Agent-Skills.md

Agent Skills: Financial Unit Economics

Use when evaluating business model viability, analyzing profitability per customer/product/transaction, validating startup metrics (CAC, LTV, payback period), making pricing decisions, assessing scalability, comparing business models, or when user mentions unit economics, CAC/LTV ratio, contribution margin, customer profitability, break-even analysis, or needs to determine if a business can be profitable at scale.

UncategorizedID: lyndonkl/claude/financial-unit-economics

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skills/financial-unit-economics/SKILL.md

Skill Metadata

Name
financial-unit-economics
Description
Analyzes profitability per customer, product, or transaction to determine business model viability and scalability. Covers CAC, LTV, contribution margin, cohort analysis, and growth-readiness assessment. Use when evaluating business model viability, validating startup metrics (CAC, LTV, payback period), making pricing decisions, comparing business models, or when user mentions unit economics, CAC/LTV ratio, contribution margin, customer profitability, or break-even analysis.

Financial Unit Economics

Table of Contents

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