How do I set up a mobile game analytics platform to measure tutorial and onboarding drop-off across iOS and Android?

To measure tutorial and onboarding drop-off across iOS and Android, set up your analytics around a clean event funnel, consistent identifiers, and platform-aware instrumentation. Here’s a practical blueprint.

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1) Define exactly what “drop-off” means

For onboarding, decide the steps you want to measure, for example:

1. App first open
2. Tutorial started
3. Step 1 completed
4. Step 2 completed
5. Account/login prompt shown
6. Tutorial completed
7. First gameplay session started

Then define drop-off as:

• users who entered a step but did not complete the next step within a time window
• or users who closed the app / uninstalled / never returned before completion

Be explicit about:

• whether a step is mandatory or optional
• whether a step completion is instant or session-based
• your attribution window for completion, e.g. same session, 24 hours, 7 days

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2) Choose an analytics stack

You need:

• event tracking
• funnel analysis
• cross-platform identity
• optionally cohorting, remote config, A/B testing

Common options:

• Firebase Analytics + BigQuery
  Good default for mobile; free-ish and easy on iOS/Android.
• Amplitude Great for funnels, retention, user journeys.
• Mixpanel Similar, strong for event analysis.
• Game-focused stacks like Unity Analytics, GameAnalytics, Adjust + analytics warehouse

If you want maximum control, use:

• SDKs on iOS/Android
• send events to a warehouse (BigQuery/Snowflake/Redshift)
• visualize in Looker/Metabase/Mode

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3) Instrument a consistent onboarding event schema

Create the same event names and properties on both platforms.

Suggested events

• app_first_open
• onboarding_started
• tutorial_step_viewed
• tutorial_step_completed
• tutorial_skipped
• onboarding_completed
• onboarding_abandoned
• gameplay_started

Event properties

Use these on every onboarding event:

• platform = ios / android
• app_version
• build_number
• tutorial_version
• step_name or step_index
• session_id
• user_id or anonymous_id
• locale
• device_model
• os_version
• country
• acquisition_channel if available

Example:

{
  "event_name": "tutorial_step_completed",
  "user_id": "12345",
  "anonymous_id": "abc-xyz",
  "platform": "android",
  "app_version": "2.4.1",
  "tutorial_version": "v3",
  "step_index": 2,
  "step_name": "move_character",
  "session_id": "sess_987",
  "timestamp": "2026-07-24T12:34:56Z"
}

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4) Track funnel steps, not just screens

For onboarding, a screen view is often not enough. Measure:

• screen shown
• action completed
• next step unlocked

Example funnel:

• onboarding_started
• tutorial_step_1_completed
• tutorial_step_2_completed
• tutorial_step_3_completed
• onboarding_completed

If a player can spend time on a step, consider tracking:

• tutorial_step_started
• tutorial_step_failed
• tutorial_step_retried
• tutorial_step_skipped

This helps you identify where they stall.

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5) Use a shared event contract across iOS and Android

Make a single tracking spec so both platforms emit identical semantics.

Create a document with:

• event name
• when it fires
• required properties
• optional properties
• examples
• owner/team

This prevents iOS and Android from drifting apart.

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6) Implement identity correctly

You need to connect:

• anonymous first launch events
• logged-in user events
• possibly cross-device identity later

Best practice:

• generate an anonymous ID on first launch
• when user logs in or signs up, alias/merge anonymous ID to stable user_id
• keep both IDs in your analytics system if supported

This matters because onboarding often happens before login.

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7) Capture session and lifecycle events

Add:

• app_open
• app_backgrounded
• app_foregrounded
• session_started
• session_ended

This lets you distinguish:

• users who left mid-tutorial
• users who completed later in the same session
• users who returned in a new session

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8) Measure drop-off with funnel analysis

Build a funnel like:

1. app_first_open
2. onboarding_started
3. tutorial_step_1_completed
4. tutorial_step_2_completed
5. tutorial_step_3_completed
6. onboarding_completed

Key metrics:

• conversion rate per step
• largest drop-off step
• time to complete each step
• drop-off by platform
• drop-off by app version
• drop-off by acquisition source

Example:

• iOS: 72% complete step 1, 55% step 2, 41% step 3, 33% finish
• Android: 80% step 1, 68% step 2, 39% step 3, 28% finish

That shows where Android may have a performance or UX issue.

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9) Segment by platform and device context

Always break results down by:

• iOS vs Android
• device model / screen size
• OS version
• country / language
• app version
• source campaign
• new vs returning users
• install date cohort

Tutorial issues often show up only on:

• small screens
• low-end Android devices
• specific locales
• older OS versions

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10) Add qualitative context to the analytics

If users drop at the same step repeatedly, attach context:

• a tutorial_error event
• reason codes from validation
• gameplay failure counts
• latency / frame drops during the step

Example:

• tutorial_step_failed
  • failure_reason = "gesture_not_recognized"
  • latency_ms = 1800

This helps determine whether drop-off is due to:

• confusion
• technical issues
• pacing
• difficulty

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11) Use A/B testing to validate improvements

Once you find a drop-off point, test variations:

• shorter tutorial
• fewer required steps
• different UI copy
• interactive vs text-only instruction
• skip option
• delayed login prompt

Measure:

• step conversion
• tutorial completion
• day-1 retention
• first purchase / early monetization
• long-term retention

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12) Validate your instrumentation

Before shipping:

• run the app in debug mode
• confirm events fire in order
• verify event properties match spec
• compare iOS and Android payloads
• test reinstall, first open, login, app kill, resume
• ensure events are not duplicated

Common bugs:

• step completion fires twice
• onboarding completion fires before actual completion
• anonymous IDs reset on app restart
• iOS and Android use different step names

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13) Practical setup with Firebase as an example

If you use Firebase Analytics:

1. add Firebase SDK to both iOS and Android
2. define custom events for onboarding
3. mark key events as conversions if needed
4. export to BigQuery for deeper analysis
5. build funnels in Looker/BigQuery or Firebase dashboard

You can then query:

• users who started onboarding
• users who completed each step
• differences by platform/version

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14) Recommended onboarding dashboard

Create a dashboard with:

Funnel

• first open → onboarding started → each tutorial step → completed

Breakdown tables

• by platform
• by app version
• by device type
• by country
• by acquisition channel

Time metrics

• time to first interaction
• time between steps
• total onboarding duration

Quality metrics

• crash rate during onboarding
• ANR rate on Android
• frame drops / loading delays
• network failures

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15) Minimum viable implementation

If you want the simplest robust setup:

• Firebase Analytics
• shared event naming spec
• anonymous ID + user ID merge
• onboarding funnel events
• BigQuery export
• dashboard with funnel conversion by platform/version

That’s enough to measure drop-off accurately on both iOS and Android.

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Example onboarding event flow

app_first_open
→ onboarding_started
→ tutorial_step_viewed(step=1)
→ tutorial_step_completed(step=1)
→ tutorial_step_viewed(step=2)
→ tutorial_step_completed(step=2)
→ tutorial_step_viewed(step=3)
→ tutorial_skipped
→ onboarding_abandoned

Then report:

• Step 1 completion rate
• Step 2 completion rate
• Skip rate
• Abandonment rate
• Completion rate by platform

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If you want, I can also give you:

1. a sample event schema
2. a BigQuery SQL funnel query
3. a Firebase implementation example for iOS/Android
4. a recommended dashboard layout