Tourism and Big Data: A Perfect Match

Massive data management has become a crucial ally in enhancing the tourism service offering and facilitating the industry's recovery after the pandemic. The use of Big Data and management tools allows tourism companies to leverage data as raw material to develop effective strategies and gain a competitive edge. Accurate and holistic data collection, from origin to tourist preferences and behaviors, enables predicting future needs and personalizing services. Moreover, the ability to share and combine data between different entities and organizations provides a more comprehensive view of tourists and facilitates agile decision-making and the development of tailored products and services.

Massive data management is the perfect ally for improving tourism service offerings. After the impact of the pandemic, technology is the most effective partner for recovery.

Big Data and tools for managing large volumes of data have gradually become significant allies in the tourism industry. Digital transformation fully affects companies in this sector regardless of their size, and data is the raw material for developing strategies that positively impact the business and provide a competitive differential.

 This has become even more relevant considering the blow the COVID-19 pandemic  meant to the industry. Global mobility restrictions caused significant losses for the sector: In Spain alone, revenues dropped by 77% in 2020, with nearly 90 million fewer international tourists and an 80% reduction in spending compared to 2019. This sector is a key and indispensable part of the Spanish economy, making technology crucial for supporting its recovery and long-term growth.

Until a few years ago, data collection in the tourism industry was done through surveys, studies, or information from documents or forms that tourists voluntarily filled out. Technologies like Big Data now allow for more accurate and holistic tracking of all tourist actions and activities, turning this data into useful information to define more effective strategies and optimize sales.

From origin to types of accommodation, frequent visits, most chosen places, length of stay, common routes or transfers between cities, or average spending, having this volume of information, analyzing it, and segmenting it allows predicting future expectations and needs of individuals. Additionally, information from apps developed by hotels, museums, airports, or other points of interest is sensitive and essential for understanding how people move when traveling. Besides apps, another major data source is mobile phone geolocation, which helps determine how each phone “travels” (where it sleeps, works, stays), providing a complete picture of the customer journey. Furthermore, social media and review sites like TripAdvisor or Google My Business are substantial data sources.

Another significant advantage of applying Big Data to the tourism sector is the ability to share and cross data between different entities and organizations. From the hotel industry to various transportation modes, tourism boards, or data from public entities managing tourism sectors, combining information from these different sources results in a more accurate and global picture of tourist behaviors and preferences.

Detecting patterns or trends emerging from this data speeds up decision-making or the development of products and services that attract more customers and retain existing ones with tailored offers.

It’s important to note that until a few years ago, success in the tourism industry was more associated with price. There was very little segmentation, and generally, tourism service offerings were more homogeneous.

 Today, price is not the only decision driver: personalization is a growing value, and experiences are considered a key element when planning trips or vacations. Anticipating tourists’ needs and preferences is crucial for sector success. The customer must be at the center of the entire strategy, and personalization and segmentation of tourism services are more effective through efficient data management.

Julio Cesar Blanco – October 13, 2022

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