# perplexity-usage-analytics

> Build usage analytics and reporting for Perplexity

## Directory Structure

```
perplexity-usage-analytics/
├── SKILL.md                    # Main skill definition with YAML frontmatter
└── examples/                   # Optional examples directory
    ├── analytics_pipeline.py   # Usage data pipeline
    ├── usage_dashboard.py      # Dashboard generation
    ├── report_generator.py     # Automated report generation
    └── metrics_schema.yaml     # Analytics metrics schema
```

## File Descriptions

| File | Type | Purpose |
|------|------|---------|
| `SKILL.md` | Markdown | Skill definition with analytics patterns |
| `analytics_pipeline.py` | Python | Collect and process usage data |
| `usage_dashboard.py` | Python | Generate usage dashboards |
| `report_generator.py` | Python | Automated reporting scripts |
| `metrics_schema.yaml` | YAML | Define tracked metrics |

## Summary

**Category:** enterprise
**Target Audience:** Data analyst or operations
**Trigger Phrases:** `perplexity analytics`, `perplexity usage`, `perplexity reports`, `track perplexity`

### What This Skill Does

This skill teaches usage analytics for Perplexity:

- Collecting usage metrics
- Building usage dashboards
- Generating automated reports
- Trend analysis and forecasting
- Cost-per-query analysis

### Technical Success Criteria

- Comprehensive usage metrics and dashboards
- Automated reporting configured
- Historical trends tracked

### Business Success Criteria

- Data-driven optimization decisions
- Clear visibility into usage patterns
- Stakeholder reporting capability

## Related Skills

- `perplexity-cost-controls` - Analytics for budgeting
- `perplexity-monitoring-alerts` - Real-time vs historical
- `perplexity-team-management` - Per-team analytics
