The number of launches for the selected report period.
For mobile apps, a launch is considered a new one if the app has been inactive on a device for 30 seconds (by default). For example, it happens when the app is launched 30 seconds after the phone was locked or the app went into the background mode.
For websites, a new launch is a view when more than 30 minutes have passed since the last view.
Launches – Flow metric
Launches CA – Current Attribution metric
Launches LT – LifeTime metric
Launches AT – Attribution Time metric
The number of launches for the selected report period.
For mobile apps, a launch is considered a new one if the app has been inactive on a device for 30 seconds (by default). For example, it happens when the app is launched 30 seconds after the phone was locked or the app went into the background mode.
For websites, a new launch is a view when more than 30 minutes have passed since the last view.
Launches – Flow metric
Launches CA – Current Attribution metric
Launches LT – LifeTime metric
Launches AT – Attribution Time metric
The number of app launches made on a platform for the selected report period.
A launch is considered a new one if the app has been inactive on a device for 30 seconds (by default). For example, it happens when the app is launched 30 seconds after the app went into the background mode.
Launches – Flow metric
Launches CA – Current Attribution metric
Launches LT – LifeTime metric
Launches AT – Attribution Time metric
The total number of authorisations on a device during the selected report period. It's a sum of Login events, tracked by MyTracker with device ID.
To log the Authorisation events, you need to configure SDK for iOS, Android, Unity, Flutter, React Native, Web platforms, or send events via S2S API.
Authorisations – Flow metric
Authorisations CA – Current Attribution metric
Authorisations LT – LifeTime metric
Authorisations AT – Attribution Time metric
The total number of authorisations during the selected report period. It's a sum of Login events, tracked by MyTracker with user ID.
To log the Authorisation events, you need to configure SDK for iOS, Android, Unity, React Native, Web platforms, or send events via S2S API.
Authorisations – Flow metric
Authorisations CA – Current Attribution metric
Authorisations LT – LifeTime metric
Authorisations AT – Attribution Time metric
The number of platform users who are authorized in the application during the report period.
Authorisations – Flow metric
Authorisations CA – Current Attribution metric
Authorisations LT – LifeTime metric
Authorisations AT – Attribution Time metric
The number of project users who are authorized in the application for the first time during the report period. In the project, a user can authorize from different devices, but only one of these authorizations will be counted as the first one.
To log the Authorisation events, you need to configure SDK for iOS, Android, Unity, Flutter, React Native, Web platforms, or send events via S2S API
First authorisations – Flow metric
First authorisations CA – Current Attribution metric
First authorisations LT – LifeTime metric
First authorisations AT – Attribution Time metric
The number of platform users who are authorized in the application for the first time during the report period.
In the project, a user can authorize from different devices, but only one of these authorizations will be counted as the first one.
First authorisations – Flow metric
First authorisations CA – Current Attribution metric
First authorisations LT – LifeTime metric
First authorisations AT – Attribution Time metric
The total number of sessions over the selected time period.
The session is a time interval, during which a user continues to interact with a website or mobile app. MyTracker logs the session after the user ends the session and starts a new one.
For mobile apps, the session starts with the launch and stops
when the application goes to the background for more than 30 seconds.
You can change this interval
by configuring the LaunchTimeout parameter of MyTracker SDK.
For websites, the session starts with a site visit and stops when more than 30 minutes have passed since the last activity. You can change this interval through the session timeout setting.
Sessions – Flow metric
Sessions CA – Current Attribution metric
Sessions LT – LifeTime metric
Sessions AT – Attribution Time metric
The total number of sessions over the selected time period.
The session is a time interval, during which a user continues to interact with a website or mobile app. MyTracker logs the session after the user ends the session and starts a new one.
For mobile apps, the session starts with the launch and stops
when the application goes to the background for more than 30 seconds.
You can change this interval
by configuring the LaunchTimeout parameter of MyTracker SDK.
For websites, the session starts with a site visit and stops when more than 30 minutes have passed since the last activity. You can change this interval through the session timeout setting.
Sessions – Flow metric
Sessions CA – Current Attribution metric
Sessions LT – LifeTime metric
Sessions AT – Attribution Time metric
The total number of broken sessions over the selected report period.
Session is considered to be broken if we do not know it's stop time. For example, when an app crashes or the OS forces an app to stop.
The session is a time interval, during which a user continues to interact with a website or mobile app. MyTracker logs the session after the user ends the session and starts a new one.
For mobile apps, the session starts with the launch and stops
when the application goes to the background for more than 30 seconds.
You can change this interval
by configuring the LaunchTimeout parameter of MyTracker SDK.
For websites, the session starts with a site visit and stops when more than 30 minutes have passed since the last activity. You can change this interval through the session timeout setting.
Broken sessions – Flow metric
Broken sessions CA – Current Attribution metric
Broken sessions LT – LifeTime metric
Broken sessions AT – Attribution Time metric
The total number of broken sessions over the selected report period.
Session is considered to be broken if we do not know it's completion time. For example, when an app crashes or the OS forces an app to stop.
The session is a time interval, during which a user continues to interact with a website or mobile app. MyTracker logs the session after the user ends the session and starts a new one.
For mobile apps, the session starts with the launch and stops
when the application goes to the background for more than 30 seconds.
You can change this interval
by configuring the LaunchTimeout parameter of MyTracker SDK.
For websites, the session starts with a site visit and stops when more than 30 minutes have passed since the last activity. You can change this interval through the session timeout setting.
Broken sessions – Flow metric
Broken sessions CA – Current Attribution metric
Broken sessions LT – LifeTime metric
Broken sessions AT – Attribution Time metric
The number of sessions from different devices.
The session is a time interval, during which a user continues to interact with a website or mobile app. MyTracker logs the session after the user ends the session and starts a new one.
For mobile apps, the session starts with the launch and stops
when the application goes to the background for more than 30 seconds.
You can change this interval
by configuring the LaunchTimeout parameter of MyTracker SDK.
For websites, the session starts with a site visit and stops when more than 30 minutes have passed since the last activity. You can change this interval through the session timeout setting.
Unique sessions – Flow metric
Unique sessions CA – Current Attribution metric
Unique sessions LT – LifeTime metric
Unique sessions AT – Attribution Time metric
The number of sessions made by different users.
The session is a time interval, during which a user continues to interact with a website or mobile app. MyTracker logs the session after the user ends the session and starts a new one.
For mobile apps, the session starts with the launch and stops
when the application goes to the background for more than 30 seconds.
You can change this interval
by configuring the LaunchTimeout parameter of MyTracker SDK.
For websites, the session starts with a site visit and stops when more than 30 minutes have passed since the last activity. You can change this interval through the session timeout setting.
Unique sessions – Flow metric
Unique sessions CA – Current Attribution metric
Unique sessions LT – LifeTime metric
Unique sessions AT – Attribution Time metric
The average session duration in seconds during the specified period.
Avg. session dur. = total duration of all sessions / number of sessions (rounded down).
The session is a time interval, during which a user continues to interact with a website or mobile app. MyTracker logs the session after the user ends the session and starts a new one.
For mobile apps, the session starts with the launch and stops
when the application goes to the background for more than 30 seconds.
You can change this interval
by configuring the LaunchTimeout parameter of MyTracker SDK.
For websites, the session starts with a site visit and stops when more than 30 minutes have passed since the last activity. You can change this interval through the session timeout setting.
Avg. session dur., sec – Flow metric
Avg. session dur., sec CA – Current Attribution metric
Avg. session dur., sec LT – LifeTime metric
Avg. session dur., sec AT – Attribution Time metric
The average session duration in seconds during the specified period.
Avg. session dur. = total duration of all sessions / number of sessions (rounded down).
The session is a time interval, during which a user continues to interact with a website or mobile app. MyTracker logs the session after the user ends the session and starts a new one.
For mobile apps, the session starts with the launch and stops
when the application goes to the background for more than 30 seconds.
You can change this interval
by configuring the LaunchTimeout parameter of MyTracker SDK.
For websites, the session starts with a site visit and stops when more than 30 minutes have passed since the last activity. You can change this interval through the session timeout setting.
Avg. session dur., sec – Flow metric
Avg. session dur., sec CA – Current Attribution metric
Avg. session dur., sec LT – LifeTime metric
Avg. session dur., sec AT – Attribution Time metric
The median session duration in seconds during the specified period.
Median session duration is defined by the number that divides a sorted ascending list of durations of all sessions in half (excluding broken sessions). For example, if durations are -1 (broken), 1 sec, 5 sec, 6 sec, then the median session duration is 5 sec.
The session is a time interval, during which a user continues to interact with a website or mobile app. MyTracker logs the session after the user ends the session and starts a new one.
For mobile apps, the session starts with the launch and stops
when the application goes to the background for more than 30 seconds.
You can change this interval
by configuring the LaunchTimeout parameter of MyTracker SDK.
For websites, the session starts with a site visit and stops when more than 30 minutes have passed since the last activity. You can change this interval through the session timeout setting.
Median session dur., sec. – Flow metric
Median session dur., sec. CA – Current Attribution metric
Median session dur., sec. LT – LifeTime metric
Median session dur., sec. AT – Attribution Time metric
The median session duration in seconds during the specified period.
Median session duration is defined by the number that divides a sorted ascending list of durations of all sessions in half (excluding broken sessions). For example, if durations are -1 (broken), 1 sec, 5 sec, 6 sec, then the median session duration is 5 sec.
The session is a time interval, during which a user continues to interact with a website or mobile app. MyTracker logs the session after the user ends the session and starts a new one.
For mobile apps, the session starts with the launch and stops
when the application goes to the background for more than 30 seconds.
You can change this interval
by configuring the LaunchTimeout parameter of MyTracker SDK.
For websites, the session starts with a site visit and stops when more than 30 minutes have passed since the last activity. You can change this interval through the session timeout setting.
Median session dur., sec. – Flow metric
Median session dur., sec. CA – Current Attribution metric
Median session dur., sec. LT – LifeTime metric
Median session dur., sec. AT – Attribution Time metric
The average session duration in seconds per device during the specified period.
Avg. session dur. per device = sum of average sessions durations of each device / number of devices.
The session is a time interval, during which a user continues to interact with a website or mobile app. MyTracker logs the session after the user ends the session and starts a new one.
For mobile apps, the session starts with the launch and stops
when the application goes to the background for more than 30 seconds.
You can change this interval
by configuring the LaunchTimeout parameter of MyTracker SDK.
For websites, the session starts with a site visit and stops when more than 30 minutes have passed since the last activity. You can change this interval through the session timeout setting.
Avg. unique session dur., sec. – Flow metric
Avg. unique session dur., sec. CA – Current Attribution metric
Avg. unique session dur., sec. LT – LifeTime metric
Avg. unique session dur., sec. AT – Attribution Time metric
The average session duration in seconds per user during the specified period.
Avg. session dur. per user = sum of average sessions durations of each user / number of users.
The session is a time interval, during which a user continues to interact with a website or mobile app. MyTracker logs the session after the user ends the session and starts a new one.
For mobile apps, the session starts with the launch and stops
when the application goes to the background for more than 30 seconds.
You can change this interval
by configuring the LaunchTimeout parameter of MyTracker SDK.
For websites, the session starts with a site visit and stops when more than 30 minutes have passed since the last activity. You can change this interval through the session timeout setting.
Avg. unique session dur., sec. – Flow metric
Avg. unique session dur., sec. CA – Current Attribution metric
Avg. unique session dur., sec. LT – LifeTime metric
Avg. unique session dur., sec. AT – Attribution Time metric
The median session duration in seconds per device during the specified period.
Median session duration per device is defined by the number that divides a sorted ascending list of median sessions durations of each device in half (excluding broken sessions).
The session is a time interval, during which a user continues to interact with a website or mobile app. MyTracker logs the session after the user ends the session and starts a new one.
For mobile apps, the session starts with the launch and stops
when the application goes to the background for more than 30 seconds.
You can change this interval
by configuring the LaunchTimeout parameter of MyTracker SDK.
For websites, the session starts with a site visit and stops when more than 30 minutes have passed since the last activity. You can change this interval through the session timeout setting.
Median unique session dur., sec. – Flow metric
Median unique session dur., sec. CA – Current Attribution metric
Median unique session dur., sec. LT – LifeTime metric
Median unique session dur., sec. AT – Attribution Time metric
The median session duration in seconds per user during the specified period.
Median session duration per user is defined by the number that divides a sorted ascending list of median sessions durations of each user in half (excluding broken sessions).
The session is a time interval, during which a user continues to interact with a website or mobile app. MyTracker logs the session after the user ends the session and starts a new one.
For mobile apps, the session starts with the launch and stops
when the application goes to the background for more than 30 seconds.
You can change this interval
by configuring the LaunchTimeout parameter of MyTracker SDK.
For websites, the session starts with a site visit and stops when more than 30 minutes have passed since the last activity. You can change this interval through the session timeout setting.
Median unique session dur., sec. – Flow metric
Median unique session dur., sec. CA – Current Attribution metric
Median unique session dur., sec. LT – LifeTime metric
Median unique session dur., sec. AT – Attribution Time metric
Percentage of single-page sessions out of the total number over the selected report period.
A single-page session is considered as a session, in which interaction with a web app on a device was cancelled from the first page.
Percentage of single-page sessions out of the total number over the selected report period.
A single-page session is considered as a session, in which a user left a web app from the first page.
The average number of pages visited on a device.
The average number of pages visited by a user.
The total number of pageviews during the selected report period (for Web only)
Pageviews Flow – Flow metric
Pageviews CA – Current Attribution metric
Pageviews LT – LifeTime metric
Pageviews AT – Attribution Time metric
The total number of pageviews during the selected report period (for Web only)
Pageviews – Flow metric
Pageviews CA – Current Attribution metric
Pageviews LT – LifeTime metric
Pageviews AT – Attribution Time metric
The total number of application version updates occurred during the selected report period.
App updates – Flow metric
App updates CA – Current Attribution metric
App updates LT – LifeTime metric
App updates AT – Attribution Time metric
The average number of active days per device for the selected report period. An active day is a day for which at least one event on the device was logged: a registration, authorization, launch, pageview, in-app impression, or payments.
Payment includes a purchase, subscription, subscription renewal, or custom revenue
Activity days Flow – Flow metric
Activity days CA – Current Attribution metric
Activity days LT – LifeTime metric
Activity days AT – Attribution Time metric
The average number of active days per user for the selected report period. An active day is a day for which at least one user action was logged: a registration, authorization, launch, pageview, in-app impression, or payment.
Payment includes a purchase, subscription, subscription renewal, or custom revenue
Activity days Flow – Flow metric
Activity days CA – Current Attribution metric
Activity days LT – LifeTime metric
Activity days AT – Attribution Time metric
The average number of active days per platform user for the selected report period. An active day is a day for which at least one user action was logged: a registration, launch, or payment.
Activity days Flow – Flow metric
Activity days LT – LifeTime metric
The number of devices for which at least one event was logged during the selected period: a registration, authorization, launch, pageview, in-app impression, or payment.
Payment includes a purchase, subscription, subscription renewal, or custom revenue
Active devices – Flow metric
Active devices CA – Current Attribution metric
Active devices LT – LifeTime metric
Active devices AT – Attribution Time metric
The number of users for whom at least one event was logged during the selected period: a registration, authorization, launch, pageview, in-app impression, or payment.
Payment includes a purchase, subscription, subscription renewal, or custom revenue
Active users – Flow metric
Active users CA – Current Attribution metric
Active users LT – LifeTime metric
Active users AT – Attribution Time metric
The number of platform users for whom at least one event was logged during the selected period: a registration, app launch, or payment.
Active users – Flow metric
Active users LT – LifeTime metric
DAU — the number of active devices per day.
On a daily basis, system computes the number of active devices. Average value of this metric for aggregation period would be the DAU value.
DAU – Flow metric
DAU CA – Current Attribution metric
DAU — the number of active users per day.
On a daily basis, system computes the number active users. Average value of this metric for report period would be the DAU value.
DAU – Flow metric
DAU CA – Current Attribution metric
DAU — the number of active platform users per day.
On a daily basis, system computes the number active users. Average value of this metric for report period would be the DAU value.
DAU – Flow metric
WAU —
the average number of active devices per the last 7 days.
On a daily basis, system computes the number of devices tah has been active for the last 7 days.
Average of the present measure for report period would be WAU.
In other words, WAU is computed using moving 7 days window. For example, if the report is aggregated by days, than WAU for 2025-10-31 would show the number of devices has been active between 2025-10-25 and 2025-10-31 inclusive.
This metric is more complicated than WAU in the classic sense.
Note new metrics
WAU per week and WAU per 7 days
WAU – Flow metric
WAU CA – Current Attribution metric
WAU per week is the number of active devices in one calendar week (Mon, Tue, etc.).
In contrast to the WAU metric, WAU per week shows the actual number of devices and processes data for the selected report period:
| Report period | WAU per week/ WAU |
|---|---|
|
Mon 09/01 - Sun 09/07 |
WAU per week: devices that were active from 09/01 to 09/07 WAU: average value of the active devices calculated from 08/26 to 09/07 |
| Mon 09/01 - Thu 09/04 |
WAU per week: devices that were active from 09/01 to 09/04 WAU: average value of the active devices calculated from 08/26 to 09/04 |
| Thu 09/04 - Wed 09/10 |
WAU per week: average value of WAU Thu-Sun and WAU Mon-Wed WAU: average value of the active devices calculated from 08/29 to 09/10 |
| Mon 09/01 - Sun 09/14 |
WAU per week: average value of WAU 09/01-09/07 and WAU 09/08-09/14 WAU: average value of the active devices calculated from 08/26 to 09/14 |
WAU per week – Flow metric
WAU per week CA – Current Attribution metric
WAU per 7 days is the number of active devices in 7 days.
In contrast to the WAU metric, WAU per 7 days shows the actual number of devices and processes data for the selected report period:
| Report period | WAU per 7 days/ WAU |
|---|---|
|
Mon 09/01 - Sun 09/07 |
WAU per 7 days: devices that were active from 09/01 to 09/07 WAU: average value of the active devices calculated from 08/26 to 09/07 |
|
Mon 09/01 - Thu 09/04 |
WAU per 7 days: devices that were active from 09/01 to 09/04 WAU: average value of the active devices calculated from 08/26 to 09/04 |
| Thu 09/04 - Wed 09/10 |
WAU per 7 days: devices that were active from 09/04 to 09/10 WAU: average value of the active devices calculated from 08/29 to 09/10 |
| Mon 09/01 - Sun 09/14 |
WAU per 7 days: average value of WAU 09/01-09/07 and WAU 09/08-09/14 WAU: average value of the active devices calculated from 08/26 to 09/14 |
WAU per 7 days – Flow metric
WAU per 7 days CA – Current Attribution metric
WAU —
the average number of active users per the last 7 days.
On a daily basis, system computes the number of users been active for the last 7 days.
Average of the present measure for report period would be WAU.
In other words, WAU is computed using moving 7 days window. For example, if the report is aggregated by days, than WAU for 2025-10-31 would show the number of users has been active between 2025-10-25 and 2025-10-31 inclusive.
This metric is more complicated than WAU in the classic sense.
Note new metrics
WAU per week and WAU per 7 days
WAU – Flow metric
WAU CA – Current Attribution metric
WAU per week is the number of active users in one calendar week (Mon, Tue, etc.).
In contrast to the WAU metric, WAU per week shows the actual number of users and processes data for the selected report period:
| Report period | WAU per week/ WAU |
|---|---|
|
Mon 09/01 - Sun 09/07 |
WAU per week: users who were active from 09/01 to 09/07 WAU: average value of the active users calculated from 08/26 to 09/07 |
| Mon 09/01 - Thu 09/04 |
WAU per week: users who were active from 09/01 to 09/04 WAU: average value of the active users calculated from 08/26 to 09/04 |
| Thu 09/04 - Wed 09/10 |
WAU per week: average value of WAU Thu-Sun and WAU Mon-Wed WAU: average value of the active users calculated from 08/29 to 09/10 |
| Mon 09/01 - Sun 09/14 |
WAU per week: average value of WAU 09/01-09/07 and WAU 09/08-09/14 WAU: average value of the active users calculated from 08/26 to 09/14 |
WAU per week – Flow metric
WAU per week CA – Current Attribution metric
WAU per 7 days is the number of active users in 7 days.
In contrast to the WAU metric, WAU per 7 days shows the actual number of users and processes data for the selected report period:
| Report period | WAU per 7 days/ WAU |
|---|---|
|
Mon 09/01 - Sun 09/07 |
WAU per 7 days: users who were active from 09/01 to 09/07 WAU: average value of the active users calculated from 08/26 to 09/07 |
|
Mon 09/01 - Thu 09/04 |
WAU per 7 days: users who were active from 09/01 to 09/04 WAU: average value of the active users calculated from 08/26 to 09/04 |
| Thu 09/04 - Wed 09/10 |
WAU per 7 days: users who were active from 09/04 to 09/10 WAU: average value of the active users calculated from 08/29 to 09/10 |
| Mon 09/01 - Sun 09/14 |
WAU per 7 days: average value of WAU 09/01-09/07 and WAU 09/08-09/14 WAU: average value of the active users calculated from 08/26 to 09/14 |
WAU per 7 days – Flow metric
WAU per 7 days CA – Current Attribution metric
WAU —
the average number of active platform users per the last 7 days.
On a daily basis, system computes the number of users been active for the last 7 days.
Average of the present measure for report period would be WAU.
In other words, WAU is computed using moving 7 days window. For example, if the report is aggregated by days, than WAU for 2025-10-31 would show the number of users has been active between 2025-10-25 and 2025-10-31 inclusive.
This metric is more complicated than WAU in the classic sense.
Note new metrics
WAU per week and WAU per 7 days
WAU – Flow metric
WAU per week is the number of active platform users in one calendar week (Mon, Tue, etc.).
In contrast to the WAU metric, WAU per week shows the actual number of users and processes data for the selected report period:
| Report period | WAU per week/ WAU |
|---|---|
|
Mon 09/01 - Sun 09/07 |
WAU per week: users who were active from 09/01 to 09/07 WAU: average value of the active users calculated from 08/26 to 09/07 |
| Mon 09/01 - Thu 09/04 |
WAU per week: users who were active from 09/01 to 09/04 WAU: average value of the active users calculated from 08/26 to 09/04 |
| Thu 09/04 - Wed 09/10 |
WAU per week: average value of WAU Thu-Sun and WAU Mon-Wed WAU: average value of the active users calculated from 08/29 to 09/10 |
| Mon 09/01 - Sun 09/14 |
WAU per week: average value of WAU 09/01-09/07 and WAU 09/08-09/14 WAU: average value of the active users calculated from 08/26 to 09/14 |
WAU per week – Flow metric
WAU per 7 days is the number of active platform users in 7 days.
In contrast to the WAU metric, WAU per 7 days shows the actual number of users and processes data for the selected report period:
| Report period | WAU per 7 days/ WAU |
|---|---|
|
Mon 09/01 - Sun 09/07 |
WAU per 7 days: users who were active from 09/01 to 09/07 WAU: average value of the active users calculated from08/26 to 09/07 |
|
Mon 09/01 - Thu 09/04 |
WAU per 7 days: users who were active from 09/01 to 09/04 WAU: average value of the active users calculated from 08/26 to 09/04 |
| Thu 09/04 - Wed 09/10 |
WAU per 7 days: users who were active from 09/04 to 09/10 WAU: average value of the active users calculated from 08/29 to 09/10 |
| Mon 09/01 - Sun 09/14 |
WAU per 7 days: average value of WAU 09/01-09/07 and WAU 09/08-09/14 WAU: average value of the active users calculated from 08/26 to 09/14 |
WAU per 7 days – Flow metric
MAU —
the average number of active devices per the last 30 days.
On a daily basis, system computes the number devices that has been active for the last 30 days.
Average of the present measure for report period would be MAU.
In other words, MAU is computed using moving 30 days window. For example, if the report is aggregated by days, than MAU for 2025-10-31 would show the number of devices been active between 2025-10-02 and 2025-10-31.
This metric is more complicated than MAU in the classic sense.
Note new metrics
MAU per month and MAU per 30 days
MAU – Flow metric
MAU CA – Current Attribution metric
MAU per month is the number of active devices in one calendar month (Jan, Feb, etc.).
In contrast to the MAU metric, MAU per month shows the actual number of devices and processes data for the selected report period:
| Report period | MAU per month/ MAU |
|---|---|
| 10/01 - 10/31 |
MAU per month: devices that were active from 10/01 to 10/31 MAU: average value of the active devices calculated from 09/02 to 10/31 |
| 10/01 - 10/14 |
MAU per month: devices that were active from 10/01 to 10/14 MAU: average value of the active devices calculated from 09/02 to 10/14 |
| 09/14 - 10/15 | MAU per month: average value of MAU 09/14-09/30 and MAU 10/01-10/15 MAU: average value of the active devices calculated from 08/16 to 10/15 |
| 09/01 - 10/31 | MAU per month: average value of MAU 09/01-09/30 and MAU 10/01-10/31 MAU: average value of the active devices calculated from 08/03 to 10/31 |
MAU per month – Flow metric
MAU per month CA – Current Attribution metric
MAU per 30 days is the number of active devices in 30 days.
In contrast to the MAU metric, MAU per 30 days shows the actual number of devices and processes data for the selected report period:
| Report period | MAU per 30 days/ MAU |
|---|---|
| 09/01 - 09/30 |
MAU per 30 days: devices that were active from 09/01 to 09/30 MAU: average value of the active devices calculated from 08/03 to 09/30 |
| 10/01 - 10/31 |
MAU per 30 days: average value of MAU 10/01-10/30 and MAU 10/31 MAU: average value of the active devices calculated from 09/02 to 10/31 |
| 10/01 - 10/14 |
MAU per 30 days: devices that were active from 10/01 to 10/14 MAU: average value of the active devices calculated from 09/02 to 10/14 |
| 09/14 - 10/15 | MAU per 30 days: devices that were active from 09/14 to 10/15 MAU: average value of the active devices calculated from 08/16 to 10/15 |
| 09/01 - 10/31 | MAU per 30 days: average value of MAU 09/01-09/30, MAU 10/01-10/30 and MAU 10/31 MAU: average value of the active devices calculated from 08/03 to 10/31 |
MAU per 30 days – Flow metric
MAU per 30 days CA – Current Attribution metric
MAU —
the average number of active users per the last 30 days.
On a daily basis, system computes the number of users been active for the last 30 days.
Average of the present measure for report period would be MAU.
In other words, MAU is computed using moving 30 days window. For example, if the report is aggregated by days, than MAU for 2025-10-31 would show the number of users been active between 2025-10-02 and 2025-10-31.
This metric is more complicated than MAU in the classic sense.
Note new metrics
MAU per month and MAU per 30 days
MAU – Flow metric
MAU CA – Current Attribution metric
MAU per month is the number of active users in one calendar month (Jan, Feb, etc.).
In contrast to the MAU metric, MAU per month shows the actual number of users and processes data for the selected report period:
| Report period | MAU per month/ MAU |
|---|---|
| 10/01 - 10/31 |
MAU per month: users who were active from 10/01 to 10/31 MAU: average value of the active users calculated from 09/02 to 10/31 |
| 10/01 - 10/14 |
MAU per month: users who were active from 10/01 to 10/14 MAU: average value of the active users calculated from 09/02 to 10/14 |
| 09/14 - 10/15 | MAU per month: average value of MAU 09/14-09/30 and MAU 10/01-10/15 MAU: average value of the active users calculated from 08/16 to 10/15 |
| 09/01 - 10/31 | MAU per month: average value of MAU 09/01-09/30 and MAU 10/01-10/31 MAU: average value of the active users calculated from 08/03 to 31/10 |
MAU per month – Flow metric
MAU per month CA – Current Attribution metric
MAU per 30 days is the number of active users in 30 days.
In contrast to the MAU metric, MAU per 30 days shows the actual number of users and processes data for the selected report period:
| Report period | MAU per 30 days/ MAU |
|---|---|
| 09/01 - 09/30 |
MAU per 30 days: users who were active from 09/01 to 09/30 MAU: average value of the active users calculated from 08/03 to 09/30 |
| 10/01 - 10/31 |
MAU per 30 days: average value of MAU 10/01-10/30 and MAU 10/31 MAU: average value of the active users calculated from 09/02 to 10/31 |
| 10/01 - 10/14 |
MAU per 30 days: users who were active from 10/01 to 10/14 MAU: average value of the active users calculated from 09/02 to 10/14 |
| 09/14 - 10/15 | MAU per 30 days: users who were active from 09/14 to 10/15 MAU: average value of the active users calculated from 08/16 to 10/15 |
| 09/01 - 10/31 | MAU per 30 days: average value of MAU 09/01-09/30, MAU 10/01-10/30 and MAU 10/31 MAU: average value of the active users calculated from 08/03 to 10/31 |
MAU per 30 days – Flow metric
MAU per 30 days CA – Current Attribution metric
MAU —
the average number of active platform users per the last 30 days.
On a daily basis, system computes the number of users been active for the last 30 days.
Average of the present measure for report period would be MAU.
In other words, MAU is computed using moving 30 days window. For example, if the report is aggregated by days, than MAU for 2025-10-31 would show the number of users been active between 2025-10-02 and 2025-10-31.
This metric is more complicated than MAU in the classic sense.
Note new metrics
MAU per month and MAU per 30 days
MAU – Flow metric
MAU per month is the number of active platform users in one calendar month (Jan, Feb, etc.).
In contrast to the MAU metric, MAU per month shows the actual number of users and processes data for the selected report period:
| Report period | MAU per month/ MAU |
|---|---|
| 10/01 - 10/31 |
MAU per month: users who were active from 10/01 to 10/31 MAU: average value of the active users calculated from 09/02 to 10/31 |
| 10/01 - 10/14 |
MAU per month: users who were active from 10/01 to 10/14 MAU: average value of the active users calculated from 09/02 to 10/14 |
| 09/14 - 10/15 | MAU per month: average value of MAU 09/14-09/30 and MAU 10/01-10/15 MAU: average value of the active users calculated from 08/16 to 10/15 |
| 09/01 - 10/31 | MAU per month: average value of MAU 09/01-09/30 and MAU 10/01-10/31 MAU: average value of the active users calculated from 08/03 to 10/31 |
MAU per month – Flow metric
MAU per 30 days is the number of active platform users in 30 days.
In contrast to the MAU metric, MAU per 30 days shows the actual number of users and processes data for the selected report period:
| Report period | MAU per 30 days/ MAU |
|---|---|
| 09/01 - 09/30 |
MAU per 30 days: users who were active from 09/01 to 09/30 MAU: average value of the active users calculated from 08/03 to 09/30 |
| 10/01 - 10/31 |
MAU per 30 days: average value of MAU 10/01-10/30 and MAU 10/31 MAU: average value of the active users calculated from 09/02 to 10/31 |
| 10/01 - 10/14 |
MAU per 30 days: users who were active from 10/01 to 10/14 MAU: average value of the active users calculated from 09/02 to 10/14 |
| 09/14 - 10/15 | MAU per 30 days: users who were active from 09/14 to 10/15 MAU: average value of the active users calculated from 08/16 to 10/15 |
| 09/01 - 10/31 | MAU per 30 days: average value of MAU 09/01-09/30, MAU 10/01-10/30 and MAU 10/31 MAU: average value of the active users calculated from 08/03 to 10/31 |
MAU per 30 days – Flow metric
