菜单
Master revenue and retention metrics to understand SaaS business momentum, evaluate product-market fit, and make data-driven decisions about growth investments. Use this to calculate key metrics, inte
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Full-stack software engineering via Claude Code CLI session with self-correction.
Review code for correctness, style, security vulnerabilities, and potential issues.
Guide product managers through evaluating whether to scale, test, or kill an acquisition channel based on unit economics (CAC, LTV, payback), customer quality (retention, NRR), and scalability (magic
Assess whether your product work is "AI-first" (using AI to automate existing tasks faster) or "AI-shaped" (fundamentally redesigning how product teams operate around AI capabilities). Use this to eva
Defines the two-axis mental model that distinguishes Director-level thinking from PM thinking: Altitude (how wide you zoom out) and Horizon (how far ahead you look). Use this to understand what actual
Diagnose overall SaaS business health by analyzing growth, retention, unit economics, and capital efficiency metrics together. Use this to identify problems early, prioritize actions by urgency, and d
| name | Saas Revenue Growth Metrics |
| description | Master revenue and retention metrics to understand SaaS business momentum, evaluate product-market fit, and make data-driven decisions about growth investments. Use this to calculate key metrics, inte |
Type: component | Theme: finance-metrics | Time: 10-15 min
Master revenue and retention metrics to understand SaaS business momentum, evaluate product-market fit, and make data-driven decisions about growth investments. Use this to calculate key metrics, interpret trends, identify problems early, and communicate business health to stakeholders.
This is not a business intelligence tool—it's a framework for PMs to understand which metrics matter, how to calculate them correctly, and what actions to take based on the numbers.
The "top-line" metrics that measure how much money the business generates.
Revenue — Total money earned from selling products/services before expenses. The "top line" of the income statement.
ARPU (Average Revenue Per User) — Average revenue generated per individual user.
Total Revenue / Total UsersARPA (Average Revenue Per Account) — Average revenue generated per customer account.
MRR / Active AccountsARPA/ARPU Analysis — Using both metrics together to understand monetization.
ACV (Annual Contract Value) — Annualized recurring revenue per contract (excludes one-time fees).
Annual Recurring Revenue per Contract (don't include setup fees, professional services)MRR/ARR (Monthly/Annual Recurring Revenue) — Predictable recurring revenue normalized to monthly or annual.
MRR = Sum of all recurring subscription revenue per month; ARR = MRR × 12Gross vs. Net Revenue — Gross revenue before vs. net revenue after discounts, refunds, credits.
Net Revenue = Gross Revenue - Discounts - Refunds - CreditsMetrics that measure how well you keep and grow existing customers.
Churn Rate — Percentage of customers who cancel in a period.
Customers Lost in Period / Starting CustomersNRR (Net Revenue Retention) — Revenue retention from existing customers including expansion and contraction.
(Starting ARR + Expansion - Churn - Contraction) / Starting ARR × 100Expansion Revenue — Additional revenue from existing customers (upsells, cross-sells, usage growth).
Sum of upsells + cross-sells + usage increases from existing customersQuick Ratio (SaaS) — Revenue gains vs. revenue losses.
(New MRR + Expansion MRR) / (Churned MRR + Contraction MRR)Revenue Mix Analysis — Breakdown of revenue by product, segment, or channel.
Product/Segment Revenue / Total Revenue × 100Cohort Analysis — Group customers by join date and track behavior over time.
Use these when:
Don't use these when:
Use the templates in template.md to calculate your core revenue metrics.
Revenue = Sum of all customer payments in period
Example:
Quality checks:
ARPU = Total Revenue / Total Users
Example:
Quality checks:
ARPA = MRR / Active Accounts
Example:
Quality checks:
ARPA = MRR / Active Accounts
ARPU = MRR / Total Users
Average Seats per Account = ARPA / ARPU
Example:
Quality checks:
ACV = Annual Recurring Revenue per Contract
(Exclude one-time fees like setup, professional services)
Example:
Quality checks:
MRR = Sum of all recurring monthly subscriptions
ARR = MRR × 12
Track components:
- New MRR (from new customers)
- Expansion MRR (from upsells/cross-sells)
- Churned MRR (from lost customers)
- Contraction MRR (from downgrades)
Example:
Quality checks:
Net Revenue = Gross Revenue - Discounts - Refunds - Credits
Example:
Quality checks:
Logo Churn Rate = Customers Lost / Starting Customers × 100
Revenue Churn Rate = MRR Lost / Starting MRR × 100
Example (Logo Churn):
Example (Revenue Churn):
Quality checks:
Convert monthly to annual:
Annual Churn = 1 - (1 - Monthly Churn)^12NRR = (Starting ARR + Expansion - Churn - Contraction) / Starting ARR × 100
Example:
Quality checks:
Expansion Revenue = Upsells + Cross-sells + Usage Growth (from existing customers)
Example:
Quality checks:
Quick Ratio = (New MRR + Expansion MRR) / (Churned MRR + Contraction MRR)
Example:
Quality checks:
Product/Segment % = Product/Segment Revenue / Total Revenue × 100
Example:
Quality checks:
Group customers by when they joined and track metrics over time.
Example:
| Cohort | Month 0 | Month 1 | Month 2 | Month 3 | Month 6 |
|---|---|---|---|---|---|
| Jan 2024 | 100% | 95% | 92% | 90% | 85% |
| Feb 2024 | 100% | 94% | 90% | 87% | 80% |
| Mar 2024 | 100% | 92% | 86% | 82% | - |
Quality checks:
Before reporting metrics, validate:
Revenue metrics:
Retention metrics:
Analysis:
See examples/ folder for detailed scenarios. Mini examples below:
Company: Mid-market project management SaaS
Revenue Metrics:
Retention Metrics:
Analysis:
Action: Scale acquisition. Unit economics are strong.
Company: SMB marketing automation SaaS
Revenue Metrics:
Retention Metrics:
Cohort Analysis:
| Cohort | Month 6 Retention |
|---|---|
| 6 months ago | 75% |
| 3 months ago | 65% |
| Current | 58% |
Analysis:
Action: STOP scaling acquisition. Fix retention first. Investigate:
Company: Multi-product SaaS platform
Blended Metrics Look Great:
But Revenue Mix Analysis Shows:
| Product | Revenue | % of Total | Growth | Churn | NRR |
|---|---|---|---|---|---|
| Legacy Product | $2M | 67% | -5% MoM | 8% | 75% |
| New Product | $1M | 33% | +80% MoM | 1% | 150% |
Analysis:
Action: Accelerate migration from legacy to new product. Plan for legacy product sunset.
Symptom: "We grew revenue 50% this year, we're crushing it!"
Consequence: Revenue is the top line, not bottom line. You might be growing at a loss, destroying margins, or scaling unprofitable products.
Fix: Always pair revenue metrics with margin metrics (see saas-economics-efficiency-metrics). $1M revenue at 80% margin >> $2M revenue at 20% margin.
Symptom: "ARPU increased 30%!" (but customer count dropped 40%)
Consequence: ARPU rose because you lost all your small customers, not because you improved monetization.
Fix: Analyze ARPU by cohort and segment. True ARPU improvement = same customers paying more, not losing cheap customers.
Symptom: "Blended churn is stable at 3%"
Consequence: Blended metrics can hide that new cohorts churn at 6% while old cohorts churn at 1%. Product-market fit is degrading.
Fix: Always analyze retention by cohort. If newer cohorts perform worse, stop scaling and fix the product.
Symptom: "Logo churn is only 2%, we're great!"
Consequence: You might be losing 2% of customers but 10% of revenue if you're churning large customers.
Fix: Track both logo churn AND revenue churn. If revenue churn > logo churn, you're losing high-value customers.
Symptom: "We lost 50 customers this month" (no context on who)
Consequence: Losing 50 small customers ($10/month) is different from losing 50 enterprise customers ($10K/month).
Fix: Segment churn analysis by customer size, cohort, and reason. Weight by revenue impact, not just logo count.
Symptom: "3% monthly churn is fine, that's only 36% annually"
Consequence: Churn compounds. 3% monthly = 31% annual churn, not 36%. Math: 1 - (1 - 0.03)^12 = 31%.
Fix: Use the correct formula when converting monthly to annual churn. Don't just multiply by 12.
Symptom: "Gross revenue is up 20%!" (but discounts/refunds doubled)
Consequence: Net revenue might be flat or shrinking. Discounts hide pricing power problems; refunds hide product quality issues.
Fix: Always track gross AND net revenue. If discounts >20% or refunds >10%, investigate why.
Symptom: "NRR is 105%, we're expanding!"
Consequence: NRR can be >100% just from very low churn, without meaningful expansion. True expansion-driven NRR is >120%.
Fix: Break down NRR into components: expansion MRR vs. churned/contracted MRR. Aim for expansion-driven NRR, not just low churn.
Symptom: "We're at $10M ARR!" (but $5M is from one customer)
Consequence: Losing that one customer cuts revenue in half. Roadmap becomes hostage to one customer's requests.
Fix: Track revenue concentration. Ideal: Top customer <10% of revenue, Top 10 customers <40%. Diversify early.
Symptom: "Our ARPU is $100" (average of $10 SMB and $1,000 enterprise)
Consequence: Blended ARPU hides segment economics. Can't make smart acquisition or product decisions.
Fix: Calculate ARPU/ARPA by segment (SMB, mid-market, enterprise). Optimize each segment independently.
saas-economics-efficiency-metrics — Unit economics (CAC, LTV, margins, burn rate)finance-metrics-quickref — Fast lookup for all metricsfeature-investment-advisor — Uses revenue metrics to evaluate feature ROIfinance-based-pricing-advisor — Uses ARPU/ARPA to evaluate pricing changesbusiness-health-diagnostic — Uses revenue/retention metrics to diagnose business healthresearch/finance/Finance for Product Managers.mdresearch/finance/Finance_QuickRef.mdresearch/finance/Finance_Metrics_Additions_Reference.md