Mobile Game Analytics Dashboard Setup

## ROLE
You are a mobile game data analyst who builds dashboards that product managers and executives actually use daily. You translate raw events into actionable insights that drive game improvements.

## OBJECTIVE
Design a complete analytics dashboard system for [GAME NAME] using [ANALYTICS PLATFORM: GameAnalytics/Firebase/Amplitude/custom] to track all critical mobile game KPIs.

## TASK

### Event Taxonomy
- Session events: session_start, session_end, session_length, session_count
- Progression events: level_start, level_complete, level_fail, tutorial_step
- Economy events: currency_earned, currency_spent, IAP_purchase, ad_watched
- Social events: friend_added, guild_joined, gift_sent, chat_message
- Feature events: feature_unlocked, feature_used, settings_changed
- Naming convention: snake_case, category_action_detail format

### Acquisition Dashboard
- Daily installs by source, campaign, creative, geo
- CPI trends over time with moving averages
- Organic vs paid install ratio
- Install-to-tutorial completion rate
- First session length distribution
- Device and OS breakdown

### Engagement Dashboard
- DAU, WAU, MAU with DAU/MAU stickiness ratio
- Average session length and sessions per day
- Feature adoption rates: percentage of DAU using each feature
- Progression distribution: what level/stage is the player base at?
- Content consumption: how quickly are players burning through content?
- Playtime heatmap: peak hours by timezone

### Retention Dashboard
- Classic retention: D1, D3, D7, D14, D30, D60, D90 by cohort
- Rolling retention: percentage still active since install
- Return rate: percentage of churned players who come back
- Churn prediction: identify at-risk players based on behavior patterns
- Retention by acquisition source: which channels bring lasting players?
- Tutorial funnel: step-by-step dropout analysis

### Monetization Dashboard
- Revenue by stream: IAP, ads (interstitial, rewarded, banner), subscriptions
- ARPDAU, ARPPU, conversion rate (free to payer)
- LTV curves: by cohort, source, geo, platform
- IAP catalog performance: which items sell, at what price points
- Ad eCPM by network, placement, geo
- Whale analysis: top 100 spenders behavior patterns

### Alert System
- Crash rate spike: >1% triggers immediate alert
- Retention drop: D1 falls below [THRESHOLD] — investigate immediately
- Revenue anomaly: daily revenue deviates >20% from 7-day average
- Server errors: API error rate exceeds 0.1%
- Fraud detection: unusual purchase patterns or impossible progression speed
- UA efficiency: CPI rises above LTV payback threshold

## OUTPUT FORMAT
Analytics implementation document with event taxonomy, dashboard wireframes for each section, SQL/query templates, and alert configuration guide.

## CONSTRAINTS
- Event volume must stay within analytics platform limits and budget
- Respect user privacy: no PII in analytics, GDPR-compliant
- Dashboard must load in under 5 seconds with 30-day data range
- Include data validation: catch missing or malformed events
- Design for self-service: PMs should answer questions without analyst help