All Products
Search
Document Center

Calculation rules for basic indicators

Last Updated: Jun 17, 2021

The following tables list the tracking and calculation rules of all the basic indicators that you see in the basic analysis reports. You might see all or some of the following indicators, which is subject to your actual workspace.

Note: If an indicator is time-sensitive, the value of the indicator is subject to the time the server receives the reported logs.

Data overview

Real-time dashboard

Indicator
Tracking
Calculation rule
Distinct or Not
Realtime or Not
Startup times
Active device/user tracking
Total number of times that users start the app, including cold start and the case that the system brings app activity to the foreground.
Not distinct
Realtime
Active users
Active device/user tracking
Total number of distinct device IDs that log in to the app within a specific period.
Distinct
Realtime
Active accounts
Active device/user tracking
Total number of distinct user IDs that are used to log in to the app within a specific period.
Distinct
Realtime

Historical trend

Indicator
Tracking
Calculation rule
Distinct or Not
Realtime or Not
Startup count
Active device/user tracking
Total number of times that users start the app, including cold start and the case that the system brings app activity to the foreground.
Not distinct
Not real-time
Active users
Active device/user tracking
Total number of distinct device IDs that log in to the app within a specific period.
Distinct
Not realtime
Cumulative users
Active device/user tracking
Total number of users visiting an app after the app connects to Mobile Analysis Service, that is, total number of distinct device IDs.
Distinct
Not realtime
New users
Active device/user tracking
New distinct device IDs that log in to the app within a specific period.
Distinct
Not realtime
Active accounts
Active device/user tracking
Total number of distinct user IDs that are used to log in to the app within a specific period.
Distinct
Not realtime
Cumulative accounts
Active device/user tracking
Total number of distinct user IDs that are used to log in to the app after the app connects to Mobile Analysis Service.
Distinct
Not realtime

Basic analysis

Behavior analysis

Indicator
Tracking
Calculation rule
Distinct or Not
Realtime or Not
Users’ active hours
Backend tracking
A user’s active hours is subject to the time the user starts to use the app, which is calculated based on the time the log is reported minus the backend duration. Active hours are based on two hours’ period starting from 0:00, for example, 2:00~4:00 am.

For example, if a user starts to use the app at 7:55 am and the app goes to backend at 8:05 am, then the user’s active hours are 6:00~8:00 am.
Not distinct
Not realtime
Daily user engagement: duration/day
Backend tracking
Total duration (seconds) of using the app by users divided by the distinct count of user IDs.
The backend tracking records the time when the app page appears on the foreground each time, and calculates the accumulative usage time length of the app based on the time recorded.
Distinct
Not realtime
Page traffic
Page automation tracking
Indicates where a specific page comes from and goes to. Based on the pid and the refer fields, all the source pages and ratio of each source page to all the source pages are shown; all the next pages and ratio of each next page to all the next pages are shown.
Not distinct
Not realtime
Download channels
Active device/user tracking
Top 3 channels from which users download the app, aggregated by the channel field based on active device tracking. Downloading the app for multiple times on the same channel by the same user are counted only once.

For example, if a user downloads the app once from Channel C1 and twice from Channel C2, C1 and C2 are both counted only once.
Distinct
Realtime
Startup speed
Performance tracking
Average startup time for first-time startup and non-first-time startup, in seconds. The first startup refers to starting an app for the first time after the app is installed; non-first startup refers to restarting an app after the first-time app startup and exit.
Not applicable
Realtime
Users by region
Active device/user tracking
Top 5 regions that have most app users (de-duplicated), aggregated by the region field based on active device tracking. Meanwhile, the proportion of users in each top 5 region to the total number of all app users is shown. For map of China, the top 5 provinces are shown; for the world map, the top 5 countries are shown.

For example, for map of China, if a user logged in twice in Province A in the morning and once in Province B in the evening, Province A and B are both counted only once.
Distinct
Realtime

Retention analysis

Indicator
Tracking
Calculation rule
Distinct or Not
Realtime or Not
Retention rate
Active device/user tracking
Retention rate refers to the number of new users who retained in the following 7 days since their first visit to an app on a certain day divided by the total count of new users, shown in the form of line chart.

For example, the count of new users on day T is N, the count of N new users who log in again on day T+1 is M1, and the count of users who log in again on day T+7 is M7. Thus, the retention rate for day T+1 is M1/N, and the rate for day T+7 is M7/N.
Distinct
Not realtime

Page analysis

Indicator
Tracking
Calculation rule
Distinct or Not
Realtime or Not
Users
Page automation tracking
Count the devices (deduplicated by device ID) visiting the current page.
Distinct
Not realtime
Accounts
Page automation tracking
Count the users (deduplicated by user ID) visiting the current page.
Distinct
Not realtime
PV
Page automation tracking
Total page views of the current page.
Not distinct
Not realtime
Exit rate
Page automation tracking
Exit rate = (total non-deduplicated PVs on the current page - non-deduplicated PVs with current page as source page)/total PVs on the current page
Not distinct
Not realtime
Time on page
Page automation tracking
Total time on the current page divided by total PVs on the current page.
Not distinct
Not realtime

Device analysis

Indicator
Tracking
Calculation rule
Distinct or Not
Realtime or Not
Startup times
Active device/user tracking
Total number of times that users start the app by device model, including cold start and the case that the system brings app activity to the foreground, counted by device model.
Not distinct
Not realtime
Active users
Active device/user tracking
Total number of distinct device IDs that log in to the app within a specific period, counted by device model.
Distinct
Not realtime
New users
Active device/user tracking
New distinct device IDs that log in to the app within a specific period, counted by device model.
Distinct
Not realtime
Active accounts
Active device/user tracking
Total number of distinct user IDs that are used to log in to the app within a specific period, counted by device model.
Distinct
Not realtime