Personalization of Travel Experiences Through Data Analytics

Abstract

Travel and tourism represent a multifaceted sector, with the customer's journey from departure to return encompassing myriad interactions. A deeper comprehension of these interactions allows for enhanced planning aimed at enriching the customer's experience. The integration of advanced data analytics has significantly advanced the focus on customer needs within the travel and tourism industry. In this specific study, data analytics is applied to tailor experiences for visitors to an amusement park, using a comprehensive dataset from a fictional park to explore how variables such as age, group makeup, admission time, ride preferences, and eating habits can enhance the visitor experience. The findings offer valuable insights into visitor behaviors, facilitating the customization of services. For instance, age-related data informs the imposition of ride restrictions, while data on arrival and departure times aid in refining park operations and managing crowds more effectively.