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startup-metrics-framework

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by wshobson · Updated Apr 16, 2026

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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.

startup-metricssaasunit-economicsinvestor-reportingbenchmarksbusiness-analysis

See It In Action

1 turns·claude
The project codebase is in your current working directory. Explore the files to understand the code before making changes. board deck locks this afternoon — can you turn our March SaaS numbers into a quick board-ready KPI health snapshot with benchmarks

Let me explore the codebase first to find the March SaaS data, then build the snapshot.

Now let me invoke the metrics framework skill and build the snapshot.

Now let me compute all the KPIs and build the board snapshot.

Snapshot is ready at board_kpi_snapshot_march2026.md. Here's the headline view:

The good:

  • 20% MoM MRR growth -- top of seed benchmark (15-20%)
  • LTV:CAC of 30x and 0.8-month CAC payback -- exceptional unit economics
  • 0.67x burn multiple -- best-in-class capital efficiency

The board conversation:

  • Runway is 10 months (below 12-month floor). With Series A targeted for Q3, fundraising prep needs to start this month.
  • 4% monthly logo churn (39% annualized) and a Quick Ratio of just 1.17x -- growth is real but churn is eating into it. NDR is flat at 100%.

Data flag: The MRR bridge has an unusual pattern -- expansion and gross churn both exceed starting MRR. Worth having finance double-check the customer-level ledger before the deck goes out.

The file includes all the computed KPIs with formulas, seed-stage benchmarks, health ratings, and three proposed board discussion items (Series A timeline, churn initiative, unit economics narrative).

Claude Sonnet 4.6

SKILL.md

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

FAQ

What does startup-metrics-framework do?

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.

When should I use startup-metrics-framework?

Use it when you need a repeatable workflow that produces text report.

What does startup-metrics-framework output?

In the evaluated run it produced text report.

How do I install or invoke startup-metrics-framework?

Ask the agent to use this skill when the task matches its documented workflow.

Which agents does startup-metrics-framework support?

Agent support is inferred from the source, but not explicitly declared.

What tools, channels, or permissions does startup-metrics-framework need?

It uses no extra tools; channels commonly include text; permissions include no explicit permission scopes.

Is startup-metrics-framework safe to install?

Static analysis marked this skill as low risk; review side effects and permissions before enabling it.

How is startup-metrics-framework different from an MCP or plugin?

A skill packages instructions and workflow conventions; tools, MCP servers, and plugins are dependencies the skill may call during execution.

Does startup-metrics-framework outperform not using a skill?

About startup-metrics-framework

When to use startup-metrics-framework

You need to define a core KPI framework for a SaaS, marketplace, consumer, or B2B startup. You want help calculating metrics like CAC, LTV, burn multiple, retention, or growth efficiency. You are preparing dashboards or investor and board reporting with standard startup benchmarks.

When startup-metrics-framework is not the right choice

You need direct integration with analytics, BI, or financial systems to pull live data automatically. You need industry-specific financial modeling beyond early-stage startup KPI frameworks.

What it produces

Produces text report.