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★ The numbers your investor will ask for

SaaS Metrics Calculators

12 calculators, each with the formula, a worked example and benchmarks. So you know what "good" looks like before the board meeting.

  • Runs in your browser
  • No signup

Unit economics

Retention

Growth

Efficiency

01

Which metric answers which question

Start from the question you are trying to answer, not the acronym.

Question to metric map
If you want to know…Use
Are we growing fast enough?MRR growth
Do customers stay?Churn
Do existing customers spend more over time?NRR
Does a customer pay back what they cost?Payback
Is the business model sound per customer?LTV:CAC
Is our burn buying growth?Burn multiple
Should we spend more on sales and marketing?Magic number
Is growth outrunning churn?Quick ratio
Is the growth and profit balance healthy at scale?Rule of 40

Every calculator runs in your browser. Nothing you type is sent anywhere, so it is safe to use real numbers.

02

Questions founders actually ask

Which SaaS metrics matter most at seed stage?
MRR growth, churn and CAC payback. They are the ones you can measure reliably with a few months of data, and they answer the questions seed investors ask: are people paying, are they staying, and does acquiring them make sense.
Which metrics do Series A investors ask for?
Usually ARR and its growth rate, net revenue retention, gross margin, CAC payback or LTV:CAC, and burn multiple. Have the definitions written down, because investors will check how you calculated each one.
Should I calculate metrics monthly or annually?
Track monthly, report on a rolling three-month or annual basis. Monthly numbers at small scale swing with a handful of deals; NRR in particular is defined over a year.
Are these calculators accurate enough for a board deck?
The formulas are the standard ones and the maths is exact. Accuracy depends on your inputs: use fully loaded costs, exclude one-off revenue, and say which definition you used.
03

More from the workbench

Fine print

Tools: on the house.
Engineer: by the hour.

Moving them is the expensive part, and the part I'm good at: activation flows, upsell moments and the product work behind better numbers.

I'm Himanshu, an AI and full-stack engineer. I build MVPs, AI agents and the growth plumbing around them for early-stage startups.