The purpose of the study is to make use of the opportunities for the sector, in particular the hotel industry, of incorporating macrodata collected from the electronic activity of anonymous foreign tourists into their market research.

1. DATA IN BUSINESS
ALBERT SOLANA
CONSULTANT ROCASALVATELLA

2. BIG DATA
THE POTENTIAL FOR DATA
TO IMPROVE SERVICE AND BUSINESS MANAGEMENT
Big Data Hispano
November 17th, 2014
Albert Solana
albert@rocasalvatella.com
@iamtxena

3. This
is
me
3
years
ago

4. BIG
DATA
New digital data flows and a real-time
processing capacity to provide a better
service and oriented to business goals!

5. DATA MANAGEMENT: 4-stage digital transformation process
1 Back Office digitalization!

6. DATA MANAGEMENT: 4-stage digital transformation process
Back Office digitalization!
Product only!
Internal data: logistics, financial &
production department!
ERP!
1
2
3
4

7. DATA MANAGEMENT: 4-stage digital transformation process

8. DATA MANAGEMENT: 4-stage digital transformation process
2 Customer Digital TouchPoints!
Source:
h/p://www.garymagnone.com/blog/content-­‐marke;ng-­‐digital-­‐touchpoints/

9. Customer Digital TouchPoints!
Product + Added-value Service!
Internal & External data: sales,
marketing & post-serv. depts!
ERP+CRM+SM!
1
2
3
4
DATA MANAGEMENT: 4-stage digital transformation process

10. DATA MANAGEMENT: 4-stage digital transformation process

11. DATA MANAGEMENT: 4-stage digital transformation process
3 Products & Services!

12. Products & Services!
Product + Sensor + Platform
+ Service + Data:!
R+D + Data analytics depts!
A unique centric database!
1
2
3
4
DATA MANAGEMENT: 4-stage digital transformation process

13. DATA MANAGEMENT: 4-stage digital transformation process

14. DATA MANAGEMENT: 4-stage digital transformation process

15. DATA MANAGEMENT: 4-stage digital transformation process

16. DATA MANAGEMENT: 4-stage business digital transformation process
data
channel
management
Social Media
Web
Blogs, forums
Product Data
WEB
Customer
Segment 1
Customer
Segment 2
Customer
Segment n
MASS AUDIENCE & MASS
RAW DATA
DATA CRUSH & AUDIENCE
SEGMENTATION
TAILORED PRODUCTS &
SOLUTIONS
DDBB
External
Databases
Mobile
Webs & SM
Products
SOURCES OF DATA OWN DATA MANAGEMENT
Mobile
Webs & SM
Products
…
…
NEW SOURCES OF DATA FROM
INDIVIDUALS

17. h1p://bit.ly/RSBigDataTourism
(web
document)
h1p://bit.ly/RSBigDataTourismPDF
(PDF
version)

18. Big Data and Tourism
Study Main Goals
Present a new methodology for improved analysis and knowledge of the Spanish
tourism industry with real data gathered from cellphones and credit card
transactions.
State differences between:
“to have the data” (Telefónica Móviles España or BBVA)
“to analyze the data” (Telefónica I+D),
“to set the specific questions to be answered with the
data” (RocaSalvatella).
Increase hotel industry business with real tourists data

19. Big Data and Tourism
Definition
Objectives:
To leverage the data opportunities for the sector, in particular the hotel
industry
To incorporate big data collected from the real electronic activity of
anonymous foreign tourists into their market research.
Key Challenge: Gather and cross two different datasets (from Telefónica & BBVA)
2-week data collection (From October 7th to October 21st 2012)
Barcelona and Madrid (No special holidays or notorious events)
21 countries studied, 680.928 cellphones and 168.921 credit cards analyzed
Anonymised, aggregate data (meeting requirements of LOPD 15/1999 and its
developing regulations, RD 1720/2007, and Ley General de Telecomunicaciones
Ley 32/2003)

20. Big Data and Tourism
3 Key Players
Telefónica Móviles de España
Telefónica I+D

21. Big Data and Tourism
Main Conclusions
Where
from?
For how
long?
Where?
How
much?

22. Big Data and Tourism
Main Conclusions
Where
from?
For how
long?
Where?
How
much?
Tourists who visit Barcelona and Madrid are mainly French, Italian and British
(50% of the total number of visitors during the analyzed period).
First non-european country ranked in 8th position (USA; 4% of total visitors).
Preferences:
Argentinians, Brazilians and Portuguese prioritize Madrid
Nordic countries choose Barcelona.

23. Big Data and Tourism
Main Conclusions
Where
from?
For how
long?
Where?
How
much?
The average stay is 2.24 days long.
Same country visitors may present a different behavior patterns depending on the
city. For example, India is one of the countries with the longest stays in Madrid
but the shortest stays in Barcelona.

24. Big Data and Tourism
Main Conclusions
Where
from?
For how
long?
Where?
How
much?
The further, the more city-centered.
As a general rule, furthest visitors (Japan, China and Brazil…) tend to stay in city
centric hotels.
On the other hand, visitors from nearby countries such as Portugal, France and
Belgium choose accommodation further from the center.

25. Big Data and Tourism
Main Conclusions
Where
from?
For how
long?
Where?
How
much?
Global average card spending per visitor during their stay was €161.5
Average card spending per day was €58.5.
Average spending on accommodation for the entire stay was around €300
Average accommodation daily expenditure or price per night was €129.

26. Big Data and Tourism
Main Recommendations for the hotel industry
Capturing more customers and highlighting the countries on which it is
recommended to focus marketing.
Detecting areas of the city in which commercial transactions are carried out,
Specially, those referring to accommodation.
Ensuring the hotel manager provides an attractive product suited to customers’
true needs (ideal length of package offers, information about complementary
services demanded by nationalities, etc.)

27. Most
visited
areas
in
Barcelona
by
Russian
tourists

29. Business Model!
Customers: Historical Data!
Product Providers: HW, SW, Security, Product
materials!
Data Management Alliances !
1
2
3
4
DATA MANAGEMENT: 4-stage digital transformation process

30. DATA MANAGEMENT: 4-stage business digital transformation process
data
ecosystem
Running
Shoes
Industry
Nutri;onist
Industry
Medical
Industry
Running
accessories
Industry
Other
Sports
Industries

31. DATA MANAGEMENT: 4-stage business digital transformation process
data
ecosystem
Running
Shoes
Industry
Nutri;onist
Industry
Medical
Industry
Data
“Productless”
Industry
Running
accessories
Industry
Other
Sports
Industries

32. DATA MANAGEMENT: 4-stage digital transformation process
Source:
h/p://nuviun.com/content/
blog/healthcares-­‐big-­‐data-­‐
scramble-­‐and-­‐interoperabilitys-­‐
i-­‐told-­‐you-­‐so

33. DATA MANAGEMENT: 4-stage digital transformation process
Source:
h/p://www.3scale.net/2013/05/the-­‐connected-­‐home-­‐app-­‐ecosystem-­‐panel/

34. 1
New Business Model!
2
3
4
DATA MANAGEMENT: 4-stage digital transformation process
From Product to Service!
Customer Digital TouchPoints!
Back Office Digitalization!

35. What’s
next?
• Define
your
posi;on
• Define
your
data
strategy
&
roadmap
• Meet
your
data
partners
• 3,
2,
1…
GO!

36. Thanks!
BARCELONA!
Av. Corts Catalanes 9-11,!
08173 St Cugat del Vallès!
(+34) 93 544 24 02!
!
MADRID!
Gran Via 6, !
28013 Madrid !
(+34) 91 523 73 51!
!
BOGOTÁ!
Calle 73 No. 7 -31 Of. 303!
Bogotá, Colombia!
(571) 3473612!
!
!
!
www.rocasalvatella.com
Albert Solana
albert@rocasalvatella.com
@iamtxena

37. 17TH ~ 18th NOV 2014
MADRID (SPAIN)