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SMU Data Science Review

Abstract

Bricks ‘N Balls is a freemium game that relies on in-app purchases and ad monetization from users to be profitable at no upfront cost to the players. This study explores how in-game data analytics and purchase data can be used to segment players. Features taken into consideration for segmentation include past purchasing habits along with the players interactions within the missions. This study uses the Recency Frequency Monetary Value (RFM) framework to extract insights on player purchasing behavior to segment players into clusters and predict how much users will spend in the future.

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