Fire after your referral backend confirms the redemption — not on code submission. Don't pass the code, the referrer's user ID, or the redemption reward.
▸Install the React Native SDK
npm install @respectlytics/react-native
# or
yarn add @respectlytics/react-nativeJavaScript-only — no native modules, no auto-linking, no New Architecture migration concerns. Bundle size: ~14KB minified+gzipped. Works in any Expo project (managed or bare) without expo prebuild.
▸Initialize Respectlytics in React Native
// App.tsx (or App.js)
import { useEffect } from 'react';
import Respectlytics from '@respectlytics/react-native';
export default function App() {
useEffect(() => {
Respectlytics.configure({ appKey: '<YOUR_APP_KEY>' });
}, []);
return <YourApp />;
}Initialize once in your top-level component. No native config; no Info.plist or AndroidManifest changes. The SDK is Hermes- and JSC-compatible.
▸Track the event in React Native
import Respectlytics from '@respectlytics/react-native';
export async function redeemReferral(code) {
const response = await referralApi.redeem(code);
Respectlytics.track(response.ok ? 'referral_redeem' : 'referral_redeem_failed');
}If the referral arrives via a deep link, fire deeplink_open plus referral_redeem — they are different signals about the same flow.
✦Privacy & implementation notes
Referral codes are short-lived credentials that grant credit. They belong in your referral backend with proper one-time-use enforcement and audit logging — not in product analytics. Respectlytics's API rejects free-text fields, so the code never reaches the analytics layer even if a teammate tries to add it.
The referrer→referree graph is high-cardinality, mutable (refunds void credits), and tied to reward payouts. It is an operational data store, not a product-analytics signal. Respectlytics's role is the rate of redemptions as a product-engagement signal; the graph is your referral system's job.
The React Native SDK is JavaScript-only — no Objective-C/Swift bridging on iOS, no Java/Kotlin bridging on Android. Side effects: no react-native link, no auto-linking, no New Architecture migration concerns, no platform-channel exception surfaces. Trade-off: no access to platform-only metadata (which we don't want to collect anyway).
Works in Expo managed workflow without expo prebuild. No config plugin is required. EAS Build users: nothing to configure. This is the smoothest integration path on RN — most analytics SDKs require ejecting from managed.
⇋How this compares to other analytics SDKs
| Referral redemption event | Firebase Analytics | Mixpanel | Respectlytics |
|---|---|---|---|
| Referral code stored | Common | Common | Rejected by API |
| Referrer user ID stored | Yes | Yes | Never |
| Referree user ID stored | Yes | Yes | Never |
| Reward amount stored | Recommended | Recommended | Out of scope |
| Redemption *rate* by country / platform | Yes | Yes | Yes |
❓Frequently asked questions
How do we know who referred whom without storing the graph?
Your referral backend stores the referrer-referree relationship — that's its job, with the credit-attribution logic that drives reward payouts. Respectlytics tells you whether the redeem-step is working at the aggregate level; the per-user graph is a referral-backend concern.
Can we still compute viral coefficient (k-factor)?
From your referral backend, yes — count of redemptions per referrer over a window is exactly what your backend has. Respectlytics tells you the redemption rate (sessions emitting referral_redeem over sessions emitting referral_code_entered); k-factor is a different question, answered by a different system.
Should we differentiate redemption reasons (organic vs paid)?
If you have a small fixed set of campaign types, distinct event names: referral_redeem_organic, referral_redeem_paid_campaign_a. For high-cardinality campaign IDs, your referral backend's reporting is the right tool.
What if the redemption fails (invalid code, expired)?
Distinct event name: referral_redeem_failed. The rate of failures relative to attempts is a UX signal — high failure rates often indicate copy-paste issues or expired-link problems.