Agent skill

Startup Metrics

When the user asks about startup metrics, SaaS metrics, unit economics, or business performance tracking. Triggers on: "startup metrics", "SaaS metrics", "CAC and LTV", "unit economics", "burn multiple", "rule of 40", "magic number", "marketplace metrics", "churn rate", "MRR", "ARR", "net revenue retention", "runway", or requests for metrics dashboards and investor reporting.

Stars 163
Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/startup-metrics-wpank-ai

SKILL.md

Startup Metrics Framework

Track, calculate, and optimize key performance metrics for different startup business models from seed through Series B+.

Installation

OpenClaw / Moltbot / Clawbot

bash
npx clawhub@latest install startup-metrics

NEVER Do

  • Focus on vanity metrics (total users without retention, page views without engagement, downloads without activation)
  • Track 50 metrics loosely instead of 5-7 core metrics intensely
  • Ignore unit economics at any stage — CAC and LTV matter even at seed
  • Present metrics without context (benchmark, target, or trend)
  • Optimize dashboard numbers instead of real business outcomes
  • Skip segmentation — always break down by customer segment, channel, and cohort

Data

The data/metrics.csv file contains 42 metrics with formulas, benchmarks by stage, interpretation guidance, and related metrics. Use it for lookups and cross-referencing.

How to Use This Skill

  1. Identify business model — SaaS, marketplace, consumer/mobile, or B2B
  2. Determine stage — Pre-seed, seed, Series A, Series B+
  3. Select 5-7 core metrics based on model and stage
  4. Apply formulas and benchmarks from the sections below
  5. Recommend tracking cadence and reporting format

Universal Metrics (All Models)

Revenue

Metric Formula Seed Target Series A Target
MRR Sum(active subs x monthly price) $10K-$50K $200K-$800K
ARR MRR x 12 $120K-$600K $2M-$10M
MoM Growth (current - prior) / prior 15-20% 10-15%
YoY Growth (current year - prior year) / prior year N/A 3-5x

Unit Economics

Metric Formula Healthy Benchmark
CAC Total S&M spend / new customers Varies by model
LTV ARPU x gross margin% x (1/churn rate) LTV:CAC > 3.0
CAC Payback CAC / (ARPU x gross margin%) < 12 months
Gross Margin (revenue - COGS) / revenue 70-85% for SaaS

Cash Management

Metric Formula Target
Burn Rate monthly expenses - monthly revenue Track gross and net
Runway cash balance / monthly burn Always 12-18+ months
Burn Multiple net burn / net new ARR < 2.0 (lower is better)

SaaS-Specific Metrics

Revenue Composition

Net New MRR = New MRR + Expansion MRR - Contraction MRR - Churned MRR

Retention

Metric Formula Best-in-Class
Net Dollar Retention (NDR) (start + expansion - contraction - churn) / start > 120%
Gross Retention (start - churn - contraction) / start > 90%
Logo Retention (end - new) / start > 95% monthly

Efficiency

Metric Formula Ready to Scale
Magic Number net new ARR (quarter) / S&M spend (prior quarter) > 0.75
Rule of 40 revenue growth% + profit margin% > 40%
Quick Ratio (new + expansion MRR) / (churned + contraction MRR) > 4.0

Marketplace Metrics

Metric Formula Target
GMV sum of all transaction values 20%+ MoM early-stage
Take Rate net revenue / GMV 10-20% (model-dependent)
Liquidity (Fill Rate) transactions / listings > 70%
Repeat Rate users with 2+ txns / total transacting > 60%
Time to First Transaction median signup-to-transaction < 3 days

Consumer / Mobile Metrics

Metric Formula Benchmark
DAU/MAU Ratio daily active / monthly active > 20% good, > 50% exceptional
Day 30 Retention % users active 30d after signup > 25%
K-Factor (Virality) invites per user x conversion rate > 1.0 = viral
Session Duration total time / sessions Context-dependent
NPS % promoters - % detractors > 50 excellent

B2B Sales Metrics

Metric Formula Target
Win Rate deals won / total opportunities 20-40%
Pipeline Coverage pipeline value / quota 3-5x
ACV total contract value / contract years Track trends
Sales Cycle avg days from opportunity to close SMB: 30-60d, Enterprise: 120-270d

Pipeline Conversion Rates

Stage Typical Rate
Lead → Opportunity 10-20%
Opportunity → Demo 50-70%
Demo → Proposal 30-50%
Proposal → Close 20-40%

Metrics by Stage

Pre-Seed (Product-Market Fit)

Focus: Active users growth, user retention (D7/D30), core engagement, qualitative feedback (NPS, interviews).

Ignore for now: Revenue, CAC, unit economics.

Seed ($500K-$2M ARR)

Focus: MRR growth (15-20% MoM), CAC and LTV baselines, gross retention (>85%), product engagement.

Start tracking: Sales efficiency, burn rate, runway.

Series A ($2M-$10M ARR)

Focus: ARR growth (3-5x YoY), unit economics (LTV:CAC >3, payback <18mo), NDR (>100%), burn multiple (<2.0), magic number (>0.5).

Mature tracking: Rule of 40, sales efficiency, pipeline coverage.

Series B+ ($10M+ ARR)

Focus: Rule of 40 (>40%), efficient growth, path to profitability, market leadership.

Tracking Best Practices

Reporting Cadence

Frequency Metrics
Daily MRR, active users, signups, conversions
Weekly Growth rates, retention cohorts, sales pipeline
Monthly Full metric suite, board reporting, investor updates
Quarterly Trend analysis, benchmarking, strategy review

Dashboard Format

Current MRR: $250K (↑ 18% MoM)
ARR: $3.0M (↑ 280% YoY)
CAC: $1,200 | LTV: $4,800 | LTV:CAC = 4.0x
NDR: 112% | Logo Retention: 92%
Burn: $180K/mo | Runway: 18 months

Always include: current value, growth rate/trend, context (target or benchmark).

What VCs Want to See

Round Key Metrics
Seed MRR growth rate, user retention, early unit economics, product engagement
Series A ARR + growth, CAC payback <18mo, LTV:CAC >3.0, NDR >100%, burn multiple <2.0
Series B+ Rule of 40 >40%, magic number, path to profitability, market leadership

Data Infrastructure

Requirements

  • Single source of truth (analytics platform)
  • Real-time or daily updates for core metrics
  • Automated calculations (no manual spreadsheets for recurring metrics)
  • Historical tracking for trend analysis and cohort comparisons

Recommended Tools

Category Tools
Product analytics Mixpanel, Amplitude, PostHog
SaaS metrics ChartMogul, Baremetrics, ProfitWell
BI dashboards Looker, Metabase, Tableau
Cohort analysis Built-in analytics + spreadsheets for custom analysis

Common Mistakes

  1. Vanity metrics — Focus on actionable metrics tied to value, not totals without context
  2. Too many metrics — Track 5-7 core metrics intensely, not 50 loosely
  3. Ignoring unit economics — CAC and LTV matter even at seed stage
  4. Not segmenting — Break down by customer segment, channel, cohort
  5. Gaming metrics — Optimize for real business outcomes, not dashboard numbers

Metric Calculation Examples

LTV Calculation

ARPU: $200/month
Gross Margin: 80%
Monthly Churn: 3%

LTV = $200 × 0.80 × (1/0.03) = $5,333

Burn Multiple

Net Burn: $150K/month
Net New ARR (quarter): $300K

Burn Multiple = ($150K × 3) / $300K = 1.5

Interpretation: Spending $1.50 to generate each $1 of new ARR — acceptable efficiency.

Magic Number

Net New ARR (Q2): $400K
S&M Spend (Q1): $500K

Magic Number = $400K / $500K = 0.80

Interpretation: Above 0.75 threshold — efficient, ready to scale S&M investment.

Quick Ratio

New MRR: $40K
Expansion MRR: $15K
Churned MRR: $8K
Contraction MRR: $4K

Quick Ratio = ($40K + $15K) / ($8K + $4K) = 4.58

Interpretation: Above 4.0 — healthy growth significantly outpacing churn.

Investor Metric Presentation

Present metrics with three components:

  1. Current value — the number itself
  2. Growth rate or trend — direction and velocity
  3. Context — benchmark, target, or peer comparison
Current MRR: $250K (↑ 18% MoM)
ARR: $3.0M (↑ 280% YoY)
CAC: $1,200 | LTV: $4,800 | LTV:CAC = 4.0x
NDR: 112% | Logo Retention: 92%
Burn: $180K/mo | Runway: 18 months
Burn Multiple: 1.8x | Magic Number: 0.65

Quick Start

To implement this framework:

  1. Identify business model — SaaS, marketplace, consumer, B2B
  2. Choose 5-7 core metrics — based on stage and model
  3. Establish tracking — set up analytics and dashboards
  4. Calculate unit economics — CAC, LTV, payback
  5. Set targets — use benchmarks from this skill
  6. Review regularly — weekly for core metrics, monthly for full suite
  7. Share with team — align on goals and progress
  8. Update investors — monthly or quarterly reporting

Data Reference

The data/metrics.csv file contains 42 metrics with:

  • Unique ID and category classification
  • Formulas for calculation
  • Benchmarks by stage (seed, Series A, Series B)
  • Interpretation guidance for each metric
  • Related metrics for cross-referencing and dependency tracking

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