Antonio López de Avila at ENTER2016 eTourism Conference in Bilbao

1. Making Spain
a Smart
Destination

2. International Arrivals 2015
68.100.000
Tourists
3rd World Ranking
109.800.000
Visitors
41.700.000
Excursionists

3. International Tourists Expenses
2nd World Ranking
EUR 65,000 Billion

4. • Hyper Conected: well informed,
multichanel and demanding.
• Before, during and after
• Smartphones offer a better
experience (mobility, information,
inspiration, book, buy)
Changes in the Travel Consumer

5. Contents Generated

6. Information Available

9. Smart Destinations
Objectives
- Creation of a methodology to help destinations
- Creation of Spanish Norms:
UNE 178501 on Smart Destinations: Governance
UNE 178502 on Smart Destinations: Indicators
- Creation of an European Norm: EN
- Creation of an ISO Norm

10. Smart Destinations
An innovative tourism destination, built on an infrastructure of
state-of-the-art technology guaranteeing the sustainable
development of tourist areas, accessible to everyone, which facilitates
the visitor´s interaction with and integration into, his or her surroundings,
increases the quality of the experience at the destination,
and improves resident´s quality of life.

11. Smart Destinations
Improve competitiveness
Improve quality of life of residents
Enhace tourists experience

12. Smart Destinations

13. Smart Destinations

14. Smart Destinations

15. Smart Destinations

16. Smart Destinations

17. Smart Destinations

18. Smart Destinations

20. • 2 Platforms: Open Source and Licensed
software
• BIG DATA model focusing on the tourism
activity and its impact in a destination.
• Structured and Non Structured Data
• USER FRIENDLY: Live automated data
from many sources in one screen
• OPEN DATA
• COMPETITIVINESS: Allows public and
private sectors to take decisions and to be
more efficient and competitive.
Intelligence System - SIT

21. Data
Collector
Credit
Cards+POS
Info Hotels
Mobility
Parkings
Tourism Office
Health Centers
Sensors
Wifi
Agenda/Events
Tourism Boards
Municipalities
Companies
Analists
Hospitality
Restaurants
Others
Tourism Intelligence Platform
DataSources Users
Business
Intelligence
Intelligence System - SIT

22. Intelligence System - SIT

23. Online Reputation – Destination & Categories
Intelligence System - SIT

24. Intelligence System - SIT

25. Economic Impact – General Scenario
Intelligence System - SIT

26. Economic Impact – DomesticTourism
Intelligence System - SIT

27. Intelligence System - SIT

28. Economic Impact – International InboundTourists
Intelligence System - SIT

29. Intelligence System - SIT

30. Tourism Activity – Overnights and Average Stay
Intelligence System - SIT

31. Intelligence System - SIT

32. Intelligence System - SIT

33. Intelligence System - SIT

35. Major Challenges
1. DATA MODEL
CHAPTER I
EXPENSES
CREDIT
CARDS
+
POS
CHAPTER II
HOSPITALITY
OCCUPANCY +
REVENUE
ONLINE
REPUTATION
CHAPTER III
MOBILITY
WIFI
SENSORS
CAMARAS
CHAPTER IV
DESTINATION:
COLLABORATIVE
SOFTWARE
PARKINGS
MUSEUMS
CLÍNICS
RESTAURANTS
LODGE
TURIST INFO
POINTS
OFFICIAL EVENTS
CHAPTER V
OTHER EVENTS
SOCIAL
MEDIA

36. Public-Private Partnership
Major Challenges

37. Major Challenges
2. AUTOMATED LIVE DATA

38. Major Challenges
3. TRAINING

39. Overall Results
1. Valid, reliable, representative and
useful information.
2. Reasonable cost of implementation
and maintenance
3. Solid base to take decisions to be
more efficient and competitive (public
and private sector)

40. Key Results
1. Decreasing of the cost to obtain
and analyse the information.
2. Real and useful information at
every level (country, region,
province or municipality).
3. Decisions taken on real activity not
on intentions neither opinions.

41. Seal of Approval

42. 42
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