176afc5c46
- SaaS metrics calculator (ARR, MRR, churn, CAC, LTV, NRR) - Quick Ratio calculator for growth efficiency - Unit economics simulator for 12-month projections - Industry benchmarks by stage/segment (OpenView, Bessemer, SaaS Capital) - 3 stdlib-only Python tools with CLI and JSON output - Complements financial-analyst skill for SaaS founders
218 lines
9.5 KiB
Python
218 lines
9.5 KiB
Python
#!/usr/bin/env python3
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"""
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SaaS Metrics Calculator — zero external dependencies (stdlib only).
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Usage (interactive): python metrics_calculator.py
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Usage (CLI): python metrics_calculator.py --mrr 48000 --customers 160 --json
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Usage (import):
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from metrics_calculator import calculate, report
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results = calculate(mrr=48000, mrr_last=42000, customers=160,
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churned=4, new_customers=22, sm_spend=18000,
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gross_margin=0.72)
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print(report(results))
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"""
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import json
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import sys
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def calculate(
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mrr=None,
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mrr_last=None,
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customers=None,
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churned=None,
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new_customers=None,
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sm_spend=None,
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gross_margin=0.70,
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expansion_mrr=0,
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churned_mrr=0,
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contraction_mrr=0,
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profit_margin=None,
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):
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r, missing = {}, []
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# ── Core revenue ─────────────────────────────────────────────────────────
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if mrr is not None:
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r["MRR"] = round(mrr, 2)
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r["ARR"] = round(mrr * 12, 2)
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else:
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missing.append("ARR/MRR — need current MRR")
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if mrr and customers:
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r["ARPA"] = round(mrr / customers, 2)
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else:
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missing.append("ARPA — need MRR + customer count")
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# ── Growth ────────────────────────────────────────────────────────────────
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if mrr and mrr_last and mrr_last > 0:
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r["MoM_Growth_Pct"] = round(((mrr - mrr_last) / mrr_last) * 100, 2)
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else:
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missing.append("MoM Growth — need last month MRR")
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# ── Churn ─────────────────────────────────────────────────────────────────
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if churned is not None and customers:
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r["Churn_Pct"] = round((churned / customers) * 100, 2)
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else:
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missing.append("Churn Rate — need churned + total customers")
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# ── CAC ───────────────────────────────────────────────────────────────────
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if sm_spend and new_customers and new_customers > 0:
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r["CAC"] = round(sm_spend / new_customers, 2)
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else:
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missing.append("CAC — need S&M spend + new customers")
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# ── LTV ───────────────────────────────────────────────────────────────────
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arpa = r.get("ARPA")
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churn_dec = r.get("Churn_Pct", 0) / 100
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if arpa and churn_dec > 0:
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r["LTV"] = round((arpa / churn_dec) * gross_margin, 2)
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else:
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missing.append("LTV — need ARPA and churn rate")
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# ── LTV:CAC ───────────────────────────────────────────────────────────────
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if r.get("LTV") and r.get("CAC") and r["CAC"] > 0:
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r["LTV_CAC"] = round(r["LTV"] / r["CAC"], 2)
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else:
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missing.append("LTV:CAC — need both LTV and CAC")
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# ── Payback ───────────────────────────────────────────────────────────────
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if r.get("CAC") and arpa and arpa > 0:
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r["Payback_Months"] = round(r["CAC"] / (arpa * gross_margin), 1)
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else:
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missing.append("Payback Period — need CAC and ARPA")
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# ── NRR ───────────────────────────────────────────────────────────────────
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if mrr_last and mrr_last > 0 and (expansion_mrr or churned_mrr or contraction_mrr):
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nrr = ((mrr_last + expansion_mrr - churned_mrr - contraction_mrr) / mrr_last) * 100
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r["NRR_Pct"] = round(nrr, 2)
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elif r.get("Churn_Pct"):
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r["NRR_Est_Pct"] = round((1 - r["Churn_Pct"] / 100) * 100, 2)
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missing.append("NRR (accurate) — using churn-only estimate; provide expansion MRR for full NRR")
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# ── Rule of 40 ────────────────────────────────────────────────────────────
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if r.get("MoM_Growth_Pct") and profit_margin is not None:
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r["Rule_of_40"] = round(r["MoM_Growth_Pct"] * 12 + profit_margin, 1)
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r["_missing"] = missing
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r["_gross_margin"] = gross_margin
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return r
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def report(r):
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labels = [
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("MRR", "Monthly Recurring Revenue", "$"),
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("ARR", "Annual Recurring Revenue", "$"),
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("ARPA", "Avg Revenue Per Account/mo", "$"),
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("MoM_Growth_Pct", "MoM MRR Growth", "%"),
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("Churn_Pct", "Monthly Churn Rate", "%"),
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("CAC", "Customer Acquisition Cost", "$"),
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("LTV", "Customer Lifetime Value", "$"),
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("LTV_CAC", "LTV:CAC Ratio", ":1"),
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("Payback_Months", "CAC Payback Period", " months"),
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("NRR_Pct", "NRR (Net Revenue Retention)", "%"),
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("NRR_Est_Pct", "NRR Estimate (churn-only)", "%"),
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("Rule_of_40", "Rule of 40 Score", ""),
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]
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lines = ["=" * 54, " SAAS METRICS CALCULATOR", "=" * 54, ""]
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for key, label, unit in labels:
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val = r.get(key)
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if val is None:
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continue
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if unit == "$":
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fmt = f"${val:,.2f}"
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elif unit == "%":
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fmt = f"{val}%"
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elif unit == ":1":
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fmt = f"{val}:1"
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else:
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fmt = f"{val}{unit}"
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lines.append(f" {label:<40} {fmt}")
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if r.get("_missing"):
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lines += ["", " Missing / estimated:"]
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for m in r["_missing"]:
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lines.append(f" - {m}")
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lines.append("=" * 54)
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return "\n".join(lines)
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# ── Interactive mode ──────────────────────────────────────────────────────────
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def _ask(prompt, required=False):
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while True:
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v = input(f" {prompt}: ").strip()
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if not v:
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if required:
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print(" Required — please enter a value.")
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continue
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return None
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try:
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return float(v)
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except ValueError:
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print(" Enter a number (e.g. 48000 or 72).")
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if __name__ == "__main__":
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import argparse
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parser = argparse.ArgumentParser(description="SaaS Metrics Calculator")
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parser.add_argument("--mrr", type=float, help="Current MRR")
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parser.add_argument("--mrr-last", type=float, help="MRR last month")
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parser.add_argument("--customers", type=int, help="Total active customers")
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parser.add_argument("--churned", type=int, help="Customers churned this month")
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parser.add_argument("--new-customers", type=int, help="New customers acquired")
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parser.add_argument("--sm-spend", type=float, help="Sales & Marketing spend")
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parser.add_argument("--gross-margin", type=float, default=70, help="Gross margin %% (default: 70)")
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parser.add_argument("--expansion-mrr", type=float, default=0, help="Expansion MRR")
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parser.add_argument("--churned-mrr", type=float, default=0, help="Churned MRR")
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parser.add_argument("--contraction-mrr", type=float, default=0, help="Contraction MRR")
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parser.add_argument("--profit-margin", type=float, help="Net profit margin %%")
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parser.add_argument("--json", action="store_true", help="Output JSON format")
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args = parser.parse_args()
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# CLI mode
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if args.mrr is not None:
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inputs = {
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"mrr": args.mrr,
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"mrr_last": args.mrr_last,
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"customers": args.customers,
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"churned": args.churned,
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"new_customers": args.new_customers,
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"sm_spend": args.sm_spend,
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"gross_margin": args.gross_margin / 100 if args.gross_margin > 1 else args.gross_margin,
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"expansion_mrr": args.expansion_mrr,
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"churned_mrr": args.churned_mrr,
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"contraction_mrr": args.contraction_mrr,
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"profit_margin": args.profit_margin,
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}
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result = calculate(**inputs)
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if args.json:
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print(json.dumps(result, indent=2))
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else:
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print("\n" + report(result))
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sys.exit(0)
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# Interactive mode
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print("\nSaaS Metrics Calculator (press Enter to skip)\n")
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gm = _ask("Gross margin % (default 70)", required=False) or 70
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inputs = dict(
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mrr=_ask("Current MRR ($)", required=True),
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mrr_last=_ask("MRR last month ($)"),
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customers=_ask("Total active customers"),
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churned=_ask("Customers churned this month"),
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new_customers=_ask("New customers acquired this month"),
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sm_spend=_ask("Sales & Marketing spend this month ($)"),
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gross_margin=gm / 100 if gm > 1 else gm,
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expansion_mrr=_ask("Expansion MRR (upsells) ($)") or 0,
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churned_mrr=_ask("Churned MRR ($)") or 0,
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contraction_mrr=_ask("Contraction MRR (downgrades) ($)") or 0,
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profit_margin=_ask("Net profit margin % (for Rule of 40, optional)"),
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)
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print("\n" + report(calculate(**inputs)))
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