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Startup Metrics Framework

Seth HobsonCommunityCreated by Seth Hobson

  • Skill
  • Guidelines
  • Business and productivity
  • MIT
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From the author

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.
— the description by Seth Hobson

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured approach to identifying, calculating, and optimizing performance metrics tailored to different startup business models, including SaaS, marketplace, consumer, and B2B. It covers essential areas such as unit economics, growth efficiency, and cash management, offering specific formulas and industry benchmarks to help founders and operators evaluate business health and prepare for investor reporting.

What it does

  • Defines core metrics for SaaS, marketplace, consumer, and B2B business models.
  • Provides formulas for calculating unit economics like CAC, LTV, and payback periods.
  • Outlines growth efficiency metrics including burn multiple, magic number, and Rule of 40.
  • Offers stage-specific guidance for pre-seed, seed, and Series A startups.
  • Suggests reporting cadences and data infrastructure requirements for metric tracking.
  • Lists common pitfalls to avoid when selecting and monitoring business performance indicators.

When to use it

  • When defining a metrics framework for a new or existing startup.
  • When preparing dashboards for board meetings or investor updates.
  • When benchmarking business health against industry standards.
  • When calculating unit economics to assess product-market fit or scaling readiness.

Advantages

  • Standardizes metric definitions across different business models.
  • Provides clear formulas for complex financial and operational calculations.
  • Includes industry-standard benchmarks for evaluating performance at various growth stages.
  • Helps prioritize actionable metrics over vanity metrics.

Usage examples

“How do I calculate the burn multiple for my startup?”
The skill provides the formula (Quarterly Net Burn / Net New ARR) and explains how to use it to measure capital efficiency.
“What metrics should I focus on for a seed-stage SaaS company?”
The skill identifies MRR growth, CAC, LTV, gross retention, and core product engagement as primary focus areas.
“What is a good LTV:CAC ratio?”
The skill defines a ratio above 3.0 as healthy, 1.0-3.0 as needing improvement, and below 1.0 as unsustainable.
“How do I measure marketplace liquidity?”
The skill suggests tracking time to transaction, fill rate, and repeat rate, with specific benchmarks for each.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/wshobson/startup-metrics-framework/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip startup-metrics-framework.zip -d .agents/skills

Documentation by Seth Hobson

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 = 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

Files

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.

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 = 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

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

No issues found by our static scan· No issues found

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Attribution and licence

Created by
Seth Hobson
Publisher
Seth Hobson (Community)
Source
wshobson/agents · plugins/startup-business-analyst/skills/startup-metrics-framework · commit 4bde316
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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