The Retention Report analyzes retention rates and the number of retained users who return to your app after a set period from their first visit. Based on the granularity you select, you can view retention rates and the number of retained users by interval for a specific event.
Track Day 1, Day 7, and Day 30 retention trends for newly installed users
Compare retention rates across ad channels to validate campaign performance
Analyze retention patterns at the cohort level, such as users acquired through a specific campaign
Estimate Predictive Lifetime (pLTV) for acquired users
Configure the identifier, cohort, granularity, date range, retention type, Start Event, Return Event, groupby, and filter to view the data you need.
The [Identifier] setting determines how a report counts users.
Device counts users based on the Airbridge Device ID. On Android, the Airbridge Device ID is the best available of GAID and App Set ID. On iOS, it is the best available of IDFA and IDFV. When none is available, the Airbridge SDK uses a randomly generated ID.
User counts users based on the Airbridge ID. The Airbridge ID is generated primarily from the user ID, or from the Airbridge Device ID when no user ID is available.
Note
If no user ID is collected, selecting User returns the same result as selecting Device.
A cohort is the user segment you want to analyze in the Retention Report. In [Cohort], click 'Add' to set a cohort. Define cohort conditions for the Retention Report based on event execution, event type, event execution count, and more. If you don't set a cohort, the report aggregates results for all users.
Granularity is the time unit by which retention rates and the number of retained users are aggregated. Retention Report results are divided into intervals based on the selected granularity. Granularity follows the app timezone.
The Date Range defines the period you view in the Retention Report. The report aggregates data for users who generated a Start Event during this range. Date Range follows the app timezone. Select a date range condition and dates to set the range. The maximum date range varies by granularity.
Minutely: 3 days
Hourly: 7 days
Daily: 184 days
Weekly: 12 weeks
Monthly: 3 months
Warning
Due to the privacy policy, some metrics attributed to Google Ads, Meta Ads, and TikTok For Business before December 21, 2025 are counted as 0 and reported as “unattributed”. For details, refer to FAQ - Real-time Reporting.
Three date range conditions are available.
For 'Last', you can add 'Include Today', 'Include this Month', or 'Offset'. Including today or this month extends the range from n days ago to today or this month. Click 'Offset' and enter a number to shift the range backward by that amount. For example, with granularity Daily and 'Last 30 days', the range covers 30 days ago to 1 day ago. Turn off 'Include Today' and add 'Offset 3 days' to shift the range to 33 days ago through 4 days ago.
Retention Type determines how Airbridge counts users who returned to the service in each interval.
Let’s say you have configured your Retention Report as follows.
Granularity: Daily
Start Event: Installs (App)
Return Event: Any Event (App)
Users A, B, and C installed your app on Day 0. The following table shows the events performed by the users.
User A returned every day from Day 1 to Day 3, User B didn’t return at all, and User C returned only on Day 2.
Depending on the retention type you choose, the number of retained users and the retention rate for Day 1 will differ.
Number of retained users by retention type
When you choose “Return On or After,” User C is included in the data points for Day 1 even though the user didn’t perform a Return Event on Day 1 because Day 2 is the last day the user returned. As a result, the number of retained users for Day 1 is 2, which includes User A and User C.
Retention rate by retention type
The same applies to the retention rate of Day 1, where you can see a higher retention rate for “Return On or After” than “Return On.”
The Retention Report aggregates retention rates and the number of retained users by checking whether users who generated a Start Event also generated a Return Event.
Start Event: An event generated when a user enters the app during the configured date range
Return Event: An event used to determine retention for users who generated a Start Event
Let's say 5 users performed various app events from 2024-04-01 to 2024-04-03 as described in the following table.
Let's say the Retention Report has been configured like the following.
Granularity and date range: Daily, From 2024-04-01 to 2024-04-03
Start Event: Install (App), Deeplink Open (App)
Return Event: Deeplink Open (App), Order Complete (App)
In this case, User A, C, D, E performed the Start Event on 2024-04-01. Among them, User A and User C also performed the Return Event on the same day. As a result, the number of retained users and the retention rate of Day 0 (2024-04-01) is 2 and 50%.
A Start Event is generated when a user enters the app during the configured date range. Users who don't generate a Start Event are excluded from analysis. Available Start Events vary by granularity. You can select multiple Start Events. For example, if you select Install (App) and Deeplink Open (App) as Start Events, only users who install the app or open a deep link are included in the Retention Report.
A Return Event determines retention for users who generated a Start Event. When a user generates a Return Event, the Retention Report treats that user as having returned to the app. Users who don't generate a Return Event or generate an Uninstall (App) event are treated as not retained. Return Events can be standard events or custom events collected at least once. Selecting Any Event (App) as the Return Event lets you view retention for users who generated any event other than Uninstall (App).
You can select multiple Return Events. For example, if you select Add to Cart (App) and View Search Result (App) as Return Events, only users who add items to the cart or view a search result are included in the retention aggregation. The maximum number of intervals returned varies by granularity. When granularity is Minutely or Hourly, the Return Event window is fixed at 60 minutes and 24 hours.
Predictive Lifetime estimates how often a cohort will return to your service in the future. Use Predictive Lifetime to calculate Predictive LTV (pLTV). For details, see Predictive Lifetime.
The Measurement Option determines how many Start Events count toward Return Event measurement. When a user journey contains multiple Start Events, the Measurement Option changes the number of retained users and retention rate.
A user took the following journey.
With the Retention Report configured as follows, the results differ by Measurement Option.
Date Range: 3/1 ~ 3/5
Start Event: Install (App)
Return Event: Any Event (App)
GroupBy: Channel
The Open (App) event performed on 2024-03-05 is attributed to both Channel X and Channel Y.
The Open (App) event is measured as the Return Event of Day 4 of the user journey initiated by the Start Event on 2024-03-01, which is attributed to Channel X.
The Open (App) event is also measured as the Return Event of Day 2 of the user journey initiated by the Start Event on 2024-03-03, which is attributed to Channel Y.
Refer to the table below.
The Open (App) event performed on 2024-03-05 is attributed only to Channel Y. The user journey initiated by the Stat Event that occurred on 2024-03-01 is no longer tracked.
The Open (App) event is not attributed to Channel X.
The Open (App) event is measured as the Return Event of Day 2 of the user journey initiated by the Start Event on 2024-03-03, which is attributed to Channel Y.
Refer to the table below.
The Open (App) event performed on 2024-03-05 is attributed to both Channel X and Channel Y.
The Open (App) event is measured as the Return Event of Day 4 of the user journey initiated by the Start Event on 2024-03-01, which is attributed to Channel X.
The Open (App) event is also measured as the Return Event of Day 2 of the user journey initiated by the Start Event on 2024-03-03, which is attributed to Channel Y.
Refer to the table below.
The Open (App) event performed on 2024-03-05 is attributed only to Channel Y. The user journey initiated by the Stat Event that occurred on 2024-03-01 is no longer tracked.
The Open (App) event is not attributed to Channel X.
The Open (App) event is measured as the Return Event of Day 2 of the user journey initiated by the Start Event on 2024-03-03, which is attributed to Channel Y.
Refer to the table below.
This setting determines how Day N is calculated, starting from Day 0 (the start event) to Day N. Based on your selection, Day N will be split either by calendar date or on a 24-hour basis starting from the event time.
A GroupBy divides metrics by a chosen dimension. The Retention Report breaks down metrics based on the selected GroupBy. For example, select Channel to view metrics by ad channel. You can select up to 6 GroupBys. GroupBy applies to Start Events.
A Filter narrows the report to specific GroupBy values. Filters use the format A is B, where A is a GroupBy and B is the value to filter on. Only values collected at least once in Airbridge appear in the value search results. 'is' is the default condition. All available conditions are listed below.
Once configuration is complete, view your results as a chart and a table.
Review interval values for the selected metric in a line chart. Hover over empty space on the chart to see all values for that interval by item. Hover over a single line to see only that item's value. Click an item in the legend below the chart to show or hide it.
Review interval values for the selected metric in a table.
The table consists of top rows and sub-rows. Also see Retention Report calculation method.
Top row: Shows retention data for the entire date range. Top rows extend from the configured start date through the day you view the report, up to the maximum number of intervals.
Sub-row: Shows retention data broken down by granularity.
Top rows and sub-rows share the same maximum number of intervals. Depending on when you view the report, top rows may provide more intervals than sub-rows. Some intervals may also be shorter than the standard interval unit. When granularity is Minutely or Hourly, sub-rows are not provided. Airbridge provides only the aggregated total of sub-row data instead.
Even for the same date range, the number of top-row intervals changes depending on when you view the report. The number of sub-row intervals stays the same regardless of query time, as long as the date range and granularity match. For example, if the configured date range is January 1 (Fri) to January 11 (Tue), the top-row and sub-row interval counts are as follows.
GroupBy availability in sub-rows depends on the configured granularity.
Daily, Weekly, Monthly: View GroupBy results in sub-rows. For example, with GroupBy set to Channel, view per-channel data such as unattributed, A channel, and B channel in sub-rows by date.
Minutely, Hourly: GroupBy results are not shown in sub-rows. The Retention Report aggregates and shows totals across each GroupBy value instead.
View Retention Report results in the table. Each cell shows the retention rate and the number of retained users for a specific interval after the user generated the Start Event. For example, the Day 3 retention rate is the rate 3 days after Day 0, when the user generated the Start Event.
Click the expand (>) icon on the far left of the table to view retention rates and the number of retained users by date. The expand icon changes to a collapse (⌵) icon. When granularity is Minutely or Hourly, the expand icon is hidden because date-level breakdowns are not available.
Top-row retention rate (%) = Σ {(sub-row retention rate) × (weight of users who generated the Start Event in each sub-row)}
Sub-row retention rate by interval (%) = (number of retained users in the interval of each sub-row) ÷ (number of Start Events in each sub-row) × 100
Sub-row retained users: The number of users who generated a Return Event among those who generated the Start Event in that interval.
Top-row retained users: The number of unique users who generated a Return Event across all sub-rows. As a result, the top-row count is less than or equal to the sum of the sub-row counts.
View Predictive Lifetime in the Predictive Lifetime column.
Share your results using the following features.
A Sharelink is a URL for downloading a CSV file with Actuals Report data. Generate a Sharelink by clicking the share button to the right of the report name. Sharelinks are only available in [Saved Reports]. For details, see Share retention data in real time via Sharelink.
Specifications and limitations of the Retention Report.
The following features are common across reports. Some features are not available in every report.
Keep the following in mind.
Under Meta's privacy policy, some Meta Ads (facebook.business) data viewed during the configured date range is masked if you have not agreed to the AMM (Advanced Mobile Measurement) terms. Masking applies under these conditions.
The sum of Impressions and Engaged Views generated by the Meta Ads campaign is less than 1,000
The data is provided through Meta Ads channel or cost integration
Masked data is excluded from aggregation in the report and displays as follows.
Note
To view all Meta Ads campaign data in reports, agree to Meta's AMM Terms. For details, see FAQ - Meta Business.
If Meta Ads data still appears masked after agreeing to the terms, try the following.
Change or extend the date range. Only data generated after agreement is provided in original form.
Change or remove some GroupBys and Filters.
Whether GroupBy results are available at the date level depends on granularity. When granularity is Minutely or Hourly, date-level data is not available in GroupBy results.
Granularity | Interval unit | Maximum number of intervals |
|---|---|---|
Minutely | 1 minute | 60 (Minute 0 ~ Minute 59) |
Hourly | 1 hour | 24 (Hour 0 ~ Hour 23) |
Daily | 1 day (24 hours) | 181 (Day 0 ~ Day 180) |
Weekly | 7 days from the start day of the week | 53 (Week 0 ~ Week 52) |
Monthly | 1 month | 37 (Month 0 ~ Month 36) |
Condition | Reference dates | Date range |
|---|---|---|
Between | Start date, end date | From the start date to the end date |
Since | Start date | From the start date to today |
Last | Number (n) | From n days (weeks, months) ago to yesterday |
Retention Type | Measurement criteria | Use case |
|---|---|---|
Return On | Counts only users who actually generated a Return Event in that interval as returned users | Measure retention based on the exact date users returned |
Return On or After | Counts a user as returned in every interval from the first interval through the interval where they last generated a Return Event | Measure cumulative retention from acquisition to last activity |
User | Day 0 | Day 1 | Day 2 | Day 3 |
|---|---|---|---|---|
A | Installs (App) | Any Event (App) | Any Event (App) | Any Event (App) |
B | Installs (App) | No action | No action | No action |
C | Installs (App) | No action* | Any Event (App) | No action |
Retention Type | Day 0 | Day 1 | Day 2 | Day 3 |
|---|---|---|---|---|
Return On | 3 | 1 | 2 | 1 |
Users A, B, C | User A | User A, C | User A | |
Return On or After | 3 | 2 | 2 | 1 |
Users A, B, C | User A, C | Users A, C | User A |
Retention Type | Day 0 | Day 1 | Day 2 | Day 3 |
|---|---|---|---|---|
Return On | 100% | 33% | 67% | 33% |
Return On or After | 100% | 67% | 67% | 33% |
User | 2024-04-01 | 2024-04-02 | 2024-04-03 |
|---|---|---|---|
User A | Install (App), | Deeplink Open (App) | Add To Cart (App) |
User B | Sign-up (App) | Add To Cart (App) | Order Complete (App) |
User C | Deeplink Open (App) | Deeplink Open (App), | Order Complete (App) |
User D | Install (App) | Add To Cart (App) | Deeplink Open (App) |
User E | Install (App), | Deeplink Open (App) | Add To Cart (App) |
Day 0 (2024-04-01) | Day 1 (2024-04-02) | Day 2 (2024-04-03) | |
|---|---|---|---|
4/1 (2024-04-01) | 2 (50%) | 3 (75%) | 2 (50%) |
Option | Measurement criteria | Description |
|---|---|---|
General | All Start Events | · Aggregates Return Events against every Start Event generated during the date range. · Return Events from the same user are attributed to every Start Event that user generated earlier in the user journey. The report identifies the same user by the Airbridge Device ID when [Identifier] is set to Device, and by the Airbridge ID when it is set to User. |
Confined | Only the most recent Start Event | · Aggregates Return Events against only the most recent Start Event in the date range. · Once a new Start Event is generated, earlier Start Events no longer affect subsequent Return Events. Return Events are attributed to the most recent Start Event in the user journey. |
Date | 3/1 | 3/2 | 3/3 | 3/4 | 3/5 |
|---|---|---|---|---|---|
User journey | Install | Launch and uninstall | Install | - | Launch |
Ad channel | A | - | B | - | - |
Channel | Date | Total Installs | Day 0 | Day 1 | Day 2 | Day 3 | Day 4 |
|---|---|---|---|---|---|---|---|
Channel X | 3/1 | 1 | 1 | 1 | 1 | 0 | 1 |
| 3/2 | 0 | 0 | 0 | 0 | 0 |
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| 3/3 | 0 | 0 | 0 | 0 |
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| 3/4 | 0 | 0 | 0 |
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| 3/5 | 0 | 0 |
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Channel Y | 3/1 | 0 | 0 | 0 | 0 | 0 | 0 |
| 3/2 | 0 | 0 | 0 | 0 | 0 |
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| 3/3 | 1 | 1 | 0 | 1 |
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| 3/4 | 0 | 0 |
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| 3/5 | 0 |
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Channel | Date | Total Installs | Day 0 | Day 1 | Day 2 | Day 3 | Day 4 |
|---|---|---|---|---|---|---|---|
Channel X | 3/1 | 1 | 1 | 1 | 0 | 0 | 0 |
| 3/2 | 0 | 0 | 0 | 0 | 0 |
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| 3/3 | 0 | 0 | 0 | 0 |
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| 3/4 | 0 | 0 | 0 |
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| 3/5 | 0 | 0 |
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Channel Y | 3/1 | 0 | 0 | 0 | 0 | 0 | 0 |
| 3/2 | 0 | 0 | 0 | 0 | 0 |
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| 3/3 | 1 | 1 | 0 | 1 |
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| 3/4 | 0 | 0 |
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| 3/5 | 0 |
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Channel | Date | Total Installs | Day 0 | Day 1 | Day 2 | Day 3 | Day 4 |
|---|---|---|---|---|---|---|---|
Channel X | 3/1 | 1 | 1 | 1 | 1 | 0 | 1 |
| 3/2 | 0 | 0 | 0 | 0 | 0 |
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| 3/3 | 0 | 0 | 0 | 0 |
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| 3/4 | 0 | 0 | 0 |
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| 3/5 | 0 | 0 |
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Channel Y | 3/1 | 0 | 0 | 0 | 0 | 0 | 0 |
| 3/2 | 0 | 0 | 0 | 0 | 0 |
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| 3/3 | 1 | 1 | 0 | 1 |
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| 3/4 | 0 | 0 |
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| 3/5 | 0 |
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Channel | Date | Total Installs | Day 0 | Day 1 | Day 2 | Day 3 | Day 4 |
|---|---|---|---|---|---|---|---|
Channel X | 3/1 | 1 | 1 | 1 | 0 | 0 | 0 |
| 3/2 | 0 | 0 | 0 | 0 | 0 |
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| 3/3 | 0 | 0 | 0 | 0 |
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| 3/4 | 0 | 0 | 0 |
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| 3/5 | 0 | 0 |
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Channel Y | 3/1 | 0 | 0 | 0 | 0 | 0 | 0 |
| 3/2 | 0 | 0 | 0 | 0 | 0 |
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| 3/3 | 1 | 1 | 0 | 1 |
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| 3/4 | 0 | 0 |
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| 3/5 | 0 |
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Option | Description |
|---|---|
Day N Starts: At Midnight | Day N is calculated on a calendar-day basis. For example, if the start event occurs on March 3rd at 2:00 PM, Day N is split as follows, regardless of the event time: • Day 0: 3/3 00:00 ~ 3/3 23:59 • Day 1: 3/4 00:00 ~ 3/4 23:59 • Day 2: 3/5 00:00 ~ 3/5 23:59 |
Day N Starts: At Start Event | Day N is calculated on a 24-hour basis. For example, if the start event occurs on March 3rd at 2:00 PM, Day N is split as follows, in 24-hour increments starting from the event time: • Day 0: 3/3 14:00 ~ 3/4 13:59 • Day 1: 3/4 14:00 ~ 3/5 13:59 • Day 2: 3/5 14:00 ~ 3/6 13:59 |
Condition | Usage | Description |
|---|---|---|
is | A is B | View only data where A equals B |
is not | A is not B | View only data where A does not equal B |
contains | A contains B | View only data where A contains B |
does not contain | A does not contain B | View only data where A does not contain B |
exists | A exists | View only data that has A |
does not exist | A does not exist | View only data that does not have A |
Granularity | Top row (as of Jan 11) | Top row (as of Jan 21) | Sub-row |
|---|---|---|---|
Daily | 11 (Day 0 ~ Day 10) | 21 (Day 0 ~ Day 20) | 11 |
Weekly (Mon-Sun) | 3 (Week 0 ~ Week 2) | 4 (Week 0 ~ Week 3) | 3 |
Weekly (week start) | 2 (Week 0 ~ Week 1) | 3 (Week 0 ~ Week 2) | 2 |
Monthly | 1 (Month 0) | 1 (Month 0) | 1 |
Feature | Description |
|---|---|
Save Report | Save a report. View saved reports in [Saved Reports]. |
Copy Settings | Use Copy Settings to share report configurations with other Airbridge users, regardless of app registration or permissions. |
Copy Table, Copy Chart | Click 'Copy Table' or 'Copy Chart' to paste the content into Excel, Google Sheets, messengers, and more. |
Download File | Download Airbridge report results in the format you select. |
Sharelink | A Sharelink is a URL for downloading a CSV file with real-time Airbridge report data. The data available through a Sharelink depends on the app role of the Airbridge user who generated it. |
Specifications and limitations | Description |
|---|---|
Maximum Return Events | 4 |
Maximum GroupBys | 6 |
Self-Serve Metrics, Custom Metrics, Custom GroupBys | Not supported |
Timezone | Follows the configured app timezone |
Data format | Table |
Data update frequency | 1 hour |
Available data | App event data |
Custom event support | Supported |
Maximum rows in the Airbridge dashboard | 10,000 rows |
Maximum rows in CSV / Google Sheets | 10,000 rows |
Data retention | 5 years (since February 1, 2023) |
Maximum date range per query | · Minutely: 3 days · Hourly: 7 days · Daily: 184 days · Weekly: 12 weeks · Monthly: 3 months |
Name | Location | Function |
|---|---|---|
Refresh | Settings panel | Refetch results while keeping the current report configuration. |
Copy Settings | Settings panel | Copy the report configuration. |
Download | Settings panel | Download the current chart or table as a file. |
Save | Settings panel | Save the report configuration. |
Collapse | Settings panel | Collapse or expand the report settings panel. |
Copy Chart | Chart | Copy the report chart. Paste directly into a messenger or design tool. |
Copy Table | Table | Copy the report table. Paste directly into Google Sheets and similar tools. |
New Report | [Saved Reports]>[New Report] | Start a new report. |
Revert | Settings panel of a saved report | Revert the configuration back to the saved report. |
Delete | Settings panel of a saved report | Delete the saved report. |
Indicator | Masking scope | Description |
|---|---|---|
Privacy Block | All data | Shows 'Privacy Block' instead of a numeric value |
+α, ±α | Partial data | Appears next to a numeric value |
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