The Revenue Report allows you to view the revenue generated by users who installed the app or opened a deep link during the analysis period. Various revenue metrics and filters are available to create a customized report.
Notes
The Revenue Report is available to users registered as ‘Owner’ and ‘In-house marketer’ only. Users registered as ‘Agency’ and ‘Media partner’ will be granted access soon.
Events
In the Revenue Report, you can see the revenue generated by users who performed a Start Event and Revenue Events afterward. Read on to learn about the different types of Events.
About the Events
The Revenue Report shows App event data only. Web or iOS SKAdNetwork events are not included in the Revenue Report.
Start Event
Start Event is the event that initiates a User Journey. Target Events, which refers to App Installs and Deeplink Opens is available as a default option.
Revenue Event
Revenue Event is an in-app event performed by the user after performing a Start Event. You can select from the four Revenue Event options described below to customize your report view.
Order Complete (App)
Select this event to see the revenue generated by users who completed an order.
First Order Complete (App)
Select this event to see the revenue generated by users who completed an order for the first time. Airbridge Device ID is used to determine the first purchase.
Airbridge Device ID
Airbridge Device ID is a Universally Unique ID used to identify devices. As a default, GAID for Android and IDFV for iOS are used. If GAID or IDFV is unavailable, randomly generated value is used instead.
Ad Impression (App)
Select this event to see the ad revenue generated by obtaining ad impressions from the users.
Ad Impression + Order Complete (App)
Select this event to see the revenue generated by obtaining ad impressions from the users and the revenue generated by users who completed an order.
User Journey
A User Journey starts with a Start Event performed by the user. All Revenue Events that come after a Start Event are considered to be in the same User Journey until a new User Journey is initiated with a new Start Event.
In other words, every time a Start Event is performed within the analysis period, a new User Journey is initiated. If the Start Event is performed only once during the analysis period, the entire analysis period is considered to be a single User Journey.
This rule of defining a User Journey is causing the discrepancy between the numbers in the Revenue Report and the Actuals Report. In the Actuals Report, the attribution window is used to define a User Journey, and the Revenue Events only within the attribution window are tracked. In the Revenue Report, however, the Revenue Events beyond the attribution window can be considered to be in a User Journey, as long as they are within the analysis period.
Metrics
The Revenue Report offers six different metrics to customize your view.
Revenue
This metric shows the revenue generated by the users who performed the Start Event and the Revenue Event.
User Counts
This metric shows the number of users who performed the Start Event and the Revenue Event.
Event Counts
This metric shows the number of the Revenue Event performed by the users during the analysis period.
ROAS (Return on Ad Spend)
This metric shows the return on ad spend of the users who performed the Start Event and the Revenue Event. ROAS is calculated by dividing the cumulative revenue by the total cost and multiplying the result by 100.
ex) How is the ‘300%’ for ‘Day 3’ ROAS calculated?
300,000 (Cumulative Revenue on Day 3) / 100,000 (Total Cost) * 100 = 300(%)
ARPU (Average Revenue per User)
This metric shows the average revenue per user who performed the Start Event. ARPU is calculated by dividing the cumulative revenue by the number of users who performed the Start Event during the analysis period. Some Facebook data may be masked due to Facebook’s Privacy Policy.
ex) How is the ‘30’ for ‘Day 3’ ARPU calculated?
9,000 (Cumulative Revenue on Day 3) / 300 (Number of users who performed Start Event) = 30
ARPPU(Average Revenue per Paying User)
This metric shows the average revenue per paying user who performed the Start Event and Revenue Event. ARPPU is calculated by dividing the cumulative revenue by the number of users who performed the Start Event and the Revenue Event during the analysis period.
ex) How is the ‘300’ for ‘Day 3’ ARPPU calculated?
9,000 (Cumulative Revenue on Day 3) / 30 (Number of users who performed the Start Event and the Revenue Event) = 300
View Types
You can select two different view types for the Revenue Report.
Cumulative
This view type allows you to view the data in cumulative sum. The revenue value on the last day of the analysis period equals the Total Revenue value.
On Day (N-Day)
This view type allows you to view the isolated data of each day. The revenue value on the last day of the analysis period does not equal the Total Revenue value.
The following table shows the view options you can select for the different metrics available in the Revenue Report.
| Metrics | Cumulative | On Day (N-Day) |
|---|---|---|
| Revenue | Yes | No |
| User Counts | No | Yes |
| Event Counts | Yes | Yes |
| ROAS | Yes | No |
| ARPU | Yes | No |
| ARPPU | Yes | No |
Sub-metrics
Sub-metrics are metrics you can view together with the revenue metric to gain comparative insights. When you choose a revenue metric, three to four sub-metrics are automatically selected and displayed in the fixed columns. Click “+Add” to add up to five sub-metrics or to remove any.
Users
This sub-metric shows the number of users who performed the Start Event. Some Facebook data may be masked due to Facebook’s Privacy Policy.
Paying Users
This sub-metric shows the number of users who performed the Start Event and the Revenue Event.
Total Revenue
This sub-metric shows the total revenue generated by the users who performed the Start Event and the Revenue Event.
Total Cost
This sub-metric shows the total cost spent to acquire users who performed the Start Event. This sub-metric is automatically selected when choosing ROAS as the revenue metric.
Total Event Count
This sub-metric shows the total number of events performed by the users who performed the Start Event and the Revenue Event. This sub-metric is automatically selected when choosing Event Count as the revenue metric.
GroupBy & Filter
You can select up to four GroupBy options to customize your Revenue report.
| GroupBy Category | GroupBy Options |
|---|---|
| Event Property | Is First Event per Used ID … |
| Touchpoint | Channel, Campaign … |
| Fraud | Touchpoint Fraud Tag … |
| Device | Device Type, OS Name … |
| App | App Version … |
| SDK | Airbridge SDK Version … |
You can also add filters to get a more granular view. The available filter options are the same as the GroupBy options. The selected GroupBy and filter options can be rearranged in the configuration box to change the display order of the data on the fixed columns. Click “+Add” to add GroupBy or filter options and “X” to remove any.
Caution!
All values displayed in the Revenue Report with the GroupBy and Filter options applied are based on users who performed the Start Event.
FAQ
Q. The Total Revenue value in the Revenue Report and that in the Actuals Report don’t match. Why is there a discrepancy?
There are three reasons why the Total Revenue value in the Revenue Report may differ from the Total Revenue value in the Actuals Report, which you can find when selecting the Revenue (App), First Revenue (App), or Attributed Revenue (App) as your metric.
Negative numbers: In the Revenue Report, negative numbers are replaced with 0, whereas in the Actuals Report, negative numbers are not replaced with 0 and are calculated as is.
User Journey: In the Actuals Report, the attribution window, is used to define a User Journey, and the Revenue Events only within the attribution window are tracked. Revenue Events that fall outside of the attribution window are considered to be unattributed.
In the Revenue Report, however, every time a Start Event is performed within the analysis period, a new User Journey is initiated. If the Start Event is performed only once during the analysis period, the entire analysis period is considered to be a single User Journey.
Because of the difference in defining a User Journey, the Revenue Report can track the Revenue Events beyond the attribution window. Therefore, the shorter the attribution window is set, the greater the discrepancy in the numbers may grow.
Double counting of events: If a user performs multiple Start Events on a single day, the Revenue Event may be subject to doubling counting in the Revenue Report.
ex) Double counting scenario
Analysis period
2022/01/01 ~ 2022/01/02
User behavior
The user opened the app twice through two different touchpoints.
1. 2022/01/01 (2 PM): Installed and opened app after viewing Ad A
2. 2022/01/01 (7 PM): Opened app through a deep link after viewing Ad B
3. 2022/01/02 (11 AM): Made a purchase in the app
Event counts
Even though the user performed only a single Revenue Event, that event is subject to double counting in the Revenue Report.
1. Revenue Event performed on 2022/01/02 attributed to Ad A
2. Revenue Event performed on 2022/01/02 attributed to Ad B
Q. The Total number of users doesn’t match the sum of the respective number of users. Same with the number of paying users. Why is there a discrepancy?
The Total number of users is always smaller or equal to the sum of the respective values of the number of users.
The Total number of users is the number of unique users who performed a Start Event across the analysis period, and the N-day number of users is the number of users who performed a Start Event on the respective days. The same applies to the number of paying users who performed the Start Event and the Revenue Event.
ex) Number of users (paying user) discrepancy scenario
Analysis period
2022/01/01 ~ 2022/01/02
User behavior
2022/01/01: Installed and opened app after viewing Ad, made a purchase, and deleted the app
2022/01/02: Re-installed and opened app after viewing Ad, made a purchase
User counts
1. Total number of users (paying users): 1
2. On Day number of users (paying users)
- 2022/01/01: 1
- 2022/01/02: 1
- Sum of the number of users (paying users): 2
