Startup Metrics

Advanced Features

• Predictive metrics modeling
• Benchmark comparisons by stage and sector
• Metric correlation analysis
• Leading vs lagging indicator tracking
• Scenario modeling for metrics
• Custom metric definitions
• Data source integrations
• Historical trend analysis

Usage

Input Requirements

• Business model type (SaaS, marketplace, etc.)
• Stage and funding status
• Available data sources
• Key business questions
• Reporting frequency
• Stakeholder requirements

Output Deliverables

• Configured metrics dashboard
• North Star metric definition
• AARRR funnel visualization
• MRR/ARR tracking charts
• Cohort analysis tables
• Runway projections
• Investor-ready reports
• Alert configurations

Process Integration

This skill integrates with the following processes:

• financial-model-development.js - Financial metrics integration
• product-market-fit-assessment.js - PMF metrics tracking
• investor-update-communication.js - Metrics reporting
• growth-experiment-design.js - Experiment metrics

Example Invocation

Skill: startup-metrics
Context: B2B SaaS startup Series A metrics dashboard
Input:
  - Model: B2B SaaS, monthly subscriptions
  - Stage: Series A
  - Data Sources: Stripe, Mixpanel, HubSpot
  - North Star Candidate: Weekly Active Teams
Output:
  - Dashboard configuration
  - Metrics definitions:
    - MRR, ARR, growth rate
    - CAC, LTV, LTV:CAC ratio
    - Churn (logo and revenue)
    - NRR, GRR
    - Activation rate
    - Time to value
  - Cohort retention charts
  - 18-month runway projection
  - Weekly metrics email template

Dependencies

• Analytics platform integrations
• Visualization libraries
• Financial data connections
• Alerting systems
• Report generation tools

Best Practices

1. Define a clear North Star metric that aligns with business value
2. Track both leading indicators (predict future) and lagging indicators (confirm past)
3. Use cohort analysis to understand true retention patterns
4. Segment metrics by customer type, plan, or acquisition channel
5. Compare metrics to stage-appropriate benchmarks
6. Update dashboards in real-time or at minimum weekly
7. Make metrics accessible to the whole team
8. Focus on trends, not single data points
9. Document metric definitions to ensure consistency
10. Regularly review and retire metrics that don't drive decisions
11. Prepare investor-ready metrics views in advance
12. Track both absolute values and growth rates