Enhancing Customer Retention in Online Games Using Customer Lifetime Value

Inamdar, Aasim (2024) Enhancing Customer Retention in Online Games Using Customer Lifetime Value. Masters thesis, Dublin, National College of Ireland.

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Abstract

Customer Lifetime Value (CLV) is a crucial metric in the online gaming industry, and proper pathway strategies to enhance user engagement, monetisation, and retention. The research dug deeper to find the key factors influencing the CLV in freemium gaming environments and the application of advanced machine learning techniques to predict the CLV accurately. The analysis of the player data, including gameplay behaviour, in-app purchases and churn likelihood, aims to identify the patterns that categorise high-value players from casual users. Predictive modelling is a hybrid approach of convolutional neural network (CNN) and recurrent neural network (RNN) where the output recommends optimising the game design, user retention strategies and personalised recommendations to retain users. The model achieved a testing accuracy of 90 per cent and a minimal loss of 0.36. Personalised interventions based on the CLV predictions lead to enhanced retention rates and faster revenue growth, with the practical applicability of the frameworks. This research bridges the gap between the theoretical CLV research and its application in dynamic ecosystems, offering insights for the developers and stakeholders in the online gaming industry, with contributions to the ever-evolving discourse on the customer centric design to provide a data-driven road map to improve player experience and long term value.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Singh, Jaswinder UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science H Social Sciences > HF Commerce > Marketing > Consumer Behaviour G Geography. Anthropology. Recreation > GV Recreation Leisure > Games and Amusements > Online Games
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	02 Sep 2025 12:52
Last Modified:	02 Sep 2025 12:52
URI:	https://norma.ncirl.ie/id/eprint/8711

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