Journal of Vacation Marketing
Volume 12 Number 1
Using visit frequency to segment ski resorts
customers
Rodoula Tsiotsou
Received (in revised form): April 2005
Anonymously refereed paper
N. Plastira 57 Lykovrisi, TK 14123 Athens, Greece
Tel. 0030 210 2849584; E-mail: [email protected]
Rodoula Tsiotsou is currently Marketing Director for the daily sports newspaper ‘Protathlitis’
and a visiting lecturer at the National & Kapodistriako University of Athens, Greece. She has
worked as Marketing Manager for the Greek
Professional Basketball League and she has
taught courses in sport marketing and management at the Department of Physical Education of
Democritus University, Greece.
ABSTRACT
KEYWORDS: experience, satisfaction,
source of information, winter tourism, ski
resorts, market segmentation
The purpose of the study is to segment ski resorts
customers according to their frequency of visits in
order to identify homogeneous groups. In particular, the study investigates the degree to which ski
experience, overall satisfaction and income discriminate customers who visit ski resorts weekly from
those who visit them monthly. A self-administered
anonymous questionnaire was given to 200 customers of two different ski resorts in Greece. The
questionnaire was answered by 191 individuals
(95.5 per cent response rate). Classification with
discriminant analysis was used to identify consumers with different visitation frequency. The hypothesis that ski experience, overall satisfaction
and income will classify consumers according to
their visitation frequency was confirmed. The findings of the study provide theoretical and practical
implications in identifying better segments and
increasing destination marketing effectiveness.
INTRODUCTION
Tourism is one of the main industries in
Greece that stimulates economic development in industries from hospitality, transport, construction and retail, to small
businesses such as restaurants, bars and tourism agents. Tourism contributes to the
Gross National Product by 22 per cent,
more that any other sector in Greece (industry 12.4 per cent and agriculture 9 per
cent).1
Winter tourism has grown rapidly over
the last two decades all over Europe. Studies
have reported that a growing number of
tourists visit ski resorts in European countries
such as the UK, Bulgaria and Greece.2
Particularly in Greece, more and more
locals prefer to spend their weekends or
winter vacations in ski resorts located in the
country. Some places have become very
popular and attract tourists in high number
during winter especially at weekends. Currently, there are more than 19 ski resorts in
Greece that constitute frequent destinations
for thousands of Greek visitors every year.
However, Greek ski resorts have not been a
destination for foreign tourists.
Because tourism is a very important sector in Greece and ski resorts are rapidly
growing, it is imperative to study and understand this market and their customers.
Studying ski resorts customers will provide
tourism marketers with valuable information
about their needs, wants and behavior in an
effort to retain current and attract new
Journal of Vacation Marketing
Vol. 12 No. 1, 2006, pp. 15–26
& SAGE Publications
London, Thousand Oaks, CA,
and New Delhi.
www.sagepublications.com
DOI: 10.1177/1356766706059029
Page 15
Using visit frequency to segment ski resorts customers
customers. Ski resorts need to segment their
customers in order to offer products and
offerings that will satisfy these customers
and attract new ones.
Consumer satisfaction, buying frequency,
product experience and demographics such
as income have been used in marketing to
identify consumer groups. However, these
variables have not been used together in an
effort to find distinct tourist segments.
Although activities have been used to segment tourists, activity experience has not
been used before to identify homogeneous
groups. Furthermore, it has been recommended that segmenting tourists ‘based on
frequency of [ski resort] use may be useful in
identifying skilled consumers’3 (p. 33). Thus,
studying ski resort visitors could provide
us with valuable information about these
customers.
This study proposes the combination of
demographic (income), behavioral (product
experience, visit frequency), and satisfaction
variables to segment ski resort customers.
Segmentation using a combination of the
above variables for the ski resorts market has
not been proposed before in the tourism
marketing literature.
The purpose of the study was to segment
ski resorts customers by using, as a segmentation base, visit frequency. In particular,
the intention was to investigate the degree
to which ski experience, overall satisfaction
and income discriminate ski resorts customers with different visitation frequency in
an effort to identify distinct customer groups
and predict customers’ future visit frequency.
The article is organized into five parts.
First, the theoretical framework of the study
is presented followed by the methodology
used. Then, the results and a discussion on
the results and implications are presented.
The limitations of the study and future
research recommendations conclude the
study.
The review of the literature on tourist
segmentation, satisfaction and product experience provides the theoretical framework for developing the hypotheses of the
study.
Page 16
THEORETICAL FRAMEWORK
Tourist segmentation
Market segmentation is one of the main
strategies in marketing that assists in identifying homogeneous groups of consumers with
similarities in an effort to satisfy their needs
and increase marketing effectiveness. Similarities refer to needs, shopping habits, media
usage, price sensitivity and other. The information gathered through market segmentation is crucial in the strategic marketing
planning process of a company.
Market segmentation benefits companies
in four ways: (a) it provides the base for
target marketing; (b) it assists in developing
more effective marketing mixes in order to
satisfy the needs of a specific segment; (c) it
facilitates product differentiation; and (d) it
provides easier identification of market
opportunities and threats.
The most often used bases for segmenting
consumer markets are demographic (age,
gender, family status, income), geographic,
behavioral (benefits, frequency of use, loyalty), and psychographic segmentation (lifestyle, personality characteristics). Often a
combination of different segmentation bases
is used.4
There are two types of segmentations, ‘a
priori’ and ‘post hoc’ segmentation. ‘A
priori’ segmentation is when the variable
used as a criterion to divide a market is
known in advance whereas ‘post hoc’ segmentation is when there is no knowledge
about distinct groups and a set of variables is
used as the base for segmentation.5
Segmentation has often been used to identify distinct groups of tourists, because, like
any other market, tourists do not respond
homogeneously to marketing activities.
Table 1 summarizes the results of several
studies and the different variables used to
segments tourists.
An overview of Table 1 indicates that the
most often used variables to segment tourists
are demographics, socioeconomics, lifestyle
and satisfaction whereas the most often statistical analysis used is cluster analysis (Kmeans). The number of segments identified
a range from two to six.
In terms of the role of income in tourism
Tsiotsou
Table 1: Summary of segmentation studies in tourism
City/
Country
Segmentation
variables
Statistical
analysis
Tourism
market
No. of
segments
Greece
Satisfaction
Leisure activities
Demographics
Psychographic
Discriminant
Adventure
visitors
2
Tsiotsou &
Vasioti (2006)
Factor
Cluster
Cluster
Residents
4
Residents
6
Schmidt &
Merser (2005)
Lawson &
Thyne (2004)
Dolnicar &
Leisch (2004)
Denmark
New Zealand
Austria
South Africa
Spain
Scotland
Virginia
USA
New Zealand
Moravia
Czech
Repub.
Guam
Taiwan
Balearic
Islands
United
Kingdom
Expenditures
Lifestyle
Summer activities
Demographics
Socioeconomic
Behavioral
Psychographic
Demographics
Socioeconomic
Geographic
Emotions
Satisfaction
Loyalty
Benefits
Socioeconomic
Behavioral
Sentiments
Demographics
Trip
characteristics
Expenditures
Lifestyle
Demographics
Destination choice
Expenditures
Demographics
Trip purpose
Travel behavior
Socio-demographics
Participation patterns
Destination
determinants
Socio-demographics
Ski level
Authors 6
Bagged
International 3–5
visitors
Cluster
Self-organizing
neural
networks
Cluster
(K-means)
Urban
visitors
3-4
Bloom (2004)
Museum
Theme park
visitors
Rural
tourists
2
Bigne & Andreu
(2004)
4
Frochot (2005)
4
Chen (2003)
Cluster
(K-means)
X2 Automatic
Interaction
Detection
Residents
Cluster
International 6
tourists
National
6
International
tourists
National
3
tourists
MANOVA
Cluster
One-way
ANOVA
Chi Square
Chi Square
segmentation, the findings are contradictory.
Lawson and Thyne7 have found that income
is significantly related to the proportion of
money spent on sightseeing activities only,
but not to other aspects of a trip such as
accommodations, food and entertainment.
International 2
tourists
Ski resorts
3
customers
Becken (2003)
Tureckova
(2002)
Mok & Iverson
(2000)
Juaneda & Sastre
(1999)
Richards, (1996)
Moreover, it has been found that some
tourist segments differ in their income. Dolnicar and Leisch8 have reported that ‘health
oriented’ holiday makers have the highest
disposable income of the four segments they
identified and they spend the highest amount
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Using visit frequency to segment ski resorts customers
of money per day and per person. However,
Mok and Iverson9 segmented Americans
based on their expenditures and found that
no significant difference exists between those
segments in terms of their income.
In the case of ski resorts, because such
destinations are characterized by a high marginal cost (skiing is a relatively expensive
sport), frequent visitors would have a high
disposable income in order to take vacations
there frequently.10 Richards11 studied the
UK ski resorts customers and found that
choice of destination was affected by the
price of the product (skiing) and by income
levels. Thus, income seems to be an important variable that needs to be included when
segmenting ski resorts tourists. It is expected
that:
H1: Customers with higher income will
visit ski resorts more often.
Product – ski experience
Experience in marketing has been extensively studied in consumer knowledge,
familiarity and expertise of products. In this
study, experience is the ability to perform
product-related tasks.12 Product-related experience has been defined as memory for
relationships between the self and the product in terms of information search, product
usage, and purchase experience.13
Experience has been utilized as a measure
of consumer knowledge or familiarity.14
Park et al.15 have made and tested two
propositions associated with product experience. The first proposition states that the
amount of product-related experience is
positively related to the amount of productclass information stored in memory. Moreover, personal experiences with products
may increase the perceived validity and
relevance of information. Thus, productrelated experiences are considered as valid
cues in making judgments related to the
products. The second proposition states that
the amount of product-related experience is
more strongly associated with the level of
self-assessed knowledge than with objective
knowledge. Self-assessed knowledge refers
Page 18
to consumers’ perceptions of what or how
much they know about a product class,
whereas objective knowledge refers to accurate information about the product class
stored in long-term memory. The above
two propositions were tested and confirmed
by the results of their study. The findings
suggested that product-related experience
plays a more important role in consumers’
knowledge assessments than productinformation cues. This can be explained by
higher accessibility of product-related experience in memory.
Mano and Oliver16 have proposed two
dimensions of product experience, the utilitarian (instrumental) and the hedonic (aesthetic). The utilitarian experience refers to
the usefulness function a product performs,
whereas the hedonic dimension refers to
intrinsically pleasing properties of a product.
They found that utilitarian evaluation is
more functional and cognitive than hedonic
evaluation because it deals with the fulfilment of instrumental consumers expectations
of the product. Hedonic evaluations are
affective. This finding may have implications
in areas that are considered hedonic such as
leisure activities (e.g. skiing), and entertainment services.
Prior experience with a product has
been related to information processing,17
product evaluation,18 familiarity and expertise19 and consumers’ goals.20 Consumers with moderate knowledge and
experience are expected to process information more than consumers with low or
high knowledge and experience. In addition, consumers with the most experience
use brand processing whereas consumers
with less experience use attribute-based
processing to a greater extent.21
Huffman and Houston22 related consumers’ goals to goal-directed experiences that
assist in developing and organizing consumers’ knowledge. Their study indicated that
the content of feedback and its consistency
with consumers’ goals affect the goal orientation and organization of brand and feature
knowledge acquired during choice experience.
In tourism, prior experience has been
Tsiotsou
found to be an important factor in activity
participation, expenditure patterns23 and destination choice,24 whereas skill level (of an
activity) is a good predictor of participation
frequency and location.25
In this study, product experience refers to
the ski experience customers of ski resorts
have, because skiing is the core product of
ski resorts. Thus, based on the review of
literature, it should be expected that:
H2: Customers with more ski experience
will visit ski resorts more often.
Consumer satisfaction
Satisfaction has been defined as a global
evaluative judgment about product usage/
consumption.26 A more recent attempt has
conceptualized satisfaction as a summary
affective response of varying intensity with
a time specific point of determination
and limited duration directed toward focal
aspects of product acquisition and/or
consumption.27
Consumer satisfaction has been considered
one of the most important constructs28 and
one of the main goals in marketing29 because
it is a key element for gaining competitive
advantage.30
Due to its importance, various theories
and models have been developed in an effort
to define the construct and explain satisfaction in different products/services
and consumption stages. The expectancy–
disconfirmation paradigm,31 the perceived
performance model,32 as well as attribution
models,33 affective models34 and equity models,35 are only some of the main theoretical
bases developed to explain consumer satisfaction. The above approaches have raised
several issues and debates among marketing
scholars.
Satisfaction plays a central role in marketing because it is a good predictor of purchase
behavior (repurchase, purchase intentions,
brand choice and switching behavior).36
Satisfaction is an important predictor of customer loyalty37 and the strength of the relationship between the two is strongly
influenced by customer characteristics such
as variety seeking, age and income.38 Satisfied customers tend to use a service more
often than not satisfied ones,39 they present
stronger repurchase intentions, and they recommend the product/services to their
acquaintances.40 It has been suggested that
satisfaction has a direct effect on repurchase
intentions,41 though some scholars have
found an indirect effect through adjusted
expectations – the post hoc expectations that
are updated on the basis of consumption
experiences.42
Several studies have been conducted on
satisfaction with tourism services. Satisfaction
in tourism has been studied from different
perspectives and for different destination
types. It has been proposed that emotions
such as pleasure and arousal could be antecedents of tourist satisfaction.43 Moreover,
demographic variables such as education and
age, and leisure activities have been found to
be good predictors of tourist satisfaction.44
Swan et al.45 studied compensatory satisfaction in a birding field trip. Their findings
confirmed the expectancy – disconfirmation
paradigm. Similarly, it has been suggested
that tourist (visitor) satisfaction is determined
by the extent to which desired outcomes or
benefits are realized.46 Webb and Hassall47
measured visitor satisfaction with Western
Australia’s conservation estate on a two-year
period. They found that the type of location
and the number of facilities were the strongest indicators of satisfaction. Tourism segments differ in their satisfaction and
enjoyment during a trip while they do not
display demographic differences in the study
conducted by Andereck and Caldwell.48
Tourist satisfaction has been proposed to
be taken into account when assessing the
strengths and weaknesses of a tourism organization. Moreover, it should be taken
into consideration when forecasting demand
for developing marketing strategies. Tourist
satisfaction is central to marketing and should
feed into the strategic and operational planning of tourism organizations.49 Finally,
satisfaction has been found to be directly
related to destination loyalty50 meaning that
satisfied tourists will revisit and recommend
a destination.
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Using visit frequency to segment ski resorts customers
Taking into consideration the findings of
the above studies, it is expected that:
H3: Satisfied customers will visit ski resorts
more often.
And
H4: Customer ski experience, satisfaction
and income will differentiate frequent
visitors of ski resorts from less frequent
visitors.
METHODOLOGY
The study utilized the survey research
method to study ski resorts costumers. A
self-administered anonymous questionnaire
was given to 200 customers of two different
ski resorts, 3–5 Pigadia and VoraKaimaktsalan, in Greece. The questionnaire
was answered by 191 individuals (95.5 per
cent response rate).
The questionnaire consisted of three parts:
Part I gathered demographic data; Part II
asked about ski knowledge and experience
and frequency of visiting ski resorts; and Part
III measured customers satisfaction. Subjects
had to indicate how satisfied they were with
equipment, social activities and facilities
using a five point likert scale (1 ¼ not at all
satisfied, 5 ¼ very much satisfied).
‘A priori’ segmentation was used to divide
ski-resort customers into homogeneous
groups by using visit frequency as segmentation base. The subjects were categorized
based on their ‘visit frequency’ as weekly
visitors, monthly visitors and yearly visitors.
However, the yearly visitors were dropped
from the analysis because there were only
seven cases. Satisfaction, income and ski
experience were used to segment ski-resorts
tourists.
RESULTS
Sample demographics
The majority of the respondents participating in the study were men (53.4 per cent)
whereas 46.5 per cent were women. The
respondents of each ski resort were almost
Page 20
equal, 49.2 per cent came from VoraKaimaktsalan and 50.8 per cent came from
3–5 Pigadia. Regarding their age group,
15.5 per cent of the respondents were
younger than 20 years old, 45.1 per cent
were 21–30 years old, 21.2 per cent were
31–40 years old, 14 per cent were 41–50
years old, and 4.1 per cent were older than
51 years. More detailed information on
sample demographics is presented in Table
2.
Regarding their level of education, most
of the respondents had a high school diploma
(34.9 per cent), 28.1 per cent had a university degree, 7.8 per cent had a technical
university degree and 10.9 per cent graduated from a college. Finally, most of the
people in the study were employees in the
private sector (21.1 per cent), several also
worked in the public sector (15.8 per cent)
whereas only 16.8 per cent were free agents,
18 per cent were students and 3.6 per cent
were unemployed.
Classification with discriminant
analysis
The basic analysis of the study was classification with discriminant analysis. Classification
with discriminant analysis involves classifying
subjects into one of several groups on the
basis of a set of measurements. Discriminant
analysis has been recommended for a priori
segmentation in tourism services in order to
identify and target tourists with similar
needs, wants and profiles.51 Moreover, criterion-based techniques such as discriminant
analysis are supported over non-criterion
methods (e.g. cluster analysis) because they
have three advantages: a) the variables of
interest can significantly discriminate among
segments; b) they provide information on
the strength of the relationship between each
segment and the criterion of interest; and c)
they assist in correctly classifying new observations into the identified segments.52
Subjects that visit ski resorts once a week
were assigned as y ¼ 0 and those who went
once a month as y ¼ 1. Subjects who visited
ski resorts yearly were also asked for, but
Tsiotsou
Table 2: Sample demographics (frequencies and proportions), N
Gender
Males
Females
Age
102 (53.4%)
89 (46.1%)
Education
Middle
school
High
School
University
College
Technical
college
Other
up to 20
21–30
31–40
41–50
51+
191
Marital status
30 (15.5%)
87 (45.1%)
41 (21.2%)
27 (14.0%)
8 (4.1%)
Employment status
Single
112 (58.9%)
Married no children 73 (38.4%)
Divorced
5 (2.6%)
Ski experience
29 (15.1%)
Unemployed
41 (21.6%)
, 5 years
57 (47.9%)
67 (34.9%)
Public sector
30 (15.8%)
5–10 years
25 (21.0%)
54 (28.1%)
21 (10.9%)
15 (7.8%)
Private sector
Free agent
Entrepreneur
40 (21.1%)
32 (16.8%)
22 (11.5%)
11–20 years
. 21 years
25 (21.0%)
12 (10.1%)
Other
26 (13.2%)
5 (2.7%)
there were only seven cases so they were
excluded from the analysis. The total sample
was randomly split into a development sample of 80 subjects and a cross validation
sample of 80 subjects to assess the classification accuracy of the discriminant variates (26
cases had missing data and were excluded
from the analysis). The classification function
was computed first on the development sample and then its hit rate was checked on the
cross validation sample. The classification
variables were ski experience, overall satisfaction and income. Descriptive statistics of
the variables are presented in Table 3.
In a preliminary analysis of the data, a case
analysis was conducted to identify possible
outliers and violations of the assumptions of
independence, multivariate normality and
the homogeneity of variance/covariance matrices. No serious violations of the assumptions were identified. The homogeneity of
variance/covariance test (Box’s M) indicated
that the data did not violate the assumption
(fail to reject at the 0.05 level; F ¼ 0.901,
p ¼ 0.493).
The overall multivariate relationship
(MANOVA) was statistically significant at
the 0.05 (chi square ¼ 13.721; Wilk’s
¸ ¼ 0.836; p ¼ 0.003) indicating that the
two groups of customers were statistically
significantly different. Thus, the variables
used were able to classify the subjects into
Table 3: Descriptive statistics
Variables
Ski experience
Overall satisfaction
Income
Means
Standard Deviations
y ¼ 0*
y ¼ 1**
y ¼ 0*
y ¼ 1**
0.67
2.23
2.90
1.30
2.73
1.95
0.896
0.945
1.654
1.218
0.952
1.395
* Subjects that visit ski resorts every week (y ¼ 0).
** Subjects that visit ski resorts every month (y ¼ 1).
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Using visit frequency to segment ski resorts customers
the two groups based on their frequency of
visiting ski resorts. Moreover, all three of the
univariate F-tests were significant, as shown
in Table 4.
The classification was based on the Bayesian probability of group membership, assuming group priors equal to the relative
group sizes (0.750 for likely to visit ski
resorts every week and 0.250 for likely to
visit ski resorts every month). To accomplish
this classification, the Fisher’s linear discriminant functions were used (Table 5).
The analysis continued with the evaluation of the performance of the classification
procedure. Table 6 shows the ‘hit rate’ for
both the development and the cross validation sample. The results for the development
sample indicated 81.3 per cent correct classification rate. There were three misclassified
cases. The ‘hit rate’ for the cross validation
sample increased to 83.8 per cent. There
were four subjects misclassified. The precision of correct classification was very satisfactory and for this reason the use of the
procedure for classification of future subjects
is recommended.
Table 4: Univariate F-tests for ski
experience, overall satisfaction and
income
Variables
Wilk’s ¸ F
Significance
Ski experience
Overall
satisfaction
Income
0.926
0.951
6.213
4.042
0.015
0.048
0.936
5.324
0.024
Table 5: Fisher’s linear discriminant
functions
Variables
Ski experience
Overall
satisfaction
Income
Constant
Page 22
Weekly visitors Monthly visitors
1.543
2.669
2.190
3.336
1.299
5.666
1.001
8.331
DISCUSSION/IMPLICATIONS
The main objective of the study was to
segment ski resorts customers based on their
visit frequency. This investigation confirmed
previous findings on the important role of
product experience, overall satisfaction and
income in predicting ski resorts customers’
behavior. The results of the study provide
important theoretical and managerial implications.
The classification with discriminant analysis was used to identify consumers who
would visit ski resorts weekly from those
visiting them monthly. Ski experience, customer satisfaction and income were the variables used to predict frequency of ski resort
visits. The main hypothesis of the study was
confirmed. Ski experience, customer satisfaction and income classified weekly from
monthly visitors of ski resorts. The two
segments were significantly different in terms
of their ski experience, overall satisfaction
and income. It should be noted that
the satisfaction results (univariate F-tests)
were close to rejecting such a difference
(p ¼ 0.048). However, the classification
procedure performed very well in correctly
classifying visit frequency indicating that ski
experience, overall satisfaction and income
could be used for future predictions as well.
Two out of the four hypotheses were not
confirmed by the study. Ski experience and
customer satisfaction affected visit frequency
inversely. Monthly visitors of ski resorts
scored higher in ski experience and satisfaction. Customers with more experience and
satisfaction do not visit ski resorts as frequently as it was expected whereas less experienced and satisfied customers visit ski
resorts weekly. This finding might be explained by the demographics of the study.
More than 66 per cent of the sample were
younger than 30 years old and thus, with an
expected lower income than older customers. Because skiing is a relatively new
activity in Greece, it is mostly young people
that know how to ski.
The dominant role of income in predicting visit frequency becomes apparent from
the study and confirms previous findings.53
Weekly visitors had a higher income mean
Tsiotsou
Table 6: Classification accuracy
Results for the development sample*:
Actual group
No. of cases
Classification
Weekly visitors
Monthly visitors
Total correct classification ¼ 81.3%
* There were three ungrouped cases
60
20
Weekly visitors
56 (93.3%)
11 (55.0%)
Actual group
No. of cases
Classification
Weekly visitors
Monthly visitors
Total correct classification ¼ 83.8%
** There were four ungrouped cases
73
7
Weekly visitors
66 (90.4%)
6 (85.7%)
Monthly visitors
4 (6.7%)
9 (45.0%)
Results for the cross validation sample**:
score than monthly visitors. Thus, high income tourists visit ski resorts more often,
though they do not have much ski experience and they are not very satisfied. Those
customers are probably older and, either
learnt to ski over the last few years, or, are
not experienced skiers but visit ski resorts for
other reasons (e.g. social). The high cost
associated with visiting ski resorts and skiing
prevents customers, who probably have
more experience but less income, from visiting them more often.
Segmentation has become increasingly
important for successful marketing practices
in the tourism industry. To get closer to their
customers, marketers need to concentrate on
the needs of specific homogeneous groups.
The segments identified from the study provide useful information to managers. Having
information about the satisfaction level, the
ski experience, the income and the frequency of visits is possible to identify distinct
segments. Moreover, the first three variables
could be used as predictors of the frequency
of visits in order to forecast product
and service needs and better satisfy their
customers.
By gaining understanding on how the two
segments are different, it could facilitate
Monthly visitors
7 (9.6%)
1 (14.3%)
managers’ efforts in developing the appropriate marketing plan for each segment. First,
ski resort managers need to retain their
‘weekly high income’ customers (the most
important segment) by increasing their satisfaction level and ski experience. High income with less ski experience customers
might be more demanding and could be
satisfied by extrinsic attributes such as offering quality services and products (e.g. quality
food, more entertainment). Second,
‘monthly lower income’ customers could
become more frequent visitors by making
them special offers (e.g. special prices on the
lift use or in renting ski equipment). Profit
could be made by selling other products and
offering additional services (e.g. restaurants,
bars, excursions) that could satisfy their
needs.
Another aspect that needs to be looked at
by ski resorts managers in Greece is the
international tourist. The rapid growth in
popularity of ski resorts as tourism destinations in Greece was due to the large market
increase of Greek tourists. Foreign visitors
do not come to Greece to take their vacation
in ski resorts. This is a market that Greek ski
resorts should try to attract. Greece has snow
for 4–5 months a year, whereas in several
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Using visit frequency to segment ski resorts customers
other European and Mediterranean countries
it does not snow much. The lack of snow in
some other European countries along with
lower prices could be two main factors that
would attract foreign skiers and visitors to
Greece. Several ski resorts are close to archeological places and museums, so other type
of activities could be offered in order to
attract more tourists. Developing travel
packages in cooperation with travel agents,
advertising in international specialized magazines and developing internet sites in several
foreign languages are some of the actions that
could be taken in order to attract foreign
tourists to Greek ski resorts.
LIMITATIONS/FUTURE RESEARCH
The study was intended to produce meaningful data that would provide a tool and
data source on which quality marketing efforts can be based. However, this research is
limited to the customers of the two ski
resorts in northern Greece. Generalizations
of the findings should be made with caution.
Ski experience, overall satisfaction, income and visit frequency should be used to
segment customers of other ski resorts in
Greece and abroad. A replication of the
study in other ski resorts could also provide
valuable information on the role of satisfaction in predicting visit frequency. The statistical results on satisfaction were close to
the 0.05 level (p ¼ 0.05), indicating that
monthly visitors might not differ significantly from weekly visitors. Larger sample
size could assist in gaining more confidence
from the results. Moreover, future studies
should investigate the kind of products and
services that could satisfy ski resorts customers with different ski experience and
income.
REFERENCES
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