Table of Content
As millions more travel abroad each year, the competition to attract these visitors becomes ever fiercer. Yet the money spent by destinations on capturing their interest can be easily wasted if not properly channeled according to a comprehensive new report on tourism market segmentation. Market segmentation is crucial in making sure that national resources are used in the most effective way. Everything they do media selection, destination positioning, branding, editorial, visuals, etc. revolves around the segments that have been identified as the most important. This is why monitoring and managing a portfolio of target segments that meet a destinations tourism objectives has become a critical function.
1. Introduction
The evolution of information technology has enabled collection and storage of huge amounts of data. With the entrance of each tourist, huge amount of data is generated in immigration department each day. As price of data storage are going reducing and processing power are going affordable, we can implement various visualization tools in order to find the similar characteristic group.
Segmentation is the process of finding small group bearing similar behavior
characteristics. It may be based on geographical, demographical, sychographic
or behavioristic. Since tourism industry are keen to implementing tourist centric enterprise, they are named with various data segmentation tools.
The effective segmentation project consists of several phases.
1. Defining the Problem to be solved
Before starting segmentation, we have to define for what purpose we are going to segment the data so that unique data mining model can be defined. Taking to business people is the best way to define the problem to be solved.
2. Assembling and Preprocessing Data
If we have to access the data from relational database or from flat file or from spreadsheet or from other sources, we have to perform effective data preprocessing process which involves data extraction, cleaning, enrichment, aggregation.
3. Modeling
In this phase the data is presented to a segmentation software which may follow several data mining processes. Sometime the variables chosen are not appropriates ones, and in this case the analyst has to go back and make some changes to the data he is using.
4. Interpreting the Results
The results should be brought together into a coherent presentation and presented to business people. The model should be evaluated with respect to problem solving objectives.
5. Applying the Results
The ultimate goal of segmentation is finding the group of people bearing similar behavior and address the interest of that group by lunching effective marketing strategies to increase their satisfaction.
The five step described here isn’t strict, because segmentation process itself isn’t linear. This means that one can move back and forth between different phases because the next phase in the sequence often depend on the outcomes associated with preceding one.
2. Reasons for Applying Segmentation in Tourism Market
For
more than 25 years segmentation has been proclaimed to be the
cornerstone of successful marketing. Ever since the publication of
Theodore Levitt’s seminal text, segmentation has continued to be
promoted as the sine qua non of successful marketing4.
Levitt’s original assertion that ‘if you’re not thinking
segments, you’re not thinking marketing’ has clearly stood the
test of time.
Put
simply, segmentation is critical to competitive advantage and should
underpin every decision that needs to be made about all aspects of
the tourism marketing mix. A real tourism marketing strategy needs to
start with the tourist visitor, not the destination or product. It is
clear that the visitor market, by definition, is not homogenous and
every visitor or potential visitor does not want the same thing. This
immediately gives rise to a segmentation issue.
The
recognition that the needs and requirements of the visitor market are
heterogeneous rather than homogenous should then become the starting
point in developing value propositions that are unambiguously
targeted at distinct and identifiable groups of visitors who are all
similarly motivated in their decision to visit a destination.
Implementing
a tourism marketing plan based on needs-based segmentation is
difficult, but not impossible2.
Yet, many destinations have still not developed effective
segmentation strategies, largely because many of the conventional
techniques are no longer suitable for an increasingly sophisticated,
discerning and fragmented tourism market.
3. The Data to Be Segmented
A huge
amount of the data generated by immigration department can’t be
analyze using traditional techniques, by using manual data analysis.
This is why different data mining techniques ought to be applied.
As
mentioned before information about the visiting of each tourist were
stored on the database. Tourist details records include their
demographic characteristics along with purpose of visit, total
duration stay and tentative places of visit. These information help
us to find out the best places for particular group according to age,
gender, type of visit or in country prospective. These data are often
not suitable for segmentation as goal of segmentation is to find the
pattern based on the group rather than each tourist3.
So, raw data should be collected and aggregated on group level. These
information also help on addressing the need of the visitor with less
miss rate.
4. Segmentation Approach
Commonsense Segmentation
Market
segments can be derived in many different ways. All segmentation
approaches can be classified as being either a priori (commonsense)
segmentation approaches or a posteriori (post hoc, data-driven)
segmentation approaches. The names are indicative of the nature of
these two approaches. In the first case destination management is
aware of the segmentation criterion that will produce a potentially
useful grouping (commonsense) in advance, before the analysis is
undertaken (a priori). In the second case destination management
relies on the analysis of the data (data-driven) to gain insight into
the market structure and decides after the analysis (a posteriori,
post hoc) which segmentation base or grouping is the most suitable
one.
Commonsense
segmentation has a long history in tourism research with many authors
referring to it as profiling. As early as 1970 tourism researchers
did investigate systematic differences between commonsense segments
with a publication titled “Study Shows Older People Travel More and
Go Farther” (author unknown) appearing in the Journal of Travel
Research.
Typical
examples of areas in which commonsense segmentation approaches are
regularly used include profiling respondents based on their country
of origin, profiling certain kinds of tourists (e.g., culture
tourists, eco-tourists) and profiling tourists who spend a large
amount of money at the destination (big spenders). In fact,
geographical segmentation such as grouping tourists by the country of
origin were among the first segmentation schemes to be used.
The
segments generated by this method can be compared based on:
socio-demographic personal characteristics (age, gender), behavioral
characteristics (duration of stay, travel party, kind of holiday,
accommodation, expenditures) and psychographic personal
characteristics (travel motives).
Data-driven Segmentation
Data-driven
method can be taken as the segmentation to the field of marketing.
While acknowledging the value of geographic and socio-demographic
information about consumers, information about benefits consumers
seek form market segments. This approach requires groups of consumers
to be formed on the basis of more than one characteristic and,
consequently requiring different statistical techniques to be used.
To sum
up, the implications of all the foundations are the following4
(1) data analysts and managers need to be aware of the exploratory
nature of data-driven market segmentation and not over interpret the
value of one single segmentation solution which was not based on
thorough preliminary data structure analysis, (2) repeated
computations of segmentation solutions can easily be undertaken to
assess the stability of alternative solutions, (3) stability analysis
will inform the data analyst and manager about the nature of the
derived segmentation, whether it reveals true clusters, identified
stable artificial groupings or represents an artificial construction
of the most suitable grouping in a data set with very little
structure, (4) it is not necessary for all segments derived from a
segmentation solution to be valid. For a tourism destination
searching for a niche, it is perfectly sufficient to have identified
or constructed one market segment which has high external validity,
(5) market segmentation is not independent. A successful market
segmentation strategy is in line with the tourism destinations
positioning and differentiation strategy, thus accounting for the
particular strengths of the destination and the competitive
environment, and (6) data-driven segmentation studies have to be
repeated regularly to ensure validity of the insight gained into the
market structure at any point in time.
5. Building Data-Driven Market Segmentation To Aid Effective Destination Marketing
A
data-driven segmentation study contains all the components of a
commonsense segmentation study. The way in which respondents are
grouped is the only difference between the commonsense and the
data-driven approach: in commonsense segmentation one criterion is
selected which usually is one single variable such as age or gender
or high versus low levels of tourism spending. In data-driven
segmentation a number of variables which ask respondents about
different aspects of the same construct (e.g., a list of travel
motives, a list of vacation activities) form the basis of
segmentation and a procedure – in tourism research typically a
clustering algorithm - is used to assign respondents to segments
based on the similarity relationships between respondents
The
approach that we defined to make effective segmentation models is
shown in table4.
In step 2a, the data analyst selects one or more segmentation
algorithms. The predominant algorithms used in tourism research are
k-means clustering and Ward’s clustering. Ward’s clustering is
one form of hierarchical clustering procedures. Hierarchical – more
precisely agglomerative hierarchical - clustering procedures
determine the similarity between each pair of two respondents and
then choose which two respondents are most similar and places them
into a group. This process is repeated until all respondents are in
one single group.
Table
: Steps in Data-driven Segmentation
Step 1: Selection of
the Segmentation Base
(e.g.
Travel Motivations, Vacation Activities)
Step 2: Grouping of repondents
Step 2(a): Selection of segmentation
algorithms(s)
Step 2(b): Stability Analysis
Step 2(c): Computation of final
segmentation solution
Step 3: Profiling (external validation) of
segments by identifying in which personal characteristics segments differ
significantly
Step 4: Managerial assessments of the
usefulness of the market segments (and formulation of targeted market
activities)
6. Basics for Segmentation
Basis |
Description |
Geographic |
Dividing a market into different geographical units such as nation, states, regions, cities or neighborhoods. For example tourism markets may be segmented into international and domestic visitors. |
Demographic |
Dividing a market based on demographic variables such as age, gender, family size, family life-cycle, income, occupation, education, religion or nationality. For example Temples like Pashupatinath may be target for Hindu people while Chaitya, Gumba may be the target for Buddhist. |
Psychographic/Life-style |
Dividing markets based on consumer values, attitudes, interests, opinions. For example adventure tourism operators may target consumers who have a strong interest in outdoor pursuits, bungee, and paragliding while epicureans are the target market for food and wine trails and cooking schools. |
Benefits |
Dividing the market into groups according to the different benefits that consumers seek from the product or service. An example of benefit segmentation can be seen in the rise of spa resorts targeting consumers who seek rejuvenation and improved health and well being from their holiday experience. |
Usage |
Dividing markets based on usage patterns such as non-user, ex-user, potential user, first-time user, regular user, high volume user. For example destination-marketing programs may use one message strategy to communicate with repeat visitors and a different approach for people who have never visited. |
Loyalty |
Dividing markets based on brand loyalty to a particular hotel chain or destination. For example the establishment of the branches of famous hotels like Taj Hotel, Hotel Sheratan, Emirates Palace in Kathmandu, Pokhara, Chitwan, Bardia etc. |
Situation |
Related to usage segmentation, situation segmentation divides markets on the basis of the consumption or purchase situation of consumers. For example travelers may find one destination suitable for a short break and a different style of holiday appropriate for a long holiday. |
Behavioural |
Dividing markets based on consumer’s knowledge of, attitude toward, uses for and responses to a product or service. |
7. Result & Discussion
The
natural endowments and cultural heritage of Nepal provide a solid
foundation for tourism market segments’ development. Specifically,
poor marketing has led to inability to capture higher-value demand.
This low-value demand has limited the incentives for new investments
in infrastructure, discouraging innovation and adoption of best
practices.
Based
on the data sets available from the Nepal Tourism Board and other
Travel Agencies situated in Kathmandu & Lalitpur, we segmented
the arrivals of international tourists on the basis of country of
origin, purpose of visit & travel partners using Orange Data
Visualization framework7.
As
shown in figures, the segmentation of the customers into different
clusters makes the better visualization about the tourists & more
informatic showing different tourism market segments8.
According to the pie-chart of the purpose of visit in Figure – 2,
the tourists arriving for the rafting are very low, almost zero,
whereas, there are world-class rafting river sites in Nepal including
Trishuli, Bhotekoshi etc. So, the segmentation analysis helps the
travel agencies, tourism boards, Government of Nepal to find the
effective market areas within the tourism industry which could highly
contribute to the country’s economy unlike just 4.3% of total GDP
as of 20129.
8. Conclusion
Market segmentation is a strategy any entity in
the tourism industry can use to strengthen their competitive
advantage by selecting the most suitable subgroup of tourists to
specialize on and target. A wide variety of alternative techniques
can be used to identify or construct segments. Approaches range from
simple commonsense segmentations (where tourists are split on the
basis of a predefined personal characteristic) to multidimensional
data-driven approaches where a set of tourist characteristics is used
as the basis for grouping10.
Once tourists are grouped using the correct and most suitable
analytical techniques the resulting segmentation solution has to be
assessed by the users (tourism managers) who will not only evaluate
the segmentation solution but also the fit of potentially interesting
segments with the strengths of the tourism destination. Tourism
managers can benefit from market segmentation by using it actively as
a method of market structure analysis. In doing so, they can gain
valuable insight into the market and specific sections of the market
and identify the most promising strategy to gain competitive
advantage. Typically such a strategy will not only require market
segmentation, but also product positioning. Both approaches will have
to be evaluated in view of competitors’ segmentation and
positioning choices to be successful. Segmentation solutions should
be computed regularly to ensure that current market structure is
captured.
The
market segmentation technique can be applied by any unit operating in
tourism industry: hotels, travel agencies, tourist attractions,
restaurants, local charities as well as the Government of Nepal.
9. References
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