Steps In Segmenting A Market

Published Date: 02 Nov 2017

There are five criteria for an effective segmentation:

Measurable: It has to be probable to establish the values of the variables used for segmentation with acceptable efforts. This is important particularly for demographic and geographic variables.

Applicable: The size and profit potential of a market segment have to be large enough to economically validate separate marketing activities for this segment.

Available: The segment has to be available and servable for the organization.

Distinguishable: The market segments have to be diverse to explain different reactions to different marketing mixes.

Practicable: It has to be probable to approach each segment with a particular marketing program and to draw advantages from that (Recklies, 2001; Freathy and O’Connell, 2000; Dibb and Simkin, 2010; Hattum and Hoijtink, 2010).

McDonald and Dunbar (2004) mentioned that there are number of factors to be considered before going on to specify the step-by-step process for effective market segmentation which are:

Suggestion flexibility: the degree to which suggestion can be tailored to the needs of different groups of customers.

Market granularity: the degree to which customer needs and motivations vary within a defined market.

Organizational considerations: the most important point about organizational structure is that there are number of issues that all firms have to address these are geographic location, products, markets and channels.

An effective segmentation process includes three distinct steps: marketing analysis to gain information or current marketing intelligence; strategy development to formalize ideas; and marketing programs to achievement the determined revised segmentation strategy. These three steps form a loop, as the formulation of marketing strategies, segment targeting, and marketing mix programs is a never-ending cycle of revisions (Dibb and Simkin, 1997).

3.10 Steps in Segmenting a Market

There are ten steps to follow in segmenting the market:

Step 1: choose a market or product class for study

Define the overall market or product category to be studied, either new or old.

Step2: register prospective needs

A brainstorming sitting is used to identify needs. Through this, identifying the reasons why consumers buy the product. The list must stress needs, benefits and satisfaction.

Step 3: Choose approach or approaches for segmenting the market

There are no systematic procedures for selecting segmentation variables. However, a successful segmentation method must produce segments that meet the four basic criteria namely: substantial, identifiable, accessible and responsive.

Step 4: choose segmentation descriptors

Descriptors identify the particular segmentation variables to use. For example, demographics may be used as a basis of segmentation. Examples may be age, occupation, sex and income.

Step 5: Profile and investigate homogeneous segments

The profile of individual segments should contain the segments’ size, expected growth, purchase frequency, current brand usage, brand loyalty, and long-term sales and profit potential (levina, 2010).

Step 6: Identify the determining dimension

A determining dimension is related to the seller’s competitive advantage. A determining dimension must be identified for each potential segment, because it will eventually determine a consumer’s decision to buy or not to buy.

Step 7: Name and select target markets (Moyo, 2005).

Step 8: Securing the resources necessary for the target(s),

Step 9: Adopting positioning plans for the market offerings for the segments, and

Step 10: Developing marketing mixes proper for each segment (Hunt and Arnett, 2004).

The most important feature of the segmentation is positioning and differentiation of offerings in the segments. The essential point in the segmentation can be expected to be specific customer needs, but the segmentation should also create the foundation for specific marketing activity consideration (Clarke and Freytag, 2008).

The approach outlined in Figure 3.3 starts with an assessment of the existing markets and market share/profitability situation in order to identify strengths, problem areas, and distinctive competencies. Change is required in any market segmentation implement, but change purely for the aim of change can simply be destructive. Core analyses examine several aspects of buyer behavior, including customer needs, buying processes and influences on each stage of the buying processes. These pieces of information are essential in order to determine segment bases and ultimately to identify the central segments in a market (Dibb et al., 1994). The remaining analyses listed in Figure 3.3 are fundamental if an organization is to update its marketing information, achieve a valid market focus, and target the "best" or most appropriate market segments. In addition, without information about customer needs, competitors’ strategies and rival brand positioning, the organization cannot determine the ideal positioning strategy (Dibb and Simkin, 1997).

A: Core analyses (Now)

• The existing situation

• General trends/marketing environment

• Strengths, weaknesses, opportunities, threats

• Customer needs/expectations/Buyer behavior

• Competitive positions/strategies

• Brand or product positioning

• Balance of portfolio

B: Strategic thinking (The future)

• Identification of new segmentation criteria/ Segmentation bases

• Determination of new/revised market segments

• Selection of new/revised target segments

• Determination of brand positioning strategies

C: Implementation programs (How)

• Marketing programs

– Product range and portfolio

– Pricing and payment issues

– Promotional strategies and tactics

– Distribution and control

– Service levels and personnel

– Sales force

– Internal communications and organization

• Resources and scheduling

– Budgets

– People and responsibilities

– Activities

• Ongoing requirements

– Product/brand development

– Marketing research

– Training

– Communications

– Monitoring performance

Figure 3.3 the stages of segmentation

Source: Dibb and Simkin, 1997

3.11 The Segmentation Models

3.11.1 Bonoma and Shapiro’s nested model

Bonoma and Shapiro (1984) developed the primary model of industrial market segmentation. Mitchell and Wilson (1998) mentioned that Bonoma and Shapiro try to bridge the gap between what is practical for sellers to use (identifiable/accessible segmentation) and most appropriate theoretically (needs/benefits-oriented segmentation), Bonoma and Shapiro extend the earlier work of Wind and Cardozo to suggest a nested approach to industrial market segmentation. Figure 3.4 illustrates the basic model. Bonoma and Shapiro argue that the benefits-orientated approach is the more attractive in the theoretical sense, but also more difficult for managers to implement, "the identifiability approach provides readily identifiable customer groupings, but can state no causal relationship to sought benefits".

The nested approach suggests that the buyer start with factors those are company-oriented, general or easily identifiable and continue to seek customer knowledge that becomes increasingly more specific and intimate until worthwhile targets become apparent. The outermost layer suggests that industrial marketers first segment customers using demographics characteristics. Demographic variables provide a broad description of the potential customer and include the company’s industry, size and location. The next base for segmentation includes operating variables. These variables include the customer’s technology base, use/non-use of particular products and brands and operating, technical and financial capabilities (Eckert and Goldsby, 1997).

The next, more precise layer of the model identifies customers according to their purchasing approaches. Viewed as an often neglected segmentation base, this nest includes identification of the potential customer’s formal purchasing organization, power structure, nature of existing organizational relationships, purchasing policies and criteria (Eckert and Goldsby, 1997; Mitchell and Wilson, 1998). The nested approach can be used for logistical segmentation and industrial market segmentation (Murphy and Daley, 1994).

Demographics

Operating variables

Purchasing approach

Situational factors

Personal characteristics

Figure 3.4 Bonoma and Shapiro’s nested model

Source: Eckert and Goldsby, 1997

3.11.2 Need Scope Consumer-Brand Relationship Model

The heart of need scope is a psychological model that summarises human emotions. This provides a constant framework to develop and implement strategy. Need scope is a unique instrument that helps to reveal the consumers needs. Consumers’ needs can be distinguished in three categories as shown in figure 3.5 the most accessible category accounts for the functional needs, such as safety, speed and ease. These needs are rational and are or are not fulfilled by the product characteristics of a brand (Wilson and Calder, 2006; Hagen, 2009).

Somewhat more difficult to interpret are the social identity needs. Every human being wants to belong to a certain group and to identify with it. The core of all consumer behaviour is emotional needs, such as the need for safety or the need for control (Hagen, 2009). These emotive needs are the real drives of brand choice and are satisfied by brand symbolism. At this level, consumer needs take two different forms which are gratification and expressive. Gratification needs are satisfied by a feeling, a change in mood, brand can make the person feel safe and secure. Expressive needs are about satisfying a personality ambition (Wilson and Calder, 2006).Untitled3.png

Untitled3.png

Consumer requirements

Brand Image

Figure 3.5 Layered subdivisions of needs

Source: Hagen, 2009

3.12 Importance of Customer Service

Customer service can be viewed as the output of the logistics structure. Also, customer service may represent the best opportunity for a firm to achieve a sustainable competitive advantage in the marketplace. Customer service can be the most cost-effective element of the marketing mix on which management can build a differential advantage for firms. There are obvious benefits from segmenting markets, the major advantage being the ability to target the marketing mix for a specific group of customers (Sharma and Lambert, 1994).

Customer service often means different things to different industries and even different companies within the same industry. Customer service is a multidimensional phenomenon. Suppliers offer a range of services which combine into a customer service package. Customers decide whether to do business with a supplier on the basis of a range of customer service (Gilmour et al., 1994). Customer service is important because it can be used to discriminate a firm’s products, keep customers loyal and increase sales and profits. The importance of customer service is in the development of a successful marketing strategy. Segmentation issues will help to develop a segmentation scheme that emphasizes customer service (Sharma and Lambert, 1994).

3.13 Segmentation Methods

Regardless of the extensive literature on market segmentation, there is no overall agreement about the optimal segmentation methodology. One reason for this diversity is the fact that segmentation can be viewed from different perspectives (Lopez and Jeronimo, 2008).

Kim and Lee (2011) sited that segmentation methods and modeling techniques established two decades ago were summarized and briefly explained by Beane and Ennis (1987), who emphasized the need for their creative application. Those were: automatic interaction detection and its multivariate variant; canonical analysis; factor analysis; cluster analysis (Park and Sullivan, 2009); regression analysis (Wu, 2001); discriminant analysis; multidimensional scaling; conjoint analysis (Pas and Huber, 1992) and componential segmentation.

Wedel and Kamakura (2000) demonstrated more recently developed methods, such as log-linear and mixture regression models, and classified them into the second two-by-two matrix shown in table 3.1

Table 3.1 Classification of Segmentation Methods

Source: Kim and Lee, 2011

A priori

Post hoc

Descriptive

Log-linear models;

contingency tables

Non-overlapping (K-means);

Overlapping; fuzzy techniques.

Predictive

Regression;

discriminate analysis

Automatic interaction detection; mixture regression models

First, the segmentation methods classification is based on either a priori if "the type and number of segments are determined in advance by the researcher" or post hoc if "the type and number of segments are determined depending on the results of data analyses". Second, the difference between those in which the statistical methods used were descriptive, analyzing relations among a set of variables but making no difference between dependent and independent variables, and those that are predictive, in which "one set consists of dependent variables to be explained by the other set of independent variables" (Lopez and Jeronimo, 2008; Kim and Lee, 2011).

Database marketing techniques have derived from simple RFM models (models involving recency of customer purchases, frequency of their purchases, and the amount of money they have spent with the firm) to statistical techniques such as chi-square automatic interaction detection (CHAID) and logistic regression (McCarty and Hastak, 2006).

There are a variety of ways of applying RFM model on customer segmentation, including K-means or fuzzy C means (FCM), artificial neutral network (ANN), and decision tree (DT) (Wang, 2010). ANOVA and clustering analysis are frequently used in segmenting analysis (Kennedy et al., 2008). Clustering analysis is an unofficial process of dividing patterns into groups and make objects within cluster show relatively high intra-similarity whereas objects between different clusters have low inter-similarity (Chih et al., 2010).

Clustering analysis is the most frequently used statistical methods for classification or segmentation of people (Fu Ho and Chi Hung, 2008). Cluster analysis is a simply empirical method of classification because it makes no prior assumptions about essential differences within a population (Mitchell, 1994). This method can be described as post hoc since the types and number of segments are determined according to the results from data analysis, and descriptive with no distinction between dependent and independent variables (Pieniak et al., 2010). Clustering-based segmentation, segments can be identified by the data analysis procedure, typically by using cluster analysis. This clustering is most regularly based on consumer statements of the importance of product attributes. In other words, cluster analysis is used to categorize subjects on the basis of rated importance of various product attributes and benefits (Kimiloglu et al., 2010). There are two types of cluster analysis which are hierarchical method like linkage method, ward’s minimum variance method and non hierarchical method cluster analysis methods like K means (Rao and Wang, 1995; ke, 2007).

Quinn et al (2007) viewed that using cluster analysis as a technique for identifying segments, managers must make decisions about:

The approach to be used for segmentation;

The variables to be used to measure the approach;

The analytical method used to identify segments; and

The number and structure of the segments they choose to have.

Conjoint analysis is a statistical technique used to study the importance of product attributes to consumers, as well as the consumer value from the same attribute levels. A product is usually composed of numerous attributes. The different combinations and specific levels of each attribute makes products diverse. For different consumers, the importance of product attributes and the utility values on different levels of the similar attribute are not the same; this is the core difference of consumer demand. The assessment of the product attributes and the utility values of the specific attribute level are appropriate standards in market segmentation (Li et al., 2011).

3.14 Marketing Strategy and Segmentation

The marketing segmentation process means dividing a market into several market groups. In each market segment consumers have similar product needs. Each segment requires a different mix of marketing strategies to satisfy its special consumer’s needs. The idea of designing marketing for marketing segments is based on consumers’ wants and interests (Lin, 2002).

Marketing strategy is defined as the total sum of the integration of segmentation, targeting, differentiation, and positioning strategies designed to create, communicate, and deliver an offer to a target market. Marketing strategy is the key to the extension of sales and the consequent beneficial effects on company performance. The planning of strategies contain: Product, pricing, promotion, place, competitive analysis, customer analysis and customer relationships (El-Ansary, 2006; Musyoka et al., 2007).

The most difficult part of any segmentation project is the translation of the study results into an effective marketing strategy. In addition to recognizing the subjective elements inherent in segmentation studies, managers must also understand and act on the information generated. The segmentation process itself does not provide prescriptive solutions to marketing problems but purely offers a description of the market. It is possible that segments generated from a particular study may already be well served by competitors or uneconomical to reach, for example managers must decide which segments to target and how to best operate the marketing mix to influence the behavior of consumers in particular segments. Therefore, segmentation studies should not be considered in separation but need to be developed with a sound understanding of the factors influencing consumer behavior and the nature of the marketing environment (Fuller et al., 2005).

3.15 The Role of Service Marketing Mix

Marketing mix is not a scientific theory, but just a conceptual framework that identifies the principal decision making managers make in configuring their offerings to suit consumers’ needs. The marketing mix tools can be used to develop both long-term strategies and short-term tactical programs (Goi, 2009).

The marketing mix concept also has two essential benefits. First, it is an important tool used to enable one to see that the marketing manager’s job is, in a large part, a matter of trading off the benefits of one’s competitive strengths in the marketing mix against the benefits of others. The second benefit of the marketing mix is that it helps to reveal another dimension of the marketing manager’s job (Goi, 2009). All managers have to allocate available resources among various demands, and the marketing manager will in turn allocate these available resources among the various competitive strategy of the marketing mix. In doing so, this will help to introduce the marketing philosophy in the organization (Low and Tan, 1995)

Service marketing mix is controlled variables which can be used by company to influence consumer reaction from certain market segment who are targeted by the company. The tools of marketing mix or internal factors that can be controlled by company from marketing mix consist of 4 main components that are product, price, distribution and promotion, and in the advancement there are 3 more added that are people, physical evidence, and process (Ivy, 2008; Fu Ho and Chi Hung, 2008; Manafzadeh,et al., 2012).

Consumer or customer chooses service provider based on their expectation and after consuming the service, they will compare it with that they desired. If the service quality they consumed is far below their expectation, then the consumer will lose interest on such service provider and vice versa. Definition of service quality centralized to fulfillment of needs and demand of customer and also the certainty of delivery to balance customer’s expectation. Service quality should start from the consumer needs and ended on consumer perception. Consumer perception towards service quality is an entire estimation of consumer on the excellence of a service (Thamrin, 2012).

3.15.1 Customer Orientation, Marketing Mix Capabilities and Firm Performance

Marketing is not only concerned with the development and achievement of successful programs and strategies. For marketing to be successful there needs to be a marketing orientation throughout the company, this fosters the marketing concept and demonstrates a marketing approach to all internal and external activities (Plomaritou et al., 2011). The concept of customer orientation emphasizes the sufficient understanding of the target customers so as to deliver superior values for them. Therefore, customer-oriented firms show a continuous and proactive nature toward identifying and meeting customers' expressed and latent needs. With customer-oriented values, firms do extremely well in creating and maintaining bonds with customers and therefore obtain affirmative attitudes, linking customer satisfaction in addition to positive financial outcomes (Zhou and Li, 2010).

Marketing mix capability is expected to perform as a connecting engine by carefully reforming a new solution, developing new approaches of advertisements and sales promotions, providing a right range of the pricing scheme, placing products at the right place and time for the customers. These carefully programmed and deployed marketing activities can change the organizational cultural level of customer orientation to better customer satisfaction, market share growth and profitability. When customer needs change rapidly, customer orientation enables firms to recognize those changes, and guides themselves to explore necessary actions and build relevant abilities to develop appropriate programs to meet customers’ needs (Shin, 2012).

3.17 Previous Studies and Research

Pas and Huber (1992) developed a demand forecasting tool that could be used to estimate the ridership and revenue for alternative rail services that might be provided in the study corridor and characterized the market for intercity passenger rail service in the corridor of interest according to the needs and preferences of potential riders in the corridor. The five primary rail service attributes that were included in this study are rail travel time, cost, and number of departures per day, food service and seating type. The five identified traveler clusters are: functional traveler, day tripper, train lover, leisure-hedonic traveler, and family traveler.

The public transport parameters that classified through CEN (European Committee for Standardization) are availability, convenience, information, time, customer care, comfort, security and environment, which reflect the criteria of the benchmarking of the service. However, passenger perceptions and preferences may not always address the proper measures for the improvement of quality. This is mainly met in the evaluation of the railway safety, where the proposed safety measures by the passengers may conflict with initiatives designed to improve safety and minimize occurring risks (Nathanail, 2008).

Krizek and El-Geneidy (2007) were use a market segmentation approach that would uncover population groups that share similar habits and preferences toward travel generally and transit specifically. After using factor and cluster analysis yielded users of the system who were classified into four categories: captive riders with regular commuting habits, captive riders with irregular commuting habits, choice riders with regular commuting habits, and choice riders with irregular commuting habits. Similarly, non-users were classified into four categories: auto captives with regular commuting habits, auto captives with irregular commuting habits, potential riders with regular commuting habits, and potential riders with irregular commuting habits.

Some service quality studies used the customers’ expectations as a basis for market segmentation, the using of expectation in measuring customer satisfaction. Apart from customer’s expectations, the importance of service quality attributes has been used as a basis for segmentation studies (Woo, 1998).

Other use expectations as a segmentation variable allows for more capable promotional activities, applying segmentation variables depend not only on personal preferences, but also on other factors, such as "word of mouth" communications or promises made by providers. Segmentation based on customer expectations provides managers with a powerful tool because of consumer identification and this can be the source of better customer service. This type of segmentation provides an instrument for companies to tailor their services to the segments they chose as targets, focusing on the factors which most influence customers’ satisfaction and making the customers feel that their needs are being understood (Martin et al., 2000).

European airport authorities used some methods to segment their customer base. Airport authorities adopt a more marketing orientated approach, use unique from of a priori segmentation to determine the most suitable mix for the airport and re-examine the means by which they classify and categorise consumers (Freathy and O’Connell, 2000).

The study of Dutch railways uses a segmentation model which focuses on the psychographic needs of train passengers. By revealing the needs of different types of people and the size of the different segments, this segmentation model allows us to ensure whether the current provision of services meets the customers’ requirements. By understanding these needs, the unfulfilled services can be developed. The segmentation model has been used to transform the provision of services both in the trains and on the stations, as well as to train employees to deal better with the varying needs of customers. Dutch railways started to look for an unambiguous segmentation instrument that was demand rather than supply- based that derived from the passengers and not from the current supply of Dutch railways. This study represents six different need segments, according to a type of passenger: the explorer, the individualist, the functional planner, the certainty seeker, the socialiser and the convenience seeker (Hagen, 2009).

Freight transport services may use benefit segmentation to guide resource allocation for the service marketing manager. Profiling the benefit segments in terms of their product characteristics, transport service characteristics, company demographics, and control variables, allows resources to targeted to particular buyers of freight services; for example, those with higher value products. If the company proposes to allocate resources to a particular segment it will wish to ensure that the members of the segment are aware of this attention to their needs (Matear and Gray, 1995).

The study of mobile TV content of public transportation used market segmentation concept to identify the profiles of market segments based on the customer characteristics (demographic, train patronage variables, mobile TV content, and life style variables) the results of the study identify three segments (Tao, 2008). Managers in railway services need to take the level of contact and the views of certain demographic segments into account if they want to maximize perceived service quality. Demographics help managers to determining which segments of the market are reasonable in terms of achieving greater market penetration. Moreover, to remain competitive, companies must be able to develop and improve their services to meet the needs and preferences of different consumer segments. Managers should take steps to ensure that all customers have their individual needs wished for (Lim et al., 2008). Kimiloglu et al (2010) discovered consumer segments with different behavioral profiles in the mobile phone market. Factor analysis is conducted on different attributes to which consumers choose in purchasing a mobile phone.

In the financial services sector (retail banking) using service quality dimensions as segmentation variables can be the basis for differentiation in a highly competitive environment. Service quality provides the opportunity to examine the potential for segmentation strategies founded on the consumer’s perceived importance of these service quality dimensions relative to other offering of financial institutions. A key concern for financial institutions is to focus on the primary benefits sought by customers. The advantage of clearly understanding the needs of segments are effectively and efficiently to position the firm’s resources towards satisfying those needs (McDougall and Levesque, 1994).

The study of airline industry identified the service dimensions that more important to the airline passengers. Passenger’s expectations of desired airline service quality are differences due to service dimensions like reliability; assurance; facilities; employees; flight patterns; customization and responsiveness. Regarding the service dimension expectations, there are no significant differences between passengers who made their own airline choice (decision makers) and those who did not (non-decision makers). However, there are significant differences between passengers of different ethnic groups/nationalities and between passengers who travel for different purposes, such as business, holiday and visiting friends/relatives (Gilbert and Wong, 2003).

Studies that have used psychological variable for segmentation can be divided into different categories depending on the nature of the variables used. On way of making such a classification is to use a portrayal of means-end chain, it is the way of linking the behavioral patterns of an individual back to their ultimate values as the guiding principles in their life (Lawson and Todd, 2003). Bojanic (2007) defined "carry out" segments for restaurant using a combination of demographics, determinant attributes, and dining behaviors.

Banks have often focused on geographic, demographic, socioeconomic and psychographic characteristic as descriptive variables of market or segment. However benefit segmentation has a causal relationship to future purchase behavior (Minhas and Jacobs, 1996). Indonesian banking sectors using benefit segmentation for customer retention, acquisition and explore any relationships between desired marketing benefits and demographic characteristics. The hierarchical cluster analysis determines three clusters which are: relationships cost sensitive and service focused (Alfansi and Sargeant, 2000).

The study of Kumar et al (2012) focused on clustering e-banking consumer based on customer characteristics, behavior, RFM analysis, LTV and demographic variables. Understanding customer value in each cluster, the bank would gain opportunities to establish better customer relationship management strategies, improve customer loyalty and revenue and find opportunities for increasing the selling.

The study of rail-trail users demonstrated that benefit segmentation can be a useful means of determining market segments of tourists, recreationists, or park users, with the purpose of helping managers and tourism promoters work more effectively toward advertising their products. This study divided rail- trail users into five benefit segments: fitness Seekers, typical trail users, group naturalists, and enthusiasts (Lupas and Moisey, 2001).

Park and Sullivan (2009) identified the segment of university student based on clothing benefits sought and develop a profile of each segment in terms of attribute evaluations, shopping orientations, and repatronage behavior. Consumers were classified into three different groups according to clothing benefits sought which are: the utilitarian benefit group, the hedonic benefit group, and the composite benefit group.

Psychographics is an approach used to identify and measure the lifestyles of consumers. It has been utilized substituted with the activities, interests and opinions measures (AIO). The study that used psychographic factors aims to generate the psychographic dimensions of female consumers in greater China and develop a typology of female consumers based on their psychographic patterns. Factor analysis was performed on the lifestyle variables for each group to review the stability of the dimensions across the groups (Tam and Tai, 1998).

Bhatnagar and Ghose (2004) used the latent class segmentation analysis to segment web shoppers, based on their purchase behavior across several product categories. The study came up with three segments; those subsequently profiled demographically and looked at their perspectives of benefits from the Web. Mukiibi and Bukenya (2008) segmented grocery shoppers in Alabama based on preferences, lifestyles and shopping habits by employing cluster analysis technique.

Dennis et al (2001) explored the differences in behavior between shoppers and draw attentions to differences between segments as to which attributes are critical in shopping center choice. Identify segments of shoppers who can be classified by importance motivation. El-Adly (2007) determine the attractiveness factors of United Arab Emirates malls from the shoppers’ perspective and segment shoppers according to these attractiveness factors using factor and cluster analysis. Park et al (2011) employed shopper segments based on benefits sought from TV home shopping and profiled the identified segments in term of personal characteristics, satisfaction and repurchase intentions. Canever et al (2007) defined the beef customers in Brazil according to benefit sough, demographic, socio-economic and purchasing-pattern.

The study of senior motor coach travelers categorized travelers based on the reasons why they traveled and what they were looking for when they traveled. Factor, cluster and discriminate analyses are conducted (Hus and Lee, 2002). Conyette (2011) used demographic factors to segment the online leisure travel booker.

Montinaro and Sciascia (2011) have investigated the possibility of identifying new type of customer loyalty by using the strategy of market segmentation and statistical indexes of customer satisfaction. Epetimehin (2011) used market segmentation as a tool for improving customer satisfaction in insurance service delivery. Chen and Chang (2004) determined a methodology for identifying appropriate customer segments by using customer satisfaction-demanding behaviour that is characterized by the disparity of derived global satisfaction and stated global satisfaction.

The study of marketing segmentation through learning machine model developed segments according to customer relationship management (CRM) and customer profitability accounting. The analysis of the market segmentation within the CRM model is considered using both psychographic and socioeconomic attributes through statistical models and decision trees techniques (Lopez and Jeronimo, 2008).

Li et al (2007) examined the potential utility of HOFSTEDE’s measure of cultural values for group segmentation in an ethnically diverse population in a forest recreation context. Socio-demographic, service quality, satisfaction, and behavioral intention variables were used to validate values-based segments. Kaze and Skapars (2011) analyzed consumption patterns and consumer behaviour in Latvian alcohol market suggesting behavioural consumer segmentation model to gain competitive advantages. Need state, lifestyle; social values and demographics factors are examined.

Souiden (2002) identified the market segments of Arab countries based on marketing mix variables. This study proposed a solution to the issue of marketing standardization adaptation by trying to find out how multinationals can apply standardize marketing plan to reach homogeneous segment while at the same time designing different strategies for different segments.

3.18 Summary

In this chapter the researcher introduced and defined the concept of market segmentation. The rationale underpinning segmentation and the criteria to do so were expanded. The discussion also included the characteristics, steps involved in segmenting markets and the different kinds and approaches of segmentation. Also, demonstrated the methods and techniques used in segmentation. The information enabled a firm to define and measure its chosen market segment and establish if it would be sustainable on an ongoing basis.

The identification of customer needs in order to serve and build the value of customer segments is a major challenge that marketers encounter. Despite the availability of demographic information on business-to business customers, the actual needs of the customer cannot be determined from this information. By linking readily available macro segmentation demographic descriptors to highly effective micro segmentation based need information, the marketer can now classify and target customers in a timely and cost-effective manner. By using a sample of customers to identify their needs and relating them to demographic factors, the necessity of identifying the specific needs of each customer. Through benefit segmentation, companies can divide large, heterogeneous markets into smaller segments that can be reached more effectively with products and services that match consumer’ unique needs. As consumers obtain satisfaction for their needs, a company can become more successful.