Home Insights Case Studies Personalizing in-game experience using reinforcement learning
Get the Case Study

To improve the gaming experience for players, a leading video game publisher sought to personalize in-game interactions, streamline model development, and increase long-term engagement and lifetime value (LTV) of users. Grid Dynamics addressed these challenges by implementing a reinforcement learning-based personalization platform, successfully delivering a minimum viable product (MVP) within just 8 weeks.
This innovative solution significantly improved user engagement, achieving up to a 25% increase in dollar-per-user metrics compared to existing baselines. The result is a more immersive and tailored gaming experience that not only captivates players but also fosters lasting loyalty and value for the publisher.
Tags
You might also like

Machine learning for optimized campaign delivery and performance: A Yieldmo case study

Advantages of a next-generation customer data platform for a top tier marketing agency on AWS

Retooling for the future: A composable commerce overhaul for an automotive tools giant

AI and business reimagination: Insights from Grid Dynamics CTO, Rajeev Sharma