The Revenue Analysis chart type shows how well you are monetizing your users. In order for data to show up on this chart, you need to call
logRevenueV2() in conjunction with the provided
Revenue interface if you are using our SDKs. If you are tracking in-app purchases (IAPs), we recommend using our revenue authentication system.
Table of Contents
- Revenue Analysis Metrics
- Chart Control Panel
- Chart Interpretation
- Data Table
Note: Amplitude currently does not support currency conversion. The revenue value you send us is what we will aggregate and display. If you receive revenue in different currencies, we recommend normalizing to a single currency before you send us revenue data.
Revenue Analysis Metrics
The Revenue Analysis chart allows you to view relevant revenue metrics for your project's performance. The metrics you can measure are:
- Total Revenue: Shows the total revenue over the specified time range based on the revenue events sent to Amplitude.
- Paying Users: Shows the number of paying users over the specified time range.
- ARPDAU (Average Revenue per Daily Active User): Shows the average revenue per daily active user over the specified time range.
- ARPPU (Average Revenue per Paying User): Shows the average revenue per paid user over the specified time range.
Chart Control Panel
The right panel in the Revenue Analysis chart control panel functions analogous to the right panel in an Event Segmentation chart. You can read more about how to compare user segments here.
Segmenting on Revenue Properties
You can segment on revenue events by specific revenue properties in the left panel of the chart control panel by using the "+where" and "+group by" functions. Note that you can also segment revenue events by those properties in an Event Segmentation chart. The revenue properties are stored as event properties with a '$' sign prefixed. To use the "+where" clause, you will have to explicitly type in the value in order to segment by it.
More details on the properties are outlined in the below table.
|price||Double||Required: The price of the products purchased (can be negative).
Note: revenue = quantity * price
|productId||String||Required: An identifier for the product (we recommend something like the Google Play Store product ID).||null|
|quantity||Integer||Required: The quantity of products purchased. Defaults to one if not specified.
Note: revenue = quantity * price
|revenueType||String||Optional: The type of revenue (e.g. tax, refund, income).||null|
|eventProperties||Object||Optional: An object of event properties to include in the revenue event.
Note: You will only be able to segment on these properties in the Events Segmentation tab.
In the image below, we have segmented out all events where '$price' = '9.99'. Note that these properties must be explicitly sent by you via our SDKs when you log revenue events. You can read more about the different types of revenue events you can send here.
You can set up and interpret any Revenue Analysis chart easily as the platform allows you to read the parameters like a sentence. For example, the following chart shows you all the revenue events that were $9.99, performed by all users, measured by total revenue daily for the last 30 days.
Like all of Amplitude's chart types, you can use the date picker to choose a more specific time range to analyze your data and can switch between "Last", "Between", and "Since". You also have the option to view data in daily, weekly, or monthly units by toggling between the different options in the dropdown menu next to the date picker.
If you are looking at multiple segments in your chart, you can manually select and deselect each segment by hovering over the segment name in the bar below the chart and removing it or by clicking the "+" button to add it back. Finally, you can click on any data point in the chart and inspect the users that make up that data point by using Microscope.
Underneath the chart is a table of the data displayed. You can select or deselect which segments you see in the graph by clicking on the segment name in the data table. Furthermore, the data table can display some simple calculations for you.
Lastly, you can download the data table by clicking the "Export CSV" button.