Tourism data is the collection of information about tourism in a specific country or region. The data is usually organized into inbound and outbound travel. Variants such as flights, car rentals, hotel stays, visits to attractions, and more are usually recorded.
The United Nations World Tourist Organization (UNWTO) is one of the largest providers of tourism data, with a focus on sustainable and accessible tourism. The UNWTO tracks tourist arrivals, departures, and spending worldwide, with data going back decades.
Aside from UNWTO, different public and private services collect tourist data. These data providers include border control, public and private transport companies. Additionally, tourism-dependent companies are also high contributors to this data, these companies include places like restaurants, hotels, and tourist attractions.
Finally, banks and other financial institutes record data on travel expenditure by travelers, as well as export taxes paid, and more.
Common attributes of tourism data include domestic and foreign arrivals and departures, traveler expenditures, national revenue generated from the industry, and the number of local residents working in the industry, the capacity and demand for accommodations. Additional attributes of this data may also include current events and seasons which affect regional or global tourism.
State and private institutions use this information to make funding and worker benefits decisions. Advertisers also use data on capacity, demand, and previous travel statistics about a location to advertise to different population segments. Future travel and tourism trends can also be predicted, enabling those in the industry to capitalize on trends and address tourist needs almost instantaneously.
For these other data sources, the most important factor in measuring data quality is the comparability of the data over time.
Filtering quality data from the abundance of information is always a difficult task. A tourism database should be built on diverse sources of information but rely predominantly on figures from official tourism sources such as UNWTO, border control, and ministries of tourism, guaranteeing validity and accuracy of information.
You should consider the information sources, the frequency of database updates, and the combination of other types of information.
While not crucial, tourism analytics can tip the scales in favor of a certain provider. Travel intent data then helps predict future travel volume, expenditure, and identification of tourist trends.
With the use of predictive analytics modeling and IoT in the form of Alexa Skills, KAYAK has set a new benchmark for other companies in the travel industry. Users can use a simple voice query like, “Alexa, ask KAYAK where can I go on vacation in October for $1000” to get a list of viable holiday options with the necessary constraints applied. KAYAK integrated with Alexa Skills helps users to track flights, book hotels and search for holiday options.
United Airlines shows a “collect and analyze” approach to their data. The company tracks customer behavior using real-time data with more than 150 variables, including individual and general historical data. This large dataset forms the input for detailed customer segmentation and adaptive UX/UI designs in real time according to the category a particular user belongs to.
Table of INEBase Guests and overnight stays by type of accommodation and Autonomous Community. Monthly. Autonomous Communities and Cities. Hotel Occupancy Survey . Campsite Occupancy Survey . Holiday Dwelling Occupancy Survey . Rural Tourist Accommodation Occupancy Survey
X-Byte’s dataset – ‘X-Byte | Travel, Hotel and Flights Price Intelligence | Travel Data API’ provides Aerospace Industry Data, Hospitality Industry Data and Tourism Data that can be used in
X-Byte’s dataset – ‘X-Byte | Global Travel and Tourism data in Real-Time API (Hotels, Airlines, Cruises, Car Rentals)’ provides Hospitality Industry Data and Tourism Data that can be used in Pricing Optimization, Competitor Analysis and