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International Journal of
Market Research

Vol. 45, No. 3, 2003

15 Northburgh Street, London, EC1V 0JR, UK
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Benefit Segmentation

A potentially useful technique of segmenting and targeting older consumers

Rizal Ahmad
The University of Kent at Canterbury


The number and proportion of older people in the United Kingdom is growing. The proportion of those who are 50 years old or over is expected to grow from 30% (20 million) in 2001 to 33% (22 million) by 2011 and to 37% (25 million) of UK's total population by 2021 (Office for National Statistics, 1999). The result of the 2001 census shows that older people (people aged 60 and over) outnumbered children (below the age of 16) by about half a million, with certain parts of the country – notably Scotland – actually experiencing a long term negative growth in population (Office for National Statistics, 2002a). But while the population of the UK and most economically developed countries may be ageing, older people are also consumers offering new market opportunities.

Current studies on older people have centred on health care service and delivery and on social policy, and researchers from those areas of research continue to dominate the debate (Harper, 2000). But changes in the demographics of the population have encouraged other researchers to take a greater interest in studying older people, particularly from the marketing perspective.

Authors generally agree that the UK's older consumer market is attractive, in terms of numbers and spending power, and that it is heterogeneous (Long, 1998; Ahmad, 2002). They, however, have not found classifications or segments of older consumers that may be generalised in the context of the UK's society. Clearly, for the purpose of marketing of consumer products, segmenting the UK's older consumer market into actionable segments that can be targeted with specific products and services and that allow effective positioning of selected products or services, is the basic step that marketers need to take.

This article reviews the traditional method of segmenting consumers, which emphasises the use of personal characteristics. We then discuss the theory of benefit market segmentation and examine its utility. Following that, we illustrate how benefit segmentation technique may, in practice, be used for segmenting older consumers in shopping for groceries. Finally, we discuss the implications of this article for practice and further research. The objective of this article is to propose the use of benefit segmentation technique for segmenting and targeting UK's older consumers.

Literature review

Market segmentation

Smith (1956, p.5) defined market segmentation as 'viewing a heterogeneous market as a number of smaller homogeneous markets, in response to differing preferences, attributable to the desires of consumers for more precise satisfaction of their varying wants'. Kotler et al. (1999, p.379) defined market segmentation as 'dividing a market into distinct groups of buyers with different needs, characteristics or behaviours, who might require separate products or marketing mixes', and Dibb et al. (2001, p.206) defined it as 'a process of grouping customers in markets with some heterogeneity into smaller, more similar or homogeneous segments; the identification of target customer groups in which customers are aggregated into groups with similar requirements and buying characteristics'. Tonks and Farr (2000) regarded it as 'a process of aggregating or disaggregating which seeks to identify groups of individuals such that within group differences are minimised and between–group differences are maximised'.

The justification for segmenting consumers on the basis of similarity of their characteristics or segmentation variables is that consumers who share similar characteristics will share similar wants, needs, and attitudes towards marketing stimuli. Consumers belonging to a particular segment can be expected to react in the similar and predictable manner to a particular stimulus, such as a price discount. In addition, Frank et al. (1972) argue that some parts of the market can be discriminated against in terms of the prices they can bear and when this occurs, it offers opportunities for profit maximisation. Some quality–conscious and hedonistic consumers, for example, do not mind paying higher prices for goods and services in return for complete personal satisfaction.

The objective of a business, however, is not merely to satisfy consumers' wants but also to provide returns to its shareholders. For a group of consumers to qualify as a market segment, it must satisfy basic qualifying criteria or measures of validity that include elements such as measurability, identifiability, accessibility, substantiality, actionability, stability, responsiveness and profitability (Frank et al. 1972; Loudon & Della Bitta 1984; Kotler 1984, 1988; Baker 1988; Webster 1991). In other words, a market segment should be identifiable, meaning that it can be targeted (with products, services or market offerings); measurable, in terms of size or attractiveness; it can be reached and served with various stimuli and/or marketing programmes, and be realistic, stable and sufficiently cost–effective for a firm to invest in various marketing activities, from product development to the provision of after–sales support.

Marketers, by and large, use the traditional approach of using demographic, socio–economic, and psychographical variables. In a review of 33 methods of segmenting the mature market, Bone (1991) found that chronological age was the most common method, besides the use of discretionary income, health, activity level, discretionary time, and response to others. Marketers find observable socio–economic and demographical data attractive to use because they, generally, are easy to obtain, understand and apply. Socio–economic and demographical data, however, only explain discriminatory factors at a general level, which largely concern consumer bases: for example, the married man whose annual income is more than £50,000. This type of information lacks richness and often has to be supplemented with other data that are able to provide a clearer picture of target groups: for example, psychographical data. Antonides and Raaij (1998, p. 550) called the traditional method of using only demographical and socio–economic data a backward type of segmentation analysis, which categorises consumers a priori.

A group of consumers may share similar personal characteristics, while their purchase and use behaviour is more variable. Two, married, 50–year–old men, living in the same neighbourhood, who both have an annual income of about £50,000, can be two very different consumers. One of them might be more homely than the other, enjoying home–cooked meals rather than restaurants, having strong opinions about the sanctity of marriage, while preferring to have fewer children. In this case the use of psychographical data in terms of their interests and opinions, will enable marketers to segregate two people, identical in terms of demographic and socio–economic variables, into two different consumers with distinctively different consumption behaviour.

With the use of psychographical data, researchers had been able to segregate consumers into a number of lifecycle and lifestyle groups. Wells and Gubar (1966) produced nine linear stages of a lifecycle and six of them, namely the full nest (1), full nest (2), full nest (3), empty nest (1), empty nest (2), and sole survivor, can be associated with the older consumer. Value and lifestyle 1 – or VAL–1 – classifies American consumers into nine types of lifestyle (Mitchell, 1983), while VAL–2 classifies American consumers into eight types of lifestyle (Riche, 1989). Lifestyle classification, however, is somewhat complex, harder to understand and apply. In order to arrive at a classification of lifestyle, researchers have to conduct empirical research on consumers and capture psychographical data. Researchers then make inferences about the consumption and buying behaviour of consumers based on commonly shared person variables, predominantly in terms of values and lifestyle scores patterns. Married people with children, for example, like to spend more time at home. They own home entertainment products, have a fully equipped kitchen and enjoy home cooked meals.

In the most recent attempt to segment older consumers, George P. Moschis used both gerontological and psychographical variables (together known as gerontographical variables) on older people to produce a lifestage segmentation model comprising of healthy indulgers, healthy hermits, ailing outgoers, and frail recluses (Moschis 1996). The segmentation model proposed by Moschis is also known as the gerontographics model, which basically acknowledges individual differences in the ageing process as well as differences in the type of ageing that occurs in later life (Moschis 1996, p.61). The approach taps into a person's biophysical and social circumstances in life and the key life events that are likely to contribute to the older person's ageing process.

The traditional method of segmenting consumers that we have explained emphasises the use of personal characteristics comprising demographical, socio–economic and psychographical data as independent variables. While the demographical and socio–economic data are useful for the purpose of identifying the size, judging the attractiveness, and accessing or contacting a group of consumers, psychographical data are more useful for the purpose of predicting consumption and/or buying behaviour. Psychographical segmentation is concerned with the study and classification of people according to their attitudes, interests and opinions. It, according to Dorney (1971) and Peterson (1972), also refers to a study that emphasises the use of generalised personality traits to provide meaningful marketing information; a study that can help to describe existing markets in terms of more than just statistics but rather, through personal traits, in the form of human portraits.

There is no common agreement among authors on the definition of the term 'psychographics' and what constitutes this type of variable. Psychographical data are sometimes used interchangeably with lifestyle data (González and Bello, 2002) and product attributes/benefits are sometimes categorised as psychographical data (for example, see Johns & Gyimóthy 2002; Ailawadi et al. 2001). In this article, psychographical data, based on Antonides and Raaij (1998, p. 554), are taken to comprise attitudes, interests and opinions, which are not directly related to specific product characteristics. Attitudes, according to Antonides and Raaij (1998, p.197), are 'the individual predispositions to evaluate an object or an aspect of the world in a favourable or unfavourable manner'. Attitudes relate to the global notion of the product: for example, attitudes towards healthy and low fat foods. Interests, according to Antonides and Raaij (1998, p.378), imply preferences regarding the consumption of time, and are the determinants of lifestyle. For example, interests on sports and fashion, rather than a liking for a specific brand of sports wear. Opinions, according to Antonides and Raaij (1998, p.379) relate to phenomena, issues, persons, products, firms, government, politicians, countries, shops, newspapers and magazines.

Psychographical variables, however, do have a number of limitations.

Limitations of psychographical variables

Although psychographical data, such as those relating to values and norms, generally remain stable over a long period of time, other data, such as those relating to individual interests and opinions on specific issues (for example, politics), tend to change over time. Researchers have also found that psychographical data do not have a strong explanatory power. Kassarjian (1971), for instance, in a review on personality and consumer behaviour, found that general personality variables are able to explain only a low percentage (at most 10%) of behavioural differences, such as in choosing brands.

At a general or global level, psychographical characteristics comprise a wide range of data, meaning that it is impractical to capture all of them. An alternative methodology is to segment consumers based on, among other things, the psychographical data that are specific to a particular consumption situation and/or a set of consumption behaviours that have a common goal (such as shopping). Van Raaij and Verhallen (1994) called this 'domain–specific' market segmentation, which they argued is related to the consequences of using particular products or services. At this 'domain–specific' level, the use of socio–economic and demographical data is neither too general, as in grouping consumers a priori, nor too restrictive and confining, as in choosing a specific brand of product or service.

The technique to segment older consumers that we propose is benefit segmentation.

Benefit segmentation

According to Haley (1968), the benefits that people are seeking in consuming a given product are the basic reasons for the existence of true market segments. As an illustration, Ms Smith is a healthy, 60–year–old lady and a pensioner, who cycles, rather than drives, to keep fit, and buys organic foods for their perceived health benefits. She is not an environmentalist and her main reason for not driving was not because she wants to avoid polluting the environment with CO2, but to be fit and healthy. The benefits that she seeks from her shopping are likely to be a wide choice of 'healthy foods' and advice on fitness training. An ample parking space and free home delivery will not be of benefit to her. Benefits sought are manifestations of both consumer requirements (needs and/or wants) and the value that consumers such as Ms Smith are willing to pay in return for the sacrifices that they are willing to make.

Benefit segmentation is a technique that segments customers on the basis of desired or sought benefits. These benefits, when they are present as attributes of a product, service or market offering, cause consumers to purchase those products, rather than merely describe who they are as consumers in terms of socio–economic, demographical or psychographical data. Benefit segmentation offers more utility than the traditional methods because it explains the reasons why consumers choose to buy or prefer particular products, or patronise particular suppliers or providers of services.

Segments of consumers, in terms of benefits they seek, are established as an ex–post rather than an a priori theory of consumption and/or buying behaviour. A marketer no longer has to guess which stimulus might induce consumers to try or buy a particular product. If a grocer knows older customers seek worry–free shopping for healthy produce, that grocer can expect older customers to visit the grocery when the factors that worry them have been removed, and the presence of desired benefits has been communicated to them. A grocer that offers 'worry–free shopping for healthy produce', among other benefits, will attract consumers who seek healthy produce regardless of its country of origin and high price, as long as the quality of that produce is credible and guaranteed. Healthy food shoppers may not necessarily be those who belong to social grade 'A', 'empty nest' life stage, or a particular age bracket.

In re–examining the utility offered by benefit segmentation method, Haley (1984) considered it as a useful approach in running two models of advertising process. The first model is about convincing people that a particular brand is superior by delivering or communicating its cognitive benefits. The second model is about making a brand more salient and therefore more likely to be purchased by emphasising its cognitive benefits. In the travel industry, a no–frills airline could convince consumers of the superiority of its brand by communicating the benefits of much lower fares when tickets are purchased in advance, a higher level of safety as a result of using newer aircraft of less than five years old, and the benefit of its punctuality in departures, if it has a good record to show. In making the brand more salient the airline could point out the overriding benefit that its fares, on similar routes, are half the price charged by scheduled airlines.

Although the usefulness of benefit segmentation is well established in the literature (among others see Haley 1984; Tynan & Drayton 1987; Loker & Purde 1992), the use of benefit segmentation to segment older consumers in any particular product markets has not been reported. In the next sections we illustrate how benefit segmentation may be used to segment older consumers in the context of shopping for groceries and in purchasing vacations or holiday breaks.

Why grocery retailing and vacations?

Groceries are basic daily needs of everyone. In the UK, household expenditure on food and non–alcoholic drinks among households where the head of household is aged between 50 and 64 years old accounts for their largest weekly expenditure at an average £65.70 (Office for National Statistics 2002b, p. 44). Grocery retailing has also been the subject of many studies and its significance to older people has been debated (among others see Goodwin & McElwee 1999; Hare et al. 1999; Hare et al. 2001). Extending the knowledge of the benefits that the UK's older people seek from shopping for groceries would be useful in order to provide a deeper understanding on the determinants of older consumers' buying behaviour. Such knowledge would provide marketing ideas for managers of grocery shops, including supermarkets.

We identify vacations or holiday breaks markets as another product market because older people are significant spenders on vacations. British residents aged 45 and over made a total of 22.8 million overseas visits in 2000 and on average spent £443.50 per person per visit (Office for National Statistics 2001, p.51 and p.125). Since 65% (14.8 million) of all overseas visits are for holiday purposes the total value of overseas holidays of older people is estimated to be more than £6.5 billion. In addition, according to the Office for National Statistics (2002b, p. 44), weekly spending on leisure services comes third after food and non–alcoholic drinks and motoring among households where the head of the household is aged between 50 and 64 years old. This works out at an average of £54.90 a week (that is almost £3,000 per year per household). Extending the knowledge of the benefits UK's older people seek from going on holiday would be useful for the purpose of gaining a deeper understanding of the determinants of older consumers' buying behaviours and generating marketing ideas for managers of tour companies.

Utility of benefit segmentation technique

Benefits sought explain what consumers are looking for or the reason/s for wanting an object or service that prompt them to buy it. Benefits, therefore, have a direct relationship with buying behaviour, and mediate person characteristics. Assuming that an extensive study by a large local supermarket in a particular large retail catchment area found that three factors captured the main features of all variables or benefits that older consumers seek, namely: 1) convenient shopping; 2) worry–free shopping, and 3) a customer–friendly environment. By knowing the benefits that consumers seek, the manager of that supermarket may modify its market offering to include elements of convenience to shoppers, elements that free consumers from worry, and elements that make them feel at ease during their shopping trip. Further analysis on the results of specific measuring variables or the significance of particular dimensions of benefits that explained the three factors might suggest the need to implement three new services on top of existing services that are provided to all customers.

These would be:

  1. Providing a shuttle bus service from the city's central bus station seven days a week;

  2. Setting up information kiosks equipped with bar code readers on the shopping floor that would enable old people, who have difficulties reading small prints on food labels/packages, to scan the products' bar codes. The kiosks would automatically display the labels on large screens or provide voice on demand explanation;

  3. Position help bells/buttons along the supermarket aisles that enable old people to call for help.

Thus, benefits sought, thus, are actively used to segment consumers and the presence of those benefits attracts consumers, causing them to return to the same supermarket.

However, although it is necessary to identify the three main factors or categories of benefits that older consumers seek, this is not sufficient to enable a grocer to target its marketing activities effectively and efficiently. In a particular retail catchment area there might be several thousand people aged 50 and over. A grocer needs to know the profile of old people who live in its catchment area in terms of their personal characteristics, so that it can identify them for marketing purposes. This may be done firstly by clustering them into groups based on personal characteristics, and secondly, by exploring the potential associations between categories of benefits sought and clusters of customers. Personal characteristics on their own, in this case, are not expected to cause consumers to patronise the grocer. Their decisions to patronise the grocer are mediated by the presence of benefits the grocer offers, and personal characteristics are used passively. The active use of benefit segmentation together with the passive use of traditional method of segmentation offers an additional utility – the more reliable targeting of older consumers.

Benefit segmentation may also be used to segment older consumers as tourists. In the vacation sector, there have been attempts to segment the tourist market but these studies mainly used personal characteristics (among others Lowyck et al. 1990; González & Bello 2002; Lehto et al. 2002). Loker and Purde (1992) used benefits sought to segment vacation travellers to North Carolina whose purpose was pleasure. In that study Loker and Purde used only 12 broad benefit statements and the respondents were all visitor parties represented by the party leaders. The study, nevertheless, provided an interesting finding. Among other things, it found that the specific age groups of party leaders could not be distinctively associated with specific segments. The naturalist and pure excitement seekers, for instance, comprised visitors with party leaders aged between 30 and 59, and non–differentiators, excitement/escape, and the escapists comprised visitors with party leaders aged between 30 and 49. Based on Loker and Purde's findings it is clear that the older consumers (in this case those aged between 50 and 59 years old) are both naturalists and excitement seekers – not exactly compatible hobbies, one would argue! Another implication of the research finding is that older vacationers seek several sets of benefits, which marketers could use to develop specific holiday packages. Benefits of a particular tour package represent the attributes of the package that older consumers perceive as valuable. These benefits are wide – from clean air to meeting new friends, and from acquiring new knowledge to helping the local economy.

An exploration of potential relationships between psychographical characteristics and the benefits sought could generate homogeneous segments of older consumers that can be identified and targeted more easily than if they were identified only in terms of psychographical characteristics or benefits sought. Knowledge of various groups of older consumers in terms of their profiles or human portraits constructed from psychographical data and/or together with socio–economic and demographical data, that can be related to the specific categories of benefits sought, would enable managers to identify those particular customers from among their larger and heterogeneous group of consumers. This can be particularly useful in an environment where UK older consumers fall anywhere within a wide age band from 50 to 75–plus. Older people have a variety of rich life experiences, which can be used to infer many consuming or buying behaviours.

An illustration of empirical research

For the purpose of segmenting grocery shoppers, market researchers might like to conduct both qualitative and quantitative studies. Based on a review of the literature, a list of benefits sought in shopping for groceries has been identified – shown in Table 1.

The hypothesised relevant psychographic variables of older consumers, under the grocery shopping product–market domain, are listed in Table 2.

Market researchers may verify the construct validity of these variables by interviewing samples of their customers and sales staff and by taking into account of the characteristics of their own markets. Finally, a quantitative study through a self–administered questionnaire is suggested and this approach is outlined below under the data collection section. Factor and cluster analysis may then be used to extract factors or benefits and to cluster older consumers in terms of personal characteristics.

Data may be obtained by way of a survey with the use of a structured questionnaire. Interviewers may administer the questionnaire through face–to–face or telephone interviews. Respondents may also administer the questionnaire by themselves. At least two primary groups of data need to be collected:

  1. Data on benefits sought. These data may be obtained by asking respondents to rate their level of agreement with specific statements that capture benefits sought;

  2. Data on personal characteristics, which comprise psychographical, socio–economic and demographical variables.

Psychographical data may be obtained by asking respondents to rate their level of agreement with specific statements that capture psychographical variables, and socio–economic and demographical data may be obtained by asking respondents to answer a combination of dichotomous and multiple–choice questions. It is usually useful to conduct a pilot study with a view to refining the measuring instruments/questions before proceeding with a large–scale quantitative study of consumers.

It is proposed that factor analysis be used to explore and detect patterning of independent variables (benefits) older consumers seek in patronising supermarkets and in choosing holiday packages. Cluster analysis may be performed to identify groups of customers to whom specific bundles of cognitive benefits may be communicated and specific cognitive benefits may be emphasised. The Statistics Package for the Social Sciences (SPSS) may be used to analyse quantitative data and specifically to perform factor analysis.

In essence, the benefits of purchasing groceries are the services that a particular supermarket is offering to older consumers.

Implications for practice and for managers

Benefit segmentation would enable managers of grocers to develop and improve their market offerings in the UK, in terms of a product's or service's attributes, on the assumption that consumers are willing to use and pay for products and services that benefit them. The traditional method of segmenting consumers a priori with the use of personal characteristics is convenient, but the result is of limited use. Consumers, despite sharing similar personal characteristics, are not guaranteed to buy products or services that do not offer them benefits. Personal characteristics, nevertheless, are useful when used jointly with benefits sought to produce segments of old consumers, which companies could then target. Knowledge about the profiles of various clusters of old people and the benefits they seek would also help firms to position their products or services.

Notwithstanding the utility of benefit segmentation, it is also essential for managers to be aware of two practical issues. The first issue concerns establishing the level of attractiveness of individual segments of older consumers within a particular product–market domain. The second issue concerns the implications of the varying elasticity various market segments may have to marketing variables or stimuli. Moreover, the level of elasticity may not be identifiable through segment descriptors alone.

It is beyond the scope of this article to discuss the two issues in greater detail, but managers, we think, should bear these issues in mind when translating segmentation findings into marketing strategies. After all, segmentation should help managers to optimise their limited marketing resources. A viable market segment is not merely a homogeneous group that can be contrasted against other groups. The segment has to be able to generate financial contributions and if not, then it does not qualify as a viable market segment.

Although older people in the UK are a lucrative market in terms of their numbers and financial assets, marketers are still faced with a challenging task of identifying their needs and the determinants of their buying behaviours. Benefits segmentation is potentially a powerful technique to identify the wants of older consumers and to segment them into targetable groups.

Implications for further research

The research methodology proposed in this article could be replicated and used to segment older consumers in the UK in other areas of consumption, such as in selecting a vacation or holiday package. It could also be used to segment older consumers in other contexts or in other countries where other elements of culture might have peculiar impacts on the type of benefits consumers seek. For instance, in certain countries medical services are not provided by the state or are not available free of charge and older people have choices as to from where they want to obtain or purchase them.


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