startup-metrics-framework
$
npx mdskill add wshobson/agents/startup-metrics-frameworkCalculates and optimizes key startup metrics for SaaS, marketplace, consumer, and B2B businesses from seed to Series A.
- Helps define metrics frameworks and benchmark business health for fundraising and operational excellence.
- Integrates with financial data sources to compute metrics like CAC, LTV, and burn multiple.
- Uses industry benchmarks and stage-specific targets to recommend optimal performance metrics.
- Presents results through structured dashboards for investor or board reporting.
SKILL.md
.github/skills/startup-metrics-frameworkView on GitHub ↗
--- name: startup-metrics-framework description: Track, 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. version: 1.0.0 --- # 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. ## 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:** 1. Active users growth 2. User retention (Day 7, Day 30) 3. Core engagement (sessions, features used) 4. Qualitative feedback (NPS, interviews) **Don't worry about:** - Revenue (may be zero) - CAC (not optimizing yet) - Unit economics ### Seed ($500K-$2M ARR) **Focus Metrics:** 1. MRR growth rate (15-20% MoM) 2. CAC and LTV (establish baseline) 3. Gross retention (> 85%) 4. Core product engagement **Start tracking:** - Sales efficiency - Burn rate and runway ### Series A ($2M-$10M ARR) **Focus Metrics:** 1. ARR growth (3-5x YoY) 2. Unit economics (LTV:CAC > 3, payback < 18 months) 3. Net dollar retention (> 100%) 4. Burn multiple (< 2.0) 5. 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: 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 for goals 6. **Review regularly** - Weekly for core metrics 7. **Share with team** - Align on goals and progress 8. **Update investors** - Monthly/quarterly reporting
More from wshobson/agents
- accessibility-complianceImplement WCAG 2.2 compliant interfaces with mobile accessibility, inclusive design patterns, and assistive technology support. Use when auditing accessibility, implementing ARIA patterns, building for screen readers, or ensuring inclusive user experiences.
- airflow-dag-patternsBuild production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.
- angular-migrationMigrate from AngularJS to Angular using hybrid mode, incremental component rewriting, and dependency injection updates. Use when upgrading AngularJS applications, planning framework migrations, or modernizing legacy Angular code.
- anti-reversing-techniquesUnderstand anti-reversing, obfuscation, and protection techniques encountered during software analysis. Use this skill when analyzing malware evasion techniques, when implementing anti-debugging protections for CTF challenges, when reverse engineering packed binaries, or when building security research tools that need to detect virtualized environments.
- api-design-principlesMaster REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.
- architecture-decision-recordsWrite and maintain Architecture Decision Records (ADRs) following best practices for technical decision documentation. Use when documenting significant technical decisions, reviewing past architectural choices, or establishing decision processes.
- architecture-patternsImplement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use this skill when designing clean architecture for a new microservice, when refactoring a monolith to use bounded contexts, when implementing hexagonal or onion architecture patterns, or when debugging dependency cycles between application layers.
- async-python-patternsMaster Python asyncio, concurrent programming, and async/await patterns for high-performance applications. Use when building async APIs, concurrent systems, or I/O-bound applications requiring non-blocking operations.
- attack-tree-constructionBuild comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.
- auth-implementation-patternsMaster authentication and authorization patterns including JWT, OAuth2, session management, and RBAC to build secure, scalable access control systems. Use when implementing auth systems, securing APIs, or debugging security issues.