Market Segmentation Techiques
Eliyahu Wolf
8/20/2017
Market Segmentation Techniques
This paper examines three aspects of market segmentation. The Introduction gives a short preface to the paper, outlaying the topics to be discussed. The Background Statement describes the history of the segmentation concept. Furthermore, it connects the background of segmentation with each of the aspects to be described in the third section. In the Literature Review, three articles from various scholarly journals are analyzed. Each of these articles examines a different aspect of the market segmentation process. Included are the topics of spatial and geographic segmentation, product variant segmentation, and demographic and psychographic segmentation. After laying out the results of the studies examined, the paper compares and contrasts them against each other. It also relates each study’s findings to my marketing internship work at the BIR Training Center in Chicago. Finally, the paper presents topics of future research. These areas have not been researched yet by the studies’ authors, and therefore, future articles should look into them.
Introduction
When a company wants to sell its product, it must target certain parts of the market. Each product is suited to fit best certain kinds of consumers. The company has to determine who is most likely to buy each of its products. This process is known as market segmentation (Smith, 1956).
This paper will discuss three academic articles, each dealing with an element of the segmentation process. First, it will present an article about geographical segmentation - identifying the target consumers based on their geographic location and crafting the product to fit the needs, wants and purchasing habits of the consumers in the area. Then, the paper will examine segmentation between product variants, as opposed to company brands. Finally, the paper will determine whether customer brand preference hinges on demographic or psychographic factors. After laying out each of the articles’ conclusions, I will compare all of the findings to each other. They may conflict, or they may all be discussing totally different subjects.
Geographical segmentation is the technique of identifying the target consumers based on their geographic location, and crafting the product to fit the needs, wants and purchasing habits of the consumers in the area (Bovee and Arens, 1992). Product variants are specific, unique characteristics of the products, such as size, color, and material (Kennedy, Ehrenberg, and Long, 2000). Demographic segmentation are the cold, hard facts about people, such as age, gender, religion, race, education level, and occupation (Bovee and Arens, 1992). Psychographic segmentation are the underlying reasons beneath the statistics. It focuses on the psychologic reasons for consumers’ purchasing choices, such as their attitudes, values, lifestyle, and personality (Bovee and Arens, 1992).
I will apply the articles’ findings about segmentation to my internship work at BIR Training Center in Chicago. Over the course of the summer, I have performed marketing research on my company’s competition. The company I was interning for is a school which teaches people various skills, such as medicine, machine manufacturing, and English as a Second Language (for foreign students). The current student body is between 20 and 35 years old. I was researching the duration, class structure, pricing, and target market of a proposed, additional Information Technology training program at our school. Doing this involved finding our competitors, going to their websites, and obtaining their course catalogs and pricing information. In this fashion, we could see what kinds of classes we should offer, and who we should target, by first evaluating their strategies and course offerings. The three components of market segmentation that I will be highlighting were extremely important in our determination of our target market.
In this paper, I will be concentrating on my school’s target market. We came up with a lot of great ideas for our target audience, many of them involving the three kinds of methods that I will set out in this paper. However, I will not be covering the topic of pricing in this paper. Although I did look at our competitor’s course prices, there is not enough room in this paper to include this topic. It is simply too broad a subject to be analyzed in this paper.
Background statement
The history of market segmentation has seen several changes in the concept’s form. Agnes and Berthon describe these changes in their article, “Affecting Adolescence: Scrutinizing the Link Between Advertising and Segmentation” (2005). Market segmentation was introduced by Wendel R. Smith (1956) as an alternative strategy to product differentiation. Product differentiation has been the preferred marketing technique until Smith's novel article. This technique was defined by Smith (1956) (pages 64-65) as a strategy which uses differences in product design to lure customers; it is a form of mass communication. By contrast, Smith's proposal technique of market segmentation involves “developments on the demand side of the market.” It views the overall market as a bunch of smaller sub-markets; the marketer is able to target each market separately and uniquely. The market segmentation technique has been accepted as the prevailing practice in the field for the development of the marketing mix (Agnes and Berthon, 2005).
There are two kinds of variables applicable to product differentiation and market segmentation. These are demographics and psychographics. Before War World War II, the variables used in product differentiation and market segmentation were purely demographic in nature. These variables include the age, gender, income and family situations of the customers. They are the hard facts about the customers; they do not look into their thought processes. Before World War II, these variables were sufficient to segment the market efficiently (Agnes and Berthon, 2005).
However, after World War II, companies realized they needed to identify customer segments based on psychographic variables also. Psychographic variables examine customer segments based on their lifestyles and personalities. They do not look at the customer only based on his external facts. Rather, psychographic segmentation examines customers’ deeper reasons for purchasing the company's products (Agnes and Berthon, 2005).
Psychographic segmentation studies were carried out in two different ways until the late 1960s. The first method equated customers’ purchasing behavior with their scores on standardized personality tests, like the Thurstone Temperament Schedule (Thurstone, 1927) and the Edwards Personal Preference Schedule (Edwards, 1957). The second technique applied the concepts and methods of Freudian-style clinical psychology to their segmentation research (Agnes and Berthon, 2005).
In the 1960s, these two methods were combined into one overall technique. The psychographic method of segmentation (Demby, 1971; Nelson, 1969, 1971; Permaca, 1974). This psychographic technique fused the descriptivity of the motivation research investigations with the objectivity of the quantitative personality inventory (Agnes and Berthon, 2005). In this way, the marketer can get a clearer picture of the company’s target market (Agnes and Berthon, 2005).
The psychographic method is increasing in its popularity. Improvements in technology have made higher quality of data analysis possible. Therefore, market segmentation is become easier, more efficient and more exact. Many values, lifestyles and personalities are used to segment customers. There are many segments used to segment the market, including the VALS2 (Values and Lifestyles), LOV (List of Values), and RVS (Rokeach Value Survey). The VALS2 system segments consumers into eight groups. These include actualizers, achievers, experiencers, strugglers, thinkers, innovators, fulfillers and believers (SRI, 2004) (Agnes and Berthon, 2005).
“Affecting Adolescence: Scrutinizing the Link Between Advertising and Segmentation” (Agnes and Berthon, 2005) explores the possibility of adolescent customer segments being created by the company’s advertising and marketing mixes. Until the research of Agnes and Berthon (2005), segments of consumers were assumed to be pre-existing. Companies would identify the segments, and then target them with their unique marketing mixes. Agnes and Berthon (2005) posit companies can create adolescent, teenage market segments through effective advertising and positioning. Adolescents are the focus of the research because they are not fully developed; they are not yet embedded with the psychographic characteristics which enable them to be classified as a market segment (Agnes and Berthon, 2005).
The results of Agnes and Berthon’s (2005) study indicate their hypothesis to be true. Marketers can, indeed, craft their own unique adolescent market segments. Through specially designed marketing mixes, groups of adolescents can be influenced to share the same lifestyles, attitudes, values and personalities (Agnes and Berthon, 2005). The advertising will do the work for the marketer; he will not have to identify the segments.
The historical development of market segmentation is very relevant to the three articles analyzed in this paper. “Identifying Spatial Segments in International Markets” (Hofstede, Wedel, and Steenkamp, 2002) writes about spatial, geographical segmentation. Consumers in spatially adjacent and spatially associated regions are assumed to have similar cultures, beliefs, and values. This, in turn, influences their purchasing decisions to be similar. They buy the same products, based on their other similarities (Hofstede, Wedel, and Steenkamp, 2002). The spatial adjacency can be viewed in two ways: demographic and psychological. These two methods are currently employed in segmenting markets. Demographically, the consumers reside in spatially close areas, so companies can target them based on this. Psychologically, both segments of consumers share the same lifestyles, personalities and attitudes because they live in the same types of geographic regions. These spatial segmentation techniques have been developed over the past century (Hofstede, Wedel, and Steenkamp, 2002).
Another topic discussed in this paper is segmentation based on product variants. “Do Product Variants Appeal to Different Segments of Buyers Within a Category?” by Tinh, Dawes, and Lockshin (2009) describes this process. Product variants are the differences in product characteristics, such as color, shape, size and material. This is opposed to the concept of brand-based segmentation, which examines the market share of different brands in the industry, and segments the market based on this information. Product variant segmentation operates on demographic and psychographic data (Tinh, Dawes, and Lockshin, 2009). In regards to demographic analysis, the marketer evaluates the age, economic status and household size of the product variants’ customers. These are the hard facts about the consumers. The psychographic method, on the other hand, looks at the thought process of the consumers. It examines the personality and lifestyle of each different product variant’s purchasers (Tinh, Dawes, and Lockshin, 2009). This way, the market can understand the reasons behind each of the functionally different variants. Therefore, the history of both the demographic and psychographic methods’ play a vital role in product variant segmentation’s development.
“Segmenting Customer Brand Preference: Demographic Or Psychographic” (Chin Feng-Lin, 2002) discusses the topic of demographic and psychographic segmentation. It first describes the technique of demographic segmentation. This technique looks at the cold, hard facts about consumers, such as their age, gender, and economic standing (Chin Feng-Lin, 2002). However, this is not enough for a marketer to get complete picture of the market. So another idea was introduced: psychographic segmentation. This technique takes into account the mind processes of the consumer. It identifies the consumer’s lifestyle, personality and attitudes (Chin Feng-Lin, 2002). Thus, the marketer can more accurately segment the company’s market. This article mirrors the assertion of “Affecting Adolescents: Scrutinizing the Link Between Advertisers and Segmentation” (Agnes and Berthon, 2005). The segmentation techniques of psychographics and demographics are very pertinent to the psychographic segmentation technique and its development.
Literature Review
In order to properly choose a segment of the market to target, the company must consider the location of the consumer. The geographical locations of consumers can be used in a few different methods. Consumers can be segmented by country borders, or cross-nationally. If cross-national methods are used, similarities in physical or psychological characteristics can be grouped together and targeted. In their study, Hofstede, Wedel and Steenkamp (2000) identify four models of spatial segmentation.
The Spatial Independence model states segments of the market are not necessarily similar, even if they are located directly adjacent to each other geographically. This is true because physical and psychological characteristics of the consumers in the adjacent areas can be completely different. For example, take a city, such as Chicago. If a car dealership will open up in the Chicago suburbs with the goal of getting customers from the city, the suburbs, and the outlying farm towns, it cannot be able to tell only one kind of car, like a sedan. Rather, it would have to target each of the markets separately. The dealership would have to sell small, compact cars to the city dwellers; larger, more spacious SUVs to those who live in the suburbs; and heavy duty pickup trucks to the farmers. Although the three areas are located right next to each other geographically, they cannot be targeted using the same product. Therefore, the company must evaluate each area according to its own individual characteristics.
The second model proposed in the study is called the Spatial Association Model. This model takes into account the physical and psychological similarities between neighboring regions. Instead of focusing on the regions’ differences, the smile proposes similarities between the regions. According to this model, the regions do not have to be geographically next to each other; they have to share the same physical and psychological attributes. An example of the similar physical attributes is a store selling shovels in the Chicago area. As in the rest of the Midwest, the Chicago area is inundated with snow every winter. It does not matter whether the customer is in the city, the suburbs, or on a farm: he will need to buy some snow shovels. Therefore, the store does not need to differentiate between its customers; all of them can be targeted with shovels. An example of psychological similarities is the similarities between the Midwestern and the Southern United States. Residents of both these areas generally reside in small towns and farms. Their needs are for very strong cars to move machinery and perform heavy duty work. They buy themselves large, sturdy pickup trucks in order to satisfy their needs. Even though these two regions are geographically far apart, they are very similar culturally and psychologically. Therefore, marketers can target both of these two regions with the same products.
The Spatial Contiguity model asserts physical contiguity to be a good way to segment the market. When regions are located right next to each other, the model assumes that the inhabitants will have many things in common. These include a common history, dialects, language, eating habits, culture, and climate. An example of this assumption is Eastern Ukraine and Western Russia. These regions are right next are next to each other on the map, and are both characterized as being cultured, intelligent, smooth places. They share the language of Russian, as opposed to Western Ukraine, which is more mountainous, and speaks the coarser Ukrainian language, belying the tougher culture of its inhabitants. Thus, products targeted towards people in Eastern Ukraine and Western Russia would be of a more cultured, fancy nature, as these two regions are spatially contiguous.
The Countries As Segments model assumes each separate country to be its own market segment. Each country has its unique customer cultures and attitudes, according to this model. An example of this belief would be a comparison between the American and the Mexican food industries. While a restaurant chain with branches both in America and Mexico would serve meat and pizza in America, it would neglect to consider the significant immigrant Mexican population in the United States. If it would consider these consumers also, it would offer a more diverse menu including Mexican fare. However, the restaurant generalizes the majority of the American population to be white, middle-class people. Therefore, the country is treated as a segment, because the average American is stereotyped as being white.
To test the four models, the authors applied them to a store image segmentation study in Europe. Store image attributes have been linked to customer values, and have been shown to display regional differences (Kahle, 1986; Gentry, Tansuhaj, Manner, John. 1988). Different kinds of stores were analyzed, including supermarkets, convenience stores, and butcher shops. Questionnaires were sent to script panels in seven European Union countries. The survey measured product quality, service quality, assortment, pricing, store atmosphere, and distance. The results were scored on a seven-point bipolar scale.
The results of Hofstede, Wedel and Steenkamp’s study (2000) indicated that customers in separate countries have more similarities than do customers in the same country. The Spatial Contiguity and Spatial Association models are shown to be the most efficient models. The marketer must evaluate the target market based on its physical and psychological characteristics. Similarities in these characteristics are quite often present in spatially continuous regions. However, this not this is not necessarily true. Two regions can be far away geographically, but yet have the same physical or psychological characteristics, and thus can be targeted with the same tactics by a company. Therefore, spatial information is useful when crafting a product’s marketing mix.
This method applies to my internship work. BIR Training Center has the option to offer three forms of courses: in-class, online and video presentations. Our competing schools structure their courses in these three formats, so these are our options, too. In-class presentations would only be marketed towards students who live in the Chicago area. This is because only they can come to our Chicago locations on a regular basis and attend our lectures physically. This is an example of the Spatial Independence Model. The Chicago area is treated as one segment of customers; no other customers are targeted. Only people in the Chicago area can physically come to the Chicago BIR center; all other students are ruled out.
On the other hand, BIR’s online courses and video presentations would be marketed towards anybody in America, or even anyone in the world, as long as he or she speaks English. Online courses consist of an instructor speaking to students over a computer remotely, in a course structure. All the students hear his voice at the same time, and follow along in the material. Video presentations, however, can be viewed by the student at any time; all the students do not have to be listening to the instructor at the same time. What the two methods have in common is that they can be marketed towards everyone in the world, not just toward students in the Chicago area. As the students do not have to be at the BIR location physically, we can target everyone in the world.
This is an example of the Spatial Contiguity Model. The model states geographically adjacent regions to have similar history, dialects, eating habits, cultural rights, and climates. The English language is a universally-used language; in other words, everyone in the world is supposed to be familiar with it. If a Chinese and an Indian company are making a business deal, the default language for the transaction is English. Since all the countries in the world are geographically adjacent to each other, we assume all of them to share the language of English. Therefore, when BIR would market its online courses and video presentations, it would be implementing the Spatial Contiguity Model.
Another article cited in this paper analyses the topic of product variant segmentation. In their literary paper, “Do Product Variants Appeal to Different Segments of Buyers Within a Category?” Tinh, Dawes, and Lockshin (2009) aim to discover whether it is more advantageous to segment customers based on product brands or product variants. When segmenting a market, one approach is to investigate the needs, wants and preferences of customers of each of the industries’ brands. For example, a beer-selling store would examine the characteristics of people who purchase Budweiser, Miller, Coors, Heineken and other brands of beer. However, the problem with this strategy is all of brands in the same category sell the same product variants. So demographic and psychographic studies of brand segments will not reveal anything about the consumer (Tinh, Dawes, and Lockshin, 2009).
Therefore, an alternative strategy has been developed, called variant-based segmentation. According to this plan, companies will segment the market based on the product variants which customers purchase. Variants are across-brand characteristics of the products. Variants include diet verse regular drinks, product materials, product sizes, product colors, product shapes, and product qualities. (Tinh, Dawes, and Lockshin, 2009). For example, if the same beer-selling store would use product-variant segmentation methods, it would investigate the differences between consumers of six packs and twenty-four packs; between purchasers of glass bottles and plastic cans; and between purchasers of light and regular beers. This study would be conducted across all the brands in the beer industry, with the assumption they all feature the same product variants, and thus brand-based segmentation would not be helpful (Tinh, Dawes, and Lockshin, 2009).
In the past, demographic segmentation of brand preferences has been the subject of several studies. The results of the studies have been negative (Frank and Boyd, 1965; Frank and Douglas 1967; Collins, 1971; Hammond, Ehrenberg and Goodhardt, 1996; Hennedy and Ehrenberg, 2001; Fennel, Allenby, Yang and Edwards, 2003). Therefore, product variants were investigated as means of segmentation. Studies on this subject show market share to drive loyalty for variants, not the functional distinctiveness or attractiveness. According to the studies, because most consumers buy regular Coke instead of diet Coke, regular Coke’s market share is bigger than the other Coke’s variants (Tinh, Dawes, and Lockshin, 2009). When comparing the customers’ demographics to product variants’ statistics, there have been contradictory conclusions. According to a study by Singh, Hanson, and Gupta (2005), product variance cannot be tied to specific customer demographics. On the other hand, a couple of other papers (Dube, 2004; Kalyanam and Putler, 1997) state demographics do, in fact, determine product variant preferences. In this paper, Trinh, Dawes and Lockshin (2009) ask whether different product variants apply to different segments of buyers.
The researchers compared the market shares of the product variance across the different segments of consumers. Their goal was to see both the purchase presentation and the purchase frequency; in other words, they wanted to see which customer segments bought the product variants and how often they bought them. The variants examined in the study were form, pack size, pack-type, and formula. There were six product categories in the study: whiskey, instant coffee, fabric care, cooking sauces, soup and soft drinks. The data used was drawn from 1500 Households in England and was drawn from 12 months of activity. The segments of consumers examined in the study were based on demographics including age, employment status, household size, employment status and the presence or absence of children in the household (Tinh, Dawes, and Lockshin, 2009).
The researchers wanted to see the magnitude of the differences between the product variance across the different groups of consumers. To do so, they compared the highest share of each variant to the lower share crossing tracks, across the entire spectrum of demographic groups. So if 24-packs of beer would have been purchased the most frequently by people aged 21 to 30, and the least frequently by people aged 50 to 60, the researchers would compare the two numbers and analyze the difference (Tinh, Dawes, and Lockshin, 2009).
The conclusions of the researchers prove product variants to be a useful method of segmentation. Different demographic groups buy different product variants, and this is a good way for a company to segment and target their consumers (Tinh, Dawes, and Lockshin, 2009). Additionally, using the information they learned from this process, companies can develop a new variant which will target segments which have been yet been targeted by the company. Furthermore, companies can customize their products to the customers’ needs and wants. If in one area of a country, people buy more light beer, the company can sell more of this variant than of the others, in order to match the demand (Tinh, Dawes, and Lockshin, 2009).
BIR Training Center has three product variants in its options for its proposed Information Technology program. These are the in-class courses, online courses and video presentations. These correspond to the competing schools’ product variants. We segment our target market based on the ability of our customers to take our courses. For example, the in-class courses are a product variant which can be marketed towards students who live in and around Chicago. As students need to be able to physically attend courses at the Chicago location, we determine the segment of the in-class product variant to be only students in Chicago. On the other hand, our other two product variants will be marketed toward anyone in the world, as long as he or she speaks English. Because the online course participants do not have to physically be present at the BIR Chicago location, we can target students in other parts of America and the world, also. The same goes for video presentations. Thus, product variants are shown to be an effective way to segment the market (Tinh, Dawes, and Lockshin, 2009).
This is in contrast to the brand segmentation method. While students may find slight differences between companies offering Information Technology training programs, differences in variants of the programs will be more important to them. A difference between brands in this case would be an additional computer language besides the languages BIR offers. A much more important factor in the potential student’s decision is the product variants, such as online and in-class courses. For example, if a student in Mexico wants to learn Information Technology, he will want to take online classes or watch instructional videos. He will care more about this variant of the program than about learning an extra computer programming language. If he can take the online program, he will not have to worry about paying for a flight, getting a visa or arranging his living arrangements in Chicago. It will be very convenient for him to take online courses on his computer. Therefore, product variants are very important in the segmentation process, more than brand-based segmentation is (Tinh, Dawes, and Lockshin, 2009).
In comparison to “Identifying Spatial Segments in International Markets” (Hofstede, Wedel, and Steenkamp, 2002), “Do Product Variants Appeal to Different Segments of Buyers Within a Category?” (Trinh, Dawes, and Lockshin, 2009) discusses a completely separate topic. “Identifying Spatial Segments in International Markets” (Hofstede, Wedel, and Steenkamp, 2002) is about spatial and geographic segmentation. “Do Product Variants Appeal to Different Segments of Buyers Within a Category?” (Trinh, Dawes and Lockshin, 2009) is about segmentation based upon product variants. When segmenting based on spatial and geographic methods, the proximity of regions is taken into account. When regions are geographically, physically to close each other, the likelihood of similarities in consumers’ product choices increases. Marketers can use this likelihood to segment similar regions together and develop marketing methods for those segments (Hofstede, Wedel, and Steenkamp, 2002). On the other hand, product variant-based segmentation has nothing to do with geographics. When looking at statistics of consumers’ purchases of different product variants, the marketer aims to identify the functional differences between the variants. Each variant performs a different function; this is the real reason why the consumer buys the variant (Trinh, Dawes and Lockshin, 2009). Therefore, there is no connection between spatial and variant-based segmentation. Only in a case such as mine at BIR Training Center, where the two topics intersect, there can be a connection.
The third article analyzed in this study discusses the demographic and psychographic methods of segmentation. In his article “Segmenting Customer Brand Preference: Demographic Or Psychographic,” Chin Feng-Lin (2002) attempts to show both demographic and psychographic methods can be used to segment a company’s market. Consumers are segmented into different groups based on variables they exhibit. These variables can themselves be put in two distinct categories: demographic and psychographic. Demographic variables focus on the hard, cold facts about the person: his/her age, gender and monthly income (Chin Feng-Lin, 2002). However, demographic statistics might reveal very little about the true nature of the consumer, as customers within the same demographic group can have very different personalities.
Therefore, Kotler introduced the idea of psychographic variables in 1997. There are two systems which measure psychographic characteristics; these are called the VALS2 (values and lifestyles) and the LOV (list of values) systems. These gauge the lifestyle and personality of the customer, thus predicting on a more realistic basis the type of product he/she would buy. Because customers buy those products which will fit their ideal lifestyle, retailers can segment the market, pinpointing their target market and matching their marketing mix to the customer’s desires (Kotler, 1997). A hybrid technique soon formed, called the multi-segmenting method. It combines both of the two primary techniques into an inclusive approach which gives the marketer a complete scope of all the factors which go into the consumer’s decision. Accordingly, the marketers can more accurately pick out the customers at whom they will direct their marketing mixes (Lin Ching-Feng, 2002).
In order to test out whether segmentation is best achieved through the demographic method or the psychographic technique, Chin-Feng Lin (2002) devised a study using VALS2 and LOV as the theoretical bases. A thousand questionnaires were given out, with only 707 actually being completed. The questionnaires spanned three sub-topics. The first set of questions measured the respondent’s degree of agreeability – from one to five on the Likert scale. These questions related to the consumers’ personality, consumption, personal values, lifestyle and personality. This set of questions was designed, in effect, to measure the thought-processes of the consumers – their inner reasons for buying the products (Chin Feng-Lin, 2002). The second set of questions concerned the demographics of the consumers surveyed. This assessed the cold, hard facts about the people, such as gender, age, level of education and monthly family income; it did not take into consideration the underlying reasons for the buyers’ decisions (Chin Feng-Lin, 2002). Finally, the third set of questions concerned the customers’ brand preferences for different brands of various items. To analyze the data, the researcher used mean analysis, analysis of variables (ANOVA), factor analysis (Varimax Method) and cluster analysis (K-means of Non-Hierarchal Method) (Chin Feng-Lin, 2002).
Lin Chin-Feng (2002) hypothesized in order to best segment the target market for itself, the retailer must employ the multi-segmenting method. It combines both the demographic and the psychographic techniques into one all-encompassing method. It is not enough to just have the cold, hard facts about the consumer; the marketer must know what is going through his/her mind as he/she makes the decision to buy the product. Thus, the marketer can more accurately tailor the marketing mix to those people who he envisions buying the product, based on his idea of the ideal customer (Lin Ching-Feng, 2002).
Indeed, the results of Lin’s study confirmed his hypothesis to be correct. Although there is some value to the demographics of the target market, the marketer must take into account the deeper reasons for the consumers’ purchasing habits. Yes, the consumer might indeed be buying a certain brand of dress shirt because he is male, fifty-five years old, white and semi-retired. However, this also might not be the reason why he is buying this particular brand of shirt. He may think it fits his lifestyle more than other shirts in its category, and it goes well with his self-image. Thus, a marketer must use the multi-segmenting technique in order to pick out the target market to whom he will be gearing his marketing mix (Lin Ching-Feng, 2002).
The assertions stated in “Segmenting Customer Brand Preference: Demographic or Psychographic” (Ching-Fen, 2002) apply to my internship work at BIR Training Center. Both the subjects of demographic and psychographic segmentation play important roles in identifying my school’s target market.
The demographic method of segmentation looks at the hard facts about certain groups of customers, such as age, gender, job status and race. Based on this info, the company can identify its target market. At BIR Training Center, I looked at my competing schools’ websites and investigated their target markets. I segmented the market into high school graduates, career changers, current computer programmers who want to update their skills, current military members, military veterans, and international students. These were our competing schools’ target markets, so I assumed them to be our targets, also. Demographics played an important part in this process. Each of the consumer descriptors I have listed as a separate market is a demographic - it is a fact about the person. It does not tell the marketer anything about the mind processes of the person. It just tells him cold, hard facts about him or her.
The psychographic method is also applicable to my internship research. The method analyzes the thought processes behind the customers’ purchases. It examines the customers’ personality and lifestyle choices. Based on these insights, the marketer can tailor his company's marketing mix toward specific kinds of personalities. At BIR Training Center, I looked at my competing schools’ websites and investigated their target markets. I segmented the market into high school graduates, career changers, current computer programmers who want to update their skills, current military members, military veterans, and international students. If examined in a different light, these segments can be psychographic markers, not demographic statistics. For example, the segment of international students is just a group of people who live outside America, according to the demographic method. Alternatively, when examined from a psychographic standpoint, the international students may come from Asia or Russia, implying they are very smart, so this is a very good market to target for our information technology training programs. Or they can come from a violence-ravaged country, such as Mexico or Iraq. In this case, they may need help recovering from their trauma, and will need extra assistance with the material in class. This would make them a less advantageous market to target. Therefore, psychographic segmentation techniques are very useful in segmenting BIR’s market.
When comparing “Identifying Spatial Segments in International Markets” (Hofstede, Wedel, and Steenkamp, 2002) to “Segmenting Customer Brand Preference: Demographic or Psychographic” (Ching-Fen), the two discussed subjects do indeed intersect. “Identifying Spatial Segments in International Markets” (Hofstede, Wedel, and Steenkamp, 2002) discusses the topic of geographic, spatial segmentation. Consumers in spatially adjacent regions tend to have similar product choices because of shared beliefs, cultures, languages and climates. Therefore, marketers can group these people together and target them with the same products. Demographic and psychographic segmentation, the topics discussed in “Segmenting Customer Brand Preference: Demographic or Psychographic” (Ching-Fen), can be applied to spatial segmentation.
Demographic segmentation is part of the process of geographic segmentation. When evaluating two regions, the marketer must look at the types of people inhabiting it. Then he can craft his marketing mix towards people in similar places. For example, an automobile seller targeting people in both the Southern and Midwestern United States will find SUVs and pickup trucks to be more effective than sedans and coupes. From a demographic viewpoint, the reason is because the residents of these two regions are white, lower middle-class or upper lower-class people who live on farms and small towns. They need sturdy machines which can give them the power they require to do heavy duty work.
The topic of psychographic segmentation is also very applicable to geographic segmentation. This is because when evaluating the product choices of people in specific geographic areas, it is imperative to find out for their underlying reasons for buying their products. This is accomplished through psychographic segmentation. Take the aforementioned example. In both the Southern and Midwestern United Sates, people buy pickup trucks. At the surface-from a demographic standpoint-they do so because they need powerful machines to do farm work. However, according to the psychographic segmentation method, a deeper reason is behind it. Small-town residents and farmers are tough people. They want to project and reinforce this image by buying big cars. They state to the world their Macho-Man attitudes with their jacked-up trucks.
Another example of demographic segmentation is of Chicago's sports teams. Each of them has a different target market, usually split between the North and South Sides of Chicago. The Chicago Cubs targets its native, mostly white, middle-class North Side crowd. These people flock to Wrigley Field, the Cubs’ stadium, without fail, even if the Cubs are the worst team in baseball. The Chicago White Sox are Chicago's other baseball team. Even though the White Sox's ballpark is located on the mostly black South Side, they attract a white fan base. Middle class, white residents of the Hyde Park, Jackson Park, Kenwood and Beverly neighborhoods are their largest segment of customers. The Chicago Blackhawks are located on the South Side, too. And just like the White Sox, they attract a white crowd. This is because they are the only hockey team; white people from the North Side want to see their hockey. The Chicago Bulls, whose stadium is on the South Side, attracts a black fan base. Finally, the Chicago Fire attracts an immigrant crowd.
When analyzing Chicago sports teams’ target markets from a psychographic perspective, they are very logical. The sport of baseball has been historically a white sport, and is considered an American pastime. In this case, Americans are stereotyped as being white, middle-class people. The Chicago Cubs, located on the mostly white North Side of Chicago, accordingly attract a wide crowd. And contrary to intuition, even though Chicago's South Side is 93% black (wikipedia.com) the White Sox still get a largely white crowd. Again, this is because baseball generally attracts a white crowd. The same goes for the Chicago Blackhawks. Hockey is a white sport; that is why the Hawks target white fans. The Bulls, though, have a black following on their native South Side. This makes sense, as basketball has been dominated by black star players since the 1960s. As the South Side of Chicago is 93% black (Wikipedia.com), they automatically patronize the Bulls games. African-Americans look to basketball players of their race as heroes. They see them as a way to get out of the inner city and get a living. Therefore, they go to the pro basketball games. The Chicago Fire are popular among Chicago area immigrants. The psychographic reason for this is because of this because the sport of soccer is more popular internationally than it is among Americans, so it make sense for immigrants from other countries to patronize the Fire’s stadium. Soccer reminds people of their former lives, so it is a form of nostalgia.
In comparison to “Do Product Variants Appeal to Different Segments of Buyers Within a Category?” (Trinh, Dawes, and Lockshin, 2009), the topics discussed in “Segmenting Customer Brand Preference: Demographic Or Psychographic,” (Chin Feng-Lin, 2002) overlap. Demographics and psychographics are instrumental when segmenting a market based on product variants.
Product variants are different because of product characteristics within each brand. Examples of this include product size, weight, color and package type. In deciding on how to target a market with different product variables, the marketer must look at his market’s demographics. Based on these statistics, he can make an educated decision. This is opposed to the brand-based segmentation method. For instance, Sprint, AT&T and Verizon all offer both phones and smartphones. Therefore, there is little difference between the brands. However, each company targets different customers with the product variants (flip phones and smartphones). Flip phones are targeted towards older people; the smart phones are targeted towards young and middle-aged people. Therefore, demographics are very important in analyzing product variants.
Psychographic variables are also essential in evaluating reasons for product variants’ purchasers. Psychographic variables examine the underlying reasons for the consumers purchases, based on their lifestyles and personalities. This can be applied to their purchases of certain product variables. For example, when a phone company such as Sprint, AT&T or Verizon targets their smart phone towards old people, there is an underlying reason. This is because old people have not been accustomed to using phones with all of their applications. They only need a simple phone for calls; they are not technologically advanced. They leave the complex stuff to their young children and grandchildren.
On the other hand, phone companies target their advanced smart phones towards a young crowd - from 50 years old and younger. The psychological reason for this is the current era is a technologically advanced one. There is a mobile application for everything and anything you need. People born into this generation pick up smartphone use much more quickly than new people who are born when cell phones did not even exist. This is why young people are targeted with the smartphone variant
Areas of Future Research
“Identifying Spatial Segments in International Markets” (Hofstede, Wedel, and Steenkamp, 2002) concludes the Spatial Association and Spatial Contiguity models to be the correct models for people in similar geographic regions to have similar cultures, eating habits, and beliefs. Therefore, the consumers inhabiting these regions will purchase the same products. The study proved this to be true by examining seven nations in Europe. European countries have very developed cultures. They have long histories of settlement and cultural development. Therefore, different sections of Europe will have similar cultures, based on shared climates and beliefs.
Future research should focus on less-developed places, such as America. Compared with Europe, the United States has a relatively short history, because it has existed for a shorter period of time. Therefore, its cultural rights are not so firm in its different sections. Future studies on this continent might reveal the Spatial Independence Model or the Countries-As Segments Model to be true (Hofstede, Wedel, and Steenkamp, 2002).
Some other factors which might alter the results of the study are different products and services, and more elaborate measurement instruments. This study was performed on meat departments in supermarkets, convenience stores and grocery shops. If different products were tested, the results might be different (Hofstede, Wedel, and Steenkamp, 2002). Similarly, this study examined the store image attributes of price quality, service quality, assortment, store atmosphere, and distance. If Hofstede, Wedel, and Steenkamp had examined other store image attributes, the results might indicate other spatial models to be correct (Hofstede, Wedel, and Steenkamp, 2002).
“Do Product Variants Appeal to Different Segments of Buyers Within a Category?” (Tinh, Dawes, and Lockshin, 2009) proves product variants to be an effective method of segmentation - even better than brand segmentation. Product variants are specific characteristics offered within each brand. Included in this category are product size, shape, color, weight, and flavor. These product variants are offered by each brand of a product. This makes product variant segmentation more effective than brand-based segmentation. Each brand offers the same variants; however, the marketer can differentiate between separate product variants within the brands. Tinh, Dawes, and Lockshin’s study proved this assertion to be true. However, there are a couple extra variables which need to be examined. These may refute the assumption product variants are a good basis for segmentation.
The first area of future research in regards to product variants is using individual data, as opposed to household data. In the Tinh, Dawes, and Lockshin’s study, household data was examined. This identified each household as being a member of the study. It did not take into account the differing product choices of the husband, wife and children. If the individual purchase data would be analyzed, the results might be even stronger in favor of product variant segmentation. On the other hand, it might swing in the other direction - towards brand based segmentation (Tinh, Dawes, and Lockshin, 2009).
Another topic of future research regarding product variants is the number of demographic variables analyzed at the same time. In this study, five demographic variables are examined. These include age, employment status, social class, household size, and the presence or absence of children in the household (Tinh, Dawes, and Lockshin, 2009). These variables were examined individually. However, further research might reveal different results if two or more variables are examined at the same time in a multivariate analysis (Tinh, Dawes, and Lockshin, 2009).
In “Segmenting Customer Brand Preference: Demographic or Psychographic” (Chin Feng-Lin, 2002), demographics and psychographics are proven to be effective segmentation methods. Demographics identify the outer facts about a person; psychographics examine his inner thought processes which influence his purchases. Combined, these two methods paint a complete picture of the consumer’s product choices (Chin Feng-Lin, 2002).
The systems used for segmentation variables are the List of Variables (LOV) and the Values and Lifestyles (VALS2). The LOV system is a scale developed by Kahle (1986) to discuss marketers’ norms. Included in this system are eight groups: self-respect, security, warm relationships with others, sense of accomplishment, being well-respected, sense of belonging, enjoyment of life and self-orientation and resources (Schiffman and Konnuk, 1994).
The other system used is the VALS2 typology (Kotler, 1997; London and Della Bitta, 1993; Kotler and Armstrong, 1999). This is a psychological system which classifies customers into eight groups. These include fulfilled, believers, achievers, strivers, experiencers, makers, actualizers, and strugglers (London and Della Bitta, 1993).
There is another classification system which Chin Feng-Lin did not use. This system is called the Rokeach Value Survey (RVS) (Rokeach, 1973). It consists of eighteen terminal values and eighteen instrumental values. The terminal values include true friendship, mature love, self-respect, happiness, inner harmony, equality, freedom, pleasure, social recognition, wisdom, salvation, family security, national security, a sense of accomplishment, a world of beauty, a world at peace, a comfortable life, and an exciting life. The instrumental values include cheerfulness, ambition, love, cleanliness, self-control, capability, courage, politeness, honesty, imagination, independence, intellect, broad-mindedness, logic, obedience, helpfulness, responsibility, and forgiveness. In future research on psychographics and demographics, marketers would use the RVS system instead of the LOV and VALS2 methods (Chin Feng-Lin, 2002). This might alter the results of the study. Alternatively, the results might be reinforced and strengthened by the new findings.
Bibliography
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