startup-metrics-framework
π―SkillHelps startup founders pick, calculate and report the business numbers that matter most at their stage, such as growth, customer retention, cost to win a customer and cash left. It also gives typical target ranges to compare against.
Installation
npx skills add wshobson/agents --skill startup-metrics-frameworkRun it in a terminal; it asks which AI coding tools to install it for (Claude Code, Codex, Cursor and more).
Uses skills.sh Β· Node.js 22.20+
After installing
Ask for related work and the agent uses it on its own, or call it yourself.
/startup-metrics-frameworkInstall by hand
Copy the whole skill folder from GitHub to the place below. Copying only SKILL.md can leave out files the skill uses.
Open the skill folder β- This project
.claude/skills/startup-metrics-framework/ - All projects
~/.claude/skills/startup-metrics-framework/
These paths are for Claude Code. For other tools, the command above puts it in the right place.
What this skill does
Overview
This skill is a guide to the business numbers, or metrics, that early startups should track. It covers software subscription companies, marketplaces, consumer apps and businesses that sell to other businesses. It explains each metric, how to calculate it and what a good value looks like.
Key Features
- Pick five to seven core metrics that fit your business type and funding stage.
- Calculate key figures like CAC (cost to win a customer) and LTV (money a customer brings over time).
- Compare your numbers with common benchmarks to judge business health.
- Build a simple dashboard for monthly investor or board updates.
- Avoid common mistakes, such as tracking numbers that look good but mean little.
Who is this for?
This is for founders and early team members preparing to raise money or report to a board. It is useful if you are unsure which numbers investors expect at seed or Series A. It also helps set up a regular routine for reviewing results.
Summarized by AI from this skill's SKILL.md. Suggest a better one
SKILL.md
View on GitHub βTrack, calculate, and optimize key performance metrics for SaaS, marketplace, consumer, and B2B startups from seed through Series A, including unit economics, growth efficiency, and cash management. Use this skill when defining a metrics framework, calculating CAC/LTV/burn multiple, benchmarking business health, or preparing metrics dashboards for investors or board reporting.
Startup 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.
For every startup analysis, first read universal revenue, unit-economics, and cash metrics; also apply its SaaS section when relevant.
Marketplace Metrics
GMV (Gross Merchandise Value)
Total Transaction Volume:
GMV = Ξ£ (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 Γ Invite Conversion Rate
Example: 10 invites/user Γ 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 β Opportunity: 10-20%
- Opportunity β Demo: 50-70%
- Demo β Proposal: 30-50%
- Proposal β 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 (β 18% MoM)
ARR: $3.0M (β 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
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