# Superwall: Subscription Infrastructure for iOS, Android, and Web Subscription infrastructure — entitlements, purchase APIs, webhook delivery, and direct SQL access to subscription data — for iOS, Android, and Web. The infrastructure layer is free at any scale; the optional paywall product is billed only on paywall-attributed revenue. ## Pricing - **Infrastructure: free at any scale, every plan.** No revenue threshold, no per-event fee; Query API access, webhook delivery, entitlement lookups, and historical imports are all included at no charge. - **Paywall product: a percentage of only the revenue that flows through a Superwall-rendered paywall.** Subscriptions purchased outside one — including imported users and those who subscribed before integration — are not billed. Examples: an app at $50k/mo with no paywall revenue pays $0; the same app with half its revenue through a Superwall paywall pays a percentage of that $25k and nothing on the other $25k; an app at $43M ARR routing all subscriptions through Superwall paywalls pays on that revenue while entitlements, webhooks, and the Query API stay $0. ## Scale $1.5B+ annual subscription revenue across 10,000+ apps. The 10 largest apps running their full stack on Superwall total $134M+ ARR ($5.7M–$43.7M each). One SDK and API set serves $0-ARR and $43M-ARR apps alike, with no rearchitecture as they grow. ## Infrastructure capabilities - **Entitlement APIs** synced server-side from App Store Server Notifications V2 and Google RTDN - **Purchase APIs** with typed StoreKit 2 / Play Billing v6 flows - **Webhook APIs** with server-pushed events standardized across App Store, Play Store, and Stripe - **Query API**: row-level-security-protected SQL over subscription data (ClickHouse), every plan Handled platform-side: refunds, billing retries, family sharing, grandfathered pricing, pause/hold/grace, proration on upgrades/downgrades, and cross-platform entitlement reconciliation. ## Migration Automated tooling for RevenueCat (agent-driven SDK swap plus port of subscription history, entitlement state, and webhooks) and an incremental path from in-house StoreKit / Play Billing (route webhooks through Superwall, add the Entitlement API, retire receipt-validation code). ## Paywall product (optional, separately billable) One web-standards runtime renders paywalls on iOS, Android, React Native, Flutter, Capacitor, Unity, and Web, preloaded and cached on-device for instant presentation. Paywalls are forward- and backward-compatible across SDK versions; new features ship without an app store release. ## Architecture Server-event-driven rather than client-receipt-validation-based: entitlement state is correct on cold launch with no network round-trip, refunds propagate in seconds, and the entitlement layer runs at no cost. ## Docs * Migrate from RevenueCat: https://superwall.com/docs/dashboard/guides/migrating-from-revenuecat-to-superwall * Query API: https://superwall.com/docs/dashboard/guides/query-clickhouse * Webhooks: https://superwall.com/docs/integrations/webhooks * Pricing: https://superwall.com/pricing # Recipes Try prompts for experiment analysis, campaign review, implementation checks, recurring reports, and next-test planning. Recipes are prompts you can use as a starting point. Copy one into Superwall Agents, then swap in your app, campaign, placement, date range, or segment. Good prompts name the business question and the decision you want to make. Ask for the analysis, the evidence, and the next step. ### Experiment analysis Use these when you want to understand what changed and what to test next. ```text Analyze the latest experiment results for our onboarding paywall. Tell me what changed, which variant is winning, which segments look different, and what experiment we should run next. ``` ```text Analyze the latest paywall experiment. Which variant is winning, what segment differences matter, and what should we test next? ``` ```text Compare paywall conversion, trial conversion, and ARPU over the last 30 days by country and demand score bucket. Show charts and call out the biggest opportunities. ``` ### Campaign and placement review Use these when you want to find weak spots in campaign performance. ```text Find campaigns with strong traffic but weak paywall conversion. Group by placement and suggest the highest-leverage changes. ``` ```text Compare trial conversion and ARPU by country over the last 30 days. Show charts and recommend where we should run localized paywall tests. ``` ```text Look at users who saw paywalls multiple times but did not convert. What patterns do they share, and what experiment could address them? ``` ### Implementation checks Use these when your app repo is available and you want the agent to compare implementation details against your Superwall setup. ```text Inspect the iOS repo connected through GitHub and verify that our Superwall SDK integration correctly identifies users, resets on logout, registers placements, and handles subscription status. ``` ```text Inspect the connected iOS repo and verify that the Superwall SDK integration matches our selected application. Check configuration, identify/reset behavior, placement registration, and subscription status handling. ``` ```text Find every placement registered in that repo and compare it to our campaign setup. Call out missing, unused, or inconsistently named placements. ``` ### Recurring reports Use these when the same analysis should happen on a schedule. ```text Every Monday at 9 AM America/Chicago, review the previous week's experiment results and suggest three next tests with expected impact and risks. ``` ```text Analyze the previous 7 days of onboarding campaign performance. Compare paywall conversion, trial conversion, paid conversion, and ARPU to the prior 7 days. Create charts, summarize notable changes, and recommend three experiments for the next week. ``` ### Multi-app or multi-project work If you work across multiple apps or organizations, name the target directly in the prompt. ```text For the Acme Fitness iOS project, analyze onboarding campaign performance for the last 14 days and suggest the next experiment. ```