Essential metrics framework for tracking startup performance across seed through Series A stages.
Works with
Covers universal metrics (MRR, ARR, CAC, LTV, burn rate, runway) plus specialized frameworks for SaaS, marketplaces, consumer, and B2B models
Includes formulas, calculation methods, and stage-specific benchmarks for evaluating unit economics and growth efficiency
Provides stage-gated guidance: pre-seed focuses on product-market fit signals; seed emphasizes retention and baseline unit eco
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionstartup-metrics-frameworkExecute the skills CLI command in your project's root directory to begin installation:
Fetches startup-metrics-framework from wshobson/agents and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate startup-metrics-framework. Access via /startup-metrics-framework in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Comprehensive guide to tracking, calculating, and optimizing key performance metrics for different startup business models from seed through Series A.
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.
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:
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:
CAC Payback Period
CAC Payback = CAC / (ARPU × Gross Margin%)
Benchmarks:
24 months = Concerning
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:
2.0 = Inefficient
Lower is better (spending less to generate ARR)
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
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:
Gross Retention
Gross Retention = (ARR Start - Churn - Contraction) / ARR Start
Benchmarks:
90% = Excellent
Magic Number
Magic Number = Net New ARR (quarter) / S&M Spend (prior quarter)
Benchmarks:
0.75 = Efficient, ready to scale
Rule of 40
Rule of 40 = Revenue Growth Rate% + Profit Margin%
Benchmarks:
40% = Excellent
Example: 50% growth + (10%) margin = 40% ✓
Quick Ratio
Quick Ratio = (New MRR + Expansion MRR) / (Churned MRR + Contraction MRR)
Benchmarks:
4.0 = Healthy growth
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 = Net Revenue / GMV
Typical Ranges:
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:
Supply/Demand Ratio: Track relative growth of supply and demand sides.
Warning Signs:
Goal: Balanced growth (1:1 ratio ideal, but varies by model)
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)
Session Frequency Average sessions per user per day/week
Session Duration Average time spent per session
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
Retention Curve Shape:
K-Factor = Invites per User × Invite Conversion Rate
Example: 10 invites/user × 20% conversion = 2.0 K-factor
Benchmarks:
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:
Average Contract Value (ACV)
ACV = Total Contract Value / Contract Length (years)
Pipeline Coverage
Pipeline Coverage = Total Pipeline Value / Quota
Target: 3-5x coverage (3-5x pipeline needed to hit quota)
Conversion Rates by Stage:
Focus Metrics:
Don't worry about:
Focus Metrics:
Start tracking:
Focus Metrics:
Mature tracking:
Requirements:
Tools:
Daily:
Weekly:
Monthly:
Quarterly:
Mistake 1: Vanity Metrics Don't focus on:
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.
Seed Round:
Series A:
Series B+:
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:
To implement startup metrics framework:
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
I recommend startup-metrics-framework for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in startup-metrics-framework — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Keeps context tight: startup-metrics-framework is the kind of skill you can hand to a new teammate without a long onboarding doc.
startup-metrics-framework is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in startup-metrics-framework — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend startup-metrics-framework for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
startup-metrics-framework is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: startup-metrics-framework is the kind of skill you can hand to a new teammate without a long onboarding doc.
startup-metrics-framework has been reliable in day-to-day use. Documentation quality is above average for community skills.
I recommend startup-metrics-framework for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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