
Startup Metrics Framework
FreeOptimize key performance metrics for startups.
Free · Opens the source repo
What Startup Metrics Framework does
The Startup Metrics Framework provides a structured approach for tracking, calculating, and optimizing essential performance metrics tailored for startups, particularly those in the SaaS, marketplace, consumer, and B2B sectors. This skill is designed for entrepreneurs, product managers, and financial analysts who need to navigate the complexities of startup growth from seed funding through Series A. By focusing on unit economics, growth efficiency, and cash management, users can gain insights into their business's health and operational performance.
This framework includes a comprehensive set of metrics, such as Monthly Recurring Revenue (MRR), Customer Acquisition Cost (CAC), and Lifetime Value (LTV), which are crucial for assessing the viability of a startup. Users can calculate these metrics using straightforward formulas provided in the skill, allowing for quick assessments of financial health and operational efficiency. The inclusion of benchmarks at various stages of growth helps users understand where they stand relative to industry standards, facilitating better decision-making and strategic planning.
Additionally, the skill covers cash efficiency metrics like burn rate and runway, which are vital for managing cash flow and ensuring sustainability in the early stages of a startup. By utilizing these metrics, startups can better prepare for investor meetings and board reports, presenting a clear picture of their financial standing and growth potential.
Overall, the Startup Metrics Framework is an invaluable resource for anyone involved in the startup ecosystem, providing the necessary tools to track performance, optimize growth strategies, and make informed decisions based on data-driven insights.
When to use it
Use this skill when establishing a metrics framework or preparing for investor reporting and strategic planning.
When not to use it
This skill may not be suitable for established companies or those outside the startup phase, as it focuses on early-stage metrics and benchmarks.
What you can build with it
Preparing for Investor Meetings
Utilize the metrics framework to compile essential performance data that demonstrates your startup's growth potential and operational efficiency.
Benchmarking Against Industry Standards
Calculate key metrics and compare them against provided benchmarks to assess your startup's performance relative to peers.
Optimizing Cash Management
Use cash efficiency metrics to ensure your startup maintains a healthy runway and manages burn rate effectively.
How to install Startup Metrics Framework
View source1. Install with the skills CLI
npx skills add wshobson/agents/startup-metrics-framework --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by wshobsonStartup Metrics Framework
Comprehensive guide to tracking, calculating, and optimizing key performance metrics for different startup business models from seed through Series A.
Overview
Track the right metrics at the right stage. Focus on unit economics, growth efficiency, and cash management metrics that matter for fundraising and operational excellence.
Universal Startup Metrics
Revenue Metrics
MRR (Monthly Recurring Revenue)
MRR = Σ (Active Subscriptions × Monthly Price)
ARR (Annual Recurring Revenue)
ARR = MRR × 12
Growth Rate
MoM Growth = (This Month MRR - Last Month MRR) / Last Month MRR
YoY Growth = (This Year ARR - Last Year ARR) / Last Year ARR
Target Benchmarks:
- Seed stage: 15-20% MoM growth
- Series A: 10-15% MoM growth, 3-5x YoY
- Series B+: 100%+ YoY (Rule of 40)
Unit Economics
CAC (Customer Acquisition Cost)
CAC = Total S&M Spend / New Customers Acquired
Include: Sales salaries, marketing spend, tools, overhead
LTV (Lifetime Value)
LTV = ARPU × Gross Margin% × (1 / Churn Rate)
Simplified:
LTV = ARPU × Average Customer Lifetime × Gross Margin%
LTV:CAC Ratio
LTV:CAC = LTV / CAC
Benchmarks:
- LTV:CAC > 3.0 = Healthy
- LTV:CAC 1.0-3.0 = Needs improvement
- LTV:CAC < 1.0 = Unsustainable
CAC Payback Period
CAC Payback = CAC / (ARPU × Gross Margin%)
Benchmarks:
- < 12 months = Excellent
- 12-18 months = Good
-
24 months = Concerning
Cash Efficiency Metrics
Burn Rate
Monthly Burn = Monthly Revenue - Monthly Expenses
Negative burn = losing money (typical early-stage)
Runway
Runway (months) = Cash Balance / Monthly Burn Rate
Target: Always maintain 12-18 months runway
Burn Multiple
Burn Multiple = Net Burn / Net New ARR
Benchmarks:
- < 1.0 = Exceptional efficiency
- 1.0-1.5 = Good
- 1.5-2.0 = Acceptable
-
2.0 = Inefficient
Lower is better (spending less to generate ARR)
SaaS Metrics
Revenue Composition
New MRR New customers × ARPU
Expansion MRR Upsells and cross-sells from existing customers
Contraction MRR Downgrades from existing customers
Churned MRR Lost customers
Net New MRR Formula:
Net New MRR = New MRR + Expansion MRR - Contraction MRR - Churned MRR
Retention Metrics
Logo Retention
Logo Retention = (Customers End - New Customers) / Customers Start
Dollar Retention (NDR - Net Dollar Retention)
NDR = (ARR Start + Expansion - Contraction - Churn) / ARR Start
Benchmarks:
- NDR > 120% = Best-in-class
- NDR 100-120% = Good
- NDR < 100% = Needs work
Gross Retention
Gross Retention = (ARR Start - Churn - Contraction) / ARR Start
Benchmarks:
-
90% = Excellent
- 85-90% = Good
- < 85% = Concerning
SaaS-Specific Metrics
Magic Number
Magic Number = Net New ARR (quarter) / S&M Spend (prior quarter)
Benchmarks:
-
0.75 = Efficient, ready to scale
- 0.5-0.75 = Moderate efficiency
- < 0.5 = Inefficient, don't scale yet
Rule of 40
Rule of 40 = Revenue Growth Rate% + Profit Margin%
Benchmarks:
-
40% = Excellent
- 20-40% = Acceptable
- < 20% = Needs improvement
Example: 50% growth + (10%) margin = 40% ✓
Quick Ratio
Quick Ratio = (New MRR + Expansion MRR) / (Churned MRR + Contraction MRR)
Benchmarks:
-
4.0 = Healthy growth
- 2.0-4.0 = Moderate
- < 2.0 = Churn problem
Marketplace Metrics
GMV (Gross Merchandise Value)
Total Transaction Volume:
GMV = Σ (Transaction Value)
Growth Rate:
GMV Growth Rate = (Current Period GMV - Prior Period GMV) / Prior Period GMV
Target: 20%+ MoM early-stage
Take Rate
Take Rate = Net Revenue / GMV
Typical Ranges:
- Payment processors: 2-3%
- E-commerce marketplaces: 10-20%
- Service marketplaces: 15-25%
- High-value B2B: 5-15%
Marketplace Liquidity
Time to Transaction How long from listing to sale/match?
Fill Rate % of requests that result in transaction
Repeat Rate % of users who transact multiple times
Benchmarks:
- Fill rate > 80% = Strong liquidity
- Repeat rate > 60% = Strong retention
Marketplace Balance
Supply/Demand Ratio: Track relative growth of supply and demand sides.
Warning Signs:
- Too much supply: Low fill rates, frustrated suppliers
- Too much demand: Long wait times, frustrated customers
Goal: Balanced growth (1:1 ratio ideal, but varies by model)
Consumer/Mobile Metrics
Engagement Metrics
DAU (Daily Active Users) Unique users active each day
MAU (Monthly Active Users) Unique users active each month
DAU/MAU Ratio
DAU/MAU = DAU / MAU
Benchmarks:
-
50% = Exceptional (daily habit)
- 20-50% = Good
- < 20% = Weak engagement
Session Frequency Average sessions per user per day/week
Session Duration Average time spent per session
Retention Curves
Day 1 Retention: % users who return next day Day 7 Retention: % users active 7 days after signup Day 30 Retention: % users active 30 days after signup
Benchmarks (Day 30):
-
40% = Excellent
- 25-40% = Good
- < 25% = Weak
Retention Curve Shape:
- Flattening curve = good (users becoming habitual)
- Steep decline = poor product-market fit
Viral Coefficient (K-Factor)
K-Factor = Invites per User × Invite Conversion Rate
Example: 10 invites/user × 20% conversion = 2.0 K-factor
Benchmarks:
- K > 1.0 = Viral growth
- K = 0.5-1.0 = Strong referrals
- K < 0.5 = Weak virality
B2B Metrics
Sales Efficiency
Win Rate
Win Rate = Deals Won / Total Opportunities
Target: 20-30% for new sales team, 30-40% mature
Sales Cycle Length Average days from opportunity to close
Shorter is better:
- SMB: 30-60 days
- Mid-market: 60-120 days
- Enterprise: 120-270 days
Average Contract Value (ACV)
ACV = Total Contract Value / Contract Length (years)
Pipeline Metrics
Pipeline Coverage
Pipeline Coverage = Total Pipeline Value / Quota
Target: 3-5x coverage (3-5x pipeline needed to hit quota)
Conversion Rates by Stage:
- 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 Metrics:
- Active users growth
- User retention (Day 7, Day 30)
- Core engagement (sessions, features used)
- Qualitative feedback (NPS, interviews)
Don't worry about:
- Revenue (may be zero)
- CAC (not optimizing yet)
- Unit economics
Seed ($500K-$2M ARR)
Focus Metrics:
- MRR growth rate (15-20% MoM)
- CAC and LTV (establish baseline)
- Gross retention (> 85%)
- Core product engagement
Start tracking:
- Sales efficiency
- Burn rate and runway
Series A ($2M-$10M ARR)
Focus Metrics:
- ARR growth (3-5x YoY)
- Unit economics (LTV:CAC > 3, payback < 18 months)
- Net dollar retention (> 100%)
- Burn multiple (< 2.0)
- Magic number (> 0.5)
Mature tracking:
- Rule of 40
- Sales efficiency
- Pipeline coverage
Metric Tracking Best Practices
Data Infrastructure
Requirements:
- Single source of truth (analytics platform)
- Real-time or daily updates
- Automated calculations
- Historical tracking
Tools:
- Mixpanel, Amplitude (product analytics)
- ChartMogul, Baremetrics (SaaS metrics)
- Looker, Tableau (BI dashboards)
Reporting Cadence
Daily:
- MRR, active users
- Sign-ups, conversions
Weekly:
- Growth rates
- Retention cohorts
- Sales pipeline
Monthly:
- Full metric suite
- Board reporting
- Investor updates
Quarterly:
- Trend analysis
- Benchmarking
- Strategy review
Common Mistakes
Mistake 1: Vanity Metrics Don't focus on:
- Total users (without retention)
- Page views (without engagement)
- Downloads (without activation)
Focus on actionable metrics tied to value.
Mistake 2: Too Many Metrics Track 5-7 core metrics intensely, not 50 loosely.
Mistake 3: Ignoring Unit Economics CAC and LTV are critical even at seed stage.
Mistake 4: Not Segmenting Break down metrics by customer segment, channel, cohort.
Mistake 5: Gaming Metrics Optimize for real business outcomes, not dashboard numbers.
Investor Metrics
What VCs Want to See
Seed Round:
- MRR growth rate
- User retention
- Early unit economics
- Product engagement
Series A:
- ARR and growth rate
- CAC payback < 18 months
- LTV:CAC > 3.0
- Net dollar retention > 100%
- Burn multiple < 2.0
Series B+:
- Rule of 40 > 40%
- Efficient growth (magic number)
- Path to profitability
- Market leadership metrics
Metric Presentation
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
Include:
- Current value
- Growth rate or trend
- Context (target, benchmark)
Quick Start
To implement startup metrics framework:
- Identify business model - SaaS, marketplace, consumer, B2B
- Choose 5-7 core metrics - Based on stage and model
- Establish tracking - Set up analytics and dashboards
- Calculate unit economics - CAC, LTV, payback
- Set targets - Use benchmarks for goals
- Review regularly - Weekly for core metrics
- Share with team - Align on goals and progress
- Update investors - Monthly/quarterly reporting
Frequently asked questions about Startup Metrics Framework
Similar skills
Business Pulse
Get a concise snapshot of your business health in one page.
Analytics Tracking
Set up and audit your analytics for actionable insights.
Ad Campaign Analyzer
Transform ad data into actionable insights for better ROI.
Metrics Review
Analyze product metrics for actionable insights.
Social Media Analyzer
Track and analyze your social media campaign performance.
Campaign Analytics
Optimize marketing campaigns with data-driven insights.
