--- name: unit-economics description: Analyze customer and product unit economics including CAC, LTV, payback period, contribution margin, and cohort analysis. Use when evaluating customer acquisition efficiency, calculating lifetime value, assessing cohort retention, measuring contribution margins, or optimizing the business model. Triggers on phrases like "unit economics", "CAC", "LTV", "lifetime value", "customer acquisition cost", "payback period", "contribution margin", "cohort analysis", "LTV:CAC ratio", "burning cash per customer". --- # Unit Economics Analysis Calculate and monitor customer-level and product-level unit economics to ensure a sustainable, scalable business model. ## Workflow ### Unit Economics Assessment Trigger when evaluating business model health, before major growth decisions, or monthly as part of standard financial review: 1. **Data aggregation**: Customer-level revenue (monthly/annual), acquisition costs by channel, fulfillment/support costs per customer, churn/retention by cohort, gross margin by segment. 2. **Cohort definition and analysis**: Group by acquisition month/quarter; track 12–24+ months; calculate retention at each period; identify quality trends. 3. **CAC calculation**: S&M spend / new customers by channel; adjust for brand/organic; calculate blended and per-channel CAC. 4. **LTV modeling**: ARPU × gross margin / churn rate; or discounted cash flow per customer; segment by customer tier and product. 5. **Payback period**: CAC / monthly gross profit per customer; track by channel; flag channels exceeding target threshold. 6. **Contribution margin**: Revenue minus variable costs by segment and product; lifecycle margin evolution; cross-sell/upsell impact. 7. **Benchmark comparison**: CAC:LTV vs. industry (>3:1 target); payback vs. cost of capital; retention vs. peers. 8. **Optimization**: Channel mix shift, pricing adjustments, retention initiatives, cost reduction in fulfillment/support. ### Calculation Framework ``` UNIT ECONOMICS CALCULATION REFERENCE ====================================== Customer Acquisition Cost (CAC): Formula: CAC = Total Sales & Marketing Spend / Number of New Customers Acquired Period: Monthly, quarterly, or trailing 12 months Sales & Marketing includes: - Paid advertising (Google, Meta, LinkedIn, programmatic) - Sales team compensation (base + commission + benefits) - Marketing team compensation - Marketing technology (HubSpot, Marketo, sales tools) - Content creation and events - Agency fees and freelancer costs - Brand marketing and PR Excludes (debatable): - Product development (generally excluded) - General overhead (generally excluded) - Organic marketing (no direct cost; tracked separately) Channel-level CAC: Paid Search: $300–$1,200 (B2B SaaS average: $800) Paid Social: $400–$1,800 (B2B SaaS average: $1,200) Content/SEO: $100–$500 (hard to attribute; use marketing-attributed) Sales-driven: $1,500–$5,000 (enterprise; $3,000 average) Referral: $50–$300 (incentive cost only) Partnerships: $200–$800 (commission/revenue share) Adjusted CAC (recommended for decision-making): Add 12 months of marketing spend / customers acquired (captures lag) Include brand marketing allocated by conversion attribution Include sales ops and enablement costs Customer Lifetime Value (LTV): Method 1: Simple formula (steady-state assumption) LTV = (ARPU × Gross Margin %) / Monthly Churn Rate Example: $200/month × 75% margin / 3% monthly churn = $5,000 Method 2: Cohort-based (actual data, more accurate) LTV = Σ(Gross Profit in Month N) for N = 1 to customer lifetime Discount future cash flows at WACC (8–12% for startups, 5–8% for mature) Example: Year 1 GP $1,200 + Year 2 GP $1,080 + Year 3 GP $950 + ... = $4,800 Method 3: Segmented (by customer tier) Enterprise LTV: $50,000–$500,000+ (ACV $100K–$1M, 3–7 year contracts) Mid-market LTV: $10,000–$50,000 (ACV $20K–$100K, 1–3 year contracts) SMB LTV: $1,000–$10,000 (ACV $1K–$20K, month-to-month or annual) Key assumptions: - ARPU: Average Revenue Per User/Account per month - Gross margin: Revenue minus COGS (hosting, payment processing, direct support) - Churn rate: Monthly or annual (use consistent period) - Expansion revenue: Include net revenue retention (NRR) in LTV calculation - Discount rate: Reflect cost of capital and risk Payback Period: Formula: Payback (months) = CAC / (Monthly ARPU × Gross Margin %) Example: $2,000 CAC / ($200 × 75%) = $2,000 / $150 = 13.3 months Target: < 12 months (growth companies), < 18 months (mature) Interpretation: Shorter payback = more capital efficiency; can reinvest faster Contribution Margin: Formula: Contribution = Revenue − Variable Costs Variable costs include: - Hosting/infrastructure (AWS, Azure, GCP) - Payment processing fees (2.9% + $0.30 per transaction for Stripe) - Third-party API costs (usage-based) - Direct support costs (tier 1 support per customer) - Content/data licensing (per-user costs) - Shipping/materials (for physical products) Excludes: Fixed costs (salaries, rent, software licenses, overhead) Target: > 50% for SaaS, > 40% for marketplaces, > 30% for e-commerce ``` ## Cohort Analysis ### Retention and Expansion Tracking ``` COHORT ANALYSIS FRAMEWORK =========================== Cohort Definition: - By acquisition month (most common for SaaS) - By acquisition quarter (for seasonal businesses) - By customer segment (Enterprise, Mid-Market, SMB) - By product/plan tier (Basic, Pro, Enterprise) - By acquisition channel (Organic, Paid, Referral, Partner) Retention Metrics: Gross Revenue Retention (GRR): GRR = (Beginning Revenue − Churned Revenue − Downgrade Revenue) / Beginning Revenue Target: > 90% for SaaS; > 85% for SMB Measures: Revenue retained from existing customers (excluding expansion) Net Revenue Retention (NRR): NRR = (Beginning Revenue − Churn + Expansion + Upgrades) / Beginning Revenue Target: > 100% for healthy SaaS; > 110% for best-in-class Measures: Total revenue change from existing customers (including expansion) > 100% = existing base growing (land-and-expand working) < 100% = existing base shrinking despite expansion Logo Retention: Logo Retention = (Customers remaining / Customers at start) × 100 Target: > 85% annual for B2B SaaS Measures: Number of customers retained (not revenue) Note: Can differ from revenue retention (small customers churn more) Cohort Trend Analysis: Improving trends (green): - Newer cohorts have higher M1 retention (onboarding improving) - Longer customer lifespans across cohorts (product stickiness increasing) - Higher expansion rates in newer cohorts (upsell motion working) - Lower CAC in newer cohorts (marketing efficiency improving) Deteriorating trends (red): - Newer cohorts churn faster (product-market fit weakening) - Higher CAC without proportional LTV increase (marketing inefficiency) - Longer payback periods (capital intensity increasing) - Lower expansion rates (land-and-expand failing) ``` ## Benchmarking ### Industry Benchmarks by Stage ``` UNIT ECONOMICS BENCHMARKS BY COMPANY STAGE ============================================ Early Stage (Seed–Series A, <$2M ARR): CAC: $500–$3,000 (high variability) LTV:CAC ratio: 2:1–5:1 (building, may not be optimal yet) Payback period: 6–18 months Gross margin: 65–80% (SaaS) Churn (annual): 15–30% (still finding product-market fit) NRR: 95–105% (learning expansion motion) Focus: Prove unit economics work; prioritize CAC reduction Growth Stage (Series B–C, $2M–$20M ARR): CAC: $800–$4,000 (scaling efficiently) LTV:CAC ratio: 3:1–8:1 (optimizing) Payback period: 6–12 months Gross margin: 70–85% (SaaS) Churn (annual): 8–15% (PMF achieved) NRR: 105–120% (expansion motion proven) Focus: Scale efficient channels; maintain LTV:CAC > 3:1 Mature Stage ($20M+ ARR, profitable): CAC: $1,000–$5,000 (enterprise focus) LTV:CAC ratio: 4:1–10:1 (optimized) Payback period: 4–10 months Gross margin: 75–85% (SaaS) Churn (annual): 5–10% (sticky product) NRR: 110–130% (strong expansion) Focus: Maximize LTV; optimize channel mix; enterprise upsell Industry-specific benchmarks: B2B SaaS: LTV:CAC > 3:1, Payback < 12mo, NRR > 100% B2C SaaS: LTV:CAC > 2:1, Payback < 6mo, NRR > 90% E-commerce: LTV:CAC > 3:1, Payback < 3 orders, Repeat rate > 30% Marketplace: LTV:CAC > 2:1 per side, Take rate > 10%, GMV growth > 50% Fintech: LTV:CAC > 4:1, Payback < 18mo, Gross margin > 80% Healthcare SaaS: LTV:CAC > 5:1, Payback < 12mo, Churn < 5% annual ``` ### Health Assessment Scorecard ``` UNIT ECONOMICS HEALTH SCORECARD ================================ Metric | Score | Target | Status --------------------------|-----------|-------------|-------- LTV:CAC Ratio | XX:1 | > 3:1 | ✓/✗ CAC Payback (months) | X.X | < 12 | ✓/✗ Gross Margin % | XX% | > 70% | ✓/✗ NRR | XXX% | > 100% | ✓/✗ GRR | XX.X% | > 90% | ✓/✗ CAC Trend | Improving | Declining | ✓/✗ LTV Trend | Improving | Improving | ✓/✗ Contribution Margin | XX% | > 50% | ✓/✗ Overall Score: XX/8 (7–8 = Excellent, 5–6 = Good, 3–4 = Warning, < 3 = Critical) Red flags requiring immediate attention: - LTV:CAC < 2:1 → Losing money on each customer; reduce CAC or increase pricing - Payback > 18 months → Capital inefficient; cannot scale without excessive fundraising - NRR < 90% → Existing base shrinking faster than expansion; churn crisis - Gross margin < 60% → Structural profitability issue; pricing or cost problem - CAC rising > 20% QoQ → Market saturation or competition; investigate channels ``` ## Edge Cases - **Freemium model**: - CAC calculated only for converting users (free users have $0 CAC) - Conversion rate critical: Free → Paid (target 2–10% depending on industry) - Viral coefficient: Each user invites K other users (K > 1 = viral growth) - LTV includes free users' potential value (data, network effects, future conversion) - Cost of free tier: Hosting/support per free user must be <$0.10/month - Example: Slack — 14% free-to-paid conversion; CAC effectively near $0 for organic - **Marketplace/two-sided economics**: - Calculate unit economics for BOTH buyers and sellers separately - Seller CAC: Cost to acquire each supply-side participant - Buyer CAC: Cost to acquire each demand-side participant - Subsidy strategy: Often subsidize one side (e.g., Uber subsidized riders early) - Take rate: Revenue = GMV × take rate (5–20% depending on category) - Network effects: Each new seller improves buyer experience → lowers buyer CAC over time - Liquidity: Match rate = successful transactions / requests (target > 50%) - **Hardware + software bundles**: - Hardware contribution: Often negative in first year (COGS > price) - Software LTV: Recurring revenue from connected device over multi-year period - Total bundle LTV: Hardware margin + Software LTV (must be positive combined) - Payback: Extended (hardware cost recovered over software lifetime) - Example: Peloton — Hardware margin ~10–15%; Subscription LTV ~$2,000+; Combined positive - Risk: Hardware inventory risk (obsolete, damaged, returned) - **Negative initial unit economics** (common in subscription models): - First-year loss per customer is normal if LTV recovers over lifetime - Validation: Projected LTV > 3× CAC over full customer lifetime - Monitoring: Track actual payback period monthly (not projected) - Investor threshold: Payback < 18 months acceptable; < 12 months preferred - Danger signs: Actual payback extending beyond projections; CAC rising without LTV increase - Mitigation: Improve onboarding (faster time-to-value), increase pricing, reduce support costs - **Multi-product companies**: - Attribute shared costs (infrastructure, support, G&A) using allocation bases - Common allocation: Revenue %, headcount %, usage %, or driver-based - Cross-sell uplift: Existing customers buying additional products have 0 marginal CAC - Product portfolio analysis: Which products drive profitability vs. which are loss leaders - Bundling impact: Bundled pricing may reduce per-product margin but increase total LTV - Example: Salesforce — Sales Cloud (highest margin) cross-sells to Service Cloud, Tableau, MuleSoft - **Long sales cycle enterprise**: - Sales cycle: 6–18 months; CAC includes extensive sales team cost - CAC per deal: $20K–$100K+ for enterprise deals - Opportunity cost: Sales capacity tied up for 6–18 months per deal - Pipeline CAC: Weighted by stage probability (25% at discovery, 75% at negotiation) - Sales productivity: Revenue per AE ($1M–$5M annually); target > $2M - Land-and-expand: Initial deal smaller ($50K–$100K); expand to $500K+ over 2–3 years ## Integration Points - **CRM**: Salesforce, HubSpot, Pipedrive — customer acquisition data, deal stages, sales costs, win rates - **Billing/Subscription**: Stripe, Chargebee, Zuora, Recurly — revenue per customer, churn data, expansion revenue, MRR/ARR - **Marketing Platforms**: Google Ads, Meta Ads Manager, LinkedIn Campaign Manager, HubSpot — S&M spend by channel, campaign performance - **Support Tools**: Zendesk, Intercom, Freshdesk — support cost per customer, ticket volume, resolution time - **Analytics**: Mixpanel, Amplitude, Segment — product usage, engagement, feature adoption, activation rates - **Finance Systems**: NetSuite, QuickBooks, Xero — cost data, gross margin calculation, variable cost allocation - **BI Tools**: Tableau, Power BI, Looker, Mode — cohort visualization, unit economics dashboards, trend analysis - **Data Warehouse**: Snowflake, BigQuery — centralized customer data, historical cohort tracking, ML model training - **Revenue Operations**: Gainsight, Planhat, Totango — customer health scoring, expansion signals, churn risk - **Attribution Platforms**: Triple Whale, Northbeam, Rockerbox — marketing attribution, channel CAC calculation