Download Text Mining for tourism - The world of typical high quality restaurants in Piedmont

Text mining for tourism
The world of typical high quality restaurants in
Piedmont
Roberto Fontana
ATR – Osservatorio Turistico Regione Piemonte
The Observatory on tourism of Piedmont in co-operation with:
Agenzia Regionale per la promozione Turistica del Piemonte
Osservatorio Turistico Regionale
SAS ITALIA
EPAT-FIPE PIEMONTE
1
The team and the software tools
Agenzia Regionale per la promozione Turistica del Piemonte
Osservatorio Turistico Regionale
Roberto Fontana
Cristina Bergonzo
Emanuela Giorgini
Sabina Silani
Sara Galli
Michela Giacomini
SAS® software
Enterprise Miner™
Enterprise Guide®
Francesca Martinengo
Cristina Giraudo
SEUGI21, 18 June 2003
N. 2
Introduction
! Tourism flows generated by the interest for food &
drink are extremely important for Piedmont.
! In this context “typical high quality restaurants”
(THQRs) play a major role.
! In May 2002, the Observatory on Tourism of
Piedmont, in co-operation with SAS and EPAT-FIPE
Piemonte, started a joint research project on THQRs .
! This work summarizes some of the results that have
been achieved so far
! For further information please refer to the contact
point reported at the end of this document
SEUGI21, 18 June 2003
N. 3
Work objectives
1. To build an atlas of “typical high quality
restaurants” (THQRs) in Piedmont,
combining the large numbers of restaurant
guides available in bookshops
2. To compare Piedmont with the other
Italian Regions in terms of number of
THQRs
3. To study customer’s preferences and to
get an estimate of the use of restaurant
places in different periods of the year
SEUGI21, 18 June 2003
N. 4
Methodological approach
! To acquire as many as possible restaurant
guides (possibly in electronic format to
facilitate the analysis)
! To use multivariate statistical methods and
software (including state-of-the-art tools
for text mining) to extract relevant
information from them
! To conduct surveys, interviewing
restaurants owners and their customers.
The first phase focused on “top
restaurants”.
SEUGI21, 18 June 2003
N. 5
Progress of work
! For 6 guides, the number of restaurants
that have been reviewed for every Italian
Region, has been determined.
! The electronic format of the chapters
related to Piedmont of three major
restaurant guides has been acquired and
analyzed.
! “Top restaurants owners” have been
interviewed in June, September and
October 2002.
SEUGI21, 18 June 2003
N. 6
Some Results
An analysis of the offer based on
some restaurant guides
7
STEP 0: THE Giallo Dat@’s DATA
! The first preliminary step was based on the analysis of
data provided by Giallo Dat@
! Giallo Dat@ is a line of services of Consodata S.p.A., a
company of the Seat Pagine Gialle Group, operating in
Customer Relationship Management.
! Giallo Dat@ offers a comprehensive database of 9 million
households and 27 million individuals across Europe, all
collected through national household surveys, for
marketing intelligence needs.
! Available data were the number of four different types of
restaurants for each Italian province:
"
"
"
"
Ristoranti
Trattorie
Ristoranti Tipici
Pizzerie
SEUGI21, 18 June 2003
N. 8
Giallo Dat@
– Distribution of Restaurants among Italian Regions
Regione
Abruzzo
Basilicata
Calabria
Campania
Emilia Romagna
Friuli Venezia Giulia
Lazio
Liguria
Lombardia
Marche
Molise
Piemonte
Puglia
Sardegna
Sicilia
Toscana
Trentino Alto Adige
Umbria
Valle d'Aosta
Veneto
ITALY
Ristoranti
Trattorie
1.020
254
837
2.449
2.511
494
3.219
1.443
4.494
1.103
193
2.388
1.311
921
1.450
2.655
882
585
225
2.071
30.505
Ristoranti tipici
95
25
50
186
831
631
732
523
1.764
111
16
644
184
63
434
447
105
99
19
1.610
8.569
SEUGI21, 18 June 2003
Pizzerie
75
22
32
109
136
46
261
112
303
49
16
166
74
35
104
140
42
34
7
134
1.897
Totale
608
126
465
1.300
1.661
414
2.344
706
2.989
762
85
1.334
1.046
733
1.110
1.533
353
375
62
2.368
1.798
427
1.384
4.044
5.139
1.585
6.556
2.784
9.550
2.025
310
4.532
2.615
1.752
3.098
4.775
1.382
1.093
313
6.183
20.374
Fonte: Giallo Dat@ - maggio 2002
61.345
N. 9
GIALLO DAT@ - Distribution of Restaurants
among Italian Regions
RISTORANTI TIPICI
0
100
PIZZERIE
200
300
LO
CA
LI
[ n]
LO
CA
LI
[%
]
LO
CA
LI
[ %cum
]
303
15. 97
261
13. 76
166
LO
CA
LI
[ n]
LO
CA
LI
[%
]
LO
CA
LI
[ %cum
]
15. 97
4494
14. 73
14. 73
29. 73
3219
10. 55
25. 28
8. 75
38. 48
2655
8. 70
33. 99
140
7. 38
45. 86
2511
8. 23
42. 22
136
7. 17
53. 03
2449
8. 03
50. 25
134
7. 06
60. 09
2388
7. 83
58. 08
112
5. 90
66. 00
2071
6. 79
64. 86
109
5. 75
71. 74
1450
4. 75
69. 62
104
5. 48
77. 23
1443
4. 73
74. 35
75
3. 95
81. 18
1311
4. 30
78. 65
74
3. 90
85. 08
1103
3. 62
82. 26
49
2. 58
87. 66
1020
3. 34
85. 61
46
2. 42
90. 09
921
3. 02
88. 62
42
2. 21
92. 30
882
2. 89
91. 52
35
1. 85
94. 15
837
2. 74
94. 26
34
1. 79
95. 94
585
1. 92
96. 18
32
1. 69
97. 63
494
1. 62
97. 80
22
1. 16
98. 79
254
0. 83
98. 63
16
0. 84
99. 63
225
0. 74
99. 37
7
0. 37
100. 00
193
0. 63
100. 00
400
0
2000
TRATTORIE
2000
3000
4000
5000
LO
CA
LI
[%
]
LO
CA
LI
[ %cum
]
LO
CA
LI
[ n]
LO
CA
LI
[%
]
LO
CA
LI
[ %cum
]
2989
14. 67
14. 67
1764
20. 59
20. 59
2368
11. 62
26. 29
1610
18. 79
39. 37
2344
11. 50
37. 79
831
9. 70
49. 07
1661
8. 15
45. 95
732
8. 54
57. 61
1533
7. 52
53. 47
644
7. 52
65. 13
1334
6. 55
60. 02
631
7. 36
72. 49
1300
6. 38
66. 40
523
6. 10
78. 60
1110
5. 45
71. 84
447
5. 22
83. 81
1046
5. 13
76. 98
434
5. 06
88. 88
762
3. 74
80. 72
186
2. 17
91. 05
733
3. 60
84. 31
184
2. 15
93. 20
708
3. 47
87. 79
111
1. 30
94. 49
608
2. 98
90. 77
105
1. 23
95. 72
465
2. 28
93. 06
99
1. 16
96. 87
414
2. 03
95. 09
95
1. 11
97. 98
375
1. 84
96. 93
63
0. 74
98. 72
353
1. 73
98. 66
50
0. 58
99. 30
126
0. 62
99. 28
25
0. 29
99. 59
62
1000
1000
LO
CA
LI
[ n]
85
0
RISTORANTI
3000
SEUGI21, 18 June 2003
N. 10
0. 42
99. 70
19
0. 22
99. 81
0. 30
100. 00
16
0. 19
100. 00
0
200
400
600
800
1000 1200 1400 1600 1800
Italian Restaurants – Giallo Dat@
TOTALE
RISTORANTI
RISTORANTI
TIPICI E
TRATTORIE
Ristoranti
Trattorie
Ristoranti
tipici
Abruzzo
85.71%
7.98%
6.30%
1190
Basilicata
84.39%
8.31%
7.31%
301
Molise
85.78%
7.11%
7.11%
225
Emilia Romagna
72.20%
23.89%
3.91%
3478
Lazio
76.42%
17.38%
6.20%
4212
Liguria
69.44%
25.17%
5.39%
2078
Lombardia
68.50%
26.89%
4.62%
6561
Piemonte
74.67%
20.14%
5.19%
3198
Puglia
83.56%
11.73%
4.72%
1569
Sicilia
72.94%
21.83%
5.23%
1988
Toscana
81.89%
13.79%
4.32%
3242
Umbria
81.48%
13.79%
4.74%
718
Friuli Venezia Giulia
42.19%
53.89%
3.93%
1171
Veneto
54.29%
42.20%
3.51%
3815
Calabria
91.08%
5.44%
3.48%
919
Campania
89.25%
6.78%
3.97%
2744
Marche
87.33%
8.79%
3.88%
1263
Sardegna
90.38%
6.18%
3.43%
1019
85.71%
10.20%
4.08%
1029
89.64%
7.57%
2.79%
251
Regione
Trentino Alto Adige
Valle d'Aosta
SEUGI21, 18 June 2003
N. 11
ITALIAN REGIONS: PERCENTAGES OF DIFFERENT TYPES OF RESTAURANTS
SEUGI21, 18 June 2003
N. 12
STEP 1: DATA FROM RESTAURANT GUIDES
!
!
!
!
Apart from the classification of restaurants into 4 different
categories, Giallo Dat@ include “all types” of restaurants
Therefore the second step has been to consider restaurant
guides commonly available in bookshops.
Indeed this kind of guides, even if with different criteria,
reviews only “high quality” restaurants
The guides (2002 edition) that have been considered are:
!
!
!
!
!
!
!
!
Gambero Rosso
Espresso
Michelin
Veronelli
Slowfood
Accademia
Touring Club
As for Giallo Dat@, the number of restaurants for each Italian
region has been taken into account
SEUGI21, 18 June 2003
N. 13
Restaurant guides- Distribution of Restaurants
among Italian Regions
Gambero Rosso
Accademia
Veronelli
Slow Food
Michelin
Espresso
Giallo Data
Abruzzo
69
100
24
57
62
57
1190
Basilicata
35
25
11
26
17
26
Calabria
51
42
18
42
44
47
Campania
128
113
100
63
114
50
Emilia Romagna
220
278
140
110
313
207
89
95
57
87
75
86
Lazio
235
141
94
68
180
215
Liguria
127
126
123
53
186
164
Lombardia
316
315
256
112
522
324
Marche
82
97
50
86
77
73
Molise
16
31
7
13
11
18
Piemonte
200
242
177
139
308
230
Puglia
101
82
58
60
94
132
70
66
31
42
63
88
Sicilia
151
90
80
68
106
173
Toscana
266
270
204
136
366
216
Trentino Alto Adige
95
79
89
48
92
79
Umbria
55
99
32
42
66
65
Valle d'Aosta
23
19
17
14
25
40
314
139
112
332
198
Friuli Venezia Giulia
Sardegna
Veneto
163
SEUGI21, 18 June 2003
Ristoranti + Ristoranti Tipici + Trattorie
Regioni
301
919
2744
3478
1171
4212
2078
6561
1263
225
3198
1569
1019
1988
3242
1029
718
251
N. 14
3815
Restaurant guides- Distribution of Restaurants
among Italian Regions
SEUGI21, 18 June 2003
N. 15
Restaurant guides- Distribution of Restaurants
among Italian Regions
SEUGI21, 18 June 2003
N. 16
Restaurant guides- Distribution of Restaurants
among Italian Regions
! Piedmont appears in the first positions in
terms of number of THQRs reviewed by the
guides
! The “densities of THQRs”, computed as the
ratio between:
- the number of THQRs reviewed by the guide
- the number of restaurants listed in GIALLODAT@
confirms the relevant percentages of THQRs
with respect to all the restaurants in
Piedmont
SEUGI21, 18 June 2003
N. 17
Restaurant guides- Densities
SEUGI21, 18 June 2003
N. 18
Restaurant guides- Densities
SEUGI21, 18 June 2003
N. 19
Nu
mb
De
ns i
er
of
R
ties
est
a
ur a
n ts
Restaurant guides- Absolute values vs. densities
SEUGI21, 18 June 2003
N. 20
STEP 2: IN DEPTH ANALYSIS OF SOME
RESTAURAUNT GUIDES
! Veronelli Editor, Slowfood Editor and Touring
Club provided their restaurant guides in
electronic format (more precisely the chapter
concerning Piedmont)
! The availability of the electronic format of the
guides opens the way to the use of
multivariate statistical methods and tools,
including state-of-the-art software for text
mining
! The pages below briefly summarize the
achieved results using standard statistical
tools and text mining tools on Veronelli’s and
Slowfood’s guide.
SEUGI21, 18 June 2003
N. 21
“I Ristoranti di Veronelli”
SEUGI21, 18 June 2003
N. 22
“La guida di Veronelli” – some statistics
Veronelli – distributions over the territory
N: 51
%: 30
N: 34
%: 20
N: 24
%: 14
N: 25
%: 15
N: 13
%: 8
N: 4
%: 2
N: 11
%: 7
N: 6
%: 4
The guide reviews 168 restaurants of Piedmont (2002 edition)
SEUGI21, 18 June 2003
N. 23
“I Ristoranti di Veronelli” – Prices distribution
The price (wine excluded) goes between 15 and 83 €
Mean price is around 39 €
SEUGI21, 18 June 2003
N. 24
“I Ristoranti di Veronelli” – Covers distribution
Almost 35% of restaurants has a number of places between 33 and 45
SEUGI21, 18 June 2003
N. 25
“La guida di Veronelli” – the menu
7 and 8 are the most common values for the number of specialties
served in these restaurants
SEUGI21, 18 June 2003
N. 26
“I Ristoranti di Veronelli” – Some indicators
14 restaurants out of 168
receive “3 chef’s hats”
Num. of chef’s hats
Almost 55% of restaurants puts
particular attention to wine and
receives from 1 to 3 “bottles”
Num. of bottles
SEUGI21, 18 June 2003
N. 27
From data analysis to text analysis
! Restaurant guides contain both quantitative
information, like prices and number of covers, and
qualitative information (the description of
restaurants)
! Multivariate statistical methods for cluster analysis
combined with tools for text mining give the
possibility to explore the huge amount of information
hidden in textual descriptions
! The restaurant descriptions which are published on
Veronelli and SlowFood books have been studied and
classified
! The classification is based on both textual and
quantitative information using text mining techniques
from SAS Text Mining Solution.
SEUGI21, 18 June 2003
N. 28
Typical structure of a restaurant guide
Restaurant guides contain both
quantitative information and
qualitative information
Quantitative data include prices,
number of seats, opening hours
Classical statistical methods are
suitable to “mine” them
Text describes, in an unstructured
way, the restaurant. Recent
advances in text mining give the
possibility to explore it.
SEUGI21, 18 June 2003
N. 29
Text Mining – What is it ?
! Discovering and using
knowledge that exists in a
document collection as a whole
Knowledge
SEUGI21, 18 June 2003
N. 30
SAS’ unique position in Text Mining
“Text Mining is Data Mining”
Gartner 2002
"
Transform unstructured data into structured data –
Text Parsing
"
Reduce Dimension of data while keeping relevant
information
"
Integrate new structured data with traditional
structured data for data mining
SEUGI21, 18 June 2003
N. 31
Text Mining
Quantitative and qualitative data can be jointly analysed,
providing a better view of the world of restaurants
Organised
Textual
data
SEUGI21, 18 June 2003
N. 32
Text Mining Process
Reading
text files
Text
parsing
Dimension
reduction
Text
analysis
SEUGI21, 18 June 2003
N. 33
Text Mining Process
! Textual data are transformed into frequency
matrix of words inside the documents. This
data can be integrated with quantitative
information and used in a Data Mining process.
Doc1
word1
Word
word2
word3
word4
1
2
0
2
Doc2
Doc3
0
4
0
7
3
0
9
12
Doc4
4
6
2
8
Document
SEUGI21, 18 June 2003
N. 34
Clustering
Cluster procedures allow to group all the restaurants
SEUGI21, 18 June 2003
N. 35
Clustering
Cluster procedures allow to group all the restaurants
SEUGI21, 18 June 2003
N. 36
Clustering
Cluster procedures allow to group all the restaurants
SEUGI21, 18 June 2003
N. 37
Clustering
Cluster procedures allow to group all the restaurants
SEUGI21, 18 June 2003
N. 38
Clustering
Cluster procedures allow to group all the restaurants
SEUGI21, 18 June 2003
N. 39
Clustering
Cluster procedures allow to group all the restaurants
SEUGI21, 18 June 2003
N. 40
Clustering
Cluster procedures allow to group all the restaurants
SEUGI21, 18 June 2003
N. 41
Clustering
Cluster procedures allow to group all the restaurants
SEUGI21, 18 June 2003
N. 42
“I ristoranti di Veronelli”
! In the next few pages some results of the
text mining process on the “Ristoranti di
Veronelli” guide are briefly synthesized
! The main objective has been to divide all
the restaurants into a manageable number
of different clusters
! Both quantitative and qualitative
characteristics have been taken into
account to “describe” each restaurant
! Each cluster is homogeneous in the sense
that it contains all the restaurants that
have similar characteristics
SEUGI21, 18 June 2003
N. 43
“I Ristoranti di Veronelli” - Cluster Analysis
Using clustering procedures, the 168 restaurants have been divided
into 6 clusters
1 - Spacious Typical Restaurants
2 –Novelty
Many seats
Good prices
Wide selection of courses and desserts
Local wines
Local dishes
Not typical
3 - Typical and Rural Restaurants
4 - Creative Cooking
Local wines
Wide selection of cheeses
Good prices
Soups
Few seats
Few courses
Confectionery
No parking facilities
Reservation adviced
5 – Very Good Typical Restaurants
6 - Prestigious Restaurants
High prices
Very high vote and many chef’s hats
Excellent wines
Confectionery
Wide selection of wines and spirits
Few seats
Good prices
High vote and many chef’s hats
Excellent local wines
Confectionery
Good choice of cheeses and spirits
In this context “typical” means closed to the values
of territory in which the restaurant lives
SEUGI21, 18 June 2003
N. 44
Restaurants distribution in clusters
CLUSTER
It is easy to look at all the restaurants that belong to a group
In this example we have selected group 6 (prestigious restaurants)
SEUGI21, 18 June 2003
N. 45
Means grid plot from Veronelli inputs
Creative Cooking Restaurants
To understand which are the
distinguishing features of cluster 4, a
comparison between the cluster 4
values and the population values is
carried out for all the variables.
Indeed the input means grid plot
compares the data set input means (in
blue) to those from cluster 4 (in
violet).
We defined cluster 4 as “Creative
Cooking” because the value of this
variable is higher than the
overall restaurants.
Besides, the variables col1-col60
represent words frequency
in documents. Indeed, the analysis
are made by using both textual and
quantitative information. It is easier to look
at textual analysis in a different way (see
below).
SEUGI21, 18 June 2003
N. 46
Means grid plot from Veronelli inputs
Very good Typical Restaurants
A similar procedure
has been adopted for all the clusters
We defined cluster 5 as “Very good
Typical restaurants” because the
restaurants that belong to this
group tend to be defined as “typical”
in the guide (“Typical=si” is higher
than the overall restaurants).
Also the number of chef’s hats is large.
SEUGI21, 18 June 2003
N. 47
Categorical Variables
Another way to look at clusters is as follows.
The slice variable displays the categorical variable “typical” (cyan).
The height variable displays the interval variable “vote”.
The cluster 2 (“Novelty”) has no “typical restaurants” and the cluster with
the highest vote from Veronelli is number 6 (“Prestigius Restaurants”).
SEUGI21, 18 June 2003
N. 48
Restaurants profiles
It could be also useful to compare clusters among them
The table displays the percentage of
categorical variables in clusters
The table displays min, max and mean
values of the interval variables in clusters
SEUGI21, 18 June 2003
N. 49
Words frequencies in clusters
Clusters can be compared
also from textual point of
view.
The table displays for each
cluster the percentage of
words frequencies in
cluster.
chocolate
elegant
Highest frequencies
fillet
oven
Lowest frequencies
nuts
piedmontese
SEUGI21, 18 June 2003
N. 50
“Osterie d’Italia” - Slowfood
SEUGI21, 18 June 2003
N. 51
Osterie d’Italia – Some statistics
Osterie d’Italia 2002 - Slowfood
! The “Osterie d’Italia”
guide reviews 139
restaurants of
Piedmont (2002
edition)
! Langhe, Roero and
Monferrato confirm
their importance in
terms of concentration
of restaurants
11esercizio
restaurant
22esercizi
restaurants
33esercizi
restaurants
restaurants
99esercizi
SEUGI21, 18 June 2003
N. 52
Osterie d’Italia – Prices distribution
The price (wine excluded) goes
between 14 and 33 €. Mean price is around 25 €
SEUGI21, 18 June 2003
N. 53
Osterie d’Italia – covers distribution
50% of “osterie” has a number of covers between 45 and 80
SEUGI21, 18 June 2003
N. 54
Osterie d’Italia – the menu
7 is the most common value for the number of specialties served
in an “Osteria”
SEUGI21, 18 June 2003
N. 55
Osterie d’Italia – the classification
bottles
A particular attention to wines
distinguishes 63 restaurants
snail
21 restaurants receive the “snail”
novelty
cheeses
Cheese plays a major role
in the menu of 31 restaurants
21 restaurants are new entries
for this guide
SEUGI21, 18 June 2003
N. 56
Osterie d’Italia – Clusters Analysis
1 – Cheap Osteria
New Osteria
Many seats
Good prices
2 –Summer Season
Many external seats
High prices
Specialized in starters, cheeses, cakes, creams and wines
3 – Typical Osteria
Few seats
Good prices
New Osteria
Few dishes choice
Specialized in starters and second meat dishes
4 - Snail Restaurants
High prices
“Snail”
Excellent cheeses, pasta and sweets
Few seats
SEUGI21, 18 June 2003
N. 57
Restaurant distribution in clusters
Easy identification of restaurants belonging to a group
In this example we have selected group 2 (Summer Season)
SEUGI21, 18 June 2003
N. 58
Means grid plot from Slow Food inputs
Summer Season
The input means grid plot
compares the data set input means
(_ALL_) to those from cluster 2.
We defined cluster 2 as “Summer
Season” because the value “external
seats” is higher than the overall
restaurants.
SEUGI21, 18 June 2003
N. 59
Means grid plot from Slow Food inputs
Snail Restaurants
The input means grid plot
compares the data set input means
(_ALL_) to those from cluster 4.
We defined cluster 4 as “Snail
Restaurants” because the
restaurants of this group tend
to get the snail (“chiocciola=1” is
higher than the overall restaurants).
SEUGI21, 18 June 2003
N. 60
Categorical Variables
The
The
The
The
row variable displays the categorical variable “Chiocciola” (snail).
slice variable displays the categorical variable “Bottles”.
height variable displays the interval variable “Prices”.
cluster with the highest prices from Slow Food is number 4.
SEUGI21, 18 June 2003
N. 61
Restaurants profiles
The table displays the percentage of
categorical variables in clusters
The table displays min, max and mean
values of the interval variables in clusters
SEUGI21, 18 June 2003
N. 62
Words frequencies in clusters
The table displays for each
cluster the percentage of
words frequencies in
clusters.
starters
meat
classic
rabbit
cream
Highest frequencies
cakes
Lowest frequencies
greens
summer
cheeses
SEUGI21, 18 June 2003
N. 63
Top Restaurants Survey
Some Results
64
Top restaurants survey
Ristoranti Espresso, Michelin, Gambero Rosso
!
!
!
11 restaurant
esercizio
esercizi
22 restaurants
8 esercizi
8 restaurants
!
“Top restaurants” were defined
according to the following
procedure:
1. Three guides (2002
Edition) have been chosen
" Espresso,
" Gambero Rosso,
" Michelin
2. A restaurant is considered
“top” if it appears in at
least two of the above
guides
Using the definition above 66 “Top
Restaurants” were identified in
Piedmont
They were asked to fill up three
questionnaires (Jun, Sep, Oct)
The rate of response has been close
to 50%
SEUGI21, 18 June 2003
N. 65
Top restaurants survey
The most suggested Menu is first
time menu and then a la carte
menu.
The most common food style
is the fusion style followed
by the local style.
SEUGI21, 18 June 2003
N. 66
Top restaurants survey
The average number of covers
is about 62, but only the 12%
of restaurants has more than
100 places.
Most of the restaurants are
elegant and lovely.
SEUGI21, 18 June 2003
N. 67
Top restaurants survey
The floor staff counts on an
average of 2.94 people.
The kitchen staff counts on an
average of 3.50 people.
SEUGI21, 18 June 2003
N. 68
Top restaurants survey
In floor staff there are very high
qualified people like the
sommellier (25%), the maitre
(15%) and the commis (15%).
In kitchen staff there are very
high qualified people like the
chef (25%), the cook (15%)
and the pastry cook (15%).
SEUGI21, 18 June 2003
N. 69
Top restaurants survey
The 25% of clients come from
abroad: Switzerland and Germany
are the first countries. Most of the
Italian people come from Piedmont
and from Lombardy.
SEUGI21, 18 June 2003
N. 70
Top restaurants survey
r
tu
a
S
n
Su
y
da
ay
d
tu
Sa
ay
rd
n
Su
ay
d
tu
Sa
ay
rd
n
Su
tu
Sa
y
da
r
tu
Sa
ay
d
n
Su
In June the net use of
covers available was less
than 50%.
ay
d
F
y
da
ri
n
Su
y
da
r
tu
Sa
ay
rd
ay
d
i
Fr
r
tu
a
S
y
da
n
Su
ay
d
F
y
da
ri
n
Su
r
tu
a
S
y
da
ay
d
i
Fr
y
da
n
Su
y
da
ay
d
In September net use of the
covers increased significantly.
In particular, during Saturday
evenings, peak values of more
than 70% were registered.
SEUGI21, 18 June 2003
N. 71
Top restaurants survey
Covers net use in October
to
ba
a
S
o
at
b
Sa
V
en
e
ì
rd
om
D
V
en
ic
a
V
en
e
ì
rd
om
D
en
i
o
at
b
Sa
o
at
b
Sa
en
er
dì
ca
om
D
en
i
ca
V
en
er
dì
om
D
en
ic
a
SEUGI21, 18 June 2003
In October,
during Saturday
evenings, net use
of covers is
always above
70%.
N. 72
Conclusion
73
Future work
! To extend the analysis to other
guides
- the guide from Touring Club has already
been acquired in electronic format
- Editors that would like to provide their
guides are welcome!
! To complete end extend the “Top
restaurants survey” , including
interviews to customers
SEUGI21, 18 June 2003
N. 74
The team and the software tools
Agenzia Regionale per la promozione Turistica del Piemonte
Osservatorio Turistico Regionale
Roberto Fontana
Cristina Bergonzo
Emanuela Giorgini
Sabina Silani
Sara Galli
Michela Giacomini
SAS® software
Enterprise Miner™
Enterprise Guide®
Francesca Martinengo
Cristina Giraudo
SEUGI21, 18 June 2003
N. 75
Acknowledgments
Authors wish to thank:
! Slowfood Editore, Veronelli Editore and Touring Club
Editore, for having provided the electronic format of
the sections of their guides related to Piedmont
! Giallo Dat@ for having provided the number of
restaurants published in their book, divided by Italian
province
! All the “top restaurants owners” for having filled up
the questionnaire
SEUGI21, 18 June 2003
N. 76
Contact
! To ask for further information please
feel free to contact
Roberto Fontana
Osservatorio Turistico Regione Piemonte
Via Magenta 12
I-10128 TORINO – Italy
[email protected]
Phone: +39.011.432.2479
SEUGI21, 18 June 2003
N. 77
THANKS FOR YOUR ATTENTION!