Metrics Knowledge

by yamz8

skill

This skill should be used when the user asks to "track metrics", "calculate ARR", "what metrics should I track", "benchmark my metrics", "understand churn", "calculate LTV", "what is burn multiple", "GMV calculation", "marketplace metrics", or mentions specific metrics like ARR, MRR, NRR, churn, CAC, LTV, burn rate, runway, GMV, take rate, or cohort analysis.

Skill Details

Repository Files

6 files in this skill directory


name: Metrics Knowledge description: This skill should be used when the user asks to "track metrics", "calculate ARR", "what metrics should I track", "benchmark my metrics", "understand churn", "calculate LTV", "what is burn multiple", "GMV calculation", "marketplace metrics", or mentions specific metrics like ARR, MRR, NRR, churn, CAC, LTV, burn rate, runway, GMV, take rate, or cohort analysis. version: 0.1.0

Startup Metrics Knowledge

Overview

This skill provides comprehensive guidance on startup metrics for SaaS and marketplace businesses. It covers metric definitions, calculation formulas, stage-appropriate benchmarks, and best practices for tracking and reporting.

SaaS Metrics Fundamentals

Revenue Metrics

Metric Formula Description
MRR Sum of monthly recurring revenue Core subscription revenue
ARR MRR × 12 Annualized recurring revenue
New MRR MRR from new customers Growth driver
Expansion MRR MRR from upgrades/upsells Land-and-expand signal
Churned MRR MRR lost from cancellations Retention indicator
Net New MRR New + Expansion - Churned Overall momentum

Growth Metrics

Metric Formula Good Great
MoM Growth (MRR₁ - MRR₀) / MRR₀ 10-15% 20%+
YoY Growth (ARR₁ - ARR₀) / ARR₀ 2x 3x
Net Revenue Retention (Starting MRR + Expansion - Churn) / Starting MRR 100-110% 120%+
Gross Revenue Retention (Starting MRR - Churn) / Starting MRR 85-90% 95%+
Logo Retention Customers retained / Starting customers 85-90% 95%+

Unit Economics

Metric Formula Target
CAC Sales & Marketing spend / New customers Varies by ACV
LTV ARPU × Gross Margin × (1/Churn Rate) 3x+ CAC
LTV:CAC Ratio LTV / CAC 3:1 to 5:1
CAC Payback CAC / (ARPU × Gross Margin) <18 months
Gross Margin (Revenue - COGS) / Revenue 70-80%+

Efficiency Metrics

Metric Formula Target
Burn Multiple Net Burn / Net New ARR <2x
Magic Number Net New ARR / Prior Q S&M Spend >0.75
Rule of 40 Growth Rate + Profit Margin >40%
Hype Ratio Implied ARR Multiple / Growth Rate <1x

Marketplace Metrics Fundamentals

Volume Metrics

Metric Formula Description
GMV Total transaction value Gross Merchandise Value
Net Revenue GMV × Take Rate Actual revenue
Take Rate Net Revenue / GMV Platform fee %
AOV GMV / Orders Average Order Value

Liquidity Metrics

Metric Formula Description
Search-to-Fill Rate Filled requests / Total searches Demand satisfaction
Time-to-Fill Avg time from request to fulfillment Efficiency
Buyer-to-Seller Ratio Active buyers / Active sellers Balance indicator
Repeat Rate Repeat transactions / Total Stickiness

Marketplace Health

Metric Description Target
Supply Liquidity % of listings with transactions >30%
Demand Liquidity % of searches resulting in purchase >20%
Supplier Concentration Top 10% supplier revenue share <40%
Cross-Side Network Effects Growth correlation between sides Positive

Burn & Runway

Burn Calculations

Metric Formula
Gross Burn Total monthly operating expenses
Net Burn Gross Burn - Revenue
Runway Cash Balance / Net Burn
Zero Cash Date Today + (Runway months)

Burn Benchmarks by Stage

Stage Acceptable Burn Multiple Target Runway
Pre-seed N/A 18-24 months
Seed <3x 18-24 months
Series A <2x 18-24 months
Series B <1.5x 24+ months
Series C+ <1x 24+ months

Stage-Appropriate Metrics

Pre-Seed / Seed

Focus on product-market fit signals:

  • Engagement metrics (DAU/MAU, retention curves)
  • Organic growth / word-of-mouth
  • Early revenue or intent signals
  • User feedback quality

Series A

Prove repeatable revenue:

  • ARR: $1-3M
  • Growth: 2-3x YoY
  • Retention: >100% NRR
  • Unit economics trending positive

Series B

Scale efficiently:

  • ARR: $5-15M
  • Growth: 2x+ YoY
  • Burn multiple: <1.5x
  • Clear path to profitability

Series C+

Efficient growth at scale:

  • ARR: $20M+
  • Rule of 40: >40%
  • Strong unit economics
  • Market leadership indicators

Cohort Analysis

Revenue Cohorts

Track how revenue from each customer cohort evolves over time:

  • Month 0: Initial MRR
  • Month 3, 6, 12: Retention %
  • Expansion curve: Upsell trajectory

User Cohorts

Track engagement by signup cohort:

  • Day 1, 7, 30 retention
  • Feature adoption rates
  • Conversion milestones

Additional Resources

Reference Files

For detailed guidance, consult:

  • references/saas-metrics-guide.md - Complete SaaS metrics with formulas and examples
  • references/marketplace-metrics-guide.md - Marketplace-specific metrics and benchmarks
  • references/benchmarks-by-stage.md - Stage and industry benchmarks

Example Files

Working examples in examples/:

  • example-metrics-snapshot.md - Sample metrics report format
  • example-cohort-analysis.md - Cohort analysis template

Related Skills

Attack Tree Construction

Build comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.

skill

Grafana Dashboards

Create and manage production Grafana dashboards for real-time visualization of system and application metrics. Use when building monitoring dashboards, visualizing metrics, or creating operational observability interfaces.

skill

Matplotlib

Foundational plotting library. Create line plots, scatter, bar, histograms, heatmaps, 3D, subplots, export PNG/PDF/SVG, for scientific visualization and publication figures.

skill

Scientific Visualization

Create publication figures with matplotlib/seaborn/plotly. Multi-panel layouts, error bars, significance markers, colorblind-safe, export PDF/EPS/TIFF, for journal-ready scientific plots.

skill

Seaborn

Statistical visualization. Scatter, box, violin, heatmaps, pair plots, regression, correlation matrices, KDE, faceted plots, for exploratory analysis and publication figures.

skill

Shap

Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model

skill

Pydeseq2

Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.

skill

Query Writing

For writing and executing SQL queries - from simple single-table queries to complex multi-table JOINs and aggregations

skill

Pydeseq2

Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.

skill

Scientific Visualization

Meta-skill for publication-ready figures. Use when creating journal submission figures requiring multi-panel layouts, significance annotations, error bars, colorblind-safe palettes, and specific journal formatting (Nature, Science, Cell). Orchestrates matplotlib/seaborn/plotly with publication styles. For quick exploration use seaborn or plotly directly.

skill

Skill Information

Category:Skill
Version:0.1.0
Last Updated:1/22/2026