Predicting Customer Lifetime Value in Free-to-Play Games

TL;DR

This paper reviews methods for predicting customer lifetime value in free-to-play games, addressing unique challenges and discussing state-of-the-art solutions to support game business decisions.

Contribution

It provides a comprehensive overview of customer lifetime value modeling tailored to free-to-play games, highlighting specific challenges and recent solutions.

Findings

Identifies key challenges in free-to-play game revenue prediction.

Summarizes current modeling techniques and their effectiveness.

Provides practical examples and references to implementations.

Abstract

As game companies increasingly embrace a service-oriented business model, the need for predictive models of players becomes more pressing. Multiple activities, such as user acquisition, live game operations or game design need to be supported with information about the choices made by the players and the choices they could make in the future. This is especially true in the context of free-to-play games, where the absence of a pay wall and the erratic nature of the players' playing and spending behavior make predictions about the revenue and allocation of budget and resources extremely challenging. In this chapter we will present an overview of customer lifetime value modeling across different fields, we will introduce the challenges specific to free-to-play games across different platforms and genres and we will discuss the state-of-the-art solutions with practical examples and references to existing implementations.