Startup Metrics Framework
Seth HobsonCommunityCreated by Seth Hobson
- Skill
- Guidelines
- Business and productivity
- MIT
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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
Download the skill as a ZIP:
https://autogineer.com/agent-skills/wshobson/startup-metrics-framework/downloadUnzip 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 GMVTarget: 20%+ MoM early-stage
Take Rate
Take Rate = Net Revenue / GMVTypical 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 / MAUBenchmarks:
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 RateExample: 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 OpportunitiesTarget: 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 / QuotaTarget: 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:
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 (↑ 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 monthsInclude:
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
Files
- ATTRIBUTION.mdAdded by AutoGineer1023 B
- LICENSELicence file added by AutoGineer1.0 KiB
- SKILL.md6.9 KiB
- references/universal-and-saas-metrics.md4.0 KiB
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 GMVTarget: 20%+ MoM early-stage
Take Rate
Take Rate = Net Revenue / GMVTypical 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 / MAUBenchmarks:
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 RateExample: 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 OpportunitiesTarget: 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 / QuotaTarget: 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:
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 (↑ 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 monthsInclude:
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
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)
- Synced
AutoGineer is not affiliated with or endorsed by Seth Hobson or Seth Hobson.
Download ZIP
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