AI Churn Prediction Implementation in Gaming

This document is a case study detailing the implementation of Evergent's AI churn prediction technology within a major Japanese gaming company. The objective was to achieve high accuracy in predicting user churn, defined as 14 consecutive days of inactivity. The gaming company provided a comprehensive dataset of over 2 million user records, which posed challenges such as processing diverse data efficiently and detecting disengagement patterns. Evergent's solution involved deploying a proprietary AI churn detection engine within an 8-week timeframe, requiring minimal integration. The AI model assigned churn scores to users, enabling targeted retention strategies. Key outcomes included identifying hundreds of thousands of at-risk users, prioritizing marketing interventions based on churn likelihood, and developing personalized engagement strategies that improved user retention and monetization. The case study also outlines future optimization priorities, including data expansion and model retraining to enhance predictive strength and adapt to evolving user behaviors.