Merge pull request #298 from abbasmir12/feat/finance-saas-metrics-coach

feat(finance): add saas-metrics-coach skill
2026-03-10 13:57:22 +01:00
parent a68ae3a05e 176afc5c46
commit e7fd0aa43d
8 changed files with 989 additions and 0 deletions
--- a/finance/CLAUDE.md
+++ b/finance/CLAUDE.md
@@ -100,3 +100,6 @@ python financial-analyst/scripts/forecast_builder.py forecast_data.json --format
 **Last Updated:** February 2026
 **Skills Deployed:** 1/1 finance skills production-ready
 **Total Tools:** 4 Python automation tools
+
+## saas-metrics-coach
+SaaS financial health advisor. Calculates ARR, MRR, churn, CAC, LTV, NRR, Quick Ratio. Benchmarks against industry standards. Includes 12-month projection simulator.
--- a/finance/saas-metrics-coach/SKILL.md
+++ b/finance/saas-metrics-coach/SKILL.md
@@ -0,0 +1,158 @@
+---
+name: saas-metrics-coach
+description: SaaS financial health advisor. Use when a user shares revenue or customer numbers, or mentions ARR, MRR, churn, LTV, CAC, NRR, or asks how their SaaS business is doing.
+license: MIT
+metadata:
+  version: 1.0.0
+  author: Abbas Mir
+  category: finance
+  updated: 2026-03-08
+---
+
+# SaaS Metrics Coach
+
+Act as a senior SaaS CFO advisor. Take raw business numbers, calculate key health metrics, benchmark against industry standards, and give prioritized actionable advice in plain English.
+
+## Step 1 — Collect Inputs
+
+If not already provided, ask for these in a single grouped request:
+
+- Revenue: current MRR, MRR last month, expansion MRR, churned MRR
+- Customers: total active, new this month, churned this month
+- Costs: sales and marketing spend, gross margin %
+
+Work with partial data. Be explicit about what is missing and what assumptions are being made.
+
+## Step 2 — Calculate Metrics
+
+Run `scripts/metrics_calculator.py` with the user's inputs. If the script is unavailable, use the formulas in `references/formulas.md`.
+
+Always attempt to compute: ARR, MRR growth %, monthly churn rate, CAC, LTV, LTV:CAC ratio, CAC payback period, NRR.
+
+**Additional Analysis Tools:**
+- Use `scripts/quick_ratio_calculator.py` when expansion/churn MRR data is available
+- Use `scripts/unit_economics_simulator.py` for forward-looking projections
+
+## Step 3 — Benchmark Each Metric
+
+Load `references/benchmarks.md`. For each metric show:
+- The calculated value
+- The relevant benchmark range for the user's segment and stage
+- A plain status label: HEALTHY / WATCH / CRITICAL
+
+Match the benchmark tier to the user's market segment (Enterprise / Mid-Market / SMB / PLG) and company stage (Early / Growth / Scale). Ask if unclear.
+
+## Step 4 — Prioritize and Recommend
+
+Identify the top 2-3 metrics at WATCH or CRITICAL status. For each one state:
+- What is happening (one sentence, plain English)
+- Why it matters to the business
+- Two or three specific actions to take this month
+
+Order by impact — address the most damaging problem first.
+
+## Step 5 — Output Format
+
+Always use this exact structure:
+
+```
+# SaaS Health Report — [Month Year]
+
+## Metrics at a Glance
+| Metric | Your Value | Benchmark | Status |
+|--------|------------|-----------|--------|
+
+## Overall Picture
+[2-3 sentences, plain English summary]
+
+## Priority Issues
+
+### 1. [Metric Name]
+What is happening: ...
+Why it matters: ...
+Fix it this month: ...
+
+### 2. [Metric Name]
+...
+
+## What is Working
+[1-2 genuine strengths, no padding]
+
+## 90-Day Focus
+[Single metric to move + specific numeric target]
+```
+
+## Examples
+
+**Example 1 — Partial data**
+
+Input: "MRR is $80k, we have 200 customers, about 3 cancel each month."
+
+Expected output: Calculates ARPA ($400), monthly churn (1.5%), ARR ($960k), LTV estimate. Flags CAC and growth rate as missing. Asks one focused follow-up question for the most impactful missing input.
+
+**Example 2 — Critical scenario**
+
+Input: "MRR $22k (was $23.5k), 80 customers, lost 9, gained 6, spent $15k on ads, 65% gross margin."
+
+Expected output: Flags negative MoM growth (-6.4%), critical churn (11.25%), and LTV:CAC of 0.64:1 as CRITICAL. Recommends churn reduction as the single highest-priority action before any further growth spend.
+
+## Key Principles
+
+- Be direct. If a metric is bad, say it is bad.
+- Explain every metric in one sentence before showing the number.
+- Cap priority issues at three. More than three paralyzes action.
+- Context changes benchmarks. Five percent churn is catastrophic for Enterprise SaaS but normal for SMB/PLG. Always confirm the user's target market before scoring.
+
+## Reference Files
+
+- `references/formulas.md` — All metric formulas with worked examples
+- `references/benchmarks.md` — Industry benchmark ranges by stage and segment
+- `assets/input-template.md` — Blank input form to share with users
+- `scripts/metrics_calculator.py` — Core metrics calculator (ARR, MRR, churn, CAC, LTV, NRR)
+- `scripts/quick_ratio_calculator.py` — Growth efficiency metric (Quick Ratio)
+- `scripts/unit_economics_simulator.py` — 12-month forward projection
+
+## Tools
+
+### 1. Metrics Calculator (`scripts/metrics_calculator.py`)
+Core SaaS metrics from raw business numbers.
+
+```bash
+# Interactive mode
+python scripts/metrics_calculator.py
+
+# CLI mode
+python scripts/metrics_calculator.py --mrr 50000 --customers 100 --churned 5 --json
+```
+
+### 2. Quick Ratio Calculator (`scripts/quick_ratio_calculator.py`)
+Growth efficiency metric: (New MRR + Expansion) / (Churned + Contraction)
+
+```bash
+python scripts/quick_ratio_calculator.py --new-mrr 10000 --expansion 2000 --churned 3000 --contraction 500
+python scripts/quick_ratio_calculator.py --new-mrr 10000 --expansion 2000 --churned 3000 --json
+```
+
+**Benchmarks:**
+- < 1.0 = CRITICAL (losing faster than gaining)
+- 1-2 = WATCH (marginal growth)
+- 2-4 = HEALTHY (good efficiency)
+- \> 4 = EXCELLENT (strong growth)
+
+### 3. Unit Economics Simulator (`scripts/unit_economics_simulator.py`)
+Project metrics forward 12 months based on growth/churn assumptions.
+
+```bash
+python scripts/unit_economics_simulator.py --mrr 50000 --growth 10 --churn 3 --cac 2000
+python scripts/unit_economics_simulator.py --mrr 50000 --growth 10 --churn 3 --cac 2000 --json
+```
+
+**Use for:**
+- "What if we grow at X% per month?"
+- Runway projections
+- Scenario planning (best/base/worst case)
+
+## Related Skills
+
+- **financial-analyst**: Use for DCF valuation, budget variance analysis, and traditional financial modeling. NOT for SaaS-specific metrics like CAC, LTV, or churn.
+- **business-growth/customer-success**: Use for retention strategies and customer health scoring. Complements this skill when churn is flagged as CRITICAL.
--- a/finance/saas-metrics-coach/assets/input-template.md
+++ b/finance/saas-metrics-coach/assets/input-template.md
@@ -0,0 +1,29 @@
+# SaaS Metrics — Input Template
+
+Fill in what you know and paste to the SaaS Metrics Coach. Leave blanks empty.
+
+---
+
+**Context**
+- Target market: [ ] Enterprise  [ ] Mid-Market  [ ] SMB  [ ] Consumer/PLG
+- Stage: [ ] Early (<$1M ARR)  [ ] Growth ($1M–$10M)  [ ] Scale ($10M+)
+
+**Revenue**
+- Current MRR: $
+- MRR last month: $
+- Expansion MRR this month (upsells/upgrades): $
+- Churned MRR this month: $
+- Contraction MRR (downgrades): $
+
+**Customers**
+- Total active customers:
+- New customers this month:
+- Churned customers this month:
+
+**Costs**
+- Sales & Marketing spend this month: $
+- Gross margin %:
+- Net profit margin % (optional):
+
+---
+*Partial data is fine — the coach works with whatever you have.*
--- a/finance/saas-metrics-coach/references/benchmarks.md
+++ b/finance/saas-metrics-coach/references/benchmarks.md
@@ -0,0 +1,101 @@
+# SaaS Industry Benchmarks
+
+Industry-standard benchmark ranges for SaaS metrics, segmented by company stage and market segment.
+
+**Sources:**
+- OpenView SaaS Benchmarks 2024
+- Bessemer Venture Partners Cloud Index
+- SaaS Capital Index
+- Paddle SaaS Metrics Report 2025
+
+**Last updated:** March 2026
+
+## Stage Definitions
+
+- Early: < $1M ARR
+- Growth: $1M–$10M ARR
+- Scale: $10M–$50M ARR
+- Late: $50M+ ARR
+
+---
+
+## Monthly Churn Rate
+
+| Segment | CRITICAL | WATCH | HEALTHY |
+|---|---|---|---|
+| Enterprise (ACV > $25k) | > 3% | 1–3% | < 1% |
+| Mid-Market ($5k–$25k ACV) | > 5% | 2–5% | < 2% |
+| SMB / PLG (< $5k ACV) | > 8% | 4–8% | < 4% |
+| Consumer | > 10% | 5–10% | < 5% |
+
+## LTV:CAC Ratio
+
+| Status | Range |
+|---|---|
+| CRITICAL | < 1:1 — losing money on every customer |
+| POOR | 1:1–2:1 — barely breaking even |
+| WATCH | 2:1–3:1 — marginally viable |
+| HEALTHY | 3:1–5:1 — industry standard |
+| EXCELLENT | > 5:1 — strong unit economics |
+| WATCH | > 8:1 — possibly under-investing in growth |
+
+## CAC Payback Period
+
+| Status | Range |
+|---|---|
+| CRITICAL | > 24 months |
+| WATCH | 18–24 months |
+| HEALTHY | 12–18 months |
+| GOOD | 6–12 months |
+| EXCELLENT | < 6 months (PLG indicator) |
+
+## NRR (Net Revenue Retention)
+
+| Status | Range |
+|---|---|
+| CRITICAL | < 80% — revenue shrinking from existing base |
+| POOR | 80–90% |
+| WATCH | 90–100% — flat, not expanding |
+| HEALTHY | 100–110% |
+| EXCELLENT | 110–120% |
+| WORLD-CLASS | > 120% (Snowflake / Datadog territory) |
+
+## MoM MRR Growth
+
+| Stage | CRITICAL | WATCH | HEALTHY | EXCELLENT |
+|---|---|---|---|---|
+| Early (< $1M ARR) | < 5% | 5–10% | 10–20% | > 20% |
+| Growth ($1M–$10M) | < 3% | 3–7% | 7–15% | > 15% |
+| Scale ($10M+) | < 1% | 1–3% | 3–7% | > 7% |
+
+## Gross Margin
+
+| Status | Range |
+|---|---|
+| CRITICAL | < 50% |
+| WATCH | 50–65% |
+| HEALTHY | 65–75% |
+| EXCELLENT | 75–85% |
+| WORLD-CLASS | > 85% (API / infrastructure businesses) |
+
+## Rule of 40
+
+| Score | Status |
+|---|---|
+| < 20 | CONCERNING |
+| 20–40 | DEVELOPING |
+| 40–60 | HEALTHY |
+| > 60 | EXCELLENT |
+
+## Quick Reference Card
+
+```
+Metric          Must Hit    Good        Great
+---------------------------------------------
+Monthly Churn   < 5%        < 3%        < 1%
+LTV:CAC         > 3:1       > 4:1       > 5:1
+CAC Payback     < 18 mo     < 12 mo     < 6 mo
+NRR             > 100%      > 110%      > 120%
+Gross Margin    > 65%       > 75%       > 80%
+MoM Growth      > 5%        > 10%       > 15%
+```
--- a/finance/saas-metrics-coach/references/formulas.md
+++ b/finance/saas-metrics-coach/references/formulas.md
@@ -0,0 +1,103 @@
+# SaaS Metric Formulas
+
+Complete reference with worked examples for all metrics calculated by the SaaS Metrics Coach.
+
+## ARR (Annual Recurring Revenue)
+```
+ARR = MRR × 12
+```
+
+**Example:**
+- Current MRR: $50,000
+- ARR = $50,000 × 12 = **$600,000**
+
+**When to use:** Quick snapshot of annualized revenue run rate. Not the same as actual annual revenue if you have seasonality or one-time fees.
+
+## MoM MRR Growth Rate
+```
+MoM Growth % = ((MRR_now - MRR_last) / MRR_last) × 100
+```
+
+**Example:**
+- Current MRR: $50,000
+- Last month MRR: $45,000
+- Growth = (($50,000 - $45,000) / $45,000) × 100 = **11.1%**
+
+**Interpretation:**
+- Negative = losing revenue
+- 0-5% = slow growth (concerning for early stage)
+- 5-15% = healthy growth
+- >15% = strong growth (early stage)
+
+## Monthly Churn Rate
+```
+Churn % = (Customers lost / Customers at start of month) × 100
+```
+
+**Example:**
+- Customers at start of month: 100
+- Customers lost during month: 5
+- Churn = (5 / 100) × 100 = **5%**
+
+**Annualized impact:** 5% monthly = ~46% annual churn (compounding effect)
+
+**Critical context:** Churn tolerance varies by segment:
+- Enterprise: >3% is critical
+- SMB: >8% is critical
+- Always confirm segment before judging severity
+
+## ARPA (Avg Revenue Per Account)
+```
+ARPA = MRR / Total active customers
+```
+
+## CAC (Customer Acquisition Cost)
+```
+CAC = Total Sales & Marketing spend / New customers acquired
+```
+Example: $20k spend / 10 customers → CAC $2,000
+
+## LTV (Customer Lifetime Value)
+```
+LTV = (ARPA / Monthly Churn Rate) × Gross Margin %
+```
+
+**Simplified (no gross margin data):**
+```
+LTV = ARPA / Monthly Churn Rate
+```
+
+**Example:**
+- ARPA: $500
+- Monthly churn: 5% (0.05)
+- Gross margin: 70% (0.70)
+- LTV = ($500 / 0.05) × 0.70 = **$7,000**
+
+**Simplified (no margin):** $500 / 0.05 = **$10,000**
+
+**Why it matters:** LTV tells you the total revenue you can expect from an average customer. Must be at least 3x your CAC to have sustainable unit economics.
+
+## LTV:CAC Ratio
+```
+LTV:CAC = LTV / CAC
+```
+Example: LTV $10k / CAC $2k = 5:1
+
+## CAC Payback Period
+```
+Payback (months) = CAC / (ARPA × Gross Margin %)
+Simplified: Payback = CAC / ARPA
+```
+Example: CAC $2k / ARPA $500 = 4 months
+
+## NRR (Net Revenue Retention)
+```
+NRR % = ((MRR_start + Expansion MRR - Churned MRR - Contraction MRR) / MRR_start) × 100
+```
+Simplified (no expansion data): NRR ≈ (1 - Revenue Churn Rate) × 100
+
+## Rule of 40
+```
+Score = Annualized MoM Growth % + Net Profit Margin %
+Healthy: ≥ 40
+```
--- a/finance/saas-metrics-coach/scripts/metrics_calculator.py
+++ b/finance/saas-metrics-coach/scripts/metrics_calculator.py
@@ -0,0 +1,217 @@
+#!/usr/bin/env python3
+"""
+SaaS Metrics Calculator — zero external dependencies (stdlib only).
+
+Usage (interactive): python metrics_calculator.py
+Usage (CLI):         python metrics_calculator.py --mrr 48000 --customers 160 --json
+Usage (import):
+    from metrics_calculator import calculate, report
+    results = calculate(mrr=48000, mrr_last=42000, customers=160,
+                        churned=4, new_customers=22, sm_spend=18000,
+                        gross_margin=0.72)
+    print(report(results))
+"""
+
+import json
+import sys
+
+
+def calculate(
+    mrr=None,
+    mrr_last=None,
+    customers=None,
+    churned=None,
+    new_customers=None,
+    sm_spend=None,
+    gross_margin=0.70,
+    expansion_mrr=0,
+    churned_mrr=0,
+    contraction_mrr=0,
+    profit_margin=None,
+):
+    r, missing = {}, []
+
+    # ── Core revenue ─────────────────────────────────────────────────────────
+    if mrr is not None:
+        r["MRR"] = round(mrr, 2)
+        r["ARR"] = round(mrr * 12, 2)
+    else:
+        missing.append("ARR/MRR — need current MRR")
+
+    if mrr and customers:
+        r["ARPA"] = round(mrr / customers, 2)
+    else:
+        missing.append("ARPA — need MRR + customer count")
+
+    # ── Growth ────────────────────────────────────────────────────────────────
+    if mrr and mrr_last and mrr_last > 0:
+        r["MoM_Growth_Pct"] = round(((mrr - mrr_last) / mrr_last) * 100, 2)
+    else:
+        missing.append("MoM Growth — need last month MRR")
+
+    # ── Churn ─────────────────────────────────────────────────────────────────
+    if churned is not None and customers:
+        r["Churn_Pct"] = round((churned / customers) * 100, 2)
+    else:
+        missing.append("Churn Rate — need churned + total customers")
+
+    # ── CAC ───────────────────────────────────────────────────────────────────
+    if sm_spend and new_customers and new_customers > 0:
+        r["CAC"] = round(sm_spend / new_customers, 2)
+    else:
+        missing.append("CAC — need S&M spend + new customers")
+
+    # ── LTV ───────────────────────────────────────────────────────────────────
+    arpa = r.get("ARPA")
+    churn_dec = r.get("Churn_Pct", 0) / 100
+    if arpa and churn_dec > 0:
+        r["LTV"] = round((arpa / churn_dec) * gross_margin, 2)
+    else:
+        missing.append("LTV — need ARPA and churn rate")
+
+    # ── LTV:CAC ───────────────────────────────────────────────────────────────
+    if r.get("LTV") and r.get("CAC") and r["CAC"] > 0:
+        r["LTV_CAC"] = round(r["LTV"] / r["CAC"], 2)
+    else:
+        missing.append("LTV:CAC — need both LTV and CAC")
+
+    # ── Payback ───────────────────────────────────────────────────────────────
+    if r.get("CAC") and arpa and arpa > 0:
+        r["Payback_Months"] = round(r["CAC"] / (arpa * gross_margin), 1)
+    else:
+        missing.append("Payback Period — need CAC and ARPA")
+
+    # ── NRR ───────────────────────────────────────────────────────────────────
+    if mrr_last and mrr_last > 0 and (expansion_mrr or churned_mrr or contraction_mrr):
+        nrr = ((mrr_last + expansion_mrr - churned_mrr - contraction_mrr) / mrr_last) * 100
+        r["NRR_Pct"] = round(nrr, 2)
+    elif r.get("Churn_Pct"):
+        r["NRR_Est_Pct"] = round((1 - r["Churn_Pct"] / 100) * 100, 2)
+        missing.append("NRR (accurate) — using churn-only estimate; provide expansion MRR for full NRR")
+
+    # ── Rule of 40 ────────────────────────────────────────────────────────────
+    if r.get("MoM_Growth_Pct") and profit_margin is not None:
+        r["Rule_of_40"] = round(r["MoM_Growth_Pct"] * 12 + profit_margin, 1)
+
+    r["_missing"] = missing
+    r["_gross_margin"] = gross_margin
+    return r
+
+
+def report(r):
+    labels = [
+        ("MRR",            "Monthly Recurring Revenue",     "$"),
+        ("ARR",            "Annual Recurring Revenue",       "$"),
+        ("ARPA",           "Avg Revenue Per Account/mo",     "$"),
+        ("MoM_Growth_Pct", "MoM MRR Growth",                "%"),
+        ("Churn_Pct",      "Monthly Churn Rate",             "%"),
+        ("CAC",            "Customer Acquisition Cost",      "$"),
+        ("LTV",            "Customer Lifetime Value",        "$"),
+        ("LTV_CAC",        "LTV:CAC Ratio",                  ":1"),
+        ("Payback_Months", "CAC Payback Period",             " months"),
+        ("NRR_Pct",        "NRR (Net Revenue Retention)",    "%"),
+        ("NRR_Est_Pct",    "NRR Estimate (churn-only)",      "%"),
+        ("Rule_of_40",     "Rule of 40 Score",               ""),
+    ]
+
+    lines = ["=" * 54, "  SAAS METRICS CALCULATOR", "=" * 54, ""]
+    for key, label, unit in labels:
+        val = r.get(key)
+        if val is None:
+            continue
+        if unit == "$":
+            fmt = f"${val:,.2f}"
+        elif unit == "%":
+            fmt = f"{val}%"
+        elif unit == ":1":
+            fmt = f"{val}:1"
+        else:
+            fmt = f"{val}{unit}"
+        lines.append(f"  {label:<40} {fmt}")
+
+    if r.get("_missing"):
+        lines += ["", "  Missing / estimated:"]
+        for m in r["_missing"]:
+            lines.append(f"    - {m}")
+
+    lines.append("=" * 54)
+    return "\n".join(lines)
+
+
+# ── Interactive mode ──────────────────────────────────────────────────────────
+
+def _ask(prompt, required=False):
+    while True:
+        v = input(f"  {prompt}: ").strip()
+        if not v:
+            if required:
+                print("    Required — please enter a value.")
+                continue
+            return None
+        try:
+            return float(v)
+        except ValueError:
+            print("    Enter a number (e.g. 48000 or 72).")
+
+
+if __name__ == "__main__":
+    import argparse
+    
+    parser = argparse.ArgumentParser(description="SaaS Metrics Calculator")
+    parser.add_argument("--mrr", type=float, help="Current MRR")
+    parser.add_argument("--mrr-last", type=float, help="MRR last month")
+    parser.add_argument("--customers", type=int, help="Total active customers")
+    parser.add_argument("--churned", type=int, help="Customers churned this month")
+    parser.add_argument("--new-customers", type=int, help="New customers acquired")
+    parser.add_argument("--sm-spend", type=float, help="Sales & Marketing spend")
+    parser.add_argument("--gross-margin", type=float, default=70, help="Gross margin %% (default: 70)")
+    parser.add_argument("--expansion-mrr", type=float, default=0, help="Expansion MRR")
+    parser.add_argument("--churned-mrr", type=float, default=0, help="Churned MRR")
+    parser.add_argument("--contraction-mrr", type=float, default=0, help="Contraction MRR")
+    parser.add_argument("--profit-margin", type=float, help="Net profit margin %%")
+    parser.add_argument("--json", action="store_true", help="Output JSON format")
+    
+    args = parser.parse_args()
+    
+    # CLI mode
+    if args.mrr is not None:
+        inputs = {
+            "mrr": args.mrr,
+            "mrr_last": args.mrr_last,
+            "customers": args.customers,
+            "churned": args.churned,
+            "new_customers": args.new_customers,
+            "sm_spend": args.sm_spend,
+            "gross_margin": args.gross_margin / 100 if args.gross_margin > 1 else args.gross_margin,
+            "expansion_mrr": args.expansion_mrr,
+            "churned_mrr": args.churned_mrr,
+            "contraction_mrr": args.contraction_mrr,
+            "profit_margin": args.profit_margin,
+        }
+        result = calculate(**inputs)
+        
+        if args.json:
+            print(json.dumps(result, indent=2))
+        else:
+            print("\n" + report(result))
+        sys.exit(0)
+    
+    # Interactive mode
+    print("\nSaaS Metrics Calculator  (press Enter to skip)\n")
+
+    gm = _ask("Gross margin % (default 70)", required=False) or 70
+    inputs = dict(
+        mrr=_ask("Current MRR ($)", required=True),
+        mrr_last=_ask("MRR last month ($)"),
+        customers=_ask("Total active customers"),
+        churned=_ask("Customers churned this month"),
+        new_customers=_ask("New customers acquired this month"),
+        sm_spend=_ask("Sales & Marketing spend this month ($)"),
+        gross_margin=gm / 100 if gm > 1 else gm,
+        expansion_mrr=_ask("Expansion MRR (upsells) ($)") or 0,
+        churned_mrr=_ask("Churned MRR ($)") or 0,
+        contraction_mrr=_ask("Contraction MRR (downgrades) ($)") or 0,
+        profit_margin=_ask("Net profit margin % (for Rule of 40, optional)"),
+    )
+
+    print("\n" + report(calculate(**inputs)))
--- a/finance/saas-metrics-coach/scripts/quick_ratio_calculator.py
+++ b/finance/saas-metrics-coach/scripts/quick_ratio_calculator.py
@@ -0,0 +1,173 @@
+#!/usr/bin/env python3
+"""
+Quick Ratio Calculator - SaaS growth efficiency metric.
+
+Quick Ratio = (New MRR + Expansion MRR) / (Churned MRR + Contraction MRR)
+
+A ratio > 4 indicates healthy, efficient growth.
+A ratio < 1 means you're losing revenue faster than gaining it.
+
+Usage:
+    python quick_ratio_calculator.py --new-mrr 10000 --expansion 2000 --churned 3000 --contraction 500
+    python quick_ratio_calculator.py --new-mrr 10000 --expansion 2000 --churned 3000 --contraction 500 --json
+"""
+
+import json
+import sys
+import argparse
+
+
+def calculate_quick_ratio(new_mrr, expansion_mrr, churned_mrr, contraction_mrr):
+    """
+    Calculate Quick Ratio and provide interpretation.
+    
+    Args:
+        new_mrr: New MRR from new customers
+        expansion_mrr: Expansion MRR from existing customers (upsells)
+        churned_mrr: MRR lost from churned customers
+        contraction_mrr: MRR lost from downgrades
+    
+    Returns:
+        dict with quick ratio and analysis
+    """
+    # Calculate components
+    growth_mrr = new_mrr + expansion_mrr
+    lost_mrr = churned_mrr + contraction_mrr
+    
+    # Quick Ratio
+    if lost_mrr == 0:
+        quick_ratio = float('inf') if growth_mrr > 0 else 0
+        quick_ratio_display = "∞" if growth_mrr > 0 else "0"
+    else:
+        quick_ratio = growth_mrr / lost_mrr
+        quick_ratio_display = f"{quick_ratio:.2f}"
+    
+    # Status assessment
+    if lost_mrr == 0 and growth_mrr > 0:
+        status = "EXCELLENT"
+        interpretation = "No revenue loss - perfect retention with growth"
+    elif quick_ratio >= 4:
+        status = "EXCELLENT"
+        interpretation = "Strong, efficient growth - gaining revenue 4x faster than losing it"
+    elif quick_ratio >= 2:
+        status = "HEALTHY"
+        interpretation = "Good growth efficiency - gaining revenue 2x+ faster than losing it"
+    elif quick_ratio >= 1:
+        status = "WATCH"
+        interpretation = "Marginal growth - barely gaining more than losing"
+    else:
+        status = "CRITICAL"
+        interpretation = "Losing revenue faster than gaining - growth is unsustainable"
+    
+    # Breakdown percentages
+    if growth_mrr > 0:
+        new_pct = (new_mrr / growth_mrr) * 100
+        expansion_pct = (expansion_mrr / growth_mrr) * 100
+    else:
+        new_pct = expansion_pct = 0
+    
+    if lost_mrr > 0:
+        churned_pct = (churned_mrr / lost_mrr) * 100
+        contraction_pct = (contraction_mrr / lost_mrr) * 100
+    else:
+        churned_pct = contraction_pct = 0
+    
+    results = {
+        "quick_ratio": quick_ratio if quick_ratio != float('inf') else None,
+        "quick_ratio_display": quick_ratio_display,
+        "status": status,
+        "interpretation": interpretation,
+        "components": {
+            "growth_mrr": round(growth_mrr, 2),
+            "lost_mrr": round(lost_mrr, 2),
+            "new_mrr": round(new_mrr, 2),
+            "expansion_mrr": round(expansion_mrr, 2),
+            "churned_mrr": round(churned_mrr, 2),
+            "contraction_mrr": round(contraction_mrr, 2),
+        },
+        "breakdown": {
+            "new_mrr_pct": round(new_pct, 1),
+            "expansion_mrr_pct": round(expansion_pct, 1),
+            "churned_mrr_pct": round(churned_pct, 1),
+            "contraction_mrr_pct": round(contraction_pct, 1),
+        },
+    }
+    
+    return results
+
+
+def format_report(results):
+    """Format quick ratio results as human-readable report."""
+    lines = []
+    lines.append("\n" + "=" * 70)
+    lines.append("QUICK RATIO ANALYSIS")
+    lines.append("=" * 70)
+    
+    # Quick Ratio
+    lines.append(f"\n⚡ QUICK RATIO: {results['quick_ratio_display']}")
+    lines.append(f"   Status: {results['status']}")
+    lines.append(f"   {results['interpretation']}")
+    
+    # Components
+    comp = results["components"]
+    lines.append("\n📊 COMPONENTS")
+    lines.append(f"  Growth MRR (New + Expansion): ${comp['growth_mrr']:,.2f}")
+    lines.append(f"    • New MRR: ${comp['new_mrr']:,.2f}")
+    lines.append(f"    • Expansion MRR: ${comp['expansion_mrr']:,.2f}")
+    lines.append(f"  Lost MRR (Churned + Contraction): ${comp['lost_mrr']:,.2f}")
+    lines.append(f"    • Churned MRR: ${comp['churned_mrr']:,.2f}")
+    lines.append(f"    • Contraction MRR: ${comp['contraction_mrr']:,.2f}")
+    
+    # Breakdown
+    bd = results["breakdown"]
+    lines.append("\n📈 GROWTH BREAKDOWN")
+    lines.append(f"  New customers: {bd['new_mrr_pct']:.1f}%")
+    lines.append(f"  Expansion: {bd['expansion_mrr_pct']:.1f}%")
+    
+    lines.append("\n📉 LOSS BREAKDOWN")
+    lines.append(f"  Churn: {bd['churned_mrr_pct']:.1f}%")
+    lines.append(f"  Contraction: {bd['contraction_mrr_pct']:.1f}%")
+    
+    # Benchmarks
+    lines.append("\n🎯 BENCHMARKS")
+    lines.append("  < 1.0  = CRITICAL (losing revenue faster than gaining)")
+    lines.append("  1-2    = WATCH (marginal growth)")
+    lines.append("  2-4    = HEALTHY (good growth efficiency)")
+    lines.append("  > 4    = EXCELLENT (strong, efficient growth)")
+    
+    lines.append("\n" + "=" * 70 + "\n")
+    
+    return "\n".join(lines)
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description="Calculate SaaS Quick Ratio (growth efficiency metric)"
+    )
+    parser.add_argument(
+        "--new-mrr", type=float, required=True, help="New MRR from new customers"
+    )
+    parser.add_argument(
+        "--expansion", type=float, default=0, help="Expansion MRR from upsells (default: 0)"
+    )
+    parser.add_argument(
+        "--churned", type=float, required=True, help="Churned MRR from lost customers"
+    )
+    parser.add_argument(
+        "--contraction", type=float, default=0, help="Contraction MRR from downgrades (default: 0)"
+    )
+    parser.add_argument("--json", action="store_true", help="Output JSON format")
+    
+    args = parser.parse_args()
+    
+    results = calculate_quick_ratio(
+        new_mrr=args.new_mrr,
+        expansion_mrr=args.expansion,
+        churned_mrr=args.churned,
+        contraction_mrr=args.contraction,
+    )
+    
+    if args.json:
+        print(json.dumps(results, indent=2))
+    else:
+        print(format_report(results))
--- a/finance/saas-metrics-coach/scripts/unit_economics_simulator.py
+++ b/finance/saas-metrics-coach/scripts/unit_economics_simulator.py
@@ -0,0 +1,205 @@
+#!/usr/bin/env python3
+"""
+Unit Economics Simulator - Project SaaS metrics forward 12 months.
+
+Usage:
+    python unit_economics_simulator.py --mrr 50000 --growth 10 --churn 3 --cac 2000
+    python unit_economics_simulator.py --mrr 50000 --growth 10 --churn 3 --cac 2000 --json
+"""
+
+import json
+import sys
+import argparse
+
+
+def simulate(
+    mrr,
+    monthly_growth_pct,
+    monthly_churn_pct,
+    cac,
+    gross_margin=0.70,
+    sm_spend_pct=0.30,
+    months=12,
+):
+    """
+    Simulate unit economics forward.
+    
+    Args:
+        mrr: Starting MRR
+        monthly_growth_pct: Expected monthly growth rate (%)
+        monthly_churn_pct: Expected monthly churn rate (%)
+        cac: Customer acquisition cost
+        gross_margin: Gross margin (0-1)
+        sm_spend_pct: Sales & marketing as % of revenue (0-1)
+        months: Number of months to project
+    
+    Returns:
+        dict with monthly projections and summary
+    """
+    results = {
+        "inputs": {
+            "starting_mrr": mrr,
+            "monthly_growth_pct": monthly_growth_pct,
+            "monthly_churn_pct": monthly_churn_pct,
+            "cac": cac,
+            "gross_margin": gross_margin,
+            "sm_spend_pct": sm_spend_pct,
+        },
+        "projections": [],
+        "summary": {},
+    }
+    
+    current_mrr = mrr
+    cumulative_sm_spend = 0
+    cumulative_gross_profit = 0
+    
+    for month in range(1, months + 1):
+        # Calculate growth and churn
+        growth_rate = monthly_growth_pct / 100
+        churn_rate = monthly_churn_pct / 100
+        
+        # Net growth = growth - churn
+        net_growth_rate = growth_rate - churn_rate
+        new_mrr = current_mrr * (1 + net_growth_rate)
+        
+        # Revenue and costs
+        monthly_revenue = current_mrr
+        gross_profit = monthly_revenue * gross_margin
+        sm_spend = monthly_revenue * sm_spend_pct
+        net_profit = gross_profit - sm_spend
+        
+        # Accumulate
+        cumulative_sm_spend += sm_spend
+        cumulative_gross_profit += gross_profit
+        
+        # ARR
+        arr = current_mrr * 12
+        
+        results["projections"].append({
+            "month": month,
+            "mrr": round(current_mrr, 2),
+            "arr": round(arr, 2),
+            "monthly_revenue": round(monthly_revenue, 2),
+            "gross_profit": round(gross_profit, 2),
+            "sm_spend": round(sm_spend, 2),
+            "net_profit": round(net_profit, 2),
+            "growth_rate_pct": round(net_growth_rate * 100, 2),
+        })
+        
+        current_mrr = new_mrr
+    
+    # Summary
+    final_mrr = results["projections"][-1]["mrr"]
+    final_arr = results["projections"][-1]["arr"]
+    total_revenue = sum(p["monthly_revenue"] for p in results["projections"])
+    total_net_profit = sum(p["net_profit"] for p in results["projections"])
+    
+    results["summary"] = {
+        "starting_mrr": mrr,
+        "ending_mrr": round(final_mrr, 2),
+        "ending_arr": round(final_arr, 2),
+        "mrr_growth_pct": round(((final_mrr - mrr) / mrr) * 100, 2),
+        "total_revenue_12m": round(total_revenue, 2),
+        "total_gross_profit_12m": round(cumulative_gross_profit, 2),
+        "total_sm_spend_12m": round(cumulative_sm_spend, 2),
+        "total_net_profit_12m": round(total_net_profit, 2),
+        "avg_monthly_growth_pct": round((monthly_growth_pct - monthly_churn_pct), 2),
+    }
+    
+    return results
+
+
+def format_report(results):
+    """Format simulation results as human-readable report."""
+    lines = []
+    lines.append("\n" + "=" * 70)
+    lines.append("UNIT ECONOMICS SIMULATION - 12 MONTH PROJECTION")
+    lines.append("=" * 70)
+    
+    # Inputs
+    inputs = results["inputs"]
+    lines.append("\n📊 INPUTS")
+    lines.append(f"  Starting MRR: ${inputs['starting_mrr']:,.0f}")
+    lines.append(f"  Monthly Growth: {inputs['monthly_growth_pct']}%")
+    lines.append(f"  Monthly Churn: {inputs['monthly_churn_pct']}%")
+    lines.append(f"  CAC: ${inputs['cac']:,.0f}")
+    lines.append(f"  Gross Margin: {inputs['gross_margin']*100:.0f}%")
+    lines.append(f"  S&M Spend: {inputs['sm_spend_pct']*100:.0f}% of revenue")
+    
+    # Summary
+    summary = results["summary"]
+    lines.append("\n📈 12-MONTH SUMMARY")
+    lines.append(f"  Starting MRR: ${summary['starting_mrr']:,.0f}")
+    lines.append(f"  Ending MRR: ${summary['ending_mrr']:,.0f}")
+    lines.append(f"  Ending ARR: ${summary['ending_arr']:,.0f}")
+    lines.append(f"  MRR Growth: {summary['mrr_growth_pct']:+.1f}%")
+    lines.append(f"  Total Revenue: ${summary['total_revenue_12m']:,.0f}")
+    lines.append(f"  Total Gross Profit: ${summary['total_gross_profit_12m']:,.0f}")
+    lines.append(f"  Total S&M Spend: ${summary['total_sm_spend_12m']:,.0f}")
+    lines.append(f"  Total Net Profit: ${summary['total_net_profit_12m']:,.0f}")
+    
+    # Monthly breakdown (first 3, last 3)
+    lines.append("\n📅 MONTHLY PROJECTIONS")
+    lines.append(f"{'Month':<8} {'MRR':<12} {'ARR':<12} {'Revenue':<12} {'Net Profit':<12}")
+    lines.append("-" * 70)
+    
+    projs = results["projections"]
+    for p in projs[:3]:
+        lines.append(
+            f"{p['month']:<8} ${p['mrr']:<11,.0f} ${p['arr']:<11,.0f} "
+            f"${p['monthly_revenue']:<11,.0f} ${p['net_profit']:<11,.0f}"
+        )
+    
+    if len(projs) > 6:
+        lines.append("  ...")
+    
+    for p in projs[-3:]:
+        lines.append(
+            f"{p['month']:<8} ${p['mrr']:<11,.0f} ${p['arr']:<11,.0f} "
+            f"${p['monthly_revenue']:<11,.0f} ${p['net_profit']:<11,.0f}"
+        )
+    
+    lines.append("\n" + "=" * 70 + "\n")
+    
+    return "\n".join(lines)
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description="Simulate SaaS unit economics over 12 months"
+    )
+    parser.add_argument("--mrr", type=float, required=True, help="Starting MRR")
+    parser.add_argument(
+        "--growth", type=float, required=True, help="Monthly growth rate (%)"
+    )
+    parser.add_argument(
+        "--churn", type=float, required=True, help="Monthly churn rate (%)"
+    )
+    parser.add_argument("--cac", type=float, required=True, help="Customer acquisition cost")
+    parser.add_argument(
+        "--gross-margin", type=float, default=70, help="Gross margin %% (default: 70)"
+    )
+    parser.add_argument(
+        "--sm-spend", type=float, default=30, help="S&M spend as %% of revenue (default: 30)"
+    )
+    parser.add_argument(
+        "--months", type=int, default=12, help="Months to project (default: 12)"
+    )
+    parser.add_argument("--json", action="store_true", help="Output JSON format")
+    
+    args = parser.parse_args()
+    
+    results = simulate(
+        mrr=args.mrr,
+        monthly_growth_pct=args.growth,
+        monthly_churn_pct=args.churn,
+        cac=args.cac,
+        gross_margin=args.gross_margin / 100 if args.gross_margin > 1 else args.gross_margin,
+        sm_spend_pct=args.sm_spend / 100 if args.sm_spend > 1 else args.sm_spend,
+        months=args.months,
+    )
+    
+    if args.json:
+        print(json.dumps(results, indent=2))
+    else:
+        print(format_report(results))