14 Reading: Segmentation Criteria and Approaches

Table 1. Common Market Segmentation Approaches

Demographic Segmentation

Demographics are statistical data that describe various characteristics of a population. Demographic segmentation consists of dividing the market into groups based on demographic variables such as age, gender, family size, income, occupation, education, religion, ethnicity, and nationality. Demographic segmentation variables are among the most popular bases for segmenting customer groups because demographic data are plentiful and customer wants and needs often link closely to these variables.

For example, the youth market (roughly ages five to thirteen) not only influences how their parents spend money, but also how they make purchases of their own. Manufacturers of products such as toys, records, snack foods, and video games have designed promotional efforts directed at this group. “Tweens” are children between the ages of eight and twelve who are discovering what it means to be a consumer and are shaping the attitudes and brand perceptions they will carry with them as they grow up and gain more purchasing power.  The elderly market (age sixty-five and over) has grown in importance for producers of products such as low-cost housing, cruises, hobbies, and health care.

Life stage is another demographic trait associated with age, gender, marital, and family status. There is evidence that individuals and families go through predictable behavioral patterns associated with buying behaviors. For example, a young couple with one young child has far different purchasing needs than empty-nesters in their late fifties or single, middle-aged professionals.^[1]

Income is perhaps the most common demographic basis for segmenting a market because it indicates who can or cannot afford a particular product. It is quite reasonable, for example, to assume that individuals earning minimum wage could not easily purchase a $80,000 sports car. Income is particularly useful as a segmentation input as the price tag for a product increases. It can also be helpful in understanding certain types of buying behavior, such which income groups are most prone to use coupons.

Similarly, other demographic characteristics can influence other types of consumer activities.

Despite the apparent advantages of demographic segmentation (i.e., low cost and ease of implementation), uncertainty exists about its effectiveness. The method can be misused. For example, it might be said that the typical consumer of Thai food is under thirty-five years of age, has a college education, earns more than $10,000 a year, lives in a suburban fringe of a moderate-size urban community, and resides in the West. While these characteristics may describe a typical consumer of Thai food, they also describe many other consumers and may paint an overly broad or inaccurate portrait of a supposed “segment.” When a segment is too broad, it loses its defining characteristics and there isn’t much to differentiate the target segment from the general population. In this situation, the segmentation approach does not provide much useful guidance to help marketers make effective marketing choices.

Psychographic Segmentation

In psychographic segmentation, consumers are divided according to common characteristics in their lifestyle, personality, attitudes, and social class. Evidence suggests that attitudes of prospective buyers toward certain products influence their subsequent purchase or nonpurchase of them. If persons with similar attitudes can be isolated, they represent an important psychological segment. Attitudes can be defined as predispositions to behave in certain ways in response to given stimulus.^[2]

For market segmentation purposes, personality is defined as long-lasting characteristics and behaviors of a person that shape how they cope and respond to their environment. Consumption of particular products or brands relates to consumer personality. For example, risk-seeking individuals are attracted to extreme sports and travel, and extroverts tend to dress conspicuously.

Social class segmentation identifies individuals based on a combination of socioeconomic such as education, occupation, income, family background, and attitudes related to these factors.

Lifestyle segmentation refers to the orientation that an individual or a group has toward consuming products, work, and play and can be defined as a pattern of attitudes, interests, and opinions held by a person. Lifestyle segmentation has become very popular with marketers, because of the availability of consumer data, measurement devices and instruments, and the intuitive categories that result from this process.^[3] As a result, producers target versions of their products and their promotions to various lifestyle segments. For example, U.S. companies like All State Insurance are designing special programs for the good driver, who has been extensively characterized through a lifestyle segmentation approach.^[4]

Lifestyle analysis generally begins by asking questions about the consumer’s activities, interests, and opinions. If a woman earns $100,000–$150,000 per year as an executive, is married and has two children, what does she think of her roles as a professional, a wife, and a mother? How does she spend her spare time? To what groups does she belong? What does she read? How does she use electronic devices? What brands does she prefer, and why? AIO (activities, interests, opinions) inventories, as they are called, reveal vast amounts of information concerning attitudes toward product categories, brands within product categories, and user and non-user characteristics.

Overall, psychographic segmentation tends to focus on how people spend their money; their patterns of work and leisure; their major interests; and their opinions of social and political issues, institutions, and themselves. While it can create intuitive groupings and useful insights into consumer behavior, it can also take significant research and effort to inform a more complex and nuanced approach to defining market segments.

Behavioral Segmentation

Consumers are divided into groups according to common behaviors they share. Typically these behaviors link to their knowledge of, attitude toward, use of, or response to a product.

The most common type of behavioral segmentation is around user segments. In 1964, the market researcher Twedt made one of the earliest departures from demographic segmentation when he suggested that the heavy user, or frequent consumer, was an important basis for segmentation. He proposed that consumption of a product should be measured directly to determine usage levels, and that promotion should be aimed directly at the heavy user. This approach has since become very popular. Considerable research has been conducted on “heavy users” of a variety of products. The results suggest that finding other characteristics that correlate with usage rate often greatly enhances marketing efforts.^[5]

Other behavioral bases for market segmentation include the following:

• User status: Looking beyond “heavy users,” it can also be helpful to identify segments based on a broader set of use patterns, such as non-users versus ex-users, or one-time users versus regular users. Mobile phone service providers examine usage patterns to create optimal plans and targeting based on specific sets of user needs: family plans, individual plans, no contract plans, unlimited talk and data plans, and so forth. New car producers have become very sensitive to the need to provide new car buyers with a great deal of supportive information after the sale in order to minimize unhappiness after the purchase.

• Purchase occasion: This approach tries to determine the reason or occasion for purchasing a product and how it will be used. For example, airlines typically segment customers based on the reason for a passenger’s trip: business versus personal travel. Someone traveling for business generally has different needs and wants from someone traveling for pleasure. A business traveler tends to be less sensitive about price and more focused on timing, location, and convenience.
• Loyalty: This approach places consumers in loyalty categories based on their purchase patterns of particular brands. A key category is the brand-loyal consumer. Companies have assumed that if they can identify individuals who are brand loyal to their brand, and then delineate other characteristics these people have in common, they will locate the ideal target market. There is still a great deal of uncertainty about the most reliable way of measuring brand loyalty.
• Readiness: Readiness segmentation proposes that potential customers can be segmented according to how ready they are to purchase a product: unaware, aware, informed, interested, desirous, and intend to buy. Using this approach, a marketing manager can design the appropriate market strategy to move them through the various stages of readiness. These stages of readiness are rather vague and difficult to measure accurately, but readiness may be a useful lens for understanding the customer’s mindset and how to nudge them toward buying, particularly when an education process is required prior to purchase.

Combining Multiple Bases for Segmentation

Marketers may find it most useful to combine different bases for segmentation in order to create a richer picture of their target market. For example, a “geo-cluster” approach combines demographic data with geographic data to create a more accurate profile of a specific consumer. Geographic data combined with behavioral data can point companies toward locations where customers are clustered who demonstrate behaviors that make them a good target for a company’s product. Overlaying demographic data onto lifestyle or behavioral segments helps marketers understand more about their target customers and how to reach them effectively with the marketing mix.

Any of these approaches may be the “right” approach for a given company and product set. It is also important for marketers to continually evaluate what’s happening in their target market and to adjust their segmentation approach as customer attitudes, behaviors, and other market dynamics evolve.

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