RevenueCat Integration in React Native MVP

Integrating Monetization into a React Native MVP: RevenueCat Experience

A developer built an MVP mobile app for learning foreign words using LLMs in just 3 days. Core feature: enter a word, get a translation and 3 example sentences via OpenRouter API. After a web prototype, switched to React Native for iOS, adding spaced repetition, audio playback, and quizzes. The MVP supported English and Serbian, one question type ("remember/don't remember"), and a repetition algorithm (×2 on success, reset on error).

Key challenge: add monetization right away to validate the business model. Without payments, user metrics are meaningless. Free version had limits: 10 words/day to add, 100 for lookup, audio restrictions. Pro version unlimited — $5/month.

Choosing the Tool: RevenueCat for React Native

RevenueCat simplifies subscription integration in cross-platform apps. It provides:

• SDK for React Native.
• Visual paywall screen editor.
• Unified iOS/Android analytics dashboard.
• Handles edge cases: cancellations, restores, expirations.

Alternative — native StoreKit (iOS) implementation, but that means manual product ID setup, subscription groups, and offers in App Store Connect.

Integration Steps:

• Register products in App Store Connect, set up Sandbox for testing.
• Install RevenueCat SDK: npm install react-native-purchases.
• Initialize: Purchases.configure({ apiKey: 'your_key' }).
• Create paywall in RevenueCat dashboard, integrate screen into app.
• Handle events: Purchases.purchasePackage(), listen for onTransactionUpdated.

Test only on device via TestFlight, not simulator. Native builds required for sandbox purchases.

Setup Issues and Launch Hurdles

Setup took a week instead of 3 days for MVP development. Main pain points:

• Linking RevenueCat to App Store Connect: product IDs, subscription groups.
• Tax forms and bank account for payouts (Turkish cards failed validation).
• Edge cases: restore purchases, grace periods, refunds.

App Store review passed without changes, despite risks (benefit claims, error handling). Post-launch: first subscription and feedback.

MVP code was AI-assisted (vibe-coding): generated AWS Polly handlers for audio (~1000 lines), SQL queries for local DB (Realm?). Half the code scrapped after beta, rest refined.

Feedback and Metrics: Value of Early Monetization

Telegram channel post (1500 subscribers) yielded:

• 1 paid subscription ($5, canceled later).
• Tons of free user feedback: AI hallucinations bugs, empty onboarding, requests for transcription, parts of speech, popular languages.

Key takeaways:

• Metric: 1% conversion (1/100) — solid baseline for scaling.
• Economics check: covers AI API + TTS costs.
• No illusions: free prototypes hide lack of willingness to pay.

Feedback backlog: add languages, question types (translation choice, typing, pronunciation), images via Stable Diffusion.

Key Lessons

• MVP without monetization is just a prototype: doesn't validate business.
• RevenueCat speeds integration: SDK + paywall, but store setup is manual.
• Free-tier limits drive upgrades: 10/100 words/day perfect for testing.
• Launch with payments validates the product: one sub > 1000 free users.
• AI vibe-coding pays off for speed: refine only what sticks.

— Editorial Team