Mobile app retention rate

Mobile app retention rate is the share of people who installed an app and came back during a defined period. For day-N retention, divide the installs in a cohort who were active on day N by all installs in that cohort, then multiply by 100.

What mobile app retention rate measures

Retention shows whether people return after their first use. It is different from installs, sessions, or total active users: those counts can rise while the share of each install group that returns falls.

Define what “active” means before calculating the rate. For a mobile app, that might be opening the app or completing a meaningful action. Apply the same event definition to every cohort you compare so a change in the number reflects user behavior rather than a change in tracking.

How to calculate day 1, day 7, and day 30 retention

Use this formula for each day:

Day-N retention = (users from an install cohort active exactly N days after install ÷ all users in that install cohort) × 100

The cohort is everyone who installed during the same starting period. Day 1 counts users active one day after their install date; day 7 counts those active seven days after install; day 30 counts those active thirty days after install. Keep the definition consistent, including the timezone used to assign calendar days.

To calculate each rate:

1. Group users by install date or install period.
2. Count all users in each install cohort. This is the denominator for that cohort’s rates.
3. Count cohort members with the chosen activity on day 1, day 7, and day 30.
4. Divide each day’s active-user count by the cohort size and multiply by 100.

Only compare a day-N rate for cohorts that have had N days to reach that point. For example, a cohort installed yesterday cannot yet provide a day-7 or day-30 result. Keep those periods out of comparisons until they are complete.

If you want to compare return behavior across groups of users, the ActivationPal cohort analysis tool turns a CSV of events or purchases into a weekly or monthly retention table. It groups users by their first dated row and shows their return in later periods; it does not calculate daily retention.

What is a good app retention rate?

A good rate depends on what the app does, how often people need it, and which activity counts as a return. A daily-use app and an app used for an occasional task have different natural return patterns, so one cutoff cannot judge both fairly.

Use your earlier cohorts as a baseline, keeping the activity event and measurement period consistent. Account for cohort size and major differences in acquisition timing or channel when interpreting a change. A category benchmark is useful only when it defines the app category, retention day, and activity measure.

How to track mobile app retention by cohort

A cohort table keeps each install group separate. Each row represents a group that started in the same week or month, and each later column shows the share that returned in that period. This makes it possible to see whether retention changes between groups instead of blending everyone into one overall rate.

For a CSV analysis, include a stable user identifier and a date for each relevant event. The cohort analysis tool accepts event or purchase rows, detects common identifier and date columns, and lets you choose the columns if needed. Select weekly cohorts for frequent returns or a shorter history, and monthly cohorts for less frequent activity or a longer view.

Read the table from left to right to follow each cohort over time. Recent rows have fewer completed periods, so later cells remain unavailable until those periods have elapsed. Use cohort analysis for mobile apps to explore cohort tables, and see how a retention curve presents return behavior over time. To measure your own app’s events and conversion activity, see ActivationPal.