Churn Rate Calculator

Churn rate = 100% − retention rate = 100% − (Retained users ÷ Total users in cohort) × 100. For example, if 1,000 users started and 350 are still active at the end of the period, retention is 35%, so churn is 65%. This calculator lets you enter starting users, remaining users, and the period (1, 7, or 30 days) to get your churn rate instantly.

Pick a period (e.g. day 1, day 7, or day 30), count how many users you had at the start of that period (e.g. installs or new signups) and how many were still active at the end. Churn rate = 100% minus (remaining ÷ starting × 100). Use this calculator: enter starting user count, remaining user count, and the period to get your churn rate and see how it affects revenue.

You need three things: (1) the number of users at the start of the period (e.g. installs or new users in a cohort), (2) the number still active at the end of the period (e.g. opened the app or completed a key action), and (3) the time window (e.g. 1, 7, or 30 days). This calculator uses those inputs to compute churn and project revenue impact.

They describe the same behavior from opposite sides: retention is the percentage who stay, churn is the percentage who leave. Retention + churn = 100%. So 40% Day 30 retention means 60% Day 30 churn. Improving retention lowers churn; reducing churn raises retention. This calculator focuses on churn and shows how reducing it increases revenue.

Churn is always “per period”: you choose the window (e.g. 1 day, 7 days, or 30 days) and compute what share of users left over that window. This calculator supports 1-day, 7-day, and 30-day churn. To compare: if 5% churn per 30 days, that’s a different curve than 5% churn per 1 day. Use the same period you use in your product so the number is actionable.

It varies by vertical and period. As a rough guide: day 1 churn is often 55–75% (so 25–45% retention); Day 7 churn ~75–85%; day 30 churn ~80–95%. “Good” means lower churn than typical for your category and improving over time. Use this calculator to see how your churn compares and how much revenue you gain by reducing it.

Higher churn shortens how long users stay, so they pay (or see ads) for fewer months and LTV goes down. Lower churn means longer average lifetime and higher LTV. LTV is often approximated as ARPU ÷ monthly churn rate, so cutting churn directly increases LTV. This calculator shows revenue over time; our Customer Lifetime Value calculator lets you model LTV and churn together.

Churn costs the revenue those users would have generated if they had stayed. The exact amount depends on your ARPU, acquisition rate, and how long users would have stayed at a lower churn. This calculator’s revenue analysis shows cumulative revenue with your current churn; the gap between “current” and “with impact” (reduced churn) is the revenue churn is costing you over 12 months.

It depends on your baseline churn, ARPU, and user growth. Even a 2–6 percentage point churn reduction can add meaningful revenue when applied to a large, active user base. Use the revenue analysis on this page: set your assumptions (ARPU, new users per month), then compare “Current state” to “With impact” (low, medium, or high churn reduction) to see revenue gained at 3, 6, and 12 months.

Common causes include: weak onboarding (users never reach value), no habit loop or reason to return, low perceived value after first use, friction or bugs, irrelevant or annoying push notifications, and a mismatch with user expectations. Diagnose with cohort and segment analysis. This calculator helps you quantify how much revenue high churn costs so you can justify and prioritize fixes like better onboarding and retention features (e.g. gamification).