Digital Platforms and Personalized Hospitality: How SaaS Is Transforming Customer Experience Ecosystems

Abstract

The hospitality industry has historically been defined by its emphasis on human interaction, relational service, and experiential value creation. Yet over the last two decades this sector has undergone a profound digital transformation as cloud-based software-as-a-service (SaaS) platforms, algorithmic personalization engines, and data-driven marketing systems have become deeply embedded in the design, delivery, and governance of hospitality experiences. This article develops a comprehensive theoretical and empirical synthesis of how SaaS architectures reconfigure personalization, trust, privacy, and customer engagement in contemporary hospitality ecosystems. Drawing on the conceptual framework articulated by Goel (2025), which positions SaaS not merely as a technical infrastructure but as a strategic logic for experiential orchestration, the article situates hospitality digitalization within broader debates on recommender systems, algorithmic bias, privacy calculus, and customer journey analytics. By integrating insights from marketing science, information systems, and behavioral economics, the study advances a multi-layered understanding of how hospitality firms deploy SaaS-based personalization technologies to optimize customer lifetime value while simultaneously navigating ethical, regulatory, and psychological constraints.

The abstract argues that SaaS-enabled hospitality is best understood as a platformized service ecology in which data flows, algorithmic decision-making, and modular digital services continuously reshape the boundaries between firm and guest. Recommender systems derived from the traditions of Adomavicius and Tuzhilin (2005) and further advanced through reinforcement learning architectures (Afsar et al., 2022) allow hotels and hospitality brands to dynamically curate offerings, from room upgrades to food and beverage recommendations. At the same time, privacy research demonstrates that personalization is governed by a paradox in which customers demand tailored experiences but resist intrusive data collection, a tension empirically documented by Acquisti et al. (2015) and Aguirre et al. (2015). This article therefore conceptualizes SaaS-based hospitality personalization as a socio-technical negotiation among algorithmic capability, consumer trust, and institutional governance.

Methodologically, the study adopts a qualitative meta-synthesis of the provided literature, treating the cited works as empirical traces of a broader transformation in marketing analytics and service design. The results demonstrate that SaaS platforms function as the connective tissue linking customer journey mapping (Anderl et al., 2016), engagement dynamics in social and digital environments (De Vries & Carlson, 2014), and customer-base modeling (Fader & Hardie, 2009). These interdependencies generate both unprecedented opportunities for loyalty and retention, as emphasized by Bain and Company (2020) and Accenture (2018), and new risks associated with algorithmic bias and discrimination (Akter et al., 2022; Akter et al., 2023). The discussion situates these findings within ongoing debates about the future of marketing automation and artificial intelligence (Davenport et al., 2020), ultimately arguing that hospitality firms must move beyond narrow efficiency logics toward a more reflexive, ethically grounded model of digital service governance. In doing so, the article contributes a theoretically rich, policy-relevant account of how SaaS is redefining what it means to host, serve, and engage the contemporary hospitality consumer.