Personalized Content, Engagement, and Monetization in a Mobile Puzzle Game
Christian Helmers, Louis-Daniel Pape, Alessandro Iaria, Stefan Wagner, and Julian Runge
Digital technologies have reduced the cost of collecting detailed information on con-sumer characteristics and behavior. Despite the large literature on the consequences of using thesedata to personalize prices, little is known about content personalization. Using detailed player-leveldata from a mobile puzzle game and a novel structural model of player behavior, we investigate theeffects on revenue of personalizing game difficulty using observable player characteristics. Our resultsshow that, while average difficulty across players is successfully set by the game developer to max-imize revenue, personalization can further increase revenue by 71%. Personalized difficulty leads toan overall increase in player engagement and, consequently, revenue generation in the form of in-apppurchases. Although the largest relative increase in revenue comes from the smallest spenders, mostof the absolute increase in revenue comes from a further increase in spending by the largest spenders