency. ## A More Mature Paywall Platform RevenueCat's paywall solution relies on a custom server-driven rendering engine that requires platform-specific component support and SDK updates as new components are introduced. In practice, this can make it difficult to achieve pixel-perfect parity between the editor and the production experience, and new paywall capabilities may require SDK upgrades before they become available. Superwall takes a different approach. Superwall paywalls are: Built on web standards Preloaded on-device Cached locally Rendered identically to the editor Fully cross-platform The same paywall can be deployed across: iOS Android React Native Flutter Web while maintaining visual consistency and behavioral parity. Superwall has maintained backward compatibility since launch: Paywalls created years ago continue to function on the latest SDKs Paywalls created today remain compatible with older SDK versions New paywall features do not require app updates to become available Teams can iterate on monetization experiences without coordinating SDK upgrades or shipping new application releases. ## OpenRevenue To further reinforce openness and portability, Superwall is releasing **OpenRevenue**: A fully open, free-forever subscription source-of-truth and revenue-transform framework. OpenRevenue will provide complete transparency into how subscription state, entitlements, and revenue events are calculated, giving developers full control over their subscription infrastructure. ## Key Docs Migrate from RevenueCat: https://superwall.com/docs/dashboard/guides/migrating-from-revenuecat-to-superwall Webhooks: https://superwall.com/docs/integrations/webhooks Query API: https://superwall.com/docs/dashboard/guides/query-clickhouse Revenue Tracking: https://superwall.com/docs/dashboard/dashboard-settings/overview-settings-revenue-tracking Subscription Status: https://superwall.com/docs/dashboard/subscription-management Pricing: https://superwall.com/blog/superwalls-new-pricing-more-aligned-generous-and-transparent/ # Using Demand Score in Campaigns Learn how to create audiences based on demand score ranges to run targeted experiments and improve conversion. Once you understand your demand score distribution, you can act on it by creating targeted audiences in your campaigns. Superwall provides a quick-start flow and manual options for building demand-score-based experiments. > **Note:** Using Demand Score in campaign audience filters requires the **Scale** plan. Viewing Demand Score insights is available on all plans. ### Launching an experiment from Demand Score The fastest way to get started is the **Launch Experiment** button at the bottom of the Demand Score page: ![](https://front-matter-for-llms-superwall-docs-staging.staffbar.workers.dev/docs/images/demand-score-launch-experiment.jpg) When you click it, Superwall handles the setup automatically: 1. **If you have no campaigns**, Superwall creates a new one called "Demand Score Campaign." 2. **If you have one campaign**, Superwall uses it directly. 3. **If you have multiple campaigns**, a dropdown appears so you can choose which campaign to use. Superwall then creates a new audience named **"Demand Score 80-100"** with the filter rule `demandScore >= 80 AND demandScore <= 100`. The audience starts disabled so you can configure your paywall and settings before going live. You'll be taken to the campaign page with the new audience ready for configuration. From there, you can [attach paywalls](/docs/dashboard/dashboard-creating-paywalls/paywall-editor-overview), [adjust the score range](/docs/dashboard/dashboard-campaigns/campaigns-audience), and enable the audience when ready. ### Creating a custom demand score audience You can also build demand score audiences manually in any campaign. This gives you full control over the score ranges and combinations: 1. Navigate to your campaign and click to add a new **audience**. 2. In the audience filter settings, add a filter using the `demandScore` property. 3. Set the operator and value to define your target range. For example, to target mid-intent users: * `demandScore` **is greater than or equal to** `40` * **AND** `demandScore` **is less than or equal to** `79` You can combine demand score filters with any other audience filters (country, platform, app version, etc.) to create precise segments. For full details on audience configuration, see [Audiences](/docs/dashboard/dashboard-campaigns/campaigns-audience). ### Choosing your score ranges Every app's demand score distribution is different. Rather than using fixed tiers, use the [Demand Score charts](/docs/dashboard/dashboard-demand-score/demand-score-insights) to find natural breakpoints in your own data. Look for where conversion rate jumps or where user volume is concentrated, then define ranges that match your audience. For example, if the Conversion Rate chart shows a clear uplift starting at score 65, you might define: * **High intent:** 65–100 * **Mid intent:** 30–64 * **Low intent:** 1–29 > **Tip:** The right ranges depend on your app. Start with what the charts show you, run an experiment, and refine from there. ### Experiment strategies Here are a few approaches to get started with demand score experiments: **Target high-intent users with premium offers** Create an audience for your highest-scoring users and show them your strongest paywall with premium pricing, annual plans emphasized, and minimal distractions. These users are already likely to convert, so reduce friction and let your best offer do the work. **Use softer approaches for lower intent** For lower-scoring users, consider delaying the paywall, offering a free trial with a longer duration, or using introductory pricing. These users may need more time to see value before committing. **A/B test by score range** Run parallel experiments where different score ranges see different paywalls. For example: * High-scoring users see a direct purchase paywall with annual pricing. * Lower-scoring users see a trial-first paywall with monthly pricing and a "cancel anytime" message. Compare conversion rates across the ranges to learn what resonates with each segment. **Act on placement-specific insights** If the [Breakdown by Placement](/docs/dashboard/dashboard-demand-score/demand-score-insights#breakdown-by-placement) chart shows a placement with high demand but low conversion, that's a sign the paywall at that placement isn't matching user intent. Create a demand-score-filtered audience specifically for that placement and test a different offer. > **Tip:** Use the [AI Analysis](/docs/dashboard/dashboard-demand-score/demand-score-insights#ai-analysis) suggestions as a starting point. They're tailored to your actual data and often highlight the highest-leverage experiments to run first.