unit-economics
This Skill analyzes unit economics for private-equity targets and other recurring-revenue businesses. It builds ARR bridges and annual cohort matrices, computes CAC, LTV, LTV:CAC ratios, gross and net retention, churn, and payback periods, and traces the full margin waterfall from revenue to EBITDA. It then benchmarks results against SaaS standards such as the Rule of 40, the Magic Number, and best-in-class retention targets, and synthesizes a revenue quality score with red flags and follow-up diligence questions. Use it when evaluating revenue quality, building a cohort analysis, or assessing customer economics before an investment decision.
npx skills add https://github.com/anthropics/financial-services --skill unit-economicsBefore / After Comparison
2 组Without this Skill, an analyst had to stitch together exports from several systems by hand to assemble the ARR bridge and annual cohort matrix, re-checking formulas repeatedly, which consumed most of a day or spilled into the next.
This Skill follows a fixed workflow to produce the ARR bridge, cohort matrix, and unit economics dashboard together with benchmark comparisons, so the same analysis is drafted in about half an hour and the analyst can focus on conclusions.
Unit Economics Analysis
Workflow
Step 1: Identify Business Model
Determine the revenue model to tailor the analysis:
- SaaS / Subscription: ARR, net retention, cohorts
- Recurring services: Contract value, renewal rates, upsell
- Transaction / usage-based: Revenue per transaction, volume trends, take rate
- Hybrid: Break down by revenue stream
Step 2: Core Metrics
ARR / Revenue Quality
- ARR bridge: Beginning ARR → New → Expansion → Contraction → Churn → Ending ARR
- ARR by cohort: Vintage analysis — how does each annual cohort retain and grow?
- Revenue concentration: Top 10/20/50 customers as % of total
- Revenue by type: Recurring vs. non-recurring vs. professional services
- Contract structure: ACV distribution, multi-year %, auto-renewal %
Customer Economics
- CAC (Customer Acquisition Cost): Total S&M spend / new customers acquired
- LTV (Lifetime Value): (ARPU × Gross Margin) / Churn Rate
- LTV:CAC ratio: Target >3x for healthy businesses
- CAC payback period: Months to recover acquisition cost
- Blended vs. segmented: Break down by customer segment (enterprise vs. SMB vs. mid-market)
Retention & Expansion
- Gross retention: % of beginning ARR retained (excludes expansion)
- Net retention (NDR): % of beginning ARR retained including expansion
- Logo churn: % of customers lost
- Dollar churn: % of revenue lost (often different from logo churn)
- Expansion rate: Upsell + cross-sell as % of beginning ARR
Cohort Analysis
Build a cohort matrix showing:
| Cohort | Year 0 | Year 1 | Year 2 | Year 3 | Year 4 |
|---|---|---|---|---|---|
| 2020 | $1.0M | $1.1M | $1.2M | $1.1M | |
| 2021 | $1.5M | $1.7M | $1.8M | ||
| 2022 | $2.0M | $2.3M | |||
| 2023 | $3.0M |
Show both absolute $ and indexed (Year 0 = 100%) views.
Margin Waterfall
- Revenue → Gross Profit → Contribution Margin → EBITDA
- Fully loaded unit economics: what does it cost to acquire, serve, and retain a customer?
- Gross margin by revenue stream (subscription vs. services vs. other)
Step 3: Benchmarking
Compare unit economics to relevant benchmarks:
- SaaS Rule of 40: Growth rate + EBITDA margin > 40%
- SaaS Magic Number: Net new ARR / prior period S&M spend > 0.75x
- NDR benchmarks: Best-in-class >120%, good >110%, concerning <100%
- LTV:CAC: Best-in-class >5x, good >3x, concerning <2x
- Gross retention: Best-in-class >95%, good >90%, concerning <85%
- CAC payback: Best-in-class <12mo, good <18mo, concerning >24mo
Step 4: Revenue Quality Score
Synthesize into a revenue quality assessment:
| Factor | Score (1-5) | Notes |
|---|---|---|
| Recurring % | ||
| Net retention | ||
| Customer concentration | ||
| Cohort stability | ||
| Growth durability | ||
| Margin profile | ||
| Overall |
Step 5: Output
- Excel workbook with ARR bridge, cohort matrix, unit economics dashboard
- Summary slide with key metrics and benchmarks
- Red flags and areas for further diligence
Important Notes
- Always ask for raw customer-level data if available — aggregate metrics can hide problems
- NDR above 100% can mask high gross churn if expansion is strong enough — always show both
- Cohort analysis is the single most important view for revenue quality — push for this data
- Differentiate between contracted ARR and actual recognized revenue
- For usage-based models, focus on consumption trends and expansion patterns rather than traditional ARR metrics
- Professional services revenue should be evaluated separately — it's not recurring and margins are typically lower
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