Customer Lifetime Value: A Data Science Approach for Hospitality Applications
Date
2022-11-04
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
International Journal of Gaming, Hospitality and Tourism
Abstract
Segmentation of databases based on Customer Lifetime Value (CLV) is the cornerstone of Customer
Relationship Management (CRM). To implement CRM strategies, the hospitality industry relies
heavily on loyalty programs to track customer behavior. Despite the prevalence of loyalty programs,
little attention has been given to CLV model formulation in hospitality. This paper reviews the extant
literature discussing CLV modeling and formulates a model with hospitality-specific considerations.
Based on the literature, a phased approach is proposed using cluster and Markov chain analyses,
while incorporating a new metric based on a customer’s expected trip cycle to identify lost customers
in the non-contractual setting. The model is empirically tested on casino loyalty data to demonstrate
the viability and robustness of the approach for hospitality sectors.
Description
This article was originally published in International Journal of Gaming, Hospitality and Tourism. The version of record is available at: https://stockton.edu/light/documents/ijght_vol.2no.1/customer_lifetime_value-data_science-11.3.22.pdf
Keywords
hospitality, casinos, customer lifetime value, Markov chains, customer relationship marketing
Citation
Webb, T. Cho. S. R. Legg, M. P. (2022). Customer Lifetime Value: A Data Science Approach for Hospitality Applications. International Journal of Gaming Hospitality and Tourism. 2(1). https://stockton.edu/light/documents/ijght_vol.2no.1/customer_lifetime_value-data_science-11.3.22.pdf