Google Introduces New Tools For Game Developers At GDC

March 2, 2017 - Written By Scottie Rowland

Google brought new developer tools yesterday to the Game Developer Conference in San Francisco that is designed to help developers get noticed by more consumers, gain more downloads, better tracking of consumers, and of course make more money. The best of the bunch is a program called playables which is a lightweight version of the game that shows up as an interactive ad that can be played inside of another app. Google already has a large ad network called Universal Ad Campaigns which consist of Google Display Network, AdMob, Youtube, Google Search and Google Play which it pushes it ads to. This will just be one more place ads can be pushed out to and should be great for developers of all types. This new feature should be available in the coming months.

The company also said that reward videos which offers gamers coins, more lives, etc. for watching ads will be available across the entire Universals Ad Campaign. Currently, it is available only AdMob and AdWords. If developers wish to re-use their current materials and avoid creating new ones they are free to do so. Google is also working to improve functions so developers can see in more detail how their customers engage with their apps and even their lifetime value. It plans to do this by integrating Firebase Analytics to developers using a C++ SDK and SDK for Unity.

Google is also adding auto flip, which flips ads to the orientation the user is currently holding their phone in. So even if you hold your phone vertically and the ad is designed for horizontal viewing, it will correct and play vertically instead. While this isn’t a huge deal for most, it’s still nice that Google is making minor adjustments to make it more comfortable for the end user. What makes this interesting is Google makes a vertical video when the horizontal is made using machine learning. In the end, Google says there is a 20% higher click through rate on the vertical ads the was auto designed because the machine learning concentrates on the important parts of the video.