harsh040506/finance/private-equity/unit-economics

Unit Economics Analysis

description: 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".

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