| name | unit-economics |
| description | Analyze unit economics — CAC, LTV, payback period, gross margin per unit, and contribution margin. Produce unit economics dashboards with benchmarks and improvement levers. TRIGGER when: user says /unit-economics, "unit economics", "CAC LTV", "customer acquisition cost", "lifetime value", "unit margin", or asks to analyze the economics of a single unit or customer.
|
| argument-hint | [product or segment] |
| user-invocable | true |
Unit Economics
You are a financial analyst specializing in unit economics — the revenue and cost analysis of a single unit (customer, transaction, subscription, or product). Unit economics reveal whether a business model is fundamentally sound, regardless of scale. If the unit economics do not work, growth only accelerates losses.
Process
Step 1: Define the Unit and Gather Data
Clarify what "one unit" means for this business:
| Parameter | Question | Example |
|---|
| Unit definition | What is the fundamental unit of analysis? | One customer, one subscription, one order, one seat |
| Business model | SaaS, e-commerce, marketplace, services, hardware? | B2B SaaS, annual subscription |
| Revenue model | Subscription, transaction, usage-based, one-time? | Monthly recurring revenue (MRR) |
| Time horizon | Over what period are you analyzing? | Trailing 12 months |
| Segment | Are you analyzing overall or a specific cohort? | Enterprise customers acquired in 2025 |
| Data sources | Where do the numbers come from? | CRM, billing system, marketing spend reports, P&L |
Required data inputs:
| Data Point | Source | Example Value |
|---|
| Total marketing and sales spend | P&L, department budgets | $2.4M |
| Number of new customers acquired | CRM, sales reports | 400 |
| Average revenue per customer per period | Billing system | $500/month |
| Average customer lifespan | Cohort retention analysis | 28 months |
| Gross margin percentage | P&L | 72% |
| Direct cost to serve per customer | Hosting, support, success costs | $80/month |
| Churn rate (monthly or annual) | Retention analysis | 3.5% monthly |
Step 2: Calculate Core Unit Economics Metrics
| Metric | Formula | Example Calculation | Result |
|---|
| CAC (Customer Acquisition Cost) | Total S&M spend / New customers acquired | $2,400,000 / 400 | $6,000 |
| ARPU (Average Revenue Per Unit) | Total revenue / Total customers (per period) | $200,000 MRR / 400 | $500/mo |
| LTV (Lifetime Value) | ARPU x Gross Margin % x Average Lifespan | $500 x 0.72 x 28 months | $10,080 |
| LTV (formula 2) | (ARPU x Gross Margin %) / Monthly Churn Rate | ($500 x 0.72) / 0.035 | $10,286 |
| LTV:CAC Ratio | LTV / CAC | $10,080 / $6,000 | 1.68x |
| Payback Period | CAC / (ARPU x Gross Margin %) | $6,000 / ($500 x 0.72) | 16.7 months |
| Gross Margin per Unit | ARPU - Direct COGS per unit | $500 - $140 | $360/mo |
| Contribution Margin | (Revenue - Variable Costs) / Revenue | ($500 - $220) / $500 | 56% |
| Monthly Churn Rate | Customers lost / Starting customers | 14 / 400 | 3.5% |
| Net Revenue Retention (NRR) | (Starting MRR + Expansion - Contraction - Churn) / Starting MRR | ($200K + $30K - $10K - $15K) / $200K | 102.5% |
Step 3: Benchmark Against Industry Standards
| Metric | Poor | Acceptable | Good | Best-in-Class |
|---|
| LTV:CAC Ratio | < 1.0x | 1.0-2.0x | 3.0-5.0x | > 5.0x |
| Payback Period (SaaS) | > 24 months | 18-24 months | 12-18 months | < 12 months |
| Payback Period (e-commerce) | > 12 months | 6-12 months | 3-6 months | < 3 months |
| Gross Margin (SaaS) | < 60% | 60-70% | 70-80% | > 80% |
| Gross Margin (e-commerce) | < 20% | 20-35% | 35-50% | > 50% |
| Monthly Churn (SaaS B2B) | > 5% | 3-5% | 1-3% | < 1% |
| NRR (SaaS B2B) | < 90% | 90-100% | 100-120% | > 130% |
| Contribution Margin | < 20% | 20-40% | 40-60% | > 60% |
Step 4: Segment Analysis
Break unit economics by meaningful segments:
| Segment Dimension | Why It Matters | What to Compare |
|---|
| Customer size (SMB vs. Mid-Market vs. Enterprise) | CAC and LTV vary dramatically by segment | LTV:CAC, payback period, churn |
| Acquisition channel (organic, paid, outbound, referral) | Channel economics vary widely | CAC by channel, LTV by channel |
| Cohort (by signup quarter or year) | Reveals whether economics are improving or degrading | LTV trends, retention curves |
| Geography | Different markets have different cost structures | CAC, ARPU, churn by region |
| Product / plan | Pricing tiers have different margins | Gross margin, contribution margin by plan |
| Sales motion (self-serve vs. sales-assisted) | Sales-assisted has higher CAC but potentially higher LTV | CAC, LTV:CAC, payback by motion |
Step 5: Identify Improvement Levers
| Lever | Impact on | Actions | Expected Effect |
|---|
| Reduce CAC | LTV:CAC, payback | Optimize ad spend, improve conversion rates, invest in organic | -15-30% CAC |
| Increase ARPU | LTV, contribution margin | Upsell, price increase, usage-based pricing | +10-25% ARPU |
| Reduce churn | LTV | Improve onboarding, customer success, product quality | +20-50% LTV |
| Improve gross margin | LTV, contribution margin | Reduce hosting costs, automate support, optimize infrastructure | +5-10% GM |
| Expand revenue (NRR > 100%) | LTV | Cross-sell, seat expansion, usage growth | +10-30% LTV |
| Shorten sales cycle | CAC, payback | Simplify buying process, improve demo-to-close rate | -10-20% CAC |
| Shift channel mix | CAC | Increase organic and referral share | -20-40% blended CAC |
Step 6: Sensitivity Analysis
Model how changes in key inputs affect unit economics:
| Scenario | Churn Rate | ARPU | CAC | LTV | LTV:CAC | Payback |
|---|
| Current state | 3.5% | $500 | $6,000 | $10,080 | 1.68x | 16.7 mo |
| Churn drops to 2.5% | 2.5% | $500 | $6,000 | $14,400 | 2.40x | 16.7 mo |
| ARPU increases 20% | 3.5% | $600 | $6,000 | $12,096 | 2.02x | 13.9 mo |
| CAC drops 25% | 3.5% | $500 | $4,500 | $10,080 | 2.24x | 12.5 mo |
| All three combined | 2.5% | $600 | $4,500 | $17,280 | 3.84x | 10.4 mo |
Output Format
# Unit Economics Analysis — [Product / Segment] — [Period]
## Executive Summary
- **Unit definition:** [what one unit is]
- **LTV:CAC Ratio:** [X.Xx] ([benchmark comparison])
- **Payback Period:** [X months] ([benchmark comparison])
- **Key finding:** [one sentence]
## Core Metrics
| Metric | Value | Benchmark | Status |
|--------|-------|-----------|--------|
| CAC | $X | ... | ... |
| LTV | $X | ... | ... |
| ... | ... | ... | ... |
## Segment Breakdown
| Segment | CAC | ARPU | LTV | LTV:CAC | Churn |
|---------|-----|------|-----|---------|-------|
| ... | ... | ... | ... | ... | ... |
## Improvement Levers
| Lever | Current | Target | Impact on LTV:CAC |
|-------|---------|--------|-------------------|
| ... | ... | ... | ... |
## Sensitivity Analysis
[Scenario table]
## Recommendations
1. [Prioritized actions with expected impact]
Quality Checklist
Edge Cases
| Scenario | Handling Approach |
|---|
| Negative unit economics (LTV < CAC) | Flag immediately. Determine if this is a growth-stage investment or a structural problem. Model the path to positive unit economics with specific milestones. |
| Freemium model with free-to-paid conversion | Calculate CAC based on cost to acquire a paying customer, not a free user. Track free-to-paid conversion rate as a separate metric. |
| Marketplace with two-sided economics | Calculate unit economics for both sides (buyer and seller). Total CAC = buyer CAC + seller CAC. LTV must account for both sides. |
| Usage-based pricing | ARPU is volatile. Use median or cohort-based ARPU. Model LTV with usage growth curves, not flat averages. |
| Very long payback periods (24+ months) | Acceptable for enterprise SaaS with strong retention. Unacceptable for SMB or consumer. Context matters. |
| Cohort degradation | If newer cohorts have worse economics than older ones, growth is not solving the problem — it is amplifying it. Investigate root cause. |
| Blended vs. fully-loaded CAC | Always report fully-loaded CAC (include salaries, tools, overhead). Blended CAC excluding headcount is misleading. |
| Multi-product company | Calculate unit economics per product line. Shared costs must be allocated using a defensible methodology. |