Active engagement
Overview Lillo's engagement tracking system provides foundational analytics and metrics collection for community interactions. The current implementation establishes core tracking capabilities, with p
Command Metrics
Metric Collection
interface CommandMetrics {
command: string;
userId: number;
chatId: number;
duration: number;
success: boolean;
error?: string;
timestamp: number;
}Storage Implementation
Real-time KV store for quick access
PostgreSQL for long-term analysis
Dual-storage strategy for performance
Automatic data retention
Data Collection
Command Analytics
Usage frequency
Success rates
Response times
Error patterns
User distribution
Storage Strategy
// Quick access in KV store
const key = `metrics:cmd:${metrics.command}:${metrics.timestamp}`;
await storeInKV(key, metrics);
// Long-term storage in PostgreSQL
await sql`
INSERT INTO command_metrics (
command, user_id, chat_id, duration,
success, error, timestamp
) VALUES (
${metrics.command}, ${metrics.userId},
${metrics.chatId}, ${metrics.duration},
${metrics.success}, ${metrics.error},
${metrics.timestamp}
);
`;Performance Tracking
Monitored Metrics
Command execution time
API response latency
Cache hit rates
Error frequencies
User engagement levels
Implementation Details
Real-time monitoring
Performance logging
Error tracking
Usage patterns
Resource utilization
Future Enhancements
The engagement system is being expanded to include:
Advanced analytics dashboard
User engagement scoring
Community health metrics
Trend analysis
Behavioral insights
Customizable reports
Data Analysis
Current Capabilities
Basic usage statistics
Performance metrics
Error tracking
User activity monitoring
Planned Features
Advanced analytics
User behavior analysis
Engagement optimization
Community insights
Trend forecasting
Best Practices
Data Collection
Respect user privacy
Optimize storage usage
Regular maintenance
Data validation
Performance Monitoring
Track key metrics
Set up alerts
Monitor trends
Regular reviews
Related Documentation
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