What is ad format adoption testing?
Whether your app is hybrid-revenue or ads-revenue driven, the adoption of different ad formats can be complicated.
Not all ad formats will suit every app, and some ad formats might perform better depending on app properties. When implementing a new ad format, you might be concerned about negative impact on user experience or retention, but you might also be curious if you can increase revenue and engagement if a new ad format is properly instrumented.
To resolve these unknowns, Firebase offers tools that help you test and then make data-driven decisions about adopting new ad formats:
Using Firebase, you can A/B test the performance of a new ad format with a small subset of users.
You can observe the test results and review recommendations from Firebase about whether the new ad format is performing better than the existing ad format.
Once you're confident that the changes will likely have a positive impact, you can roll out the changes to more of your users with a click of a button.
Business case and the value
On average, developers and publishers who use Google AdMob and Firebase tools for adding a new ad format enjoy major revenue uplifts (up to 10X*) while keeping the retention rate stable.
*Revenue uplift based on results from 8 large publishers in 2020.
Pomelo Games uses Firebase to increase revenue by up to 35% without losing players.
Qtonz uses Firebase to achieve 4x increase in Ads Revenue and 190% increase in ARPDAU.
Implementing the solution
To implement this solution, you can follow our step-by-step tutorial (find an overview of this tutorial later on this page).
In this multistep tutorial, you'll learn how to use Firebase to test a new Google AdMob ad format for your app. It uses a rewarded interstitial ad as the example test case, but you can extrapolate and use these same steps to test out other ad formats.
This tutorial assumes that you already use AdMob in your app and that you'd like to test whether adding another ad unit (with a new ad format) will have an impact on your app's revenue or other metrics. However, if you don't already use AdMob in your app, that's ok! The steps in this tutorial can also help you understand if simply adding an ad unit to your app has an impact on your app's metrics.
Products and features used for this solution
Google AdMob enables you to create ad unit variants that will be served within your app. When you link AdMob with Firebase, AdMob sends ad revenue information to Firebase to improve ad strategy optimization.
Google Analytics gives you insight into user engagement, retention, and monetization metrics like total revenue, AdMob revenue, purchase revenue, and much more. It also allows you to create user audiences and segments.
Firebase Remote Config
Firebase Remote Config enables you to dynamically change and customize the behavior and appearance of your app for desired user segments — all without publishing a new version of your app. In this tutorial, you'll use Remote Config parameters to control whether a new ad unit is shown to your users.
Firebase A/B Testing
Firebase A/B Testing provides the interface and infrastructure to run product and marketing experiments in your app. It takes care of distributing experiment variants to users, and then performs statistical analysis to determine if an experiment variant is outperforming the control group based on your selected key metric, such as revenue or user retention.
Solution tutorial overview
Create a new rewarded interstitial ad unit in AdMob.
Implement the ad unit placement within your app's code.
Define testing basics, targeting, and the goals that the test will run against.
Define test variants and set up the Remote Config parameter that will control whether to show the new ad unit to users in the test.
Use the Remote Config parameter in your app.
Implement the logic for displaying the ad unit based on the parameter's value.
After starting the test and allowing it to run for a few days or weeks, check the Firebase console for whether the A/B test has a winning variant based on the primary goal of the A/B test.
Review the impact on secondary metrics for each variant to ensure the variants didn't cause unintended negative impacts to those metrics.
If A/B Testing determines that the variant showing the new ad format is the winner, you can start showing the ad format to all users targeted in the experiment, all users of your app, or to a subset of your users.
If a clear winner isn't yet determined, you can either continue running the experiment to gather more data, or end the experiment if it's already been running for a long period with inconclusive results.
View a list of common terms for this solution
View a list of common terms for this solution
AdMob revenue: AdMob network and open bidding revenue
IAP revenue: In app purchases revenue
Total revenue: Total revenue
Retention: Retention as a key metric in A/B tests is tracked as 1 day, 2-3 days, 4-7 days, 8-14 days, or 15+ days user retention
Remote Config parameter: The configurable parameter used to control whether we show the new ad format or not. In this guide, it will be a boolean value.
Baseline configuration: The as-is configuration in any particular A/B test — also known as the control. The control usually uses the default value for the Remote Config parameter, but it can be configured to use a new control value if needed.
Variant configurations: The variant configurations are the alternative configurations with different Remote Config parameter values that we would like to test against the baseline configuration.