Customer Lifetime Prediction Based on Customer Profile Data in Mobile Game Industry
Bildiriler > Özet Bildiri · 2020
Yazarlar: İnanç KABASAKAL
International Conference on Access to Recent Advances in Engineering and Digitalization, Türkiye, Kayseri, Ulusal, Sözlü Sunum, Özet Bildiri, 2020-2020, ss 55-55
Özet
<p>Mobile game development has been a globally rapidly growing industry. Two major ecosystems (IOS and Android) support their participant developers by providing access to customer profiles. By this means, leveraging customer data with customer analytics is crucial for such businesses. This study presents a lifetime prediction model designed to identify relatively valuable players. The model depends on prior players' in-game behaviors and extracts patterns that signify a player with high lifetime value. For such purpose, our approach initially involves lifetime value calculation and, subsequently, frequent in-game action rule extraction. Next, predictor rules are discovered with the association rule mining technique. The model is presented along with a case study over a limited dataset for in-game player behaviors obtained from a mobile game developer in Turkey.</p>