financial-unit-economics

Financial Unit Economics

Table of Contents

• Workflow
• Common Patterns
• Guardrails
• Quick Reference

Example

Scenario: SaaS startup, $100/month subscription

• CAC: $20k spend / 100 customers = $200
• Gross margin: ($100 - $20 variable) / $100 = 80%
• Monthly churn: 5% -> Average lifetime = 20 months
• LTV: $100 x 20 months x 80% = $1,600
• LTV/CAC: 8:1 (healthy, >3:1), Payback: 2.5 months (good, <12 months)
• Interpretation: Strong unit economics. Can profitably scale marketing spend.

Workflow

Copy this checklist and track your progress:

Unit Economics Analysis Progress:
- [ ] Step 1: Define the unit
- [ ] Step 2: Calculate CAC
- [ ] Step 3: Calculate LTV
- [ ] Step 4: Assess contribution margin
- [ ] Step 5: Analyze cohorts
- [ ] Step 6: Interpret and recommend

Step 1: Define the unit

What is your unit of analysis? (Customer, product SKU, transaction, subscription). See resources/template.md.

Step 2: Calculate CAC

Total acquisition costs (sales + marketing) ÷ new units acquired. Break down by channel if applicable. See resources/template.md and resources/methodology.md.

Step 3: Calculate LTV

Revenue over unit lifetime minus variable costs. Use cohort data for retention/churn. See resources/template.md and resources/methodology.md.

Step 4: Assess contribution margin

(Revenue - Variable Costs) ÷ Revenue. Identify levers to improve margin. See resources/template.md and resources/methodology.md.

Step 5: Analyze cohorts

Track retention, LTV, payback by customer cohort (acquisition month/channel/segment). See resources/template.md and resources/methodology.md.

Step 6: Interpret and recommend

Assess LTV/CAC ratio, payback period, cash efficiency. Make recommendations (pricing, channels, growth). See resources/template.md and resources/methodology.md.

Validate using resources/evaluators/rubric_financial_unit_economics.json. Minimum standard: Average score ≥ 3.5.

Common Patterns

Pattern 1: SaaS Subscription Model

• Key metrics: MRR, ARR, churn rate, LTV/CAC, payback period, CAC payback
• Calculation: LTV = ARPU × Gross Margin % ÷ Churn Rate
• Benchmarks: LTV/CAC ≥3:1, Payback <12 months, Churn <5% monthly (B2C) or <2% (B2B)
• Levers: Reduce churn (increase LTV), upsell/cross-sell (increase ARPU), optimize channels (reduce CAC)
• When: Subscription business, recurring revenue, retention critical

Pattern 2: E-commerce / Transactional

• Key metrics: AOV (Average Order Value), repeat purchase rate, contribution margin per order, CAC
• Calculation: LTV = AOV × Purchase Frequency × Gross Margin % × Customer Lifetime (years)
• Benchmarks: Contribution margin ≥40%, Repeat purchase rate ≥25%, LTV/CAC ≥2:1
• Levers: Increase AOV (bundling, upsells), drive repeat purchases (loyalty programs), reduce variable costs
• When: Transactional business, e-commerce, retail

Pattern 3: Marketplace / Platform

• Key metrics: Take rate, GMV (Gross Merchandise Value), supply/demand CAC, liquidity
• Calculation: LTV = GMV per user × Take Rate × Gross Margin % ÷ Churn Rate
• Benchmarks: Take rate 10-30%, LTV/CAC ≥3:1 for both sides, network effects kicking in
• Levers: Increase take rate (value-added services), improve matching (increase GMV), balance supply/demand
• When: Two-sided marketplace, platform business

Pattern 4: Freemium / PLG (Product-Led Growth)

• Key metrics: Free-to-paid conversion rate, time to convert, paid user LTV, blended CAC
• Calculation: Blended LTV = (Free users × Conversion % × Paid LTV) - (Free user costs)
• Benchmarks: Conversion ≥2%, Time to convert <90 days, Paid LTV/CAC ≥4:1
• Levers: Increase conversion rate (improve product, optimize paywall), reduce time to value, lower CAC via virality
• When: Product-led growth, freemium model, viral product

Pattern 5: Enterprise / High-Touch Sales

• Key metrics: CAC (including sales team costs), sales cycle length, NRR (Net Revenue Retention), LTV
• Calculation: LTV = ACV (Annual Contract Value) × Gross Margin % × Average Customer Lifetime (years)
• Benchmarks: LTV/CAC ≥3:1, Sales efficiency (ARR added ÷ S&M spend) ≥1.0, NRR ≥110%
• Levers: Shorten sales cycle, increase ACV (upsell, premium tiers), improve retention (NRR)
• When: Enterprise sales, high ACV, long sales cycles

Guardrails

1. Fully-loaded CAC: Include all acquisition costs (sales salaries, marketing spend, tools, overhead allocation). Excluding sales team salaries is a common miss that inflates perceived economics.

2. True variable costs: Only include costs that scale with each unit (COGS, hosting per user, transaction fees). Exclude fixed costs (rent, core engineering). Accurate margins are essential for LTV.

3. Cohort-based LTV: Early cohorts are not the same as recent cohorts. Track retention curves by cohort. Base LTV on observed retention, not assumptions.

4. Use conservative time horizons: LTV is a prediction. For new products with limited data, weight recent cohorts more heavily and avoid projecting far beyond observed behavior.

5. Optimize both payback and LTV/CAC: High LTV/CAC but long payback (>18 months) strains cash. Fast payback (<6 months) allows rapid reinvestment.

6. Analyze at channel level: Blended metrics hide the truth. CAC and LTV vary by channel (paid search vs. referral vs. content). Break down separately to optimize spend.

7. Retention drives LTV exponentially: Improving monthly churn from 5% to 4% increases LTV by 25%. Retention improvements typically matter more than acquisition improvements.

8. Gross margin floor: SaaS needs >=60% gross margin, e-commerce >=40%, to be viable. Low margin means even high LTV/CAC ratios yield poor cash flow.

Common pitfalls:

• ❌ Ignoring churn: Assuming customers stay forever. Reality: churn compounds. Use cohort retention curves.
• ❌ Vanity LTV: Using unrealistic retention (e.g., 5 year LTV with 1 month of data). Stick to observed behavior.
• ❌ Blended CAC: Mixing profitable and unprofitable channels. Break down by channel, segment, cohort.
• ❌ Not updating: Unit economics change as product, market, competition evolve. Re-calculate quarterly.
• ❌ Missing costs: Forgetting support costs, payment processing fees, fraud losses, refunds. Track everything.
• ❌ Premature scaling: Growing before unit economics work (LTV/CAC <2:1). "We'll make it up in volume" rarely works.

Quick Reference

Key formulas:

CAC = (Sales + Marketing Costs) ÷ New Customers Acquired

LTV (subscription) = ARPU × Gross Margin % ÷ Monthly Churn Rate

LTV (transactional) = AOV × Purchase Frequency × Gross Margin % × Lifetime (years)

Contribution Margin % = (Revenue - Variable Costs) ÷ Revenue

LTV/CAC Ratio = Lifetime Value ÷ Customer Acquisition Cost

Payback Period (months) = CAC ÷ (Monthly Revenue × Gross Margin %)

CAC Payback (months) = S&M Spend ÷ (New ARR × Gross Margin %)

Gross Margin % = (Revenue - COGS) ÷ Revenue

Customer Lifetime (months) = 1 ÷ Monthly Churn Rate

MRR (Monthly Recurring Revenue) = Sum of all monthly subscriptions

ARR (Annual Recurring Revenue) = MRR × 12

ARPU (Average Revenue Per User) = Total Revenue ÷ Total Users

NRR (Net Revenue Retention) = (Starting ARR + Expansion - Contraction - Churn) ÷ Starting ARR

Benchmarks (varies by stage and industry):

Metric	Good	Acceptable	Poor
LTV/CAC Ratio	≥5:1	3:1 - 5:1	<3:1
Payback Period	<6 months	6-12 months	>18 months
Gross Margin (SaaS)	≥80%	60-80%	<60%
Gross Margin (E-commerce)	≥50%	40-50%	<40%
Monthly Churn (B2C SaaS)	<3%	3-7%	>7%
Monthly Churn (B2B SaaS)	<1%	1-3%	>3%
CAC Payback (SaaS)	<12 months	12-18 months	>18 months
NRR (SaaS)	≥120%	100-120%	<100%

Decision framework:

LTV/CAC	Payback	Recommendation
<1:1	Any	Stop: Losing money on every customer. Fix model or pivot.
1:1 - 2:1	>12 months	Caution: Marginal economics. Don't scale yet. Improve retention or reduce CAC.
2:1 - 3:1	6-12 months	Optimize: Unit economics acceptable. Focus on improving before scaling.
3:1 - 5:1	<12 months	Scale: Good economics. Can profitably invest in growth.
>5:1	<6 months	Aggressive scale: Excellent economics. Raise capital, increase spend rapidly.

Inputs required:

• Revenue data: Pricing, ARPU, AOV, transaction frequency
• Cost data: Sales/marketing spend, COGS, variable costs per customer
• Retention data: Churn rate, cohort retention curves, repeat purchase behavior
• Channel data: CAC by acquisition channel, LTV by segment
• Time period: Cohort definition (monthly, quarterly), historical data range

Outputs produced:

• unit-economics-analysis.md: Full analysis with CAC, LTV, ratios, cohort breakdowns
• cohort-retention-table.csv: Retention curves by cohort
• channel-profitability.csv: CAC and LTV by acquisition channel
• recommendations.md: Pricing, channel, growth recommendations based on metrics