Grouping hotel restaurant customers based on a behavioral scoring model: An exploratory study

초록

Segmentation, targeting, and positioning are the most important keys to a successful marketing strategy in the hospitality industry. Among these three keys, segmentation is the first step for a marketer to identify various customer needs and desires. Hospitality operators have been trying to increase customer satisfaction and corporate profits by utilizing mass marketing, database marketing, and individual marketing. Despite the increased interest in scoring consumer behavior, applications of the score remain difficult. The lack of understanding and utilization of scores has been an important issue in the hospitality industry. Analysis of customer behavior is not an easy problem to solve because dynamic modeling is required due to changes to customers’ records over time. The current study explores customer data in hotel restaurants and proposes an individual behavior scoring model (BSM) based on the traditional RFM (recency, frequency, monetary) concept. By comparing it with the traditional profiling scoring model (PSM), it is shown that BSM provides a high prediction power of future consumers' behavior. However, PSM has an important role in a complementary sense to identify potential customers who have low behavior scores. This research proposes how to build and validate BSM and PSM with a focus on the utilization of the two models to identify future potential customers efficiently.

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