App developers are constantly looking for new ways to leverage the data from their apps to deliver better, more targeted engagement and monetization campaigns. After all, the more targeted they can be, not only will they likely earn more money, but they can then deliver a more personalized and ultimately more rewarding user experience as well.
Here at Tapjoy, we aim to give our developer partners the data-driven tools they crave, and today we are pleased to announce the launch of two new such tools: Ad Behavorial Targeting and Content A/B Testing.
Ad Behavioral Targeting
With our new Ad Behavioral Targeting capabilities, app developers can now target ads to specific sets of users based on their previous ad-related behaviors, such as whether they have completed ads in the past, have viewed but never converted on an ad, or have never viewed any ads at all. Developers can also target based on specific ad types.
This new tool is extremely valuable for when developers want to serve ads just to those users who they know are interested in taking part, or for when they want to customize which type of ad or offer to serve to specific users. For instance, some relevant use cases include:
Ad Behavioral Targeting is now available for ad types including the Tapjoy Offerwall, Videos, Interstitial, Native to Earn, Message to Earn, Mediated Videos, Mediated Interstitials, as well as for engagement formats including Announcements, IAP Promotions and Rewarded Giveaways.
Content A/B Testing
Our new Content A/B Testing tool takes the work out of A/B tests by making it extremely simple to compare two different types of offers or promotions without any additional coding. Now, when developers want to optimize the conversion rates for certain types of content, they can test variations of text, colors, calls to action and more to see what drives the best performance.
Content A/B Testing is available for content types including Native to Earn, Message to Earn and Announcements. Developers can use their usual segmentation and targeting options, set a time limit for the test, and easily change the percentage of how many users receive variant A versus variant B with a simple sliding tool.
It is now easier than ever for developers to conduct data-driven A/B testing on in-app engagement and monetization campaigns!
To learn more about our new Ad Behavioral Targeting or Content A/B Testing tools, contact your account manager or email email@example.com today.