Smart segmentation (Beta)
Overview of Smart Segmentation (Beta)
Smart segmentation enables you to identify and monetize app users who are unlikely to spend in your app. Smart segmentation uses machine learning to predict your users’ purchasing behavior and segments them into two groups:
- Predicted non-purchasers: Users who are not likely to make in-app purchases.
- Predicted purchasers: Users who are likely to make in-app purchases, like buying extra lives, etc. Limiting the amount of ads shown to these users may help to improve their overall in-app experience and lifetime value.
With smart segmentation, ad requests for predicted non-purchasers will be filled, while ad requests for predicted purchasers will not be filled. This may help to unlock new revenue by monetizing the non-purchasers with ads, while preserving an ad-free experience for the purchasers.
On average, predicted non-purchasers make up about half of your users.
Note: Behind the scenes, smart segmentation predicts the likelihood that a given user is a non-purchaser and serves only those users ads. When a user is ineligible for personalized ads or has disabled them, Google does not predict purchase behavior. Accordingly, such users will not be identified as likely non-purchasers and will not be served ads.
There are two ways to use smart segmentation:
- Experiment mode: Experiment mode allows you to test the ad unit with smart segmentation enabled on 10% of your app’s users for 90 days. Learn more.
- Full mode: The ad unit with smart segmentation enabled is used on 100% of your app’s users. Learn more.
In your Home dashboard, the smart segmentation card lists your apps that are eligible to use smart segmentation. App eligibility is based on user traffic and the amount of in-app purchases visible to AdMob. Additionally, iOS apps must be linked to Firebase to be eligible for smart segmentation.
The smart segmentation card estimates the increase in ad earnings that a smart segmentation interstitial could provide when used in addition to existing ad units.