Setting Up Mobile App Analytics Funnels

We’ve seen projects where the registration funnel showed 0% due to incorrect identity merge. After fixing it, conversion jumped from 0% to 23%. In 80% of cases, funnels in Firebase and GA4 are built with errors: wrong conversion window, mismatched event parameters, duplicate events on client and server. Once, in an e-commerce app, the client lost 70% of users at the checkout step — the purchase event wasn’t logged on iOS. After adjustments, conversion rose from 8% to 15% in a week. A properly set funnel increases conversion by 20–30% on average, and up to 50% with smart segmentation. We help companies set up funnels in Firebase, Amplitude, and Mixpanel to identify bottlenecks and improve key metrics. Contact us for a funnel audit and get specific recommendations.

Where to Build Funnels

Three main tools depending on your stack:

• Firebase / Google Analytics 4 — Explore section → Funnel Exploration. Funnels are based on events from the stream.
• Amplitude — Funnel Analysis in the Analytics section. More flexible settings: you can set conversion window per step, group by properties. Amplitude's segmentation flexibility is 3x higher than Firebase's.
• Mixpanel — Funnels in the Reports section. It allows viewing funnels by unique users, sessions, or events — different metrics give different numbers.

How to Properly Structure Events for a Funnel?

A registration funnel should look like this:

app_open → sign_up_start → sign_up_email_entered → sign_up_password_entered → sign_up_success

Each event is a separate step. A common mistake: developers log only the start and end. Then you can’t tell where users drop off — after email or after password.

// Correct — each step separately
Analytics.logEvent("sign_up_start", parameters: ["method": "email"])

// After email entered
Analytics.logEvent("sign_up_email_entered", parameters: [:])

// After password entered
Analytics.logEvent("sign_up_password_entered", parameters: [:])

// After successful registration
Analytics.logEvent(AnalyticsEventSignUp, parameters: ["method": "email"])

How to Set Up a Funnel in Firebase Explore?

1. Explore → + New Exploration → Funnel Exploration
2. Add steps in order
3. Set Conversion Window — typical values: 1 day for registration, 7 days for onboarding, 30 days for first purchase
4. Enable Open funnel if step order is not mandatory, Closed for strictly sequential

Conversion Window is the most influential parameter. The same funnel with a 1-day vs 7-day window can show 15% and 40% conversion, respectively. The choice depends on how fast users actually make decisions. For precise conversion window setup, refer to Firebase documentation (https://firebase.google.com/docs/analytics/funnels).

Why Is Conversion Window So Critical?

Typical windows for different funnels:

Another important setting is the step property. For example, add an item_category parameter to the purchase event to build a funnel for each category separately. This helps pinpoint weaknesses in specific flows.

Funnels with Segmentation Parameters

One powerful technique is comparing funnels across segments. In Amplitude, this is done via breakdown:

// Funnel steps remain the same, but broken down by:
// - install source (utm_source)
// - device type (iOS vs Android)
// - app version

Example: conversion from registration to first purchase for paid traffic users is 8%, for organic — 22%. This signals that the UA audience quality needs review. Cutting spending on ineffective channels can save up to 30% of the ad budget — one client saved $2000 per month after fixing checkout.

Comparison of Funnel Tools

Firebase is better for startups with limited budgets, Amplitude for mature products needing complex segments. Mixpanel suits teams focused on events-based analytics.

Errors That Break Funnels

• Different user IDs across steps. If a user starts the funnel as anonymous (device_id) and later becomes authenticated (user_id), and analytics doesn’t merge identities — the funnel breaks at the registration step. In Firebase, use Analytics.setUserId() after successful authentication. In Amplitude, identify.setUserId() + identify.alias().
• Events logged on both server and client. A purchase with the same transaction_id is sent from both iOS SDK and backend. In the funnel, the user passes the step twice — conversion is distorted.
• Wrong timestamp. If on Android events are sent with a delay (offline queue) using server timestamp instead of client timestamp — event order in the funnel can be disrupted.
• Google’s official documentation recommends always checking identity merge before building funnels.

We also help analyze user crashes at each funnel step.

What’s Included in Our Work

• Audit of current events for funnel step compliance
• Adding missing intermediate events
• Configuring funnels in Firebase Explore / Amplitude / Mixpanel
• Setting conversion window based on real user behavior
• Setting up segmentation by source, platform, version
• Documenting the funnel schema for the team
• 30 days of support after setup

Order a funnel audit to get specific recommendations for improving conversion. Get a consultation — we’ll tell you how to optimize your analytics.

Timeline

One funnel with event audit: 1 day. Full set of funnels (registration, onboarding, monetization): 3–4 days. Price is calculated individually. Contact us — we’ll help identify issues in your funnels and increase conversion. Over 5 years of experience and 30+ projects guarantee data correctness.

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.

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.

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.