METhODOlOG ICAl NOTE

5.1. Description of the

datasets

Fields and descriptions of BBVA’s dataset

DATE COUNTRY TELEPHONE ID CELL ID LATITUDE LONGITUDE

Date and time the event took place

Country of the operator that issued the telephone’s SIM card The telephone’s ID.

Under no circumstances is it the telephone’s real number The ID of the base station the telephone was

connected to when the event took place Latitude of the base station’s position Longitude of the base station’s position

Field Description

One aspect to take into account is that credit or debit card payments are only part of the total payments in the shop since approximately 50% of spending in shops is carried out using cash. This percentage fluctuates depending on the shop’s category and its surrounding area but also cultural biases inherent to the user’s nationality. None of the results presented in this report is an extrapolation used to deduce total spending by foreign tourists. In all cases, the figures shown are those gathered by BBVA’s electronic payment systems and they should not be taken as absolute figures for spending through any means of payment.

The dataset used in this study comes from records of certain network events generated by telephones with a SIM card issued by operators outside of Spain, which are roaming on Telefónica Móviles España’s network. Examples of these kinds of events include turning on the telephone, sending an SMS, making a call or changing coverage area. When one of these events takes place, it is logged together with the base station the telephone is connected to and the time it took place. Since the exact location of each base station is known, that gives an approximate idea of where the telephone is at that time. Logs basically have the following format:

5.1.2. Telefónica’s dataset

Table 18:

Fields and descriptions of Telefónica’s dataset

To comply with data protection regulations and ensure privacy, these logs are anonymous since the real telephone number is replaced with a unique identifier in a way that makes it impossible to carry out the process in reverse (you cannot obtain the telephone number from the identifier). However, furthermore, the logs are not used individually: they are always aggregated in order to identify general behaviour (normally by nationality) and never individually. As if that were not enough, the identity of the owners of roaming telephones (those used in this study) is information that Telefónica Móviles España never possesses as they are not its own subscribers. In view of all this, it is totally impossible to individually identify the owners of those telephones.

5. Methodological note

As with all datasets, there are certain limitations of which one needs to be aware. The telephone’s location is not totally precise as what we have is actually the base station’s location. That is not too problematic in urban environments as the density of base stations there is high enough to provide reasonable precision; but it can be in rural areas. There may be another limitation when extrapolating total data from the information obtained. One specific example is that not all telephones used by Russian tourists who visit Spain connect to Telefónica’s network, which means that if one wants to know the total number of Russian telephones then some extrapolation is necessary that could introduce certain errors. In this report all of the data presented are not extrapolated, so they cannot be taken as absolute. However, we think that nevertheless they provide a pretty clear idea of the situation.

This report has been drawn up based on anonymised, aggregate data that have then been extrapolated through a statistical process ensuring they are completely disassociated pursuant to Spanish law (LOPD 15/1999 and its developing regulations, RD 1720/2007, and Ley General de Telecomunicaciones

32/2003). This completely prevents the identification of any individual based on the data used and so guarantees users’ privacy.

The data and recommendations described are based on the data gathered as described in 5.1.1 and 5.1.2. Coefficients have not been used to extrapolate all of the indicators in this report.

Data was processed subject to a responsible code of conduct by all parties and processing was carried out solely in order to encourage progress in transforming society and tourism.

Unique telephones registered (Telefónica data) Average stay (Telefónica data)

Average stays in Barcelona depending on the day on which the visits start and the total (Telefónica data)

Average stays in Madrid depending on the day on which the visits start and the total (Telefónica data)

Percentage distribution of the number of telephones in Barcelona according to four stay length ranges (Telefónica data)

Percentage distribution of the number of telephones in Madrid according to four stay length ranges (Telefónica data)

Travel between cities (B-Barcelona, M-Madrid) expressed in percentages. For example, B shows the telephone does not leave Barcelona and B-M-B shows the telephone moved to Madrid and back to Barcelona (Telefónica data)

Distribution of accommodation by district in Barcelona (BBVA data) Distribution of accommodation by district in Madrid (BBVA data) Distance (km) from accommodation to the city centre: Plaza de Cataluña and Puerta del Sol (BBVA data)

Average spending (€) by card during the stay broken down by nationality and city (BBVA data)

Average daily spending in Barcelona by card broken down by nationality (BBVA and Telefónica data)

Average daily spending by card in Madrid broken down by nationality (BBVA and Telefónica data)

Average spending (€) on accommodation by card throughout the study period broken down by nationality and city (BBVA data)

Average daily spending on accommodation in Barcelona by card broken down by nationality (BBVA and Telefónica data)

Average daily spending on accommodation in Madrid broken down by nationality (BBVA and Telefónica data)

Fields and descriptions of BBVA’s dataset Fields and descriptions of Telefónica’s dataset

Table 1: Table 2: Table 3: Table 4: Table 5: Table 6: Table 12: Table 14: Table 16: Table 7: Table 11: Table 13: Table 15: Table 17: Table 18: Table 8: Table 9: Table 10:

6.1. List of tables

6. ANNEx

6. ANNEX

6.2. List of figures

Distribution of visitors by country (Telefónica data)

Distribution of visitors between Barcelona and Madrid (Telefónica data) City preference, Barcelona over Madrid (Telefónica data)

City preference, Madrid over Barcelona (Telefónica data) Average stay in days in Barcelona and Madrid (Telefónica data) Overall distribution of length of stay (Telefónica data)

Distribution by days spent in Barcelona (Telefónica data) Distribution by days spent in Madrid (Telefónica data)

Percentage of overnight stays by district in Barcelona (BBVA data) Percentage of overnight stays by district in Madrid (BBVA data)

Percentage of overnight stays inside and outside of the city (BBVA data) Average overall spending by card throughout the study period by country and city (BBVA data)

Average daily spending by card broken down by country and city (BBVA data)

Average spending by card on accommodation during the study period by country and city (Telefónica data and BBVA)

Average daily spending by card on accommodation by country and city (Telefónica data and BBVA)

Figure 1: Figure 2: Figure 3: Figure 4: Figure 5: Figure 6: Figure 7: Figure 8: Figure 9: Figure 10: Figure 11: Figure 12: Figure 13: Figure 15: Figure 14: 14 14 14 14 18 18 19 20 24 26 26 28 30 35 33