Arenametrix and Dotmap

Data & Tourism: Your competitiveness depends on your data

Your competitiveness is
through your data

According to D. Buhalis, professor of marketing specializing in innovation for tourism: " The competitiveness of a tourist destination is based on its ability to continuously attract tourists by offering high quality and unique experiences, ensuring benefits for stakeholders and thus enabling sustainable development. ». This article aims to present an overview of the possibilities of Big Data as a path to sustainable development for tourism destinations.

I Towards a relevant reading of your data

Tourism is an information-intensive industry. According to D. Cardon, a sociologist specializing in digital technology "the main challenge facing big data is to make sense of this magma of raw data".. The main challenge for tourist destinations is therefore not so much to collect large quantities of data as to understand the interest and how to use them. There are three types of data:

a) User Generated Content (UGC)

This data is generated by tourists in order to share their experiences. It encompasses a large part of the digital activity of users, such as online reviews, travelogues or photographs taken during the stay. They allow:

  • to measure the satisfaction of tourists with the various products tested
  • to establish tourist circuits according to the destinations
  • to measure the various points of interest of visitors.
data airport

B) Transactions data

These data includes data recorded by your various contacts during their interactions with your organization. It corresponds to their banking data, their Internet searches, their ticket purchases and their various reservations. It is intended to ensure a more detailed knowledge of your tourists and to carry out predictive analyses of their behaviour.

To take up the idea of D. Cartons idea, making the best use of this data is a challenge for organisations, which must manage to centralise data from diverse and often compartmentalised sources. The CDP (Customer RelationShip Management) is often their best ally.

(c) Devices data :

This last category encompasses all data recorded via electronic devices. GPS, Roaming, RFID, WIFI, Bluetooth etc. data can thus provide a wealth of additional information by tracking the tourist experience:

  • Mobile data can be used to visualize the seasonality and provenance of tourists within a region, and between different areas. 
  • Weather data can be used to anticipate variations in demand for sports and cultural activities.
  • Finally, GPS data allows us to reconstruct the routes taken by tourists during their stays, which can lead to reflections on optimising the proposed tourist routes.

The use of data from these technical devices is an important source of innovation for companies, such as Dotmap. This company offers its clients a white-label solution to produce interactive maps aimed at reinforcing the link between structures and visitors by offering interactive, personalized and fun routes.

Table presenting the uses of the new data sources collected, as well as their limitations

Data source Possible uses Benefits Barriers

Mobile data

  • Provides detailed information on tourist flows and mobility patterns.
  • This makes it possible to track tourists' interest in specific cultural attractions and the trajectories of their visits.
  • Collected automatically.
  • Representative of the population.
  • Captures same day visitors. 
  • Legal restrictions (privacy regulations).
  • Public fear of being tracked.

Data from the social media

  • Provides information on tourist flows, and their perceptions of tourist attractions.
  • Predicts tourists' decisions about certain sites.
  • Includes qualitative information.
  • Data often available in real time.
  • Generally available online at little or no cost.
  • Data may not be available in machine-readable formats.
  • Their use is still in the experimental stage. 

Data on tourist trips

  • Provides information on tourist mobility patterns.
  • Allows you to monitor traffic to specific cultural sites.
  • Assists in planning new cultural tourism facilities.
  • Automatically generated data.
  • Captures same day visitors.
  • Identifies the various facilities of interest to the target group. 

It is difficult to distinguish between local and tourist traffic.

Data from the collaborative economy

  • Provides information on visitor mobility and consumption that is not included in official tourism statistics.
  • Provides more detailed data on visits to specific cultural sites.
  • Allows monitoring of the movement and consumption of tourists who do not use traditional accommodation and transport services.
  • Large amount of data at a detailed geographical level.
  • Increasingly important data source due to its growing use.
  • Data not readily available.
  • Requires high quality predictive models to support information selection.

II Towards the development of Smart Tourism

The growing dependence of tourism on ICT (Information and Communication Technologies) and data has been taken into account in the concept of "Smart Tourism". Behind this abstract notion lies the idea of connecting data from multiple stakeholders to improve the visitor experience. Smart destinations, i.e. tourist destinations that integrate ICT, are a central element of smart tourism. Destinations have done this, for example, by using sensors to measure and manage people's movement, by providing tourists with geo-located information via smartphone applications, by collecting real-time location information on public transport and sharing it live on information screens at bus stops, etc.

Lyon smart tourism capital
Festival of Lights in Lyon

France has nothing to be ashamed of in this respect. In 2019 Lyon has been elected European Capital of Smart Tourism in 2019 Lyon has been awarded the title of European Smart Tourism Capital in 2019, tied with Helsinki-against 37 other European cities. Among other things, the deployment of its CDP destination was praised. Europe OnlyLion Experience. The adoption of this tool will allow each visitor to benefit from personalised advice before, during and after their stay in Lyon to make it a unique experience. Although the concept of smart tourism is focused on improving the traveller's experience, the data generated by smart tourism applications can also be used for tourism planning and governance at an international level.

III Towards the development of the sharing economy

One of the recent trends that has had a significant impact on tourism, and more specifically on cultural tourism, is the rapid growth of the sharing economy. This term refers to " business models in which activities are facilitated by collaborative platforms that create an open market for the temporary use of goods or services often provided by individuals". For example, AirBnB/ for accommodation bookings can map accommodation facilities at detailed regional/city/village levels. The sharing economy generates a lot of data that can be very beneficial for city planners, tourism promotion agencies and the management of various cultural attractions. Open, big data based predictive models could help predict tourist decisions to optimize marketing strategies.

Sources :

  • Buhalis, D.; Law, R. Progress in tourism management: Twenty years on and 10 years after the internet: The state of eTourism research. Tour. Manag. 2008, 29, 609–663. [Google Scholar] [CrossRef][Green Version]
  • GSMA. The Mobile Economy. Available online: (accessed on 13 July 2020).
  • The impact of digital and innovation on tourism, 2017. . Digital Corner. URL (accessed 3.18.21).
Sophia Baladi

Sophia Baladi

Would you like to carry out a data & CDP diagnosis of your organisation? Take advantage of 30 minutes of free consulting by reserving your slot.

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Solène Jimenez

Would you like to carry out a data & CDP diagnosis of your organisation? Take advantage of 30 minutes of free consulting by reserving your slot.

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