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Predicting Customer Lifetime Value in Free-to-Play Games

Research Output:
Conference Article in Proceeding or Book/Report chapter
Book chapter
Peer-review

Publication Information

Output type

Research Output:
Conference Article in Proceeding or Book/Report chapter
Book chapter
Peer-review

Original language

English

Publication milestones

  • Published - 18/06/2019

Publication status

Published - 18/06/2019

Publisher

Taylor & Francis

Book series

  • Book series name: Data Analytics Applications
978-1138104433

Chapter Number

5

Publication IDs

  • Scopus: 85122969248

Host publication title

Data Analytics Applications in Gaming and Entertainment

Abstract

As game companies embrace increasingly a service oriented business model, the need for predictive models of player behaviour becomes more pressing. Various 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 behaviour make predictions about the revenue and allocation of budget and resources extremely challenging.

In this chapter we will present and overview of customer lifetime value modelling 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.

Publication metrics

PlumX

Captures
34
Citations
16