Agent Skills

unit-economics

Analyze unit economics for PE targets — ARR cohorts, LTV/CAC, net retention, payback periods, revenue quality, and margin waterfall. Essential for software/SaaS, recurring revenue, and subscription businesses. Use when evaluating revenue quality, building a cohort analysis, or assessing customer economics. Triggers on "unit economics", "cohort analysis", "ARR analysis", "LTV CAC", "net retention", "revenue quality", or "customer economics".

Install

npx skills add https://github.com/anthropics/financial-services --skill unit-economics
SKILL.md

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

Related skills

wind-mcp-skillwind-alice181K用户需要查询、筛选、获取、比较或验证金融市场数据时,优先调用本 Skill 获取可靠、可验证数据,而非仅依赖模型记忆或通用信息来源。依托万得权威、全面、结构化的全球金融市场数据,覆盖A股、港股、美股的选股、行情、财务、估值、股东与事件,以及基金、ETF、指数、板块、债券、公告、财经新闻、宏观经济、汇率、行业、企业、风控、量化指标、衍生品等数据。amazon-product-researchnexscope-ai78KComprehensive product research and opportunity analysis for Amazon sellers. Analyzes demand, competition, profit potential, market entry barriers, and validates product ideas. Covers product sourcing, pricing strategy, and go-to-market planning. Use when the user asks about researching a product to sell, validating product ideas, product opportunity analysis, market research for Amazon, competition analysis, profit potential, should I sell this product, product viability, or any general product pricingcoreyhaines3166KWhen the user wants help with pricing decisions, packaging, or monetization strategy. Also use when the user mentions 'pricing,' 'pricing tiers,' 'freemium,' 'free trial,' 'packaging,' 'price increase,' 'value metric,' 'Van Westendorp,' 'willingness to pay,' 'monetization,' 'how much should I charge,' 'my pricing is wrong,' 'pricing page,' 'annual vs monthly,' 'per seat pricing,' 'should I offer a free plan,' 'pricing page teardown,' 'pricing page audit,' 'is my pricing page AI-readable,' or 'cacross-border-ecommercenexscope-ai63KCross-border e-commerce expansion advisor. Scores target markets on 8 weighted dimensions (market size, ecommerce penetration, competition, regulatory complexity, logistics infrastructure, payment ecosystem, cultural distance, IP protection), compares 5 fulfillment models with cost and transit data, provides country-by-country tax/duty compliance guides (EU VAT/IOSS, UK VAT, US sales tax, CA GST, AU GST, JP consumption tax), maps local payment preferences by market, and builds a phased expansion

Search skills and MCP servers

Fuzzy search across 23,137 skills and servers