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Microsoft files patent for machine learning system to optimize in-game ad placements
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Illustration only Photo by Compare Fibre on Unsplash
Microsoft's new patent aims to create a machine learning system that minimizes player annoyance from in-game ads by timing them better.
This patent highlights a significant shift in how advertising could be integrated into gaming experiences. By using machine learning to analyze player behavior, the system aims to enhance monetization strategies while attempting to mitigate player frustration. This could lead to more sophisticated ad delivery systems that change the landscape of in-game advertising.
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The patented system uses machine learning to determine optimal timing for in-game ads based on player activities.
It proposes a credit system for players who interact with ads, potentially gamifying the ad consumption experience.
The technology could identify critical gameplay moments to avoid interrupting players, enhancing the overall experience.
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What the cluster adds up to.
The newly filed patent describes a system that leverages machine learning to analyze player interactions and optimize when in-game ads are presented. This system aims to deliver ads at moments when players are least likely to be annoyed, potentially improving user experience in monetized games.
Implementing such a system would require significant development resources, including advanced algorithms capable of real-time analysis of gameplay data. This could increase upfront costs for developers but may lead to higher long-term revenue through effective ad placements.
The approach details specific scenarios where ads could be introduced without disrupting gameplay, such as during pauses or safe moments. However, its effectiveness might be limited in fast-paced gaming environments where player focus fluctuates rapidly and unpredictably.
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