Leveraging Big Data Analytics for Personalized Marketing Strategies in the Hospitality Sector

Abstract

Purpose: This study sought to understand leveraging big data analytics for personalized marketing strategies in the hospitality sector. Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library. Findings: The findings reveal that there exists a contextual and methodological gap relating to leveraging big data analytics for personalized marketing strategies in the hospitality sector. Preliminary empirical review revealed that the integration of big data analytics presented significant opportunities for enhancing marketing initiatives within the hospitality industry. It emphasized the importance of investing in robust data infrastructure and analytics capabilities, addressing challenges such as data privacy concerns and organizational resistance to change, and continuously refining personalized marketing strategies based on data-driven insights. Overall, the study highlighted the transformative potential of leveraging big data analytics to drive customer engagement, satisfaction, and revenue growth in the hospitality sector. Unique Contribution to Theory, Practice and Policy: The Relationship Marketing Theory, Technology Acceptance Model (TAM) and Service Dominant Logic (SDL may be used to anchor future studies on leveraging big data analytics for personalized marketing strategies in the hospitality sector. The study provided several recommendations for advancing theory, practice, and policy in the industry. It suggested further exploration of the intersection between big data analytics and relationship marketing theory, emphasizing the importance of understanding employees' attitudes towards data-driven initiatives. Practically, the study recommended investing in data infrastructure, analytics capabilities, and fostering a culture of data-driven innovation within hospitality organizations. Policy-wise, it advocated for the development of industry standards for data privacy and skills development, as well as fostering collaboration between stakeholders to drive innovation and knowledge exchange in the field. Keywords: Leveraging, Big Data Analytics, Personalized Marketing Strategies, Hospitality Sector, Relationship Marketing