Keywords
personalization
clustering of guest flows
digital technologies
behavioral models
How to Cite
Abstract
The article is devoted to the problem of increasing the personalization of service in the hotel business through the digital clustering of guest flows. The relevance of the research is due to a shift in the attitude towards data as a strategic resource of the enterprise and the need to find new tools for working with clients in an economy of impressions. The authors note that the existing online (CRM) and offline (GEM) datasets are isolated, which reduces the effectiveness of their interpretation. The research purpose is to study the adaptation of digital array processing technologies to increase personalization. The key hypothesis transforms personalization from creating an absolutely unique service into a multiservice model for socio-psychological groups of guests. The concept of a “guest data array” is introduced and a behavioral marker is highlighted as a connecting element. The main contribution is made by the customer service response (CSR) model, which captures behavioral signals along four vectors (control orientation, structural demands, emotional openness, and risk sensitivity) and forms a digital profile of the guest for optimal selection of service patterns. Mathematical clustering methods (k-means, hierarchical clustering, LCA) are considered. Special attention is paid to legal, organizational, and ethical constraints, including compliance with 152-FL and the principles of responsible use of AI. The authors emphasize that clustering should serve as a tool to help staff, and not replace professional judgment. The conclusions emphasize the transition from the question “who is the guest” to the question «how to work with him”, which opens up prospects for the evolution of service systems in the digital economy.
References
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27. Sorgente, A., Caliciuri, R., Robba, M. et al. (2025) Publisher Correction: A systematic review of latent class analysis in psychology: Examining the gap between guidelines and research practice. Behav Res 57, 331. https://doi.org/10.3758/s13428-025-02871-4
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