> For the complete documentation index, see [llms.txt](https://docs.treem.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.treem.io/treem-dao/email-system/email-analytics.md). # Email Analytics ## Email Analytics Monitor email performance, delivery rates, and user engagement through comprehensive analytics and reporting. ### Overview The email analytics system provides insights into: * **Delivery Performance**: Success rates and failure analysis * **Template Usage**: Most popular email templates * **Sending Volume**: Email activity over time * **Error Tracking**: Detailed failure information * **Trend Analysis**: Performance patterns and improvements ### Analytics Dashboard #### Accessing Analytics 1. Navigate to **Admin Dashboard → Settings → Email System** 2. Click on the **Analytics** tab 3. Select your desired time range (7, 30, or 90 days) #### Key Metrics Overview The dashboard displays four primary metrics cards: **Total Sent** * **Description**: Successfully delivered emails * **Icon**: Green checkmark * **Calculation**: Count of emails with 'sent' status * **Good Performance**: High numbers indicate active email system **Pending** * **Description**: Emails currently being processed * **Icon**: Yellow mail icon * **Calculation**: Count of emails with 'pending' status * **Normal Range**: Should be low during non-sending periods **Failed** * **Description**: Emails that couldn't be delivered * **Icon**: Red alert circle * **Calculation**: Count of emails with 'failed' status * **Target**: Keep as low as possible (< 5% of total) **Delivery Rate** * **Description**: Percentage of successful email deliveries * **Icon**: Blue trending up arrow * **Calculation**: (Total Sent / Total Emails) × 100 * **Benchmark**: Aim for > 95% delivery rate ### Charts and Visualizations #### Email Activity Over Time **Chart Type**: Bar chart showing daily email activity**Purpose**: Track sending patterns and identify peak usage**Data Displayed**: * Green bars: Successfully sent emails * Red bars: Failed deliveries * Yellow bars: Pending emails **Insights**: * Identify busy sending periods * Spot unusual activity spikes * Monitor system reliability over time #### Template Usage Distribution **Chart Type**: Pie chart showing template popularity**Purpose**: Understand which templates are used most frequently**Data Displayed**: * Template names with usage percentages * Color-coded segments for different templates * Hover tooltips with exact counts **Insights**: * Identify most valuable templates * Find unused templates for cleanup * Guide template optimization efforts ### Template Performance Analysis #### Performance Metrics Table For each email template, the system tracks: **Total Usage**: Number of times template was used**Sent Count**: Successfully delivered emails using this template**Failed Count**: Failed deliveries for this template**Success Rate**: Percentage of successful deliveries**Performance Badges**: Visual indicators for performance levels #### Performance Indicators **Success Rate Badges**: * **Green (Default)**: > 95% success rate * **Yellow (Secondary)**: 90-95% success rate * **Red (Destructive)**: < 90% success rate #### Template Optimization Use performance data to: 1. **Identify problematic templates**: Low success rates 2. **Optimize content**: Improve deliverability 3. **Update configurations**: Fix technical issues 4. **Archive unused templates**: Clean up template library ### Time Range Analysis #### Available Time Ranges **Last 7 Days**: Recent performance and immediate issues * Best for: Daily monitoring and quick issue identification * Update frequency: Real-time **Last 30 Days**: Monthly trends and pattern analysis * Best for: Regular performance reviews * Update frequency: Hourly **Last 90 Days**: Quarterly analysis and long-term trends * Best for: Strategic planning and system evaluation * Update frequency: Daily #### Comparative Analysis When switching time ranges, compare: * **Volume changes**: Increasing or decreasing email activity * **Performance trends**: Improving or degrading delivery rates * **Error patterns**: Recurring vs. one-time issues * **Template adoption**: New templates gaining popularity ### Error Analysis #### Error Categorization The system categorizes email failures into: **SMTP Errors**: * Authentication failures * Connection timeouts * Rate limiting issues * Server unavailability **Recipient Errors**: * Invalid email addresses * Mailbox full * Domain not found * Spam filtering **Content Errors**: * Template rendering failures * Variable substitution errors * Malformed HTML content * Size limitations #### Error Resolution **Common SMTP Errors**: 1. Check SMTP configuration settings 2. Verify credentials and authentication 3. Review provider rate limits 4. Test connection manually **Recipient Issues**: 1. Validate email address formats 2. Clean email lists regularly 3. Handle bounces appropriately 4. Monitor reputation scores **Content Problems**: 1. Test templates before deployment 2. Validate all required variables 3. Check HTML formatting 4. Monitor email size limits ### Performance Benchmarks #### Industry Standards **Delivery Rate**: > 95% * Excellent: > 98% * Good: 95-98% * Needs improvement: < 95% **Bounce Rate**: < 5% * Excellent: < 2% * Acceptable: 2-5% * High: > 5% **Failure Rate**: < 3% * Excellent: < 1% * Acceptable: 1-3% * High: > 3% #### DAO-Specific Considerations **Governance Emails**: Higher engagement expected * Target delivery rate: > 98% * Critical for voting notifications * Monitor closely during voting periods **Transactional Emails**: Must be highly reliable * Target delivery rate: > 99% * Includes purchase confirmations, security alerts * Immediate delivery required **Marketing Emails**: May have higher bounce rates * Target delivery rate: > 90% * Users may opt out more frequently * Monitor unsubscribe rates ### Automated Reporting #### Daily Reports Automated daily summaries include: * Previous day's sending volume * Delivery rate performance * Any error spikes or issues * Template usage changes #### Weekly Reports Weekly analytics reports provide: * 7-day performance trends * Template performance comparison * Error pattern analysis * Recommendations for improvement #### Monthly Reports Comprehensive monthly reports feature: * Complete performance analysis * Template optimization suggestions * System health assessment * Strategic recommendations ### Data Export #### Available Export Formats **CSV Export**: Raw data for external analysis * Email logs with timestamps * Success/failure status * Template usage statistics * Error details and codes **PDF Reports**: Formatted analytics summaries * Executive summary format * Charts and visualizations * Performance benchmarks * Recommendations section #### Export Process 1. Select desired time range 2. Choose export format (CSV or PDF) 3. Click export button 4. Download generated file 5. Import into external tools if needed ### Integration with Other Systems #### Supabase Analytics Email analytics integrate with Supabase's built-in analytics: * Database query performance * Function execution metrics * API usage statistics * Overall system health #### External Tools Export data for use with: * **Google Analytics**: Track email-driven website traffic * **Business Intelligence**: Comprehensive performance dashboards * **CRM Systems**: Customer communication tracking * **Marketing Platforms**: Campaign performance analysis ### Troubleshooting Analytics #### Missing Data If analytics show no data: 1. Verify time range selection 2. Check if any emails were sent in the period 3. Confirm database connectivity 4. Review error logs for issues #### Incorrect Metrics If numbers seem wrong: 1. Cross-reference with email logs 2. Check for timezone differences 3. Verify data aggregation logic 4. Compare with SMTP provider statistics #### Performance Issues If analytics load slowly: 1. Reduce time range scope 2. Check database performance 3. Clear browser cache 4. Contact system administrator ### Best Practices #### Regular Monitoring 1. **Daily checks**: Review key metrics during active periods 2. **Weekly analysis**: Identify trends and patterns 3. **Monthly reviews**: Comprehensive performance evaluation 4. **Quarterly planning**: Strategic improvements and goals #### Data-Driven Decisions Use analytics to: 1. **Optimize sending times**: Find peak engagement periods 2. **Improve templates**: Focus on high-performing content 3. **Clean email lists**: Remove consistently failing addresses 4. **Plan capacity**: Prepare for high-volume periods #### Continuous Improvement 1. **Set benchmarks**: Establish performance goals 2. **Track progress**: Monitor improvement over time 3. **Test changes**: A/B test template modifications 4. **Document learnings**: Keep records of successful optimizations This comprehensive analytics system ensures you have complete visibility into your email system's performance and can make data-driven decisions to improve communication effectiveness. --- # Agent Instructions This documentation is published with GitBook. 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