14 KiB
Finance & Metrics
Compressed reference for SaaS finance: 32 metrics with formulas and benchmarks, diagnostic frameworks, and decision logic for feature investment, channel evaluation, and pricing changes.
SaaS Revenue & Growth Metrics
Core Revenue Metrics
| Metric | Formula | Benchmarks |
|---|---|---|
| Revenue | Sum of all customer payments in period | Growth rate >20% YoY (varies by stage) |
| ARPU | Total Revenue / Total Users | B2C: $5-50/mo; B2B: $50-500+/mo; track trend |
| ARPA | MRR / Active Accounts | SMB: $100-$1K/mo; Mid: $1K-$10K; Ent: $10K+ |
| ACV | Annual Recurring Revenue per Contract (exclude one-time fees) | SMB: $5K-$25K; Mid: $25K-$100K; Ent: $100K+ |
| MRR/ARR | MRR = sum of recurring subs; ARR = MRR x 12 | Track components: New + Expansion - Churned - Contraction |
| Gross vs Net Revenue | Net = Gross - Discounts - Refunds - Credits | Refunds >10% = product problem; Discounts >20% = pricing power problem |
ARPA/ARPU combined analysis: Average Seats per Account = ARPA / ARPU. High ARPA + low ARPU = undermonetized seats. Low ARPA + high ARPU = small deal sizes.
Retention & Expansion Metrics
| Metric | Formula | Benchmarks |
|---|---|---|
| Churn Rate (Logo) | Customers Lost / Starting Customers | Monthly: <2% great, 2-5% ok, >5% crisis |
| Churn Rate (Revenue) | MRR Lost / Starting MRR | Annual: <10% great, 10-30% ok, >30% crisis |
| NRR | (Start ARR + Expansion - Churn - Contraction) / Start ARR x 100 | >120% excellent; 100-120% good; <90% problem |
| Expansion Revenue | Upsells + Cross-sells + Usage Growth | Should be 20-30% of total revenue |
| Quick Ratio | (New MRR + Expansion MRR) / (Churned MRR + Contraction MRR) | >4 excellent; 2-4 healthy; <2 leaky bucket |
Churn compounding: 3% monthly != 36% annual. Use Annual Churn = 1 - (1 - Monthly)^12. 3% monthly = ~31% annual. 5% monthly = ~46% annual.
Analysis Frameworks
Revenue Mix: Product/Segment Revenue / Total Revenue x 100. No single product >60% ideal. Top customer <10% revenue; top 10 <40%.
Cohort Analysis: Group customers by join date, track retention/expansion over time. Recent cohorts should perform same or better than older ones. If newer cohorts degrade, PMF is eroding -- stop scaling, fix product.
Unit Economics & Efficiency
Customer-Level Profitability
| Metric | Formula | Benchmarks |
|---|---|---|
| Gross Margin | (Revenue - COGS) / Revenue x 100 | SaaS: 70-85% good; <60% concerning |
| CAC | Total S&M Spend / New Customers Acquired | Enterprise: $10K+ ok; SMB: <$500 target |
| LTV (simple) | ARPU x Avg Customer Lifetime (months) | Must be 3x+ CAC |
| LTV (better) | ARPU x Gross Margin % / Monthly Churn Rate | Use this for decisions |
| LTV:CAC | LTV / CAC | <1:1 unsustainable; 1-3:1 marginal; 3-5:1 healthy; >5:1 underinvesting |
| Payback Period | CAC / (Monthly ARPU x Gross Margin %) | <12mo great; 12-18 ok; >24 concerning |
| Contribution Margin | (Revenue - All Variable Costs) / Revenue x 100 | 60-80% good; <40% concerning |
| Gross Margin Payback | CAC / (Monthly ARPU x Gross Margin %) | Same formula as Payback above; use this version |
COGS includes: Hosting, infrastructure, payment processing, customer onboarding costs. Variable costs include: COGS + support + payment processing + variable customer success.
Critical insight: 4:1 LTV:CAC with 36-month payback is a cash trap. 3:1 LTV:CAC with 8-month payback is better for growth.
Capital Efficiency
| Metric | Formula | Benchmarks |
|---|---|---|
| Burn Rate (Gross) | Total Monthly Cash Spent | Context-dependent |
| Burn Rate (Net) | Monthly Cash Spent - Monthly Revenue | Early <$200K manageable; >$500K needs revenue path |
| Runway | Cash Balance / Monthly Net Burn | 12+ good; 6-12 ok; <6 crisis. Raise at 6-9 months, not 3 |
| OpEx | S&M + R&D + G&A | Should grow slower than revenue |
| Net Income | Revenue - COGS - OpEx | Early negative ok; mature 10-20%+ margin |
Working capital: Annual contracts paid upfront boost cash. Monthly billing delays collection. Cash-based runway != revenue-based runway.
Efficiency Ratios
| Metric | Formula | Benchmarks |
|---|---|---|
| Rule of 40 | Revenue Growth % + Profit Margin % | >40 healthy; 25-40 ok; <25 concerning |
| Magic Number | (Q Revenue - Prev Q Revenue) x 4 / Prev Q S&M Spend | >0.75 scale; 0.5-0.75 optimize; <0.5 fix GTM |
| Operating Leverage | Revenue Growth Rate vs OpEx Growth Rate | Revenue growth must exceed OpEx growth |
Rule of 40 by stage: Early = 60% growth + (-20%) margin = 40. Growth = 40% + 5% = 45. Mature = 20% + 25% = 45.
Business Health Diagnostic
Four-Dimension Framework
- Growth & Retention -- Revenue growth, NRR, churn, Quick Ratio
- Unit Economics -- CAC, LTV, LTV:CAC, payback, gross margin
- Capital Efficiency -- Burn, runway, Rule of 40, Magic Number
- Strategic Position -- Market pricing, moat, concentration, leverage
Stage-Specific Benchmarks
| Metric | Early (<$10M ARR) | Growth ($10-50M) | Scale ($50M+) |
|---|---|---|---|
| Growth YoY | >50% | >40% | >25% |
| LTV:CAC | >3:1 | -- | -- |
| NRR | -- | >100% | >110% |
| Gross Margin | >70% | -- | -- |
| Rule of 40 | -- | >40 | >40 |
| Magic Number | -- | >0.75 | -- |
| Profit Margin | negative ok | -- | >10% |
| Runway | >12 months | -- | positive cash flow |
Red Flag Severity
Critical (fix immediately): Runway <6mo, LTV:CAC <1.5:1, churn accelerating cohort-over-cohort, NRR <90%, Magic Number <0.3.
High priority (fix within quarter): Rule of 40 <25, payback >24mo, Quick Ratio <2, gross margin <60%, revenue concentration >50% in top 10.
Medium priority (address within 6 months): NRR 90-100%, Magic Number 0.3-0.5, negative operating leverage, stable but high churn (>5% monthly).
Diagnostic Scoring
- Healthy: All dimensions at/above stage benchmarks, no critical flags, improving trends. Action: scale aggressively.
- Moderate: 1-2 dimensions need attention, medium-priority flags. Action: fix specific issues before scaling further.
- Concerning: Multiple critical flags, 2+ dimensions problematic. Action: urgent intervention -- stop scaling, fix retention and unit economics.
- Critical: Runway <3mo or LTV:CAC <1:1. Action: survival mode -- emergency fundraise or cut burn 50%+.
Feature Investment Analysis
Revenue Connection Types
- Direct monetization -- new tier, paid add-on, usage fee. Calculate: Customer Base x Adoption Rate x Price.
- Retention improvement -- addresses churn reason. Calculate: LTV Impact = Lifetime Increase x Base x ARPU x Margin.
- Conversion improvement -- trial-to-paid lift. Calculate: Trial Users x Conversion Lift x ARPU.
- Expansion enabler -- upsell/cross-sell path. Calculate: Base x Expansion Rate x ARPU Increase.
ROI Thresholds
| Scenario | Build if | Don't build if |
|---|---|---|
| Direct monetization | ROI >3x year one | Negative contribution margin in downside case |
| Retention feature | LTV impact >10x dev cost | Payback exceeds avg customer lifetime |
| Strategic override | Competitive moat, platform enabler, compliance | "Strategic" without clear definition |
Cost Structure Check
- One-time: development cost (team size x time)
- Ongoing: COGS impact (hosting, infra) + OpEx (support, maintenance)
- Margin impact: if COGS >20% of projected revenue, flag margin dilution
- Contribution margin: (Revenue - COGS) / Revenue must stay positive
Decision Patterns
Build now: ROI >3:1 (direct) or LTV impact >10:1 (retention), positive contribution margin, payback < customer lifetime.
Build for strategic reasons: ROI <2:1 but competitive moat, platform enabler, or compliance. Cap investment, monitor adoption, re-evaluate at 6 months.
Don't build: ROI <1:1, negative contribution margin, no strategic value. Consider reducing scope or changing monetization.
Build later: High uncertainty in adoption or impact assumptions. Validate with surveys, prototypes, churn interviews first.
Channel Economics
Channel Evaluation Framework
Evaluate each channel on four dimensions:
- Unit economics -- CAC, LTV, LTV:CAC, payback (per channel, not blended)
- Customer quality -- cohort retention, churn rate, NRR, ICP fit (per channel)
- Scalability -- Magic Number, addressable volume, CAC trend
- Strategic fit -- segment match, sales motion compatibility
Channel Decision Matrix
| LTV:CAC | Payback | Customer Quality | Scalability | Decision |
|---|---|---|---|---|
| >3:1 | <12mo | Good retention | High volume | Scale aggressively |
| 2-3:1 | 12-18mo | Average retention | Medium | Test & optimize |
| <2:1 | >18mo | Poor retention | Low | Kill or fix |
Scale Criteria
Scale when ALL met: LTV:CAC >3:1 AND payback <12mo AND Magic Number >0.75 AND customer quality >= blended. Increase budget 50-100%, monitor weekly for CAC increase >20% (saturation signal).
Optimize Playbook
- If CAC too high: Improve conversion rate, reduce cost-per-click, shorten sales cycle.
- If LTV too low: Improve onboarding for channel cohort, target higher-value segments, add expansion plays.
- If targeting off: Narrow audience, improve messaging, add qualification step.
- Timeline: 4-8 weeks. Target LTV:CAC >3:1, payback <12mo. If unachievable, kill.
Kill Criteria
LTV:CAC <1.5:1 with no clear improvement path. Reallocate budget to top-performing channel. Exception: strategic channels (enterprise field sales) get capped spend and 6-12 month runway to prove out.
Incrementality
Test with holdout groups. Only count truly incremental conversions. Retargeting campaigns often claim credit for conversions that would have happened organically.
Pricing Analysis
Pricing Change Types
- Price increase -- new customers only (grandfather existing) vs all customers
- New premium tier -- upsell path, watch cannibalization
- Paid add-on -- monetize feature; assess retention risk if previously free
- Usage-based -- charge per unit (seats, API calls, storage); enables expansion revenue
- Discount strategy -- annual prepay (cash flow), volume (larger deals), promotional (urgency)
- Packaging change -- rebundle features, change pricing metric
Five-Dimension Impact Assessment
- Revenue: ARPU lift = (New ARPU - Current ARPU) / Current ARPU. Expected MRR increase = Base x ARPU Lift.
- Conversion: Higher prices may reduce trial-to-paid. Model conversion drop and its effect on new customer volume.
- Churn: Model scenarios -- conservative (+2pp churn), base (+1pp), optimistic (+0). Churn-driven MRR loss = additional churn % x base x new ARPU.
- Expansion: Does change create upsell path? Usage-based pricing enables natural expansion as customers grow.
- CAC Payback: Higher ARPU = faster payback, but lower conversion = higher effective CAC. Calculate net effect.
Decision Patterns
Implement broadly: Net revenue clearly positive (>10% ARPU lift, <5% churn risk), minimal conversion impact. Grandfather existing customers.
Test first (A/B): Uncertain impact, moderate risk. Test 60-90 days with 100+ customers per cohort. Roll out if conversion stays within acceptable range.
Modify approach: Original proposal too risky. Options: smaller increase, grandfather existing, segment-based pricing (raise enterprise only).
Don't change: Churn-driven loss exceeds revenue gains, or high competitive pressure. Focus on retention/expansion instead.
Annual Discount Guardrails
Limit to 10-15% for annual prepay. 30% annual discounts destroy LTV. Balance cash flow improvement with revenue protection.
Quality Gates
Vanity Metric Traps
- Revenue without margin: $1M at 80% margin >> $2M at 20% margin
- ARPU growth from mix shift: ARPU rose because small customers churned, not because monetization improved
- Signups without conversion: 10,000 signups at 5% conversion = 500 customers. Calculate CAC on paid, not signups
- Engagement without revenue: Feature increases engagement but not retention or monetization -- not a business outcome
- Gross revenue hiding net contraction: Track discounts and refunds; gross up 20% but discounts doubled = flat net
Blended Metric Dangers
Never use blended averages for decisions. Always segment by:
- Channel: One channel at $10K CAC hides in $500 blended CAC
- Segment: $100 ARPU blends $10 SMB and $1,000 enterprise -- useless for decisions
- Cohort: Blended 3% churn hides newer cohorts at 6% and old cohorts at 1%
- Product: 67% legacy product dying at -5% growth masked by 33% new product at +80%
Common Calculation Errors
- LTV without margin: Use
ARPU x Margin % / Churn, notARPU x Lifetime - Churn multiply-by-12: Churn compounds. 3% monthly = 31% annual, not 36%
- Payback without margin: Use gross margin payback, not revenue payback
- CAC comparison without payback: $5K CAC with 24mo payback is worse than $8K CAC with 8mo payback
- Rule of 40 without runway: Score of 50 means nothing with 3 months runway
- LTV:CAC without payback: 6:1 ratio with 48-month payback is a cash trap
Decision-Making Anti-Patterns
- Scaling acquisition when Quick Ratio <2 (leaky bucket)
- Raising prices without modeling churn scenarios
- Celebrating NRR >100% from low churn alone (not expansion-driven)
- Using "strategic" as catch-all for building low-ROI features
- Fixing everything simultaneously instead of prioritizing top 1-3 issues
- Killing channels before 3-6 months and 100+ customers of data
- Over-relying on one channel (>50% of acquisition)
- Annual discounts >15% that destroy LTV for short-term cash
- Testing pricing on 10 customers (need 100+ per cohort for significance)
- Celebrating feature requests from 0.5% of base while ignoring the other 99.5%