ARR / MRR Estimator

First, it estimates new customers: new = pageViews × conversionRate. It then projects active customers month-by-month using churn: customers_t = customers_(t-1) × (1 − churn) + new (and uses a safe special handling when churn is 0). Finally, it multiplies active customers by a bundled revenue-per-customer/transaction input that depends on product type, producing MRR and ARR (ARR = MRR × 12).

The calculator uses simplified steady-state assumptions and constant monthly churn, so results are best for early-stage directional planning rather than investor-grade forecasts. For media/ads, it infers how many monetizable “users” you have from page views per user; for marketplace and e-commerce, it relies on take rate and purchase frequency rather than a full funnel. If churn is high relative to conversion, customer counts can stay low even with strong traffic.

Avoid plugging page views that are not comparable to your actual monetization surface (e.g., including untracked traffic or counting only impressions). Also double-check units: conversion rate is a % visitor→customer rate, churn is % customers lost per month, and marketplace take rate is already the percentage of each transaction you keep. If CAC is 0, the tool will skip LTV:CAC and payback verdicts—use that as a “speed mode,” not as proof the unit economics are perfect.

If churn = 0%, LTV becomes undefined/infinite under the simplified LTV = revenuePerCustomer ÷ churn logic, so the calculator avoids dividing by zero and instead displays a capped/“very high” style output. If CAC = 0, it treats payback as immediate and marks LTV:CAC as not applicable. With extremely low conversion (near 0%), revenue can be near zero even when page views are high; with very high inputs, make sure they match your real traffic and conversion measurement window.