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AI & Automation Overview AI Voice Agents Workflow Automation AI Lead Response Cold Outreach AI Reporting DashboardA retention rate calculator shows what percentage of users or customers stay active over time. Calculate from simple counts or cohort data (D1, D7, D30) to measure retention trends.
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A retention rate calculator measures what percentage of users or customers remain active after signup or purchase. Enter starting users, ending users and new users added, or use cohort data (Day 1, Day 7, Day 30 retention rates). The calculator shows your retention percentage and trends over time. Retention is the single most important metric for apps because it directly drives lifetime value. This calculator helps you spot retention problems early and measure whether product changes improve stickiness.
Retention measures the percentage of users who stay or return to active use. Cohort retention (D1, D7, D30) tracks a group of users from their install date; it is the best measure of product stickiness.
Cohort of 10,000 users installed on day 0:
This curve is typical for consumer apps: steep drop from D1 to D7 (most casual users leave), then flattens. The plateau (D7 to D30) shows your committed users.
Simple mode example: 10,000 users at start, 8,500 at end, 2,000 new during period:
Typical D30 retention by app category:
D1 retention is usually 25% to 50% (one-third to half of users return on day 1). D7 is typically 50% to 70% of D1. If your D7 is much lower, first-week experience needs work.
Measure the curve first, then fix by segment:
Day 1, Day 7 and Day 30 retention measure what percentage of users from a cohort (group installed on the same day) are active on those days. Day 0 is install day. D1 is day after install.
No, not for product retention. Count them active if they complete a core action (send a message, log a workout, submit a form). Opening without action is meaningless.
Weekly at minimum, ideally daily. Cohort tables with weeks on rows (cohorts) and columns (D1, D7, D30) show trends. Improving trends beat absolute numbers; declining trends warn of problems.
Cannot be negative. If users at end minus new users is below zero, churn exceeded starting users. Measure again; if real, acquisition is outpacing retention and growth is unsustainable.
No. Retention is cohort-based (percentage of an install cohort). MAU churn is percentage of a month's active users who did not stay. Retention is more precise for product decisions.
It varies by category, which is why the retention benchmark checker asks for yours first. Games lose users faster than productivity or finance apps. If day 7 is where your curve collapses, fix onboarding and feature discovery before scaling user acquisition.
D30 retention is close to monthly retention if cohort is mature, but not exact. Monthly retention = (Users at end minus new users) / Users at start x 100, which is the formula this calculator's simple mode uses. Use this calculator with actual user counts from your analytics, not just daily cohort retention, for the most accurate monthly trend.
Last reviewed 23 September 2026. Formulas and benchmarks are published on the page so you can check them. This tool gives estimates, not quotes.