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Unit Economics

AnthropicOfficialPublished by Anthropic

  • Skill
  • Research and analysis
  • Business and productivity
  • Apache-2.0
  • No issues found

From the author

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".
— the description by Anthropic

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured methodology for evaluating the financial health and revenue quality of SaaS and recurring revenue businesses. It guides users through the calculation of critical metrics such as LTV/CAC, net retention, and ARR cohorts, enabling a deep dive into customer economics. By synthesizing these metrics into a revenue quality score and benchmarking against industry standards, the skill helps identify growth durability, margin profiles, and potential red flags in a target company's financial performance.

What it does

  • Calculates core SaaS metrics including LTV/CAC, payback periods, and net retention.
  • Constructs cohort matrices to visualize customer retention and growth over time.
  • Performs an ARR bridge analysis to track revenue movement across periods.
  • Evaluates revenue quality through concentration analysis and margin waterfall assessments.
  • Benchmarks company performance against established SaaS metrics like the Rule of 40.
  • Synthesizes findings into a standardized revenue quality score for investment diligence.

When to use it

  • During private equity due diligence of a software or subscription-based target.
  • When assessing the sustainability and quality of a company's recurring revenue.
  • When building a cohort analysis to understand long-term customer value.
  • When evaluating the efficiency of customer acquisition and retention strategies.

Advantages

  • Provides a standardized, repeatable framework for complex financial analysis.
  • Helps uncover hidden issues often masked by aggregate financial metrics.
  • Facilitates objective benchmarking against industry-standard SaaS performance indicators.
  • Enables clear communication of financial health through structured reporting.

Usage examples

“Analyze the unit economics for our latest SaaS acquisition target.”
The agent will request the necessary financial data and proceed to calculate LTV/CAC, net retention, and cohort performance to assess the target's revenue quality.
“Build a cohort analysis for our 2020-2023 customer base.”
The agent will generate a cohort matrix showing retention and expansion trends for each annual group, indexed to their starting value.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/anthropics/unit-economics/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip unit-economics.zip -d .agents/skills

Documentation by Anthropic

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:

CohortYear 0Year 1Year 2Year 3Year 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:

FactorScore (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

Files

ATTRIBUTION.md

Attribution

This folder is an unmodified copy of the Agent Skill "unit-economics", distributed by AutoGineer (https://autogineer.com/agent-skills).

The skill's own files are unmodified copies. AutoGineer is not affiliated with or endorsed by the author or the publisher.

Files added by AutoGineer

  • ATTRIBUTION.md: this file, written by AutoGineer

  • LICENSE: copied from LICENSE

Requirements and compatibility

Written for: Claude Code, Claude apps

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

No issues found by our static scan· No issues found

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by
Anthropic
Publisher
Anthropic (Official)
Source
anthropics/financial-services · plugins/vertical-plugins/private-equity/skills/unit-economics · commit 6056506
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Anthropic or Anthropic.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download unit-economics.zip