Profiling Players with Engagement Predictions
The possibility of using player engagement predictions to profile high spending video game users is explored. In particular, individual-player survival curves in terms of days after first login, game level reached and accumulated playtime are used to classify players into different groups. Lifetime value predictions for each player—generated using a deep learning method based on long short-term memory—are also included in the analysis, and the relations between all these variables are thoroughly investigated. Our results suggest this constitutes a promising approach to user profiling.