In some coastal tourist towns like Biarritz on the Basque coast, the population may multiply 4-fold with the arrival of the sunny months. In the mountains, second homes often make up the majority of a ski resort's housing stock and 30% to 40% of the accommodation is considered to be "cold beds".*. School holidays, long weekends, weather and sports competitions are all factors which influence the phenomena of seasonality and whose consequences on economic balance and local infrastructures greatly affect all aspects of city management. Thus, tourist services, traffic flow, entertainment, facilities and cleaning, are all affected by these population flows.
In high season, public services and businesses in cities must adapt to fluctuations in population, hence their interest in forecasting these. To do this, daily measurement of water consumption provides an overview of visitor numbers. In the French Alps, at Les 2 Alpes ski resort, the water consumption recorded by SUEZ ON’connect™ smart meters multiplied 6-fold between the opening and closing of the ski slopes. By combining these data with those of other influencing factors, such as weather forecasts or the French school holidays and those of our European neighbours, it is possible to discover the occupancy rates for tourist accommodation precisely and on a detailed scale, whether these are second homes or hotels. Using this information, the city can both regulate its supply of housing and tourist services, and adapt the resources allocated to the running of the town.
ON'CONNECT TOURISM: A WEB PLATFORM DESIGNED FOR PROFESSIONALS IN CITY AND TOURIST SERVICES
For cities with smart water meters, the ON’connect™ tourism platform offers a daily overview of tourist accommodation occupancy rates. This daily updated information makes it possible to compare the activity of one district with another, and to observe variations in visitor numbers over time and between two periods. The platform also makes it possible to estimate tourist arrivals for all or part of the region, a calculation made according to the occupancy rate for the accommodation and the average expenditure. Finally, cross-referencing of data permits the forecasting of tourist visitor numbers, which is the first step towards adapting municipal services.