Firebase and AppsFlyer are not competitors, and picking "one or the other" is the wrong question. Firebase Analytics tells you what users do inside your app — sessions, retention, which screens convert. AppsFlyer tells you where they came from — which ad campaign drove each install and whether that user later spent money. Most apps running paid acquisition need both, because each answers a question the other can't.
Two different jobs
The clearest way to choose is to name the job:
- Product analytics (Firebase): in-app behavior. What happens after the app opens — onboarding completion, feature usage, engagement, retention, and revenue events you log yourself.
- Attribution (AppsFlyer): marketing measurement. Which campaign, network, and creative drove an install, and what that cohort did downstream. This is the job of a Mobile Measurement Partner (MMP).
Firebase can't tell you that a user came from a specific TikTok campaign; attribution lives outside your app, in the handshake between the ad network, the App Store, and an MMP. AppsFlyer isn't built to be your deep product-analytics warehouse. They're complementary by design.
At a glance
- Primary question: Firebase — "what do users do in the app?" · AppsFlyer — "which campaign drove this install?"
- Category: Firebase — product analytics · AppsFlyer — Mobile Measurement Partner (attribution).
- iOS privacy: Firebase — measures consenting in-app behavior · AppsFlyer — handles SKAdNetwork and ATT-limited attribution.
- Pricing: Firebase — free, GA4-powered · AppsFlyer — paid, priced around attributed conversions.
- Cross-network view: Firebase — no · AppsFlyer — yes, one consistent view across ad networks.
What Firebase Analytics is for
Firebase Analytics is Google's app analytics, powered by Google Analytics 4 (Firebase). It's free, logs effectively unlimited custom events, and automatically tracks engagement and retention. For an Expo or React Native app, it's the default first stop: instrument your canonical lifecycle events (session_started, signup_completed, trial_started, purchase_completed) and you can answer most "what are users doing?" questions without paying for a dedicated analytics tool.
Where Firebase stops is acquisition. It sees the user once they're in the app; it does not resolve which paid campaign deserves credit for the install.
What AppsFlyer is for
AppsFlyer is an MMP — its job is install attribution and the privacy-safe plumbing that makes attribution work on modern iOS. That includes handling Apple's SKAdNetwork, the framework that attributes iOS installs without identifying the user (Apple Developer), and reconciling it with deterministic data where consent allows. AppsFlyer connects ad spend on Meta, TikTok, and other networks to installs and downstream revenue, so you can compute return on ad spend by campaign.
If you're buying installs, you need this. Self-reported numbers from each ad platform overstate their own contribution; an independent MMP is what gives you one consistent attribution view across channels.
How they fit together
A common, sensible stack pairs an MMP for attribution with a product-analytics tool for in-app behavior. With VibesFlyer that pairing is explicit: you connect Firebase for product analytics and AppsFlyer for attribution, map the same canonical events to both, and pull the results into one normalized schema. The shared taxonomy is what lets the two line up — a purchase_completed event means the same thing whether Firebase is measuring engagement or AppsFlyer is attributing revenue to a campaign.
Concretely: a user installs from a Meta campaign, completes onboarding, starts a trial, and subscribes a week later. AppsFlyer credits the Meta campaign for the install and the downstream purchase_completed, so you can compute that campaign's ROAS. Firebase, fed the same events, shows that this cohort finishes onboarding at a higher rate and retains better than organic users. One instrumentation pass; two complementary readouts. Without the shared taxonomy you'd be stitching together mismatched event names across two tools and never trusting either.
When you might use only one
- Firebase only: pre-revenue or organic-only apps that aren't running paid user acquisition yet. You need product analytics; you don't yet need attribution.
- AppsFlyer only: rare, and usually a sign you're under-measuring product behavior. Even attribution-heavy teams keep a product-analytics layer.
For anything spending money on installs, "Firebase and AppsFlyer" is the answer. Firebase also bundles adjacent services many apps want anyway — Crashlytics for stability, Remote Config, push — which makes it an easy default to keep even once an MMP is in place.
The honest takeaway
The two tools answer different halves of the same question — did this user stick around and spend? (Firebase) and which campaign brought them? (AppsFlyer). Treat owned, first-party events as the source of truth that feeds both, keep one canonical event taxonomy across them, and you get product insight and campaign ROAS from a single instrumentation pass — instead of arguing about which dashboard is "right."