Build Comprehensive Analytics Dashboard with Historical Data Tracking and Predictive Insights #9
Description
We need a full-featured analytics system that tracks historical data, provides insights, and helps users make informed decisions about markets and staking strategies.
Current Limitations
- No historical data tracking
- Limited market insights
- No user performance metrics
- Missing platform-wide statistics
- No predictive analytics
Proposed Analytics Features
- Market Analytics
Individual Market Metrics:
- Stake distribution over time (line chart)
- Odds movement history
- Participation rate trends
- Volume by time period
- Unique participants count
- Average stake size
- Momentum indicators
Comparative Analytics:
- Similar market performance
- Category benchmarks
- Creator track record
- Resolution accuracy by creator
- User Portfolio Analytics
Performance Tracking:
- Total P&L (realized + unrealized)
- Win rate by market category
- ROI over time periods (7D, 30D, 90D, ALL)
- Sharpe ratio (risk-adjusted returns)
- Best/worst performing markets
- Staking patterns analysis
Portfolio Composition:
- Asset allocation by outcome (YES/NO)
- Exposure by category
- Risk distribution
- Liquidity analysis
- Platform-Wide Statistics
Volume Metrics:
- Daily/weekly/monthly volume
- Volume by category
- TVL (Total Value Locked)
- Volume growth rate
- Peak trading hours
User Metrics:
- Active users (DAU, MAU)
- New user growth
- Retention rate
- User segmentation (whales, regulars, new)
Market Health:
- Total markets created
- Active vs resolved markets
- Average time to resolution
- Resolution accuracy rate
- Abandonment rate
- Predictive Analytics
Market Predictions:
- Likely resolution time
- Expected final pool size
- Predicted odds movement
- Risk score calculation
User Insights:
- Suggested markets based on history
- Optimal stake amounts
- Risk warnings
- Portfolio rebalancing suggestions
Technical Implementation
Backend/Data Layer
typescript
// New data structures
interface HistoricalSnapshot {
marketId: string;
timestamp: number;
yesStake: number;
noStake: number;
participants: number;
oddsYes: number;
oddsNo: number;
}
interface UserAnalytics {
userId: string;
totalStaked: number;
totalWon: number;
totalLost: number;
winRate: number;
roi: number;
marketCount: number;
avgStake: number;
riskScore: number;
}
interface PlatformMetrics {
timestamp: number;
dailyVolume: number;
activeUsers: number;
newMarkets: number;
resolutions: number;
tvl: number;
}
Data Collection Strategy
-
Event Logging
- Log all stakes to storage
- Track market state changes
- Record user actions
- Timestamp all events
-
Snapshot System
- Hourly market snapshots
- Daily user portfolio snapshots
- Weekly platform metrics
- Store in decentralized storage (IPFS/Gaia)
-
Aggregation Service
- Background job for calculations
- Cache computed metrics
- Update on-chain events
- Rate limit to prevent spam
Frontend Components
Dashboard Pages:
/analytics
├── /platform - Platform-wide stats
├── /market/:id - Individual market analytics
├── /portfolio - User portfolio analytics
└── /leaderboard - Top performers
Key Components:
<VolumeChart />- Historical volume visualization<OddsMovement />- Odds over time graph<PortfolioBreakdown />- Asset allocation pie chart<PerformanceMetrics />- Key metrics grid<PredictiveInsights />- AI-powered suggestions<CompareMarkets />- Side-by-side comparison<LeaderboardTable />- Top users/markets<HeatMap />- Activity heatmap by time<TrendIndicators />- Bull/bear indicators
Charting Library
Options:
- Recharts (already imported) - Simple, React-native
- Chart.js (already imported) - More features
- D3.js (already imported) - Maximum flexibility
- Victory - Mobile-friendly
Recommendation: Use Recharts for simple charts, D3 for complex visualizations
Implementation Phases
Phase 1: Data Collection (Week 1-2)
- Set up event logging system
- Create snapshot mechanism
- Implement storage solution
- Build data aggregation service
Phase 2: User Analytics (Week 3-4)
- Calculate user metrics
- Build portfolio dashboard
- Create performance charts
- Add export functionality
Phase 3: Market Analytics (Week 5-6)
- Individual market analytics
- Comparative tools
- Trend analysis
- Predictive models
Phase 4: Platform Analytics (Week 7-8)
- Platform dashboard
- Leaderboards
- Category analytics
- Public API for stats
Phase 5: Advanced Features (Week 9-10)
- Predictive insights
- Recommendations engine
- Risk scoring
- Portfolio optimization
Data Storage Considerations
On-Chain vs Off-Chain
On-Chain (Expensive but Permanent):
- Current market state
- Critical events
- User positions
Off-Chain (Cheaper, Faster):
- Historical snapshots
- Computed metrics
- Chart data
- User preferences
Storage Solutions
- Gaia - Stacks native storage
- IPFS - Decentralized file storage
- localStorage - Client-side cache
- IndexedDB - Large client-side data
Performance Optimization
Caching Strategy
typescript
// Multi-layer cache
- Browser cache (localStorage) - 5 minutes
- CDN cache - 1 hour
- Server cache - 15 minutes
- Database - source of truth
Lazy Loading
- Load basic stats first
- Fetch charts on demand
- Progressive data loading
- Infinite scroll for tables
Real-time Updates
- WebSocket for live data
- Optimistic UI updates
- Background sync
- Conflict resolution
Success Metrics
- Analytics page loads < 2s
- Charts render < 500ms
- 80%+ users view analytics
- 50%+ users export data
- 90%+ metric accuracy
Security & Privacy
- Anonymize user data in public stats
- Rate limit analytics API
- Prevent data scraping
- GDPR compliance for exports
Future Enhancements
- Machine learning predictions
- Social sentiment analysis
- Cross-platform analytics
- Mobile app integration
- Real-time alerts
Resources