Take the guesswork out of your monetization strategy. Now you can test different ad monetization strategies and know with certainty which one will maximize your LTV.Get monetizaton A/B testingGet monetizaton A/B testing
What is monetization A/B testing?
Until now, obstacles like a lack of reliable tools and a drain on development resources have prevented app developers from conducting robust, frequent and scalable tests on their ad monetization strategies – leaving you with an incomplete picture of how to best maximize revenue and retention.
ironSource’s A/B testing tool puts this all in the past. Using our platform, you can quickly and easily conduct full end-to-end tests, from setup and configuration, to reporting and data analysis. Finally, you’ll have a holistic understanding of how your players engage with ads, and you’ll be empowered to stay competitive in an increasingly crowded market.
The benefits of ironSource A/B testing
Ultimately, A/B testing can be used to continually improve your users’ experience with ads, and help you discover a monetization strategy that will generate maximum revenue yield. You’ll be able to achieve the perfect balance of great user experience and higher revenues.
Test with less risk
Now you can know with certainty that a new ad integration won’t hurt your game. With our tool, you can roll out new ad features and minimize the risk involved, from controlled traffic allocation to careful monitoring of the results.
Save development resources
Running your own monetization A/B tests through your own tech stack is often laborious, manual and consumes a lot of development resources – not to mention the time waiting to upload a new app version to the store. With our tool, we take care of the heavy lifting so there’s no need to rely on your own valuable R&D resources. Everything is managed directly from our platform, so you control the process and your developers can focus their efforts elsewhere.
Make data-driven decisions
Once a test is live, you’ll have access to full-funnel reporting for both groups, along with trend indicators, so you know how the two groups fare against each other. This includes performance metrics like revenue, eCPM and ARPDAU, as well as user activity metrics like retention and engagement rate – allowing you to easily compare results between groups and make informed decisions.
you can try
There are an endless amount of tests you can run with our tool. It all depends on which KPIs you want to increase, and how to achieve that through better ad implementation. Here are some of our suggestions to help inspire your next A/B test.
- Manual position vs. auto-optimization
- Single instance vs. multiple instances
- Flat eCPMs deals vs. network optimized pricing
Ad unit tests
- Rolling out new video placements
- Changing the reward amount or currency
- Pacing and frequency of interstitial ads
- Removing competitors you’ve blacklisted
- Including or excluding playable ads
How does it work?
Create your A/B test
Simply allocate what percentage of your users should be included in the B test group, and we will automatically divide the users to each group. Each user is randomly allocated and is sticky per group, to ensure a fair A/B test.
Complete the setup by inputting new instance IDs for each of your active networks. This allows us to track revenue between the two groups to show you which group is performing better.
Set up app configurations
Once the test is scheduled, go ahead and set up the app configurations of what you want to test.
All platform features can be controlled between the A and B groups. Each platform page has a simple toggle to move between groups for easy setup and clear visualizations.
Monitor and analyze
Once the test is live, you’ll have all the data you need to monitor the results and make informed decisions on next steps.
The overview report demonstrates how your groups fared against each other, with trend indicators for important metrics like revenue, retention, and ARPDAU.
Enjoy a breakdown by A/B in your Performance and User Activity reports for an in-depth analysis of your A/B test performance.