Recognizing Hotel Visitors Preferences Based on Service Consumption Level Using K-Means Method

Abstract

Consumer segmentation is an old issue that remains interesting to study today, given the magnitude of the benefits obtained when consumers can be segmented properly. Marketing cost efficiency is one of the great benefits of this process. Likewise, the effectiveness of marketing activities to maintain customer retention. It is because companies can better identify consumers. Based on the hotel service consumption level, this research could identify consumer clusters based on hotel consumer preferences. Thus, hotel management could target specific types of service promotion better and on target. This research built a hotel visitor clustering model using the K-Means Clustering method to determine customer segments based on the level and type of hotel service consumption. The K-Means model was built based on hotel visitor consumption data for each type of service. Furthermore, the hotel visitor clusters formed were identified by their characteristics. Four consumer clusters were obtained based on the silhouette score analysis, which described the characteristics of consumers in each cluster.