The User Count in the sub-rows is always smaller or equal to the total User Count. This is because the User Count in the sub-rows is the number of unique users aggregated during the specific time range the sub-row represents, whereas the total User Count in the top rows is the number of unique users aggregated during the entire configured date range. The same logic applies to Paying Users, which is a sub-metric.
Let's say a user interacted with your app as described below.
Day 0: Installed app after viewing an ad. Completed an order in the app and deleted the app afterward.
Day 1: Installed the app again after viewing an ad. Completed an order in the app.
In this case, the User Count and Paying Users on Day 0 and Day 1 will show as follows.
Total Users, Paying Users: 1
User Count and Paying Users on Day 0: 1 each
User Count and Paying Users on Day 1: 1 each
The following reasons could be the cause of the discrepancy.
Difference in the negative number conversion rules
Difference in the attribution rules
Event duplication
Note that the Revenue Events used in the Revenue Report correspond to different events in the Actuals Report that can be configured as metrics, as shown in the table below.
Revenue Event | Actuals Report Metric |
|---|---|
First Order Complete (App) | First Revenue (App) |
Order Complete (App) | Revenue (App) |
Ad Impression(App) | Ad Impression Revenue (App) |
Ad Click (App) | Ad Click Revenue (App) |
Subscribe (App) | Subscription Revenue (App) |
The Revenue Report converts negative numbers to 0, whereas the Actuals Report doesn't convert them to 0 and aggregates them as is.
Actuals Report: The revenue-related events that occurred within the attribution window are measured. Events outside the attribution window are not aggregated.
Revenue Report: The Revenue Event is attributed to the touchpoint that is the winning touchpoint for the Start Event. The attribution window does not apply.
In the Revenue Report, you can also view the revenue that has been generated outside the attribution window. When the attribution window is smaller, the discrepancy between the measurements may become larger.
When a user performs multiple Start Events in a day, the Revenue Event may be duplicated in the Revenue Report.
Let's say a user interacted with your app as described below.
2 PM, Day 0: Installed app after viewing a video ad
7 PM, Day 0: Opened the app via a deep link after viewing a search ad
11 AM, Day 1: Completed an order in the app
The Revenue Report will report as the following:
Number of Revenue Events attributed to the video ad on Day 1: 1
Number of Revenue Events attributed to the search ad on Day 1: 1
Yes, all settings are saved when you save the Revenue Report, so you can reuse them whenever you like.
Note, however, that for reports saved before June 27, 2024, the ranges for aggregating the Return Events are set to a maximum of Day 30, Week 4, or Month 3, depending on the chosen granularity. The range settings saved in the Revenue Reports can be modified.
The Revenue Report aggregates data collected in the past. If the set date range is too recent, no data may be available for certain ranges because no data has been collected yet, and the number of ranges displayed in the Revenue Report may be less than the selected Day N range option. Refer to the following example.
Let's say the Retention Report has been configured as follows.
Date Range: January 1, 2024 - January 3, 2024
Granularity: Daily
Day N option for Revenue Events: Max Day 30
If today is January 15, 2024, the retention data will be provided in 15 ranges from Day 0 to Day 14. This is because Airbridge has only data collected until today, which is January 15, and therefore cannot display the retention data from Day 15 to Day 30 even though "Max Day 30" has been chosen as the Max Day N for Return Events.
The Revenue Report aggregates data collected in the past. If the set date range is too recent, no data may be available for certain ranges because no data has been collected yet, and some data points may be missing in the sub-rows. Refer to the following example.
Let's say the Retention Report has been configured as follows.
Date Range: January 1, 2024 - January 3, 2024
Cycle: Daily
Day N option for Revenue Events: Maximum Day 30
If today is February 1, 2024, the revenue data will be provided in 31 ranges from Day 0 to Day 30. The sub-rows for January 1 and January 2 will show data points in 31 ranges, as January has 31 days.
However, the sub-row for January 3 will show data points in 30 ranges from Day 0 to Day 29, and the data point for Day 30 will be missing. This is because Airbridge has data collected until today, which is February 1 and Day 29, considering January 3 as Day 0, and there is simply no data collected yet for February 2, Day 30.
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