Revenue Per Download (RPD) is a measurement of an app’s performance available in App Analysis of Store Intelligence. RPD represents cumulative revenue divided by cumulative downloads, or simply put: RPD is the average revenue that an app earns per download. 

RPD allows you to compare monetization strategies and can be used as a signal for an app’s LTV or ARPU. You can learn more about how to use RPD in the Use Cases below.

By default, RPD is calculated as the ratio between all-time revenue to all-time downloads. All-time RPD is the clearest signal of an app’s overall per-user monetization performance. One shortcoming of all-time RPD is that as an app accumulates downloads and revenue over time, more recent signals in the ratio can be drowned out by older data.

To highlight changes in monetization performance over time, it may be more helpful to set RPD to a rolling duration. This control is available from the RPD dropdown:

 

Instead of calculating the ratio between all-time revenue and downloads, rolling RPD calculates the ratio between revenue and downloads over a given period, rolling over time. So, for example, 30-Day RPD would represent the revenue an app earned over 30 days divided by the downloads the app earned over the same 30 days. 

Rolling RPD is more reactive to changes in an app’s performance. For apps that churn users more quickly, you could think of rolling RPD as treating a given period of downloads and revenue as a cohort, and showing how that cohort has monetized. Rolling RPD is also helpful for looking at user spend for apps with live ops events that drive both downloads and revenue.

A tradeoff in the rolling RPD calculation is that revenue lags downloads. The revenue and downloads in a given window do not represent 100% the same users, so rolling RPD may be a less accurate signal for LTV. The rolling RPD for apps with long term retained users tends to become volatile, as highly engaged users continue to spend in patterns and user acquisition slows gradually. Various rolling RPD periods can be helpful in finding insights across different apps.

RPD renders data in the App Analysis graph, and all-time RPD is included in a column in the Breakdown Table. You can compare the RPD of one or more apps, of selected countries, of competing publishers, and across iOS devices.

Note: RPD is a front-end only feature. RPD is not available in the API or CSV. Only All-Time RPD is available in the App Analysis breakdown table. Rolling RPD forces daily date granularity. RPD measurement is only available for all-time date range. Store Intelligence data goes back to 2012 for iOS and 2014 for Android (improved regional coverage starting 2016). Downloads and revenue from before those dates will not be included in RPD. You may find some spikes in your charts when these data are introduced.

Use Cases

The Revenue Per Download measurement is helpful for estimating per-user monetization and finding interesting changes in an app's performance.

We’ll show a few ways that RPD can help you find actionable insights into the mobile app market.

1. Juxtapose Apps' User Monetization
2. Breakdown User Monetization by Country
3. Live Ops Performance
4. Identify Monetization Improvements

Juxtapose Apps’ User Monetization (All-Time RPD)

If you add a variety of different apps to App Analysis and measure All-Time RPD, you’ll see that each monetization system tends to produce a family of RPD curves. Free apps with IAP start at zero revenue and gradually approach an asymptote. Paid apps start at a relatively high figure and RPD gradually fall as discounts lower the average selling price. Subscription apps tend to start at zero and curve up, but can be affected by users migrating to direct billing. If you add several apps with similar monetization systems, you can compare their per-download performance. The Align by Launch toggle can be helpful in comparing apps launched months or even years apart.

 

Breakdown User Monetization by Country (All-Time RPD)

You can explore an app or set of apps’ per-download monetization by country. Navigate to App Analysis by Country Breakdown and select the All-Time RPD Measure to look at how apps monetize across different regions. With launch alignment, you can even measure the adoption of paid features that are rolled out to different countries over time. Below, we can see that YouTube monetizes best in the United States and Australia, with South Korea lagging slightly.
 

Live Ops Performance (7-Day RPD)

Like most gacha games, Dragalia Lost regularly releases new content, and we can see from the Revenue measure that its users tend to spend on weekends. That pattern is only barely visible from all-time RPD. Given the roughly weekly cadence of new banners and user spend, let’s look at Dragalia’s 7-Day Rolling RPD.
 

In this view, the user spend is immediately visible. The successful New Year’s event on January 1st 2019 is noticeable from the Downloads and Revenue measurements, but rolling RPD shows that on a per download basis, that event monetized on a per-downloads basis almost as well as other events. Rolling RPD can stretch spikes horizontally, but a Dragalia player would still be able to identify the popular banners that these spikes are associated with. 

Monetization Improvements (30-Day RPD)

Tinder released new IAP subscriptions in the summer of 2017. That spike is visible in all-time RPD and overall Revenue, but the change in per-download performance is much clearer at a 30-Day Rolling RPD measurement: