Analysis of Intelligent Technology Applications in Personalized Hotel Marketing

Intelligent technologies are profoundly transforming the marketing paradigm in the hotel industry, driving its shift from standardized services to personalized experiences. This study demonstrates through systematic analysis and case studies that technologies such as Artificial Intelligence (AI) recommendation algorithms have been widely applied across multiple stages—including user demand mining, customized marketing content, and scenario-based services. By constructing multidimensional user profiles, enabling precise product recommendations, and delivering intelligent interactive services, these technologies significantly enhance both user experience quality and hotel operational efficiency. However, the application of intelligent technologies still faces numerous challenges. At the data level, there are privacy compliance risks and data quality issues; at the technical implementation level, challenges include high deployment costs and technical compatibility difficulties; at the user level, issues such as varying experience perceptions and divergent group acceptance rates must be addressed. These challenges require hotels to prioritize balancing privacy protection, cost control, and human-cantered service while advancing intelligence. Future intelligent development in the hospitality industry should establish a dynamic matching mechanism between technology application and user needs. It must fully leverage smart technologies to elevate service standards while avoiding the pitfall of “technology supremacy,” ultimately achieving the dual-win goal of maximizing personalized marketing.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-11-13
DOI
https://doi.org/10.1051/shsconf/202522501044/pdf
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
0.00
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article

Analysis of Intelligent Technology Applications in Personalized Hotel Marketing

Springer Link (Chiba Institute of Technology)
Digital Marketing and Social Media
article

Analysis of Intelligent Technology Applications in Personalized Hotel Marketing

article en

Abstract

Intelligent technologies are profoundly transforming the marketing paradigm in the hotel industry, driving its shift from standardized services to personalized experiences. This study demonstrates through systematic analysis and case studies that technologies such as Artificial Intelligence (AI) recommendation algorithms have been widely applied across multiple stages—including user demand mining, customized marketing content, and scenario-based services. By constructing multidimensional user profiles, enabling precise product recommendations, and delivering intelligent interactive services, these technologies significantly enhance both user experience quality and hotel operational efficiency. However, the application of intelligent technologies still faces numerous challenges. At the data level, there are privacy compliance risks and data quality issues; at the technical implementation level, challenges include high deployment costs and technical compatibility difficulties; at the user level, issues such as varying experience perceptions and divergent group acceptance rates must be addressed. These challenges require hotels to prioritize balancing privacy protection, cost control, and human-cantered service while advancing intelligence. Future intelligent development in the hospitality industry should establish a dynamic matching mechanism between technology application and user needs. It must fully leverage smart technologies to elevate service standards while avoiding the pitfall of “technology supremacy,” ultimately achieving the dual-win goal of maximizing personalized marketing.

Springer Link (Chiba Institute of Technology)
Industry, innovation and infrastructure
Openalex Percentile: Top 29%
Digital Marketing and Social Media
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Analysis of Intelligent Technology Applications in Personalized Hotel Marketing · Springer Link (Chiba Institute of Technology) (2025) | TGRS Research Map | TGRS