A parsimonious stochastic model for forecasting gamers' revenues in casinos
Article first published online: 27 MAR 2012
Copyright © 2012 John Wiley & Sons, Ltd.
Applied Stochastic Models in Business and Industry
Volume 29, Issue 3, pages 254–263, May/June 2013
How to Cite
Hui, S. K. (2013), A parsimonious stochastic model for forecasting gamers' revenues in casinos. Appl. Stochastic Models Bus. Ind., 29: 254–263. doi: 10.1002/asmb.1914
- Issue published online: 17 JUN 2013
- Article first published online: 27 MAR 2012
- Manuscript Revised: 23 JAN 2012
- Manuscript Accepted: 23 JAN 2012
- Manuscript Received: 13 MAY 2011
- revenue forecasting;
- casino industry;
- stochastic model
The gaming industry is the largest entertainment industry in the United States, with more than $80 billion in revenue annually. Because of the stochasticity of gambling outcomes and the complexity of the casino context, forecasting individual-level revenues in a casino setting is extremely challenging, and yet crucial for customer relationship management. Current approaches for customer base analysis are usually too general to handle the unique context of the casino setting. To fill this gap between research and practice, this paper develops a stochastic model that incorporates visitation, wagering, and gambling outcomes to forecast gamers' revenues for a major casino operator. The proposed model is parsimonious and can be scaled to handle massive casino customer databases. Despite its parsimony, a holdout prediction test shows that the proposed model provides more accurate individual-level revenue predictions than other forecasting methods that are based only on the observed data. Copyright © 2012 John Wiley & Sons, Ltd.