Skip to content
Agentmart
Submit a tool

saas-metrics

Use this skill when calculating, analyzing, or reporting SaaS business metrics.

Skill by mkurman

IndexedMIT★ 325
Write a review

Chalk Labs

Need help deploying saas-metrics?

Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.

Book a call

Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/mkurman-saas-metrics

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

Get the weekly diff

The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.

We use your email only for this newsletter. Privacy

About

Use this skill when calculating, analyzing, or reporting SaaS business metrics. Triggers on MRR, ARR, churn rate, LTV, CAC, LTV:CAC ratio, cohort analysis, net revenue retention, expansion revenue, board deck metrics, investor reporting, unit economics, payback period, or SaaS financial modeling. Covers metric definitions, formulas, spreadsheet implementation, cohort tables, and board-ready reporting for founders, finance teams, and growth operators.

Use cases: spreadsheets, presentations, marketing, finance

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/saas-metrics

What's inside

Skill name
saas-metrics
Description
Use this skill when calculating, analyzing, or reporting SaaS business metrics. Triggers on MRR, ARR, churn rate, LTV, CAC, LTV:CAC ratio, cohort analysis, net revenue retention, expansion revenue, board deck metrics, investor reporting, unit economics, payback period, or SaaS financial modeling. Covers metric definitions, formulas, spreadsheet implementation, cohort tables, and board-ready reporting for founders, finance teams, and growth operators.
License
MIT
Instructions
298 lines in SKILL.md · view on GitHub

Files (6)

  • README.md
  • SKILL.md
  • evals.json
  • board-reporting.md · references/
  • cohort-analysis.md · references/
  • metric-formulas.md · references/

SKILL.md (first lines)

## Key principles

1. **MRR is the atomic unit** - Every SaaS metric derives from Monthly Recurring
   Revenue. Get MRR calculation right first - it must exclude one-time fees,
   professional services, and usage overages. All other metrics (ARR, churn,
   LTV, NRR) build on top of a clean MRR number.

2. **Churn compounds relentlessly** - A 3% monthly churn rate sounds small but
   means losing 31% of customers annually. Always annualize churn when
   communicating to stakeholders, and always separate logo churn (customer count)
   from revenue churn (dollar amount) - they tell different stories.

3. **Cohort over aggregate** - Aggregate metrics hide trends. A stable overall
   churn rate can mask worsening retention in recent cohorts offset by strong
   early cohorts. Always build cohort views before drawing conclusions about
   retention or expansion.

4. **Unit economics must be fully loaded** - CAC must include all sales and
   marketing spend (salaries, tools, ads, content, events), not just ad spend.
   LTV must use gross margin, not revenue. Partial calculations give false
   confidence.

5. **Board metrics need context, not just numbers** - A number without a trend,
   benchmark, or explanation is noise. Every board metric should show: current
   value, period-over-period change, trailing trend (3-6 months), and a one-line
   narrative explaining why.

---

## Core concepts

**MRR waterfall** is the movement model that explains how MRR changes month to
month. Starting MRR + New MRR + Expansion MRR - Contraction MRR - Churned MRR =
Ending MRR. This waterfall is the single most important operational view because
it isolates growth drivers from retention issues.

**Revenue retention** comes in two flavors. Gross Revenue Retention (GRR) measures
dollar retention excluding expansion - it can never exceed 100% and shows the
floor of your revenue base. Net Revenue Retention (NRR) includes expansion and
can exceed 100%, meaning existing customers grow faster than others leave. NRR
above 120% is considered elite for B2B SaaS.

**Unit economics** connect acquisition cost to customer value. CAC (Customer
Acquisition Cost) is total sales + marketing spend divided by new customers
acquired. LTV (Lifetime Value) is ARPA times gross margin divided by revenue
churn rate. The LTV:CAC ratio indicates efficiency - below 3:1 means
unprofitable acquisition, above 5:1 may signal underinvestment in growth. CAC
Payback Period (months to recover CAC from gross profit) is often more
actionable than LTV:CAC because it avoids long-horizon LTV assumptions.

**Cohort analysis** groups customers by their signup month (or quarter) and tracks
a metric (retention, revenue, usage) over time relative to their start date.
The cohort table has signup periods as rows, months-since-signup as columns, and
the tracked metric as cell values. Reading down a column shows whether newer
cohorts perform better or worse than older ones.

---

## Common tasks

### Calculate MRR and ARR

MRR = sum of all active subscriptions normalized to monthly amounts. Annual
contracts must be divided by 12. Exclude one-time charges, usage overages, and
professional services.

**Formula:**
```
MRR = SUM(monthly_subscription_values for all active customers)
ARR = MRR * 12
```

**MRR waterfall breakdown:**
```
New MRR         = MRR from customers acquired this month
Expansion MRR   = MRR increase from existing customers (upgrades, seat adds)
Contraction MRR = MRR decrease from existing customers (downgrades)
Churned MRR     = MRR lost from customers who cancelled
Net New MRR     = New + Expansion - Contraction - Churned
Ending MRR      = Starting MRR + Net New MRR
```

> Always reconcile: Starting MRR + Net New MRR must equal Ending MRR. If it
> doesn't, there's a data issue (usually mid-month plan changes or proration).

### Calculate churn rates

Separate logo churn (customers lost) from revenue churn (dollars lost).

**Logo churn rate:**
```
Monthly Logo Churn = Customers lost this month / Customers at start of month
Annual Logo Churn  = 1 - (1 - Monthly Logo Churn)^12
```

**Gross revenue churn rate:**
```
Monthly Revenue Churn = (Contraction MRR + Churned MRR) / Starting MRR
```

**Net revenue churn rate (can be negative if expansion exceeds churn):**
```
Net Revenue Churn = (Contraction + Churned - Expansion) / Starting MRR
```

> Never use ending-period denominators for churn. Use start-of-period or
> average-period customer/revenue counts. Ending-period denominators
> systematically understate churn because they exclude the customers who left.

### Calculate LTV and CAC

**Customer Acquisition Cost:**
```
CAC = Total Sales & Marketing Spend / New Customers Acquired
     (over the same period, typically monthly or quarterly)
```

Include in S&M spend: salaries, commissions, ad spend, content production,
tools, events, agency fees. Exclude product costs and general overhead.

From mkurman/zorai, MIT.

More from mkurman/zorai

Signals

Stars
325
Forks
24
Open issues
0
Last commit (this folder)
May 5, 2026 (5 months ago)
Last release
Oct 23, 2026 (7 days ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
Website
zorai.app/
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from mkurman

Done for you

Rather not set it up yourself?

Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.

See how we build AI agents →Read the case studies

Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.

launches shipped
50+
launches shipped
media placements
500+
media placements
founders on every account
2
founders on every account

Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block

Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.

Get saas-metrics running in your business

Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.

Goes to the Chalk Labs founders, not the newsletter. Privacy

Need help deploying saas-metrics?

CallGet help
Cite this page

saas-metrics skill. Agent Mart. https://agentmart.dev/skills/mkurman-saas-metrics (last updated 2026-10-24)