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Posted by Harish on June 1 2020

Gaming companies, are all vying for the same thing: increased game play and revenues. In all aspects of Gaming, be it live streaming, game play, in-app purchases; companies are looking to leverage machine learning and AI to grow customer engagement, revenues and viewership of their game play to strengthen their community. Below are some of the key use cases of ScoopML’s predictive analytics for the Gaming platforms.

  • 1. Gamer Churn
  • 2. Gamer Purchases
  • 3. Live Stream Stats
  • 4. Optimize Game Play

Determining the value of each player, including influential players on platforms like Twitch and Mixer, is a vital factor in deciding where to aim personalized marketing efforts. ScoopML can help determine the likely following each individual customer will generate over their entire game, as well as when a gamer is likely to churn; allowing you to focus your efforts on those likely to be most influential eventually reducing churn and increasing revenues.

Gaming companies want to know how likely gamers are to upgrade or make in game purchases. ScoopML's predictions can offer unprecedented insight into gamer behavior, allowing businesses to optimize their game design and product offerings.

As gamers live stream their games on Twitch, YouTube, Mixer and other platforms, it builds community and provides an incredible opportunity to bring on more followers on the game. ScoopML helps you keep these influencer gamers on the game, understand their stats and predict their likely influence and revenue. So you can channel marketing efforts accordingly.

ScoopML can help predict more technical nuances such as video encoders to use when live streaming the game, what game levels are cause more players to churn or cause players to continue, etc. All of this in a matter of minutes, allowing game makers to optimize their game plays.