/startup-metrics-framework

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.

For every startup analysis, first read [universal revenue, unit-economics, and cash metrics](references/universal-and-saas-metrics.md); 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 engage