International Journal of
Market Research
Vol. 45, No. 3, 2003
Tel: +44-20-7490 4911, Fax: +44-20-7490 0608
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International Journal of |
Vol. 45, No. 3, 2003 |
| 15 Northburgh Street, London, EC1V 0JR, UK Tel: +44-20-7490 4911, Fax: +44-20-7490 0608 |
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.
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.
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.
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.
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.
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:
Providing
a shuttle bus service from the city's central bus station seven days a week;
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;
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.
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:
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;
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.
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.
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
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