Customer Lifetime Value: A Data Science Approach for Hospitality Applications

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Author(s)Webb, Timothy
Author(s)Cho, S. Ray
Author(s)Legg, Mark P.
Date Accessioned2023-01-05T18:50:43Z
Date Available2023-01-05T18:50:43Z
Publication Date2022-11-04
DescriptionThis 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
AbstractSegmentation 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.
CitationWebb, 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
URLhttps://udspace.udel.edu/handle/19716/31985
Languageen_US
PublisherInternational Journal of Gaming, Hospitality and Tourism
Keywordshospitality
Keywordscasinos
Keywordscustomer lifetime value
KeywordsMarkov chains
Keywordscustomer relationship marketing
TitleCustomer Lifetime Value: A Data Science Approach for Hospitality Applications
TypeArticle
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