SaaS Metrics
SaaS business metrics analysis - MRR, ARR, Churn, LTV, CAC, cohort analysis, and investor reporting
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# SaaS Metrics
Comprehensive SaaS metrics analysis covering MRR, ARR, Churn, LTV, CAC, cohort analysis, and investor reporting. Essential for SaaS founders, finance teams, and investors.
## Overview
This skill enables:
- Revenue metrics calculation (MRR, ARR, NRR)
- Churn and retention analysis
- Unit economics (LTV, CAC, LTV:CAC)
- Cohort analysis and forecasting
- Investor-ready reporting
---
## Core Metrics Framework
### 1. Revenue Metrics
```
┌─────────────────────────────────────────────────────────────┐
│ MRR WATERFALL │
├─────────────────────────────────────────────────────────────┤
│ │
│ Starting MRR $100,000 │
│ + New MRR (new customers) +$15,000 │
│ + Expansion MRR (upgrades) +$8,000 │
│ + Reactivation MRR +$2,000 │
│ - Contraction MRR (downgrades) -$3,000 │
│ - Churn MRR (cancellations) -$7,000 │
│ ───────────────────────────────────────────── │
│ = Ending MRR $115,000 │
│ │
│ Net New MRR = $15,000 │
│ MRR Growth Rate = 15% │
│ │
└─────────────────────────────────────────────────────────────┘
```
**Calculations**:
```yaml
mrr_metrics:
# Monthly Recurring Revenue
MRR: sum(all_active_subscriptions.monthly_value)
# Annual Recurring Revenue
ARR: MRR × 12
# MRR Components
new_mrr: sum(new_subscriptions_this_month)
expansion_mrr: sum(upgrades_this_month)
contraction_mrr: sum(downgrades_this_month)
churn_mrr: sum(cancelled_subscriptions_mrr)
reactivation_mrr: sum(reactivated_subscriptions)
# Net New MRR
net_new_mrr: new_mrr + expansion_mrr + reactivation_mrr - contraction_mrr - churn_mrr
# Growth Rates
mrr_growth_rate: (ending_mrr - starting_mrr) / starting_mrr × 100
mom_growth: (current_mrr - previous_mrr) / previous_mrr × 100
```
---
### 2. Churn Metrics
```yaml
churn_metrics:
# Logo Churn (Customer Count)
logo_churn_rate:
formula: customers_lost / customers_start_of_period × 100
benchmark: <5% monthly for SMB, <2% for Enterprise
# Revenue Churn (MRR)
gross_revenue_churn:
formula: churned_mrr / starting_mrr × 100
benchmark: <3% monthly
# Net Revenue Churn (includes expansion)
net_revenue_churn:
formula: (churned_mrr - expansion_mrr) / starting_mrr × 100
target: negative (net expansion)
# Net Revenue Retention (NRR)
nrr:
formula: (starting_mrr - churn + expansion) / starting_mrr × 100
benchmark:
good: 100-110%
great: 110-120%
best_in_class: >120%
```
**Churn Analysis Template**:
```markdown
## Churn Analysis - {Month}
### Summary
| Metric | Value | Benchmark | Status |
|--------|-------|-----------|--------|
| Logo Churn | 3.2% | <5% | ✅ |
| Gross Revenue Churn | 2.8% | <3% | ✅ |
| Net Revenue Retention | 108% | >100% | ✅ |
### Churn Breakdown
| Reason | Customers | MRR Lost | % of Total |
|--------|-----------|----------|------------|
| Price | 5 | $2,500 | 35% |
| Competitor | 3 | $1,800 | 25% |
| No longer needed | 4 | $1,500 | 21% |
| Product issues | 2 | $800 | 11% |
| Other | 2 | $600 | 8% |
### Cohort Performance
- Q1 2025 cohort: 95% retention at month 6
- Q4 2024 cohort: 88% retention at month 9
- Enterprise segment: 97% retention (best)
```
---
### 3. Unit Economics
```
┌─────────────────────────────────────────────────────────────┐
│ UNIT ECONOMICS │
├─────────────────────────────────────────────────────────────┤
│ │
│ Customer Lifetime Value (LTV) │
│ ──────────────────────────── │
│ ARPU × Gross Margin % │
│ ─────────────────────── = LTV │
│ Churn Rate │
│ │
│ Example: │
│ $100 ARPU × 80% margin / 3% churn = $2,667 LTV │
│ │
│ ═══════════════════════════════════════════════════════ │
│ │
│ Customer Acquisition Cost (CAC) │
│ ──────────────────────────────── │
│ Sales & Marketing Spend │
│ ─────────────────────────── = CAC │
│ New Customers Acquired │
│ │
│ Example: │
│ $50,000 S&M / 50 customers = $1,000 CAC │
│ │
│ ═══════════════════════════════════════════════════════ │
│ │
│ LTV:CAC Ratio = $2,667 / $1,000 = 2.67x │
│ CAC Payback = $1,000 / ($100 × 80%) = 12.5 months │
│ │
└─────────────────────────────────────────────────────────────┘
```
**Benchmarks**:
```yaml
unit_economics_benchmarks:
ltv_cac_ratio:
poor: <1x
acceptable: 1-2x
good: 2-3x
great: 3-5x
excellent: >5x
cac_payback_months:
enterprise: <18
mid_market: <12
smb: <6
consumer: <3
gross_margin:
saas_typical: 70-85%
infrastructure: 50-70%
services_heavy: 40-60%
```
---
### 4. Cohort Analysis
```yaml
cohort_analysis:
# Define cohorts by signup month
cohort_definition: signup_month
# Track retention over time
retention_matrix:
columns: [Month_0, Month_1, Month_2, ..., Month_12]
rows: [Jan_cohort, Feb_cohort, Mar_cohort, ...]
values: active_customers / initial_customers × 100
# Track revenue retention
revenue_cohort:
values: current_mrr / initial_mrr × 100
# Cohort LTV calculation
cohort_ltv:
formula: sum(all_revenue_from_cohort) / initial_cohort_size
```
**Cohort Table Example**:
```
Retention by Cohort (% of customers still active)
Month 0 Month 1 Month 2 Month 3 Month 6 Month 12
Jan '25 100% 92% 87% 84% 78% 65%
Feb '25 100% 94% 89% 86% 80% -
Mar '25 100% 93% 88% 85% - -
Apr '25 100% 95% 90% - - -
May '25 100% 94% - - - -
Jun '25 100% - - - - -
Average 100% 94% 89% 85% 79% 65%
```
---
## Quick Ratio
```yaml
quick_ratio:
formula: (new_mrr + expansion_mrr) / (contraction_mrr + churn_mrr)
interpretation:
"<1": Shrinking (losing more than gaining)
"1-2": Sustainable growth
"2-4": Good growth efficiency
">4": Excellent (hypergrowth potential)
example:
new_mrr: 15000
expansion_mrr: 8000
contraction_mrr: 3000
churn_mrr: 7000
quick_ratio: (15000 + 8000) / (3000 + 7000) = 2.3
```
---
## Investor Reporting Template
### Monthly Metrics Dashboard
```markdown
# {Company} - Monthly Metrics Report
## {Month Year}
### Key Metrics Summary
| Metric | Current | Previous | Change | Benchmark |
|--------|---------|----------|--------|-----------|
| ARR | $1.38M | $1.20M | +15% | - |
| MRR | $115K | $100K | +15% | - |
| Net New MRR | $15K | $12K | +25% | - |
| NRR | 108% | 105% | +3pp | >100% ✅ |
| Logo Churn | 3.2% | 3.5% | -0.3pp | <5% ✅ |
| LTV:CAC | 2.7x | 2.5x | +0.2x | >3x ⚠️ |
| CAC Payback | 12.5mo | 13mo | -0.5mo | <12mo ⚠️ |
### MRR Waterfall
```
Starting MRR: $100,000
+ New: +$15,000 (12 customers)
+ Expansion: +$8,000 (25 upgrades)
+ Reactivation: +$2,000 (5 returns)
- Contraction: -$3,000 (15 downgrades)
- Churn: -$7,000 (18 cancellations)
═════════════════════════════
Ending MRR: $115,000
```
### Customer Metrics
| Segment | Customers | MRR | ARPU | Churn |
|---------|-----------|-----|------|-------|
| Enterprise | 45 | $45K | $1,000 | 1.5% |
| Mid-Market | 120 | $36K | $300 | 2.8% |
| SMB | 350 | $34K | $97 | 4.5% |
| **Total** | **515** | **$115K** | **$223** | **3.2%** |
### Runway & Burn
- Cash Balance: $2.5M
- Monthly Burn: $85K
- Runway: 29 months
- Revenue/Burn Ratio: 1.35x
### Goals vs Actuals
| Goal | Target | Actual | Status |
|------|--------|--------|--------|
| New Customers | 15 | 12 | 🔴 80% |
| Net New MRR | $12K | $15K | 🟢 125% |
| NRR | 105% | 108% | 🟢 103% |
| CAC Payback | 12mo | 12.5mo | 🟡 96% |
### Next Month Outlook
- Pipeline: $45K in qualified opportunities
- Expected closes: 8-10 customers
- Projected MRR: $125-130K
- Key risks: Enterprise deal slip, holiday slowdown
```
---
## Forecasting Model
### Bottom-Up Revenue Forecast
```yaml
forecast_model:
# Starting point
base_mrr: 115000
# Growth assumptions
assumptions:
new_customers_monthly: 15
avg_new_customer_mrr: 1250
expansion_rate: 2% # of existing MRR
contraction_rate: 0.5%
logo_churn_rate: 3%
# Monthly calculation
monthly_forecast:
new_mrr: new_customers × avg_mrr
expansion_mrr: existing_mrr × expansion_rate
contraction_mrr: existing_mrr × contraction_rate
churn_mrr: existing_mrr × churn_rate
ending_mrr: |
starting_mrr
+ new_mrr
+ expansion_mrr
- contraction_mrr
- churn_mrr
```
### 12-Month Projection
```
Month Starting New Expansion Churn Ending Growth
Jan $115,000 $18,750 $2,300 $3,450 $132,600 15.3%
Feb $132,600 $18,750 $2,652 $3,978 $150,024 13.1%
Mar $150,024 $18,750 $3,000 $4,501 $167,274 11.5%
...
Dec $285,000 $18,750 $5,700 $8,550 $300,900 5.6%
Annual Summary:
- Starting ARR: $1.38M
- Ending ARR: $3.61M
- Growth: 162%
```
---
## Segmentation Analysis
```yaml
segment_analysis:
by_plan:
- name: Starter
mrr: 20000
customers: 300
arpu: 67
churn: 6%
- name: Professional
mrr: 45000
customers: 150
arpu: 300
churn: 3%
- name: Enterprise
mrr: 50000
customers: 50
arpu: 1000
churn: 1.5%
by_industry:
- tech: {mrr: 60000, churn: 2.5%}
- finance: {mrr: 30000, churn: 2%}
- retail: {mrr: 25000, churn: 5%}
by_company_size:
- 1-50: {arpu: 100, churn: 5%}
- 51-200: {arpu: 350, churn: 3%}
- 201+: {arpu: 1200, churn: 1.5%}
```
---
## Output Example
**Request**: "Calculate SaaS metrics for my company"
**Output**:
```markdown
# SaaS Metrics Analysis
## Executive Summary
Your SaaS business is showing healthy growth with some areas for optimization.
### Strengths ✅
- Net Revenue Retention of 108% (above 100% benchmark)
- Quick Ratio of 2.3x (good growth efficiency)
- Enterprise segment showing 97% retention
### Areas to Improve ⚠️
- LTV:CAC ratio at 2.7x (target: >3x)
- CAC payback at 12.5 months (target: <12 months)
- SMB segment churn at 4.5% (target: <4%)
### Recommendations
1. **Reduce CAC**: Focus on lower-cost acquisition channels
2. **Improve SMB retention**: Add onboarding sequences
3. **Expand enterprise**: Higher ARPU, lower churn
4. **Increase expansion revenue**: Upsell/cross-sell programs
### Key Metrics at a Glance
| Metric | Value | Status |
|--------|-------|--------|
| ARR | $1.38M | 📈 +15% MoM |
| NRR | 108% | ✅ Healthy |
| LTV:CAC | 2.7x | ⚠️ Improve |
| Runway | 29 months | ✅ Safe |
```
---
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