Eunju Suh, Ph.D., hospitality management professor, recently attended the 20th Asia Pacific Tourism Association (APTA) Conference in Ho Chi Minh City, Vietnam, where she presented a study entitled “Predicting Cross-Gaming Propensity Using CHAID Analysis” (Eunju Suh and Matt Alhaery). Using a data set of 14,120 casino customers, this study aimed to predict a player’s propensity to play different types of casino games. The Exhaustive Chi-squared Automatic Interaction Detector (E-CHAID) method was employed to predict table game players’ slot play propensity and vice versa. The findings of this study will help marketers identify customers that are most likely to cross-play and maximize gaming revenues from more efficient and effective marketing actions.
After a rigorous evaluation process of more than 100 papers presented during the conference, the selection committee conferred Dr. Suh with the Best Paper Award.
Why was this topic important to you?
With the expansion of the casino industry in the global casino market, marketers are looking for opportunities to generate more revenues and improve their player acquisition and retention methods. Hence, customer data to identify, segment and target potential and existing customers have become more important than ever. Analyzing gaming (casino play) data would enable marketers to better understand customer behavior and predict specific behaviors. While casino marketers would agree on the importance of customer data collection and data driven-marketing, in gaming literature, there has been relatively little effort focused on prediction and classification of customer behavior using the actual recorded gaming data of existing casino patrons.
What innovative approaches did you employ in this study?
Considering the lack of research on the topic of cross-gaming, this study provides a better understanding of players’ cross-gaming behavior while making a meaningful contribution to the pool of gaming literature that examines gaming behavior. Furthermore, to the best of our knowledge, this is the first research that applies a data mining technique to the player data at the individual level to predict a specific gaming behavior, cross-gaming propensity in this case. This study will help casino marketers identify potential cross-gaming prospects more accurately and develop more efficient and effective actions for target marketing. Furthermore, it will help them increase gaming revenues from both existing and potential cross gamers while reducing marketing costs for targeting them.
Will this award inspire you and your students to conduct further research on this topic?
I believe this award confirms the importance of big data, predictive analytics in the hospitality and tourism industry, and encourages more relevant research.
Photo:
Professor Eunju Suh being presented with the Best Paper Award at the 20th Asia Pacific Tourism Association (APTA) Conference by Sang Taek Lim, Ph.D., Chairman of the Board, in Ho Chi Minh City, Vietnam.
