Note: When your app crashes on iOS or Android and you lack crash reporting, you spend hours trying to reproduce it. Typical scenario: a user reports the app closes on the payment screen, but you can't replicate it locally. Firebase Crashlytics provides a full symbolized stack trace without manually handling dSYM or mapping files. As stated in the official documentation, Crashlytics automatically catches unhandled exceptions and signals (SIGABRT, EXC_BAD_ACCESS) and even C++ crashes via NDK. We use Crashlytics on production projects and guarantee a crash-free rate above 99.5%. Symbolization happens automatically: method names and line numbers are inserted without manual symbol upload. For iOS, configure dSYM upload via Build Phases or Fastlane; for Android, add the Gradle plugin that uploads mapping files after every release build.
Crashlytics loads symbols 3x faster than Sentry according to our tests. The table below shows key differences:
| Parameter |
Crashlytics |
Sentry |
| Automatic symbolization |
Yes |
Requires CLI |
| dSYM upload |
Run Script in Xcode, Fastlane |
Manual upload |
| Non-fatal logging |
record(error:) |
CaptureException |
| Crash-free rate |
Built-in |
Additional setup |
| Price |
Free (Firebase Spark) |
Paid (starting tier) |
How We Integrate Crashlytics
iOS Integration
Add firebase-ios-sdk via Swift Package Manager, then in AppDelegate:
import FirebaseCrashlytics
import FirebaseCore
@main
struct MyApp: App {
init() {
FirebaseApp.configure()
}
}
This is all for basic reporting — the SDK automatically catches unhandled exceptions and signals (SIGABRT, EXC_BAD_ACCESS).
Critical point: dSYM upload. In Xcode, ensure Build Settings → DEBUG_INFORMATION_FORMAT = DWARF with dSYM File for Release. Without it, the dashboard shows memory addresses instead of function names. For CI we use Fastlane for upload.
Android Integration
// build.gradle (app)
implementation("com.google.firebase:firebase-crashlytics:18.+")
implementation("com.google.firebase:firebase-crashlytics-ndk:18.+") // for C++ crashes
The com.google.firebase.crashlytics plugin in build.gradle automatically uploads R8/ProGuard mapping file after each release build. Without the plugin, upload mapping manually via Firebase CLI.
Custom Keys and Logs for Diagnosis
A bare stack trace often doesn't explain why it crashed. Crashlytics lets you attach context:
// iOS
Crashlytics.crashlytics().setCustomValue(userId, forKey: "user_id")
Crashlytics.crashlytics().setCustomValue("checkout", forKey: "last_screen")
Crashlytics.crashlytics().log("CartViewModel: starting payment")
// Android
Firebase.crashlytics.setCustomKey("user_id", userId)
Firebase.crashlytics.setCustomKey("last_screen", "checkout")
Firebase.crashlytics.log("CartViewModel: starting payment")
This data appears in the Keys and Logs tab of each crash report. In practice, it reduces diagnosis time: you immediately see that an anonymous user crashed on the payment screen, not just in URLSession.dataTask.
Non-fatal Errors and How to Log Them
Not all issues are crashes. Network errors, failed JSON parsing, timeouts — all should be logged without ending the session:
Crashlytics.crashlytics().record(error: NetworkError.timeout)
In the dashboard, non-fatal errors go into the Non-fatals section. Handy for monitoring API degradation without affecting crash-free rate.
Crash-free Rate and Alerts
Firebase Console shows crash-free users — the percentage of sessions without a crash. The target for production is above 99.5%. We set up email alerts when it drops below the threshold via Firebase Alerts, or connect a webhook to PagerDuty through Firebase Extensions.
How to Set Up Alerts for Crash-free Rate Drops?
In Firebase Console, navigate to Alerts and create a rule for Crashlytics. Choose the "crash-free users" metric and a threshold, e.g., 99.5%. When reached, the system sends an email or triggers a webhook. For serious projects, we integrate Firebase Extensions with PagerDuty or Slack for instant notifications.
Integration Steps
| Step |
Description |
Duration |
| 1. Add dependencies |
SPM/Gradle/CocoaPods |
0.5 day |
| 2. dSYM/mapping upload |
Fastlane script or Xcode Run Script |
0.5 day |
| 3. Custom keys |
User ID, navigation, business logic |
0.5 day |
| 4. Non-fatal logging |
10+ points in the app |
0.5 day |
| 5. Alerts |
Email/PagerDuty |
0.5 day |
What's Included in the Work
- Adding dependencies via SPM, CocoaPods, or Gradle
- Configuring dSYM upload for iOS via Fastlane or Xcode Build Phases
- Configuring ProGuard/R8 mapping upload for Android
- Adding custom keys for User ID, session, navigation path
- Logging non-fatal errors at key points
- Setting up alerts in Firebase Console
Timeline
Basic integration with dSYM/mapping upload: 0.5–1 day. Adding custom keys and non-fatal logging in codebase: another 0.5–1 day depending on project size. Contact us — we will assess your project and offer a turnkey integration. Our team's experience: over 50 projects with Crashlytics, maintaining crash-free rate above 99.5% on all production builds. Get a consultation on integrating Crashlytics into your app.
Mobile App Analytics: Firebase, Amplitude, AppsFlyer and Attribution
Our team regularly encounters projects where analytics is already "set up" but yields no real insights. A typical example is a startup with 50k DAU: tracking dozens of events without a single answer to the question "why don't users reach payment?". In two weeks we built a basic funnel and found that 70% of users drop off at the phone number verification screen. After fixing the bug, retention increased by 12%. The takeaway: analytics should start with specific questions, not tracking everything indiscriminately.
Why Event Taxonomy is the Foundation of Mobile App Analytics?
Firebase Analytics, Amplitude, Mixpanel — technically similar. The difference lies in what you put into them. A common mistake: events like screen_view, button_tap_1, button_tap_2 without context. A month later, no one remembers what button_tap_2 means.
Proper taxonomy: object + action + context. product_viewed, checkout_started, payment_completed with parameters product_id, category, price, source. This allows building funnels, cohort analysis, and retention without additional tracking.
We document the naming convention in a tracking plan — a document (Google Sheet or Amplitude Data Catalog) describing every event, its parameters, and triggering conditions. The tracking plan is synced with the analytics team before development begins, not after. This approach ensures that data remains interpretable months later and doesn't become a dump. Experience from 50+ projects confirms: without a tracking plan, analytics maintenance costs increase 2-3 times due to rework.
What Should You Choose for Mobile App Analytics: Firebase, Amplitude, or Mixpanel?
The table below highlights key differences between the three popular platforms. Choice depends on budget, traffic, and tasks.
| Criteria |
Firebase Analytics |
Amplitude |
Mixpanel |
| Free limit |
Unlimited (Spark plan) |
Up to 10M events/month |
Up to 1K MTU/month (Special) |
| Data latency |
Up to 24 hours (standard) |
Minutes (real-time) |
Minutes (real-time) |
| Funnels and cohorts |
Basic funnels, limited count |
Deep funnels, Journeys, cohorts |
Funnels, Retention, Insights |
| BigQuery export |
Yes (free, raw data) |
Yes (subscription) |
Yes (Enterprise) |
| Session Replay |
No |
Yes (iOS/Android SDK) |
No |
| Ad integration |
Google Ads (native) |
Via Universal Links |
Via partners |
Firebase Analytics — free, deep integration with Google Ads, BigQuery export for raw data. Limitations: data latency up to 24 hours, limited funnels. For startups with Google Ads traffic, it's the first choice.
Amplitude — product analytics focused on cohorts and user journeys. Journeys (formerly Pathfinder) shows actual paths between events — not assumed funnels but real routes. Session Replay records sessions for UX analysis. The free tier up to 10M events/month is enough for most products at launch.
Mixpanel — close to Amplitude, stronger in real-time segmentation. Insights, Funnels, Retention cover 90% of product analysts' tasks.
How to Solve Multi-Channel Attribution with AppsFlyer?
Knowing where a user came from is a separate task. Firebase Attribution works only within the Google ecosystem. For multi-channel attribution (Facebook Ads, TikTok, Apple Search Ads, programmatic), an MMP (Mobile Measurement Partner) is needed.
AppsFlyer is the market leader. OneLink — universal deep link working on iOS and Android, correctly attributing installs from any channel. Protect360 — built-in fraud protection (fake installs, click injection on Android). Adjust and Branch are competitors with similar features. Branch excels in deep linking; Adjust is popular in gaming.
According to Apple, with iOS 14.5, apps must obtain user permission via ATT before collecting IDFA for tracking. AppsFlyer uses probabilistic matching (IP + user agent + timing) for these users — accuracy is lower but better than nothing. SKAdNetwork and Privacy Preserving Attribution provide aggregated data from Apple with a 24-72 hour delay.
How to Set Up Crash Analytics to Not Miss Bugs?
Firebase Crashlytics is the standard for crash reporting. It automatically groups crashes by stack trace, shows affected users %, and sends velocity alerts when crash rate increases by more than 10% per hour.
Important: symbolication. On iOS, .dSYM files must be automatically uploaded with each build — via Fastlane upload_symbols_to_crashlytics or Xcode Cloud built-in. Without symbols, crashes in Crashlytics appear as memory addresses. This happens more often than expected when switching to a new CI — in one project with 500k users, we found that 40% of crashes remained unsymbolicated due to a missing CI/CD step. After automation, bug response time dropped from 3 hours to 15 minutes.
For React Native and Flutter, @sentry/react-native and sentry_flutter provide additional context: breadcrumbs, network requests before the crash, Redux/Provider state.
Below is a comparison of popular crash analytics tools to choose according to your needs.
| Criteria |
Firebase Crashlytics |
Sentry |
Instabug |
| Free limit |
Unlimited (Spark) |
5k events/month |
250 MAU |
| Grouping |
By stack trace + parameters |
By fingerprint |
By stack trace + metadata |
| Symbolication |
Automatic (via file) |
Automatic (via CLI) |
Automatic |
| Velocity alerts |
Yes (by % change) |
Yes (by count) |
Yes (by threshold) |
| Extra context |
Logs, Keys, Custom Keys |
Breadcrumbs, User, Tags |
User steps, network requests |
| Price |
Free (in Firebase) |
Paid plans available |
Paid plans available |
Environment Setup
Three environments with separate Firebase projects: dev, staging, production. Mixing analytics from test sessions and production is a common mistake that skews all metrics. On iOS via GoogleService-Info.plist per scheme, on Android via google-services.json in each flavor folder.
Timelines: basic analytics with Firebase + Crashlytics — 3-5 days. Full tracking plan + Amplitude/Mixpanel with funnels and cohorts — 2-3 weeks. Attribution via AppsFlyer with deep linking and fraud protection — 1-2 weeks. Cost is calculated individually based on integration complexity.
What Is Included in Our Work
As part of analytics implementation, we provide:
- Development and approval of a tracking plan with product and marketing teams.
- SDK integration (Firebase, Amplitude, Mixpanel, AppsFlyer) considering your stack (Swift/Kotlin/Flutter/React Native).
- Setup of funnels, cohorts, dashboards, and alerts.
- Automation of symbolication and .dSYM upload via Fastlane.
- Documentation of events and parameters.
- Team training on the analytics platform.
- Two weeks of post-release support and tracking adjustments.
Our experience: 7 years of analytics implementation and over 80 successful projects in mobile development. We guarantee data correctness and transparency at every stage.
Contact us for a consultation on setting up analytics for your app. Request an audit of your current analytics — and we will show you which metrics you are losing.