What is it about?
In the competitive mobile gaming industry, retaining players and maximizing engagement are crucial for long-term success. This research employs machine learning techniques alongside the Beta-Geometric/Negative Binomial Distribution (BG/NBD) model to predict customer lifetime value (CLTV) and identify players at risk of churning. By leveraging these predictive insights, gaming companies can design targeted marketing strategies that significantly enhance player retention and overall engagement. This study highlights the transformative role of machine learning in addressing real-world challenges in the gaming industry.
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Why is it important?
Helps companies develop better customer retention strategies as it is more costly to acquire customers than to retain the existing ones.
Perspectives
The article provides practical and time tested methodologies to implement Machine Learning to Predict Player Loyalty and Boost Engagement in Mobile Games
Naga Lakshmi Subha Pavan Kumar Ghantasala
Purdue University
Read the Original
This page is a summary of: Enhancing Player Retention in Mobile Gaming through Predictive Customer Lifetime Value Modeling using BG/NBD, AI Matters, June 2024, ACM (Association for Computing Machinery),
DOI: 10.1145/3694712.3695754.
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