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.

Featured Image

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.
You can read the full text:

Read

Contributors

The following have contributed to this page