Utilizing Big Data for Improved Targeting and Personalization for Digital Marketing Purposes in the Tourism Industry: A Comprehensive Review

This paper aims to provide a holistic literature review of big data analytics and how they complement digital marketing, within the travel and tourism sector. It combines big data with the traditional marketing theories and gives an insight into how advanced analytics can help firms improve their consumer segmentation, targeting, and personalization strategies. The defining features of big data (volume, velocity, variety veracity, and value) unlock the ability to synthesize tremendously large datasets with different primary sources into actionable information. Such insights enable tourism marketers to craft laser-focused and high-impact marketing campaigns, which leads in better customer engagement and retention. The paper discusses the theory around big data analytics within the context of tourism and offers insights into practical implementations of advanced storage/processing technologies (e.g., Hadoop, Apache Spark) that are useful for analyzing large volumes from original data sources. It also explores the impact of recent technological developments, such as AI and blockchain in redefining digital tourism marketing. At the same time, developments such as AI through machine learning and natural language processing are making real-time customer interactions more personal than ever, while blockchain gives security in data and transparency. The research highlights the huge opportunities for innovation and success in digital marketing in tourism, through the use of big data analytics. Its implications provide valuable insights for both practitioners and researchers, while pointing out future trends that can be used to guide the integration of emerging technologies with ethical considerations on data analytics tools in tourism marketing.