Finance Metrics Quickref Agent Skill

Purpose

Quick reference for any SaaS finance metric without deep teaching. Use this when you need a fast formula lookup, benchmark check, or decision framework reminder. For detailed explanations, calculations, and examples, see the related deep-dive skills.

This is not a teaching tool—it's a cheat sheet optimized for speed. Scan, find, apply.

Input

Works best with: The metric you need — name it and get the formula, benchmark, and decision context.

Also useful: Your numbers, if you want the formula applied on the spot.

Anything supplied with the invocation itself — text after the skill name, a pasted context dump, or an appended ARGUMENTS: line — counts as answers already given. Use it and skip whatever it covers; don't re-ask.

Arriving empty-handed? That works too. Ask for the metric family you're working in (revenue, retention, efficiency, capital) and scan from there.

Example invocation: Quick ref: burn multiple — formula, benchmark, and whether 1.7 is bad for Series B.

Key Concepts

Metric Categories

Metrics are organized into four families:

• Revenue & Growth — Top-line money (revenue, ARPU, ARPA, MRR/ARR, churn, NRR, expansion)
• Unit Economics — Customer-level profitability (CAC, LTV, payback, margins)
• Capital Efficiency — Cash management (burn rate, runway, OpEx, net income)
• Efficiency Ratios — Growth vs. profitability balance (Rule of 40, magic number)

When to Use This Skill

Use this when:

• You need a quick formula or benchmark
• You're preparing for a board meeting or investor call
• You're evaluating a decision and need to check which metrics matter
• You want to identify red flags quickly

Don't use this when:

• You need detailed calculation guidance (use saas-revenue-growth-metrics or saas-economics-efficiency-metrics)
• You're learning these metrics for the first time (start with deep-dive skills)
• You need examples and common pitfalls (covered in related skills)

Application

All Metrics Reference Table

| Metric | Formula | What It Measures | Good Benchmark | Red Flag |

|------------|-------------|----------------------|-------------------|--------------|

| Revenue | Total sales before expenses | Top-line money earned | Growth rate >20% YoY (varies by stage) | Revenue growing slower than costs |

| ARPU | Total Revenue / Total Users | Revenue per individual user | Varies by model; track trend | ARPU declining cohort-over-cohort |

| ARPA | MRR / Active Accounts | Revenue per customer account | SMB: $100-$1K; Mid: $1K-$10K; Ent: $10K+ | High ARPA + low ARPU (undermonetized seats) |

| ACV | Annual Recurring Revenue per Contract | Annualized contract value | SMB: $5K-$25K; Mid: $25K-$100K; Ent: $100K+ | ACV declining (moving downmarket unintentionally) |

| MRR/ARR | MRR × 12 = ARR | Predictable recurring revenue | Growth + quality matter; track components | New MRR declining while churn stable/growing |

| Churn Rate | Customers Lost / Starting Customers | % of customers who cancel | Monthly <2% great, <5% ok; Annual <10% great | Churn increasing cohort-over-cohort |

| NRR | (Start ARR + Expansion - Churn - Contraction) / Start ARR × 100 | Revenue retention + expansion | >120% excellent; 100-120% good; 90-100% ok | NRR <100% (base is contracting) |

| Expansion Revenue | Upsells + Cross-sells + Usage Growth | Additional revenue from existing customers | 20-30% of total revenue | Expansion <10% of MRR |

| Quick Ratio | (New MRR + Expansion MRR) / (Churned MRR + Contraction) | Revenue gains vs. losses | >4 excellent; 2-4 healthy; <2 leaky bucket | Quick Ratio <2 (leaky bucket) |

| Gross Margin | (Revenue - COGS) / Revenue × 100 | % of revenue after direct costs | SaaS: 70-85% good; <60% concerning | Gross margin <60% or declining |

| CAC | Total S&M Spend / New Customers | Cost to acquire one customer | Varies: Ent $10K+ ok; SMB <$500 | CAC increasing while LTV flat |

| LTV | ARPU × Gross Margin % / Churn Rate | Total revenue from one customer | Must be 3x+ CAC; varies by segment | LTV declining cohort-over-cohort |

| LTV:CAC | LTV / CAC | Unit economics efficiency | 3:1 healthy; <1:1 unsustainable; >5:1 underinvesting | LTV:CAC <1.5:1 |

| Payback Period | CAC / (Monthly ARPU × Gross Margin %) | Months to recover CAC | <12 months great; 12-18 ok; >24 concerning | Payback >24 months (cash trap) |

| Contribution Margin | (Revenue - All Variable Costs) / Revenue × 100 | True contribution after variable costs | 60-80% good for SaaS; <40% concerning | Contribution margin <40% |

| Burn Rate | Monthly Cash Spent - Revenue | Cash consumed per month | Net burn <$200K manageable early; <$500K growth | Net burn accelerating |

| Runway | Cash Balance / Monthly Net Burn | Months until money runs out | 12+ months good; 6-12 ok; <6 crisis | Runway <6 months |

| OpEx | S&M + R&D + G&A | Costs to run the business | Should grow slower than revenue | OpEx growing faster than revenue |

| Net Income | Revenue - All Expenses | Actual profit/loss | Early negative ok; mature 10-20%+ margin | Losses accelerating without growth |

| Rule of 40 | Revenue Growth % + Profit Margin % | Balance of growth vs. efficiency | >40 healthy; 25-40 ok; <25 concerning | Rule of 40 <25 |

| Magic Number | (Q Revenue - Prev Q Revenue) × 4 / Prev Q S&M | S&M efficiency | >0.75 efficient; 0.5-0.75 ok; <0.5 fix GTM | Magic Number <0.5 |

| Operating Leverage | Revenue Growth vs. OpEx Growth | Scaling efficiency | Revenue growth > OpEx growth | OpEx growing faster than revenue |

| Gross vs. Net Revenue | Net = Gross - Discounts - Refunds - Credits | What you actually keep | Refunds <10%; discounts <20% | Refunds >10% (product problem) |

| Revenue Concentration | Top N Customers / Total Revenue | Dependency on largest customers | Top customer <10%; Top 10 <40% | Top customer >25% (existential risk) |

| Revenue Mix | Product/Segment Revenue / Total Revenue | Portfolio composition | No single product >60% ideal | Single product >80% (no diversification) |

| Cohort Analysis | Group customers by join date; track behavior | Whether business improving or degrading | Recent cohorts same/better than old | Newer cohorts perform worse |

| CAC Payback by Channel | CAC / Monthly Contribution (by channel) | Payback by acquisition channel | Compare across channels | One channel far worse than others |

| Gross Margin Payback | CAC / (Monthly ARPU × Gross Margin %) | Payback using actual profit | Typically 1.5-2x simple payback | Payback using margin >36 months |

| Unit Economics | Revenue per unit - Cost per unit | Profitability of each "unit" | Positive contribution required | Negative contribution margin |

| Segment Payback | CAC / Monthly Contribution (by segment) | Payback by customer segment | Compare to allocate resources | One segment unprofitable |

| Incrementality | Revenue caused by action - Baseline | True impact of marketing/promo | Measure with holdout tests | Celebrating revenue that would've happened anyway |

| Working Capital | Cash timing between revenue and collection | Cash vs. revenue timing | Annual upfront > monthly billing | Long payment terms killing runway |

Quick Decision Frameworks

Use these frameworks to combine metrics for common PM decisions.

Framework 1: Should We Build This Feature?

Ask:

• Revenue impact? Direct (pricing, add-on) or indirect (retention, conversion)?
• Margin impact? What's the COGS? Does it dilute margins?
• ROI? Revenue impact / Development cost

Build if:

• ROI >3x in year one (direct monetization), OR
• LTV impact >10x development cost (retention), OR
• Strategic value overrides short-term ROI

Don't build if:

• Negative contribution margin even with optimistic adoption
• Payback period exceeds average customer lifetime

Metrics to check: Revenue, Gross Margin, LTV, Contribution Margin

Framework 2: Should We Scale This Acquisition Channel?

Ask:

• Unit economics? CAC, LTV, LTV:CAC ratio
• Cash efficiency? Payback period
• Customer quality? Cohort retention, NRR by channel
• Scalability? Magic Number, addressable volume

Scale if:

• LTV:CAC >3:1 AND
• Payback <18 months AND
• Customer quality meets/beats other channels AND
• Magic Number >0.75

Don't scale if:

• LTV:CAC <1.5:1 AND
• No clear path to improvement

Metrics to check: CAC, LTV, LTV:CAC, Payback Period, NRR, Magic Number

Framework 3: Should We Change Pricing?

Ask:

• ARPU/ARPA impact? Will revenue per customer increase?
• Conversion impact? Help or hurt trial-to-paid conversion?
• Churn impact? Create churn risk or reduce it?
• NRR impact? Enable expansion or create contraction?

Implement if:

• Net revenue impact positive after churn risk
• Can test with segment before broad rollout

Don't change if:

• High churn risk without offsetting expansion
• Can't test hypothesis before committing

Metrics to check: ARPU, ARPA, Churn Rate, NRR, CAC Payback

Framework 4: Is the Business Healthy?

Check by stage:

Early Stage (Pre-$10M ARR):

• Growth Rate >50% YoY
• LTV:CAC >3:1
• Gross Margin >70%
• Runway >12 months

Growth Stage ($10M-$50M ARR):

• Growth Rate >40% YoY
• NRR >100%
• Rule of 40 >40
• Magic Number >0.75

Scale Stage ($50M+ ARR):

• Growth Rate >25% YoY
• NRR >110%
• Rule of 40 >40
• Profit Margin >10%

Metrics to check: Revenue Growth, NRR, LTV:CAC, Rule of 40, Magic Number, Gross Margin

Red Flags by Category

Revenue & Growth Red Flags

| Red Flag | What It Means | Action |

|--------------|-------------------|------------|

| Churn increasing cohort-over-cohort | Product-market fit degrading | Stop scaling acquisition; fix retention first |

| NRR <100% | Base is contracting | Fix expansion or reduce churn before scaling |

| Revenue churn > logo churn | Losing big customers | Investigate why high-value customers leave |

| Quick Ratio <2 | Leaky bucket (barely outpacing losses) | Fix retention before scaling acquisition |

| Expansion revenue <10% of MRR | No upsell/cross-sell engine | Build expansion paths |

| Revenue concentration >50% in top 10 customers | Existential dependency risk | Diversify customer base |

Unit Economics Red Flags

| Red Flag | What It Means | Action |

|--------------|-------------------|------------|

| LTV:CAC <1.5:1 | Buying revenue at a loss | Reduce CAC or increase LTV before scaling |

| Payback >24 months | Cash trap (long cash recovery) | Negotiate annual upfront or reduce CAC |

| Gross margin <60% | Low profitability per dollar | Increase prices or reduce COGS |

| CAC increasing while LTV flat | Unit economics degrading | Optimize conversion or reduce sales cycle |

| Contribution margin <40% | Unprofitable after variable costs | Cut variable costs or increase prices |

Capital Efficiency Red Flags

| Red Flag | What It Means | Action |

|--------------|-------------------|------------|

| Runway <6 months | Survival crisis | Raise capital immediately or cut burn |

| Net burn accelerating without revenue growth | Burning faster without results | Cut costs or increase revenue urgency |

| OpEx growing faster than revenue | Negative operating leverage | Freeze hiring; optimize spend |

| Rule of 40 <25 | Burning cash without growth | Improve growth or cut to profitability |

| Magic Number <0.5 | S&M engine broken | Fix GTM efficiency before scaling spend |

When to Use Which Metric

Prioritizing features:

• Revenue impact → Revenue, ARPU, Expansion Revenue
• Margin impact → Gross Margin, Contribution Margin
• ROI → LTV impact, Development cost

Evaluating channels:

• Acquisition cost → CAC, CAC by Channel
• Customer value → LTV, NRR by Channel
• Payback → Payback Period, CAC Payback by Channel
• Scalability → Magic Number

Pricing decisions:

• Monetization → ARPU, ARPA, ACV
• Impact → Churn Rate, NRR, Expansion Revenue
• Efficiency → CAC Payback (will pricing change affect it?)

Business health:

• Growth → Revenue Growth, MRR/ARR Growth
• Retention → Churn Rate, NRR, Quick Ratio
• Economics → LTV:CAC, Payback Period, Gross Margin
• Efficiency → Rule of 40, Magic Number, Operating Leverage
• Survival → Burn Rate, Runway

Board/investor reporting:

• Key metrics: ARR, Revenue Growth %, NRR, LTV:CAC, Rule of 40, Magic Number, Burn Rate, Runway
• Stage-specific: Early stage emphasize growth + unit economics; Growth stage emphasize Rule of 40 + Magic Number; Scale stage emphasize profitability + efficiency

Examples

Example 1: Feature Investment Sanity Check

You are deciding whether to build a premium export feature.

• Use Framework 1 (Should We Build This Feature?)
• Pull baseline metrics: ARPU, Gross Margin, LTV, Contribution Margin
• Model optimistic, base, and downside adoption
• Reject if contribution margin turns negative in downside case

Quick output:

• Base case ROI: 3.8x
• Contribution margin impact: +4 points
• Decision: Build now, with a 90-day post-launch check on churn and expansion

Example 2: Channel Scale Decision

Paid social is generating many signups but weak retention.

• Use Framework 2 (Should We Scale This Acquisition Channel?)
• Check CAC, LTV:CAC, Payback Period, and NRR by channel
• Compare against best-performing channel, not company average

Quick output:

• LTV:CAC: 1.6:1
• Payback: 26 months
• NRR: 88%
• Decision: Do not scale; cap spend and run targeted optimization tests

Common Pitfalls

• Using blended company averages instead of cohort or channel-level metrics
• Scaling acquisition when Quick Ratio is weak and retention is deteriorating
• Treating high LTV:CAC as sufficient without checking payback and runway impact
• Raising prices based on ARPU lift alone without modeling churn and contraction
• Comparing benchmarks across mismatched company stages or business models
• Tracking many metrics without a clear decision question

References

Related Skills (Deep Dives)

• saas-revenue-growth-metrics — Detailed guidance on revenue, retention, and growth metrics (13 metrics)
• saas-economics-efficiency-metrics — Detailed guidance on unit economics and capital efficiency (17 metrics)
• feature-investment-advisor — Uses these metrics to evaluate feature ROI
• acquisition-channel-advisor — Uses these metrics to evaluate channel viability
• finance-based-pricing-advisor — Uses these metrics to evaluate pricing changes
• business-health-diagnostic — Uses these metrics to diagnose business health

External Resources

• Bessemer Venture Partners: "SaaS Metrics 2.0" — Comprehensive SaaS benchmarking
• David Skok (Matrix Partners): "SaaS Metrics" blog series — Deep dive on unit economics
• Tomasz Tunguz (Redpoint): SaaS benchmarking research and blog
• ChartMogul, Baremetrics, ProfitWell: SaaS analytics platforms with metric definitions
• SaaStr: Annual SaaS benchmarking surveys

Provenance

• Adapted from research/finance/Finance_QuickRef.md
• Formulas from research/finance/Finance for Product Managers.md
• Decision frameworks from research/finance/Finance_For_PMs.Putting_It_Together_Synthesis.md