Market Segementation

19t7,1, No. 3. 301-335

Market Segmentation

A. Caroline TynanLecturer, Department of Business Studies, University of Edinburgh

AND

Jennifer Draytonlecturer, Department of Marketing, University of Strathctyde, Gtasgew

Market segmentation is a crucial marketing strategy. Its aim is to identify and delineatemarket segments or "sets of buyers" which would then become targets for the company'smarketing plans. The advantage to marketing management is that Ais technique dividestotal demand into relatively homogeneous segments which are identified by some commoncharacteristics. These characteristics are relevant in explaining and in predicting theresponse of consumers, in a given segment, to marketing stimuli.

The market can be subdivided by geographic, demographic, psychological, psycho-graphic or behavioural variables. The advantages and disadvarUages of each of thesetypes of segmentation variables are discussed in detail in this paper. Kotler {1984) hasidentified four requirements that a marketer can use in evaluating the desirability ofpotential market segments, namely measureability, accessibility, substantiality andactionability. Once a segment has been identified which meets these requirements, it ispossible to develop a product or service which meets the unfulfilled needs of thissegment. A marketing mix can then be devised to reach the segment identifiedeconomically and efficiently. A strategy of market segmentation attempts to regain someof the benefits of the closer association with customers which was the strength oftraditional business operations.

INTRODUCTION

This paper presents a review of the literature concerning the concept andpractice of market segmentation. This key strategy is essential to thedevelopment of a strategic plan for a brand. It is a decision-making tool forthe marketing manager in the crucial tasks of selecting a target market for agiven product and designing an appropriate marketing mix.

The uses of this technique are discussed, together with the procedures forsegmenting markets. Possible bases for segmenting consumer markets arereviewed in detail. The more straightforward objective bases have beenbriefly outlined whereas the more complex subjective behavioural bases arediscussed in more depth. The requirements for segmentation to be effectiveare noted and some criticisms of the technique presented.

301

302 A. CAROLINE TYNAN AND JENNIFER DRAYTON

Market segmentation has long been "considered one of the most funda-mental concepts of modern marketing" {Wind 1978, p. 317). Sheth (1967,p. 728) has described it as "essential to marketing". According to thedefinition found in the Oxford English Dictionary "to segment" is to"divide into parts". In marketing terms these parts can either refer togroups of consumers with similar requirements or to groups of goods orservices with similar attributes. The term and concept of "market segmen-tation" have been attributed to Wendell R. Smith, in a paper first publishedin 1956. He (Smith 1956, p. 6) commented "Segmentation is based upondevelopments on the demand side of the market and represents a rationaland more precise adjustment of product and marketing effort to consumeror user requirements. In the language of the economist, segmentation isdisaggregative in its effects and tends to bring about recognition of severaldemand schedules where only one was recognized before". In a brief"Retrospective Note on Market Segmentation" published in the intro-duction to the special edition of the Journal of Marketing Research editedby Wind, Smith (1978, p. 316) asserts that "the roots of early marketsegmentation research, carried on almost a quarter of a century ago, can befound in the writings of a group of marketing practitioners and scholarswhose undisputed leader was the late Wroe Alderson".

Baker (1984, p. 123) considers the "concept of market segmentation restsupon recognition of a differentiated demand for a product, while its use as amarketing tool depends uf)on identification of the most appropriate variableor variables with which to subdivide total demand into economically viablesegments. Economically viable segment may be understood as being ofsufficient size to enable a marketer to earn an adequate profit by cateringto the specific needs of its members. In fact Haley (1968, p. 30) considersthat "the idea that all markets can profitably be segmented has nowreceived almost as widespread acceptance as the marketing concept itself".Howard and Sheth (1969, p. 70) have noted market segmentation dependson the idea that "the company should segment or divide the market in sucha way as to achieve sets of buyers". These sets of buyers, or subsegments ofthe market, would then become targets for the company's marketing plans.The potential methods of subdividing total markets must be validated byresearch. It is then the responsibility of management to devise marketingmixes which are effective in the market segments. Thus market seg[men-tation has as its aim the identification and delineation of market segmentswith a view to providing more efficient and satisfactory marketing service."The strategy of market segmentation recognises that people differ in theirtastes, needs, attitudes, motivations, life-styles, family size and compositionetc." (Chisnall 1985, p. 264).

The concept of market segmentation hsis only been recognised compara-tively recently. Historically sellers engaged in mass marketing. That is theymzss produced, mass distributed, and mass promote! one product to allconsumers in an attempt to obtain economies of scale. In the face of thecompetition inevitably generated by this approach producers sought to

MARKET SEGMENTATION 303

obtain a differential advantage through making their products or servicesdifferent from those of competitors. This product differentiation strategy is"designed to offer variety to buyers rather than to appeal to differentsegments" (Kotler 1984, p. 251). According to Staudt et al. (1976 p. 6)product differentiation has followed the approaches shown below:

(a) physical differentiation of product(b) psychological differentiation of product(c) differences in purchasing environment(d) difference by virtue of physical distribution capability(e) differences in after-purchase assurance of satisfaction in use(f) differences in prices and terms of sale.Product differentiation proved moderately successful but because it does

not centre upon the needs and requirements of the consumer it has failed toyield maximum benefits to the producer and consumer (Ogwo 1980, p. 24).Companies are increasingly embracing market segmentation strategies as aresult of the dissatisfaction they have experienced with productdifferentiation.

At a superficial level the theory of market segmentation appears toconflict with basic economic theory. The tailoring of a product to meet theneeds and wants of a market segment militates against long production runsand the resulting economies of scale. The development of the segmentationapproach to market planning was associated with the end of rationing afterthe war, the acceleration of technological progress, increased social mobilityand growth in the variety of wants felt by consumers and the revival ofcompetition as a market force (Crimp 1985). Manufacturers were thus ableto identify marketing opportunities, design and launch a product to fulfilthe requirements of that segment and concentrate marketing effort on thatsegment. This yielded a two-fold benefit. The manufacturer could adjustprices, distribution channels, promotions and advertising to reach the targetmarket efficiently. "Instead of scattering their marketing effort ('Shotgun'approach), they can focus it on the buyers who have the greatest purchaseinterest ('rifle' approach)" (Kotler 1984, p. 251). In addition the manu-facturer could develop sufficient loyalty for his product to withstand theprice appeal of retailers own label products.

USES OF THE MARKET SEGMENTATION APPROACH

The importance of the market segmentation approach has already beenstressed in the introduction to this paf)er. It can help to set the basicobjectives for the whole marketing operation, and to indicate appropriatestrategies by which these objectives can be realised. The type of objectiveand strategy will affect the type of segmentation problem posed, which inturn will determine the kind of research necessary. Lunn (1978 p. 346) has

304 A. CAROLINE TYNAN AND JENNIFER DRAYTONidentifled four characteristic types of marketing problem which wouldnormally be solved through a market segmentation study.

(a) Defining the marketIt is important to view a market from a consumer's viewpoint rather thanfrom that of the manufacturer. Products which are viewed as substitutes bythe customer may come from several distinct product fields when themanufacturers perspective is considered. On one hand the consumersproduct field concept may range quite widely, and on the other she maynot necessarily consider all the brands from any one field as being suitablefor a particular need or set of needs.

(b) To rationalise policies for existing brands and productsThe company is constantly seeking to devise optimum strategies for itsproducts. The objective may be to improve market share, weaken thepMDsition of a key competitor, or protect a brand from competitive activity.In the light of the market segmentation research, attempts may be made toincrease the purchase rate of current buyers, to convert buyers fromcompeting brands or to attract a new group of customers to the productfield.

(c) To position ranges of brands and of product varietiesIn a market with several different segments of consumers who have differentneeds a company is well advised to cater for several of the more importantsegments if it has sufficient resources. At the same time compietition betweenthe company's brands in any segment should be minimised.

(d) To idmtify gaps in tbe market wbicb oFer new productopportunities

The aim here is to identify customer segments whose needs are not beingmet by any existing brand. These needs may be met by launching a newproduct or by altering an existing product.

PROCEDURES FOR SEGMENTING MARKETS

Yoram Wind (1978) has identified four basic methods for segmentingmarkets, the traditional a priori and cluster based designs and the newerflexible and componential procedures. The classification of segmentationstudies into the first two of these categories, that is a priori and cluster basedor post hoc, was suggested by Green (1977). He maintains that a priorisegmentation models have had as the dejjendent variable (the basis forsegmentation) either product specific variables like product usage or loyalty,or general customer characteristics in demographic terms. Survey resultsshow the segments' estimated size and their demographic, socio-economic,

MARKET SEGMENTATION 305psychc^raphic and other relevant characteristics. A typical research designfor an a priori segmentation model involves the following seven stages:

(a) Selection of the a priori basis for segmentation.(b) Selection of a set of segment descriptors, including hypwtheses on the

jMJSsible link between those descriptors and the basis for segmentation.(c) Sample designmostly stratified and occasionally a quota sample

according to the various classes of the dejjendent variable.(d) Data collection.(e) Formation of the segments based on a sorting of respondents into

categories.(f) Establishment of the (conditional) profile of the segments using

multiple discriminator analysis, multiple regression analysis or someother appropriate analytical procedure.

(g) Translation of the findings about the segments estimated size andprofile into specific marketing strategies, including the selection oftarget segments and the design or modification of sf>ecific marketingstrategy.

Cluster based or post hoc segementation models differ from a priori modelsin that the basis for segmentation is selected after the data has beencollected. Most commonly the variable used in this type of mode! areneeds, attitudes, lifestyle and other psychographic characteristics, or benefitssought from the product or service. Frequendy the clustering procedure ispreceeded by a factor analysis to reduce the original set of variables. Thevariables are grouped according to their correlation with each other and theamount of variance they can explain in the dependent variable. As in apriori designs the size and demographics, socio-economic, purchase and otherrelevant characteristics are estimated.

Flexible segmentation offers a dynamic approach to the segmentationproblem. It allows management to develop and examine a large number ofalternative segments, each composed of a group of consumers who exhibit asimilar response to new "test" products. The approach is based on theintegration of the results of a conjoint analysis and a computer simulation ofconsumer choice behaviour. Conjoint analysis studies usually consist of threeparts:

(a) Preference ranking or rating of a set of hypothetical products.(b) Perceptual ranking or rating of current brands on the same set of

attributes used in ranking the hypothetical products above.(c) A set of demographic and other background characteristics.The simulation uses these three data bases as inputs, and requires

management to assist in the development of "new product offerings". Theconsumer response to these offerings is then simulated. When a segment has


been selected, information on its estimated size and discriminating charac-teristics is available.

The compMDnential segmentation procedure, which was promulgated byGreen ei al. (1977) shifts the emphasis of the segmentation model from thepartitioning of a market to a prediction of which type of person will bemost respKjnsive to what type of product feature. The type of person isdescribed in terms of demographic and psychographic attribute levels. Theprocedure used is an extension of conjoint analysis.

The componential segmentation model offers a new conceptualisation formarket segmentation because it offers both an analysis of the marketsegment for a particular product offering and an evaluation of the mostdesirable product offering or positioning.

BASES FOR SEGMENTING MARKETS

Realising the potential benefits of market segmentation requires bothmanagement acceptance of the concept and an empirical segmentationstudy before implementation can begin. Wind (1978, p. 318) states that"most segmentation studies have been conducted for consumer goods".However both the concept of segmentation and the majority of segmen-tation approaches are equally applicable to consumer and to industrialmarkets (Webster and Wind 1972, Nicosia and Wind 1977).

The segmentation model requires the selection of a basis for segmentation,(the dependent variable), and descriptors, (the independent variables), ofthe various segments. There is a very wide selection of variables mentionedin the consumer literature as possible bases for and descriptors of segments.The segmentation base chosen to subdivide a market will depend on "thetype of product, the nature of demand, the method of distribution, themedia available for market communication, and the motivation of buyers"(Chisnall 1985, p. 266). These segmentation bases are rarely used alone, acombination of two or more of them is more usual. The various bases ofsegmentation analysis are discussed under the following headings:

1. Geographic bases in which markets are divided into geographic units.2. Demographic bases include segmentation studies based on age, sex,

socio-economic group, family size, life cycle, income, occupation,education, etc.

3. Psychological bases in which personality factors, attitudes, risk, moti-vation, etc. are used to divide the market.

4. Psychographic bases include lifestyle, activities, interests, opinions,needs, values and the like as market delineators.

5. Behavioural bases include brand loyalty, usage rate, benefits sought,use occasions.

6-7. Industrial segmentation and product segmentation are briefly discussedfor the sake of completeness.

MARKET SEGME>rrATION 307

I. Gcogra^dc segmmtatioDGeographic segmentation was jserhaps the first type of segmentation toexist, historically speaking (Lunn 1978). This is because many companiesoperate along geographic lines. "Small manufacturers who wished to limittheir investments, or whose distribution channels were not large enough tocover the entire country, segmented the US market in effect by selling theirproducts only in certain areas" (Haley J968, p. 30). These comments applyto many countries other than the United States of America.

Markets can be analysed nationally, regionally or locally. When assessingmarket oppiortunities in different countries a useful categorisation is basedupon gross national product per capita. This generates three main segments;those of the industrialized countries, the developing countries and the lessdeveloped countries. Weber (1974) has noted the piotential ofthe developingcountries which account for only 19% of the world's population but 32% ofthe world's income. Areas can be studied for differences in buyingbehaviour attributed to locale. Food habits, for instance, tend to haveregional variations. In Scotland, the consumption of both vegetables andbeverages recorded by the National Food Survey is considerably lower thanthat of England and Wales (Household Food Consumption and Expen-diture 1981 (1983), pp. 45-52}.

One major development in the field of geographic based segmentation isRichard Webber's ACORN (A Classification Of Residential Neighbour-hoods). The system was developed from sociological research into urbandeprivation in Liverpool and it classifies people and households according tothe typie of neighbourhoods in which they live. After joining ConsolidatedAnalysis Centre Inc. (CACI), Webber extended his original classification.Presently ACORN recognises 38 neighbourhood types, identified by acombination of 40 variables from census data. These 40 variables includeage and household comjjosition, housing type, social and employmentstatus. This division into 38 different types of household offered more detailthan was necessary and so the 11 Family Group Classification shown belowwas devised (Chisnall 1986).

ACORN is a powerful segmentation tool which offers a detailed profileof particular segments together with their precise location. "It clearly hasparticular relevance to direct marketing, leaOet distribution and local mediaselection" (Chisnall 1986, p. 280).

In 1983 the Consumer L,ocation System (CLS) was launched. This systemhas combined BMRB's Target Group Index (TGI) and ACORN. TGIexamines the purchasing habits of approximately 24,000 consumers acrossmore than 500 product fields. The TGI results are correlated with ACORNneighbourhood types to identify the concentrations of potential purchasersfor a specific product. Actual names and addresses of people in relevanttarget groups can be generated as the electoral register has been com-puterised by CNN systems. This is clearly a much tighter specification of amass consumer market than is currently available through any othermedium (Rines 1983).


AB

C

D

EFGHIJKU

ACORN groups

Agricultural areasModem family housing,higher incomesOlder housing ofintermediate statusPoor quality olderterraced housingBetter-off council estatesLess well-off council estatesPoorest council estatesMultiracial areasHigh-status non-family areasAffluent suburban housingBetter-off retirement are2isUnclassified

1981 population(OOOs)

1811

8667

9420

23206976503240482086224885142041

388

%

3.4

16.2

17.6

4.353.09.47.63.94.2

15.93.80.7

Households(%)3.3

14.8

18.7

4.612.210.46.83.54.9

18.94.80.1

Source: CACI Imernationai.FIGURE 1 ACORN'S 11 family group classification.

2. Demographic segmentatioaiThis consists of dividing the market into groups on the basis of demo-

graphic variables such as age, sex, socio-economic group, family size, lifecycle, income, occupation and education. Kotler (1984, p. 255) states that"demographic variables are the most piopular bases for distinguishingcustomer groups", pxjssibly because of the ease with which this kind of datacan be collected. These characteristics have become the basic terms inwhich many marketers consider the consumer. This is reasonable in asmuch as demographic variables describe impiortant aspects of the consumerwhich give rise to purchasing requirements. Additionally demographic datahas been collected over such a long period of time that relationships withother marketing variables e.g. media use have become well-known (Lunn1978, p. 349). Thus many marketers collect demographic data on thecharacteristics of their consumers routinely, even when they intend to usesome other bjise for segmentation.

In recent years demographic segmentation has been subject to consi-derable criticism. Stan ton (1978) has commented that "Looking at thedemographic variables... rarely is a useful market segment identified by asingle market factor". McCarthy (1978) takes a similar stance commentingthat product choice is only weakly related to demographics. A number ofstudies have revealed that demographic variables such as age, sex, incomeand occupation are pKXjr predictors of behaviour, and as such are of limitedvalue in the formulation of market segmentation studies. Haley (1968, p.31) has noted that they rely on descriptive rather than causal factors and assuch are "not efficient predictors of future buying behaviour, and it is futurebuying behaviour that is of central interest to marketers". Perhaps the most

MARKET SEGMENTATION 309widely cited study quoted in this context is the study of 57 grocery productsby Frank et al. (1967, p. 189). These authors concluded "socioeconomic anddemographic characteristics are poor predictors of consumption for a widerange of specific grocery products". Support for their conclusions have comefrom other researchers (Koponen 1960, HUdegaard and Krueger 1964;Frank 1967, Massy et al. 1968}. The only researchers to take exception tothis conclusion are Bass et al. (1968) and more recently Wheatley et al.(1980). Both these research teams have taken the approach of examininggroup rather than individual behaviour which may account for their successin using demographic segmentation variables where approaches based onthe individual consumer failed. However demographic bases for segmen-tation of both individual and group behaviour are still avidly defended bymany marketing research practitioners (e.g. Ckjrnish 1981).

Age has frequently been used as a base for segmentation on the basis thatconsumer wants and capacities change with age. 'A notable state of the artreview of this variable was conducted by Phillips and Stemthal (1977).They examined the differences made by age in information processing witha view to designing more appropriate advertising communications fordifferent age segments. The study addressed two issues:

(a) Whether elderly individuals show a differential sensitivity in processinginformation in relation to younger people.

(b) At what age these differences are manifested.They concluded that age differences result in a complex set of changes in

individuals' sources of information, ability to learn and susceptibility tosocial influence. These changes do not necessarily occur at 65 yeare but theyare related to the social, psychological and physical changes that accom-pany ageing.

In many product areas the sex of a consumer determines the product heor she will buy. For instance, sex segmentation has long been applied toclothing, magazines, cosmetics and toiletries (Kotler 1984). More recentwork has indicated sex differences in a product area not normally consi-dered to have a sex link, that of food (Dickens and Chappell 1977).

In some cases the life cycle concept has proved a more useful segmen-tation variable than age (Lansing and Kish 1957). These authors made acomparison between life cycle and age on six aspects of the family'sconsumption pattern and concluded that life cycle discriminated better thanage in all six cases, and that life cycle analysis provided some usefulinformation that analysis by age tended to conceal. life cycle is a compositevariable, made up of factors which include age, number of years married,age of children and working status. The concept was postulati in the 1930sbut only developed in a marketing sense in the 1950s and 1960s. It isapplicable to the conventional nuclear family. Berkman and Gilson (1981,p. 179) consider that it may "not reflect current trends such as the twoincome family". Derrick and Lehfeld (1980, p. 214) give a detailed analysisof the litnitations of the traditional life cycle which they consider "fall under

310 A. CAROLINE TYNAN AND JENNIFER DRAYTONtwo main headingsoperationalising the stages and interpreting theresults".

An important conference, entitled "The Life Cycle and ConsumerBehaviour" was held in Michigan in 1954 (Clark 1955) where several keypapers were presented. Other important contributions came from Lansingand Kish (1957), Wells and Gubar (1966) and more recently StampQ(1978). A detailed and extensive analysis of the relationship betwen lifecycle and consumption behaviour is presented by Reynolds and Wells intheir book Consumer Behaviour (1977). Their model is presented below inFigure 2.

Age Development level Stage in ihe family life-cycle

18-34 Early adulthood

35-54 Middle adulthood

55+ Later adulthood

1 The bachelor stage: young,single people

2 Newly married couples:young, no children

3 The full nest I: youngmarried couples withdependent children:(a) Youngest child under

six(b) Youngest child over

six4 The full nest II: older

married couples withdependent children

5 The empty nest: oldermarried couples with nochildren living with them:(a) Head in labour force(b) Head retired

6 The solitary survivors: theolder single people(a) In labour force(b) Retired

Source: Reynolds, F. D. and Wells, W. D. (1977), Consumer Behaviour, NewYork, McGraw-Hill, p. 41.

FIGURE 2 Family life-cycles

The basic assumption underlying the family life cycle approach is thatmost households pass through an orderly progression of stages each with itsown characteristic purchasing pattems. In spite of the difficulties ofclassifying some respondents who do not fit neatly into any of the usualstages, e.g. older single pieople, or the widow who has young children, lifecycle remains a useful segmentation base at a general level.

Income is another important segmentation base, and one which has beenreasonably well researched. There are difficulties in establishing household


income from all sources after deductions, some of which can be attributed topeoples' reluctance to divulge this type of information, and some to thecomplications of having more than one wage earner in the family. Severalauthors have concluded that income is the best of the demographic bases forsegmenting markets (Allt 1975, Stanton and Haug 1971, Slocum andMathews 1970).

Socio-economic classification has the advantages of being both widelyunderstood and used as the basis for media classification for many years(Chisnall 1985). To some extent it also subsumes the other segmentationvariables, income, occupation and education. In Britain the classificationsystem most popular with market researchers for socio-economic group isthe A to E grading used in readership surveys and advocated by the MarketResearch Society (Wolfe 1973). This classification is shown below in Figure 3.

Socialgrade

A

B

C,

c.DE

Social status

Upper middle class

Middle class

Lower middle class

Skilled working classWorking classThose at lowestlevels of subsistence

Head of hmtsehoid's occupation

Higher managerial, administrativeor professionalIntermediate managerial,administrative or professionalSupervisory or clerical andjunior managerial, administrativeor professionalSkilled manual workersSemi and unskilled manual workersState pensioners or widows(no other earner), casual orlowest-grade workers

Approximatepercentageof families

3

10

243025

8

Source: Monk, D. (1970, "Social grading on the national readership survey", London,Research Services, Joint Industry Committee for National Readership Surveys.

FIGURE 3 Socio-economic classification

Social class, by whatever definition, is popular as a segmentation variablein spite of its doubtful ability as a predictor of consumer behaviour. It hasbeen cited as a useful segmentation base by several authors. Martineau(1958) found a close relationship between store choice, patterns of spendingand social class. Packard (1969) also noted the "pride, pleasure andprestige" which many women feel in patronising a high-class store. Accord-ing to Rich and Jain (1968) the higher the social class of a consumer themore quickly she wished to complete her shopping. However since this earlyresearch, the market place and the consumer have both changed consider-ably with the result that many authors consider social class is now a poordiscriminator in many product fields, particularly for fast moving consumergoods. The social mobility of many individuals in our affluent society has

312 A. CAROLINE TYNAN AND JENNIFER DRAYTONundoubtedly contributed to this change. The sharp divisions betweendifferent social classes are blurring as consumption and earning habitschange. It is unlikely that social class will ever regain its prominence as asegmentation variable.

In an attempt to improve the j>oor predictive ability of segmentationbased on single demographic variables Research Services Limited developiedSAGACITY, a classification based upon a combination of life cycle, incomeand socio-economic group. SAGACITY is founded on the premise thatconsumers have different aspirations and behaviour at different stages of thelife cycle. Four life cycle stages are subdivided by income, either better orwoKe off and by occupation, either manual (blue-collar) or non-manual(white-collar). The SAGACITY model is shown below with a briefdescription of the twelve groups and an indication of their size whencompared to the total adult population (Market Research Society 1984).

1 Life Cycle I Dependent Pie-Family

2 Income

3 Occupation Wiitt Blue

Family

Sull

Better Off

JLWhite

JLaiua

Worsi

JLWhite

9 Off

}LBlue

f lBetter Off

JL JL^31 ue

llWorse Off

JL

FIGURE 4 The Sagacity model and twelve SAGACITY segments

Dependent, White (DW) 6%Mainly under 24s, Uving at home or full time student, where head of household is in anABC, occupation group.Dependent, Blue (DB) 10%MaitUy under 24s, living at home or full time student, where head of household is in a C^DEoccupation group.

Pre-family, White (PFW) 4%Under 35s who have established their own household but have no children and where thehead of household is in an ABCj occupation group.Pre-family, Blue (PDB) 4%Under 35s who have estabUshed their own household but have no children and where thehead of household is in a CjDE occupation group.Family, Better off. White (FW +) 6%Housewives and heads of household, under 65, with one or more children in the household,in the "better off" income group and where the head of household is in an ABC, occupationgroup. {63% are AB).Family, Better off. Blue (FB + ) 8%Housewives and heads of household, under 65, with one or more children in the household,in the "better off" income group and where die head of household is in a CjDE occupationgroup. (80% areCj) .


Family, Worse off. White ( F W - ) 8%Housewives and heads of household, under 65 with one or more children in the household,in the "worse off" income group and where the head of household is in an ABCj occupationgroup. (70% are C,).Fanuly, Worse off, Blue (FB-) 14%Housewives and heads of household, under 65, with one or more children in the household,in the "worse off" income group and where the head of household is in a CjDE occupationgroup. (53% are DE).Late, Better off. White (LW +} 5%Includes all adults whose children have left home or who are over 35 and childless, are inthe "better off" income group and where the head of household is in an ABC, occupationgroup. (61% are AB).Late, Better off. Blue (LB + ) 6%Includes all aduits whose children have left home or who are over 35 and childless, are inthe "better off" income group and where the head of household is in a C^DE occupationgroup. (72% are DE).Late, Worse off, White (LW - ) 9%Includes all adults whose children have left home or who are over 35 and childless, are inthe "worse off" income group and where the head of household is in an ABC, occupationgroup. (67% a reC, ) .Late, Worse off. Blue (LB-) 20%Includes all adults whose children have left home or who are over 35 and childless, are inthe "worse off" income group and where the head of household is in a C^DE occupationgroup (72% are DE).Source: Research Services Ltd., 1981.

Combining severat demographic variables offers an improvement indiscrimination over using them alone but this method is still liable to thecriticisms levelled at income and socio-economic classifications mentionedabove.

3. Psychological segmentatioiiGeneral dissatisfaction with geographic and demographic characteristics assegmentation bases led to the use of psychological variables as a basis forpredicting consumer behaviour. It was anticipated that procedures developedand tested by anthropologists, sociologists and psychologists could beapplied to the segmentation of consumer markets. The work has centred onthe use of variables such as personality, risk, reference groups and attitudes.

The use of personality as a segmentation variable has not met with anysignificant success. Kassarjian (1971) calls the results "equivocal", VanVetdhoven (1973) calls them "disappointing", although a great deal ofwork has been conducted in this area. The idea of classifying people bypersonality tyjje is not new, one famiUar personality segfmentation is that ofHippocrates who used the four humours, choleric, melancholic, sanguineand phlegmatic. Another example is provided in Spranger's book. Types of


Men., published in 1928 and reported much later by E)^enck (1954). Heidentified six types:

Theoretical dominant interest in discovering the truth, a cognitiveattitude towards life.

Economic dominant interest in what is useful, a practical approach tolife.

Aesthetic dominant interest in form and harmony, an artisticapproach to life.

Social dominant interest is in peoplelove is his main approachto life.

Political dominant interest is in social relations but with a basic lifeapproach of power.

Religious dominant interest in doctrines and philosophy, with amystical approach to life.

According to Kassarjian (1971) there is no accepted defmition of the term"personality". However Jahoda and Warren (1969, p. 9) have defined it as"the total organisation of internal psychological functioning". One under-lying basic assumption of personality theories is that "personality reflectsenduring needs of the individual; that is needs that are 'common denomi-nator?' of the person's behaviour regardless of the nature of the problemsituation with which he is faced" (Mostyn 1977, p. 27). This implies that anindividual has an enduring set of tendencies to behave in a given way togiven classes of stimuli.

One of the earliest papers linking psychological factors with consumerbehaviour was that of Mason Haire (1950). Resp)ondents were asked todescribe the personality and character of the women whose shopping listthey examined. They were given two lists which only differed in respect ofthe coffee listed, one was Nescafe Instant, the other Maxwell House Dripgrind (a type of finely ground coffee bean). The respondents were able tocharacterise these two women with the result that they saw the Nescafeshopf>er as lazy and a poor household planner and the Maxwell Houseshopper as thrifty and a good wife. Since this work psychological segmen-tation has proliferated. A useful examination of the topic has been publishedby Mostyn (1977). Firstly, some of the important pajiers which haveindicated a significant correlation {in the author's opinion) between person-ality and consumer behaviour will be examined. This will be followed bythose studies which found a weak correlation.

Koponen (1960) used the Edwards Personal Preference Schedule in astudy of smoking and found that sex dominance, aggression and achieve-ment needs were positively related to cigarette smoking in men. A signifi-cant correlation between extroversion, as measured by Eysenck's scales, andsmoking was established by Eysenck et al. (1960). Tucker and Painter(1961) found significant correlations between pereonality traits and the useof headache remedies, vitamins, mouthwash, alcoholic drinks, motor cars


and chewing gum using the Gordon Personal Profile. Westfall (1%2)established significant differences between convertible, compact and stan-dard car owners using Thurstone's Temperament Schedule. Claychamp(1965) used the Edwards Personal Preference Schedule and found thatpersonality variables predicted better than demographic variables whethera resfKindent was a customer of a bank or savings and loan association. Astudy in 1970 by Lehmann, found that mothere who were both anxiotis andhigh on self-esteem were less likely to be persuaded to try new ideas fortheir babies, whereas mothers who were low on these traits were easier topersuade. Fry (1971) used a variety of personality tests, including a specialself-confidence scale, and established a significant correlation between sex,class and brand choice for cigarettes. Using the Rokeach dogmatism scale ina study conceming fashion and cosmetic products, Jacoby (1971) found thelow-dogmatic women signiGcantly more likely to make innovative choices.Coney (1972) replicated and extended this study by including men andadditional product categories. He confirmed that low-dogmatics weresignificantly more likely to be innovators. Blake et al. (1973) established thatdogmatism was significantly related to the acceptance of new products, butnot the acceptance of novel products.

The foiiowing pajiers all found poor correlation between personality andconsumer behaviour. In a study reported by Britt (1966, p. 182) andsponsored by the Advertising Research Foundation, it was found that "inpredicting toilet tissue purchase behaviour, information on the demographicand personality traits was little better than no information at ali". Myers(1967) reported little correlation between pereonality and attitudes towardsprivate brands. He used the Cattell Personality Factor Inventory and couldexplain only 5% of the variance in the purchase data. In a similar study ofown label (store brands) versus branded goods, Massy et ai. (1968) used theEdwards Personal Preference Schedule. They concluded that in only 26% ofcases did personality variables add a significant increment to the predictionthat could be made with socio-economic data alone. Robertson and Myers(1969) used the California Personality Inventory plus measures for inno-vativeness and opinion leadership in a study of new appliances, food andclothing products. They found only a minimal relationship between pierson-ality variables and behaviour towards new products. Levonian (1969) statedthat of eight studies claiming to associate personality and opinion changefoiiowing a mass communication, 40% actually yielded results in theopposite direction. Personality was not a useful discriminator variable indifferentiating between "new season's" and "last year's model" car buyers(Wiseman 1971). Pizam (1972) found that only 16 of the 37 personalitytraits he tested had a significant association with innovativeness. Finally,Villani (1975) found that demographic variables "outperformed" person-ality variables in his study of television programme viewing.

In the research cited above both significant and not significant resultshave been obtained using the same personality tests and frequently withreference to the same subject, innovativeness for example. Clearly some of


the studies suffer from problems of reliability and validity. An additionalproblem has best been summed up by Kassarjian (1965, p, 146) "Theconsumer researcher too often expects more from an instrument than it wasoriginally intended to furnish". As Kotler (1984) has jrointed out, evenwhere evidence has been found of the influence of personality on consumerbehaviour, the implications for marketing strategy have remained unclear.

Another of the psychological areas that has been used by marketen topredict consumer behaviour is risk, Bauer first proposed the concept of"perceived risk" in buying decisions in 1960. He intimated that risk isassessed differently according to the perceptions of individual buyere. Sincethen many empirical studies have been conducted on various aspects of riskin consumer decision making, Taylor (1974) has hypothesised that theelement of choice in consumer behaviour involves risk because the outcomeof the choice is uncertain, and that this risk is seen in terms of a possiblefinancial, social, performance, psychological, physical or convenience loss.The individuals reaction to these "piotential losses would depend on thatindividual's amount of perceived risk", Peter and Ryan (1976) have definedperceived risk as the expectation of losses associated with a purchase whichacts as an inhibitor to purchase behaviour. On the assumption thatindividuals would behave in such a way as to reduce the amount of risk ina purchase situation, Cunningham (1967) has shown that brand loyalty isdetermined to a great extent by perceived risk, Arndt (1968) showed asimilar relationship between the use of word of mouth communication abouta product and perceived risk, as did Bearden and Mason (1978) inprescribed drug purchases. Another risk related theory is Festinger's (1957)Theory of Cognitive Dissonance, In essence this theory states that anindividual wil! seek to try to reduce dissonance or disharmony within hiscognitive structure and attempt to reach a state of harmony. This isachieved by resolving the conflict between the various factors which are notpsychologically consistent with one another. The individual is motivated tochange his opinion, attitude or behaviour in order to reach a state ofharmony. In two studies of automobile purchase, Ehrlich et al. (1957)indicated that as automobile buyers seek information on model and makealready bought they are dissonant consumers, Engel (1963) howeversuggested that as automobiles are no longer a status symbol there should belittle dissonance after purchase.

The psychological concept of reference groujjs has also been used toexplain consumer behaviour and segment markets. The concept of referencegroup was first propiosed by Hyman (1942) to describe the kind of groupused by an individual as a pwint of reference for his own judgement, beliefsand behaviour, Venkatesan (1966), Friedman and Fireworker (1977) haveconfirmed that much consumer decision-making is influenced by thepressure to conform to group norms. Bourne (1957) indicated that the moreconspicuous a product, the more likely its purchase is susceptible toreference group behaviour. Reference group influence is more likely to beeffective in the case of products which reflect {>ersonal taste (Chisnall 1985),


There is also the unproved implication in many of these studies that anindividual's susceptibility to reference group influence is related in some wayto his personality.

The final psychological variable to be considered separately in this studyis attitude. This concept is frequently considered for use as both asegmentation base and a possible predictor of consumer behaviour. Insegmenting a market the users of a product are frequently identified bymeans of their attitude towards that brand or product. This assumes thatthere is some causal link between the attitude and the purchase behaviour,a link which while frequently hypothesised has not been proved.McGuinness et al. (1977), Crespi (1977), Howitt and McCabe (1978) allconsider that attitude does predict behaviour. Fishbein (1967), Ajzen andFishbein (1973), Pinson and Roberto (1973) however deny the causai linkbetween attitude and behaviour. Work still continues to determine the truelink between attitudes and behaviour.

In conclusion it should be noted that much of the published work onpsychological bases of segmentation is in conflict. Although these variablesdo influence buying behaviour there is no reason to believe there exists ageneralised pattern of influence. According to Chisnall (1985, p. 268)"individual products should be carefully analysed for the potential or actualpersonality factors influencing their sales".

4. Psychographic segmentationDuring the 1960s, a blend of personality and motivation research began totake shape (Wells 1975). It has been referred to "as the marriage betweenthe richness of motivational research with its emphasis on qualitativemethods and projective techniques and the statistical sophistication of thefactor and trait theorists who made psychological segmentation studiespossible" (Mostyn 1977, p. 31). This new area has been variously cjdledlifestyle (Plummer 1971, 1971-2), psychographics (Nelson 1969, 1971a,1971b, Demby !971, Pernica 1974), activity and attitude research (Hustadand Pessemier 1971, 1974, Wells and Tigert 1971) and "activities, interestand opinions" research (Engel et al. 1978). Therefore psychographic researchershave moved beyond demographics and considered activities, interests,opinions, needs, values, attitudes and personality traits. There is as yet nogenerally agreed definition. In his excellent review article. Wells (1975, p.197) has proposed an operational defmition of psychographic research as"quantitative research designed to place consumers on psychological asdistinguished from demographic dimensions". The technique divides themarket into segments on the bauis of interest, values, opinion, personalitycharacteristics, attitudes and demographic variables using techniques offactor analysis, cluster analysis and canonical correlation (Kassarjian 1971).It is assumed that products which fit into the lifestyle will have value for theconsumer. Wells (1968) named this approach "backward segmentation"because it groups people by their behavioural characteristics before seeking

318 A. CAROLINE TYNAN AND JENNIFER DRAYTONcorrelates. In this approach the analysis of buyer behaviour starts with thebehaviour itself. Complex statistical techniques such as factor analysis andcluster analysis are applied to purchasing data across a wide variety ofproducts to seek for pattems of complementary and substitutable products(Bass et al. 1969). The three main applications of backwards segmentationare to

(a) Stimulate ideas and guide future research.(b) Simplify marketing strategies.(c) Increase understanding by stimulating researchers to question why

sets of products group together as they do.Nelson (1971b} has noted some of the reasons for the growing ptopularity

and importance of psychographics.(a) The general acceptance of the need for the application of behavioural

science information to advertising and marketing problem solving.(b) The availability of computer programmes that can perform multi-

variate analysis on large numbers of pieople.(c) Acceptance of the concept of market segmentation.(d) Decreasing relevancy of certain demographic characteristics.(e) Change taking place in our social structure.Psychographics emphasises the importance of general environmental,

cultural and social factors, e.g. socialisation and group pressure and as suchtakes up where psychological segmentation leaves off (Mostyn 1977).Psychographic surveys usually employ Likert Scales and self-administeredquestionnaires which are largely precoded to facilitate analysis. The samplestend to be large and the analysis ranges from the use of simple cross-tabulations to the more complex factor analysis, cluster analysis or canonicalcorrelation.

Wells (1974) has discussed the uses of psychographics in detail. He hassummarised the techniques used in market segmentation the following way.

"Life style and psychographic research can assist market segmentationin a variety of ways. It can provide useful descriptions of existingsegments of present markets. It can help the analyst understand theresults of multidimensional scaling or prciduct benefit segmentation. Itcan contribute new and useful dimensions along which consumers maybe segmented. It can create new segments based upon product and/orbrand related interests, needs and values. And it can create newsegments based ufjon more general aspects of life style".

Tipton (1972) has noted the general uses to which psychographicsegmentation has been put, apart from market segmentation they are;

(a) New product development in which a "gap" of unfulfilled needs orwants is identified in the market and a new product designed to fillthat gap.

MARKET SEGMENTATION 319(b) Media selectionthe knowledge of the psychographic profile enables

the selection of the most effective and economical media mix to reachthe segment,

(c) Creative applicationknowledge of how consumers live and think ishelpful to a researcher in designing an advertising campaign ormaking a new product appealing.

Wells (1975) divided segmentation studies into those where the segmen-tation was based on general life style dimensions and those in which thepsychographic items were product si>ecific. An example of the "general"approach has been drawn from Wells (1975, p, 201), In this exampleapproximately 4000 respondents, answered psychographic, product use andmedia exposure questions. Using factor analysis the eight homogeneousgroups described in Figure 5 were derived.

The product and media use of these eight psychographic groups werethen calculated.

In Britain, Attwood Statistics characterise the housewives on theirconsumer panel by their psychographic groups and behaviour into thefollowing types (Crimp 1985, p. 115),

1, Conscientiousness related to housework,2, Economy consciousness,3, Conservatism in brand (tending to better known brands rather than

experimenting with a new brand or product),4, Traditionalism in housework (related to the use of labour-saving or

convenience products),5, Willingness to experiment in shopping.

Many general life style profiles have appeared in the literature. Theyinclude the following papers. Ziff (!971, 1973) used psychographics to showthat both products and product classes can be differentiated by attitudes,needs and values. Both Plummer (1971-2) and Tigert (1974) researchedpsychographic profiles for magazine readers, Tigert also investigated televi-sion viewers. Scales representing fashion interest, fashion venturesomeness,cognitive style, information seeking, relative popularity and relativeconfidence have been used to predict fkshion opinion leadership by Dardenand Reynolds (1972), Other general profiles have investigated carry-outfoods (Tigert el al. !97I), beer (Tigert 1971), and bank charge cards(Plummer 1971). An interesting study of shopper types, recently publishedby Lesser and Hughes (1986), examined psychographic segmentationsolutions from different locations. The authors concluded that psychographicsegments developed for markets in one geographic location are generalizableto markets in other geographic locations.

The second group of studies involves those in which product specificvariables have been employed. Pernica (1974) has reported on a psycho-graphic segmentation for stomach remedies. He focused on product related


Group I. "The Quiet Family Man" (8% of total males).He is a self-sufficient man who wants to be left alone and is basically shy. Tends to be aslittle involved with community life as possible. His life revolves around the family, simplework and television viewing. Has a marked fantasy life. As a shopper he is practical, lessdrawn to consumer goods and pleasures than other men.

Low education and low economic status, he tends to be older than average.

Group II. "The Tradiuonalist" (16% of total maies).The man who feels secure, has self-esteem, follows conventiotial rules. He is proper andrespectable, regards himself as altruistic and interested in the welfare of others. As a shopperhe is conservative, Ukes popular brands and well known manufacturers.

Low education and low or middle socio-economic status; the oldest age group.

Group III. "The Discontented Man" (13% of total males).He is a man who is likely to be dissatisfied with his work. He feels by passed by life, dreamsof better jobs, more money and more security. He tends to be distrustful and socially aloof.As a buyer, be is quite price conscious.

Lowest education and lowest socio-economic group, mostly older than average.

Group IV. "The Ethical Highbrow" (14% of total maies).This is a very concerned man, sensitive to people's needs. Basically a puritan, content withfamily life, friends, and work. Interest in culture, religion and social reform. As a consumerhe is interested in quality, which may at times justify greater expenditure.

Well educated, middle or upper socio-economic status, mainly middle aged or older.

Group V. "The Pleasure Oriented Man" (9% of total males).He tends to emphasise his masculinity and rejects whatever appears to be soft or feminine.He views himself a leader among men. Self-centred, dislikes his work or job. Seeks immediategratification for his needs. He is an impulsive buyer, Ukely to buy products with a masculineimage.

Low education, lower socio-economic class, middle aged or younger.

Group VI. "The Achiever" (11 % of total males).This is likely to be a hardworking man, dedicated to success and all that it implies, socialprestige, power and money. Is in favour of diversity, is adventurous about leisure timepursuits. Is stylish, likes good food, music, etc. As a consumer he is status conscious, athoughtful and discritninating buyer.

Good education, high socio-economic status, young.

Group VII. "The He-Man" (19% of total males).He is gregarious, likes action, seeks an exciting and dramatic life. Thinks of himself ascapable and dominant. Tends to be more of a bachelor than a family man, even aftermarriage. Products he buys and brands preferred are likely to have "self-expressive value",especially a "Man of Action" dimension.

Well educated, mainly middle socio-economic status, the youngest of the male groups.

Group VIIl . "The Sophisticated Man" (10% of total males).He is hkely to be an intellectual, concerned abou! social usues, admires men with artistic andintellectual achievements. Socially costnopolitan, broad interests. Wants to be dominant, anda leader. As a consumer he is attracted to the unique and fashionable.

Best educated and highest status of all groups, younger than average.FIGURE 5 Eight male psychographic segments

MARKET SEGMENTATION 32!The Severe SufferersThe Severe Sufferere are the extreme group on the potency side of the market. They tend tohe young, have children, and he well educated. They are irritable and anxious people, andbelieve that they suffer more severely than others. They take the ailment seriously, fuss aboutit, pamper themselves, and keep trying new and different products in search of greaterpotency. A m

322 A. CAROLINE TYNAN AND JENNIFER DRAYTONincluding drugs, food and household products. Bernay (1971) also usedproduct specific variables in her study of magazine subscribers and non-subscribers. They were also used to distinguish between light and heavybeer drinkers by Kinnear and Taylor (1976). Other product specificpsychographic segmentation studies have been conducted by Heller (1968),Donnelly (1970), Frank and Strain (1972) and Young (1972).

Psychographics are open to question in four areas, those of reliability,validity, applications to real world marketing problems, and contributionsto the study of consumer behaviour. On the issue of reliability. Wells (1975,p. 203) has concluded "both homemade and standarized psychographicmeasurements can have reliability high enough to support fairly strongrelationships". The validity of psychographic research varies from study tostudy. The predictive validity of many studies is poor as measured by theamount of variance of individual behaviour they can account for. Howeverpsychographic variables are capable of showing substantial differencesbetween groups of consumers. Many studies have already contributed to theunderstanding of real world marketing problems and solutions. Finally,there is the problem of the lack of theory. Wind et al. (1973, p. 244) haveexpressed their amazement that there is "so little explicit theory guiding thecompilation of statements". A criticism which is still valid. However formany researchers and practitioners these disadvantages are outweighed bythe usefulness of the rich, descriptive typologies generated.

5. Behavionral basesIn this method of segmentation, the consumers are divided on the basis oftheir use of, or response to, a product. Benefit segmentation, brand loyalty,user rate, user status, usage situation and backward segmentation come intothis category. According to Kotler (1984, p. 259) "Many marketers believethat behavioral variables are the best starting point for constructing marketsegments".

Benefit segmentation was so named by Haley (1968, 1971), although hemaintained that it had been in use since 1961. "The belief underlying thissegmentation strategy is that the benefits which people are seeking inconsuming a given product are the basic reason for the existence of truemarket segments" (Haley 1968, p. 31). This approach classifies buyersaccording to the different benefits they seek from the product and thusdefines the segment by causal rather than descriptive factors. An early studyby Yankelovich (1964) used benefit segmentation to analyse the market forwatches. He found that

" I . approximately 23% of buyers bought for lowest price2. another 46% bought for durability and general product quality3. and 31% bought watches as symbols of some important occasion".

The majority of better known watch companies appiealed to the third


segment concentrating their advertising in November and December. So theTimex Company of America marketed a low price watch aimed at the firsttwo segments, and by advertising all year round got exclusive attention tenmonths of the year.

Haley (1968), in what has become a classic example, produced a benefitsegmentation of the toothpaste market, which is shown below. He pioneeredthe idea of the "principal benefit" sought fi-om a product and used this asthe criterion for segmentation.

The following simple three-step method for conducting a benefit segmen-tation has been promulgated by Miller and Granzin (1979).

(a) delineation of the market(b) determination of the benefits sought by the target market(c) providing the benefits.

It is an approach which is particularly appropriate to market planning foran existing brand. However it should be noted that respondents do not findit particularly easy to define the benefits they seek.

Brand loyalty is a possibly useful criterion for segmentation but the resultsof the research into this topic are somewhat confiicting. An early study byCunningham (1956) which utilised panel data obtained from the ChicagoTribune showed conclusively that a significant amount of brand loyaltydoes exist within individual product groups. However it does not generaliseover product fields. Bass et at. (1968) examined brand loyalty for onecategory of food product. They reported that their findings did not suppwrtthe usefulness of brand loyalty as a guide for segmentation of markets. Aresult which is questionable as only one product category was evaluated.

An interesting experiment by Tucker (1964) involving consumer brandchoices among four previously unknown food brands came to the followingconclusions. Firstly, the women shoppers displayed considerable variance ontheir susceptibility to brand loyalty. Secondly, even when there is nodiscernible difference between brands some consumers seem to exhibit brandloyalty. Finally, it appeared that shoppers frequently select brands on a trialbasis, to explore the available alternative, so repeat purchases areproblematical.

More recently, Blattberg and Sen (1976) have produced a framework forthe definition of segments of a wide variety of frequently purchasedproducts, namely:

(a) high national brand loyal segment(b) national brand loyal segment(c) national brand switcher segment(d) national/private switcher segment(e) last purchase loyal segment(f) private label loyal segment(g) private label switcher segment


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MARKET SEGMENTATION 325(h) national brand switcher (deal) segment(i) deal-oriented segment.A form of loyalty segmentation was devised by Starr and Rubinson

(1978). They derived empirical probabilities from consumers willingness toswtich from a regular brand and used this data to segment consumers into"loyalty groups".

There are certain difficulties in using loyalty segmentation; what appearsto be brand loyalty among consumers may in fact "reflect habit, indif-ference, low price or nonavailability of other brands" (Kotler 1984, p. 263).It is obviously an ambition of many marketers to build strong brand loyaltyfor their products but as yet there are few guidelines available of anypractical value (Chisnall 1985).

Another straightforward way of classifying the consumer is in tenns oftheir product usage. This is sometimes referred to as volume segmentation.The "heavy half" theory popularised by Twedt (1964) argues that in manyproduct fields 30% of the customers account for 80% of the consumption,and that these high volume customers should command maximum marketingeffort. However several authors have questioned Twedt's conclusions. Haley(1968) has pointed out that people do not always buy products for thesame reasons, and therefore are not equally good prospects for a givenbrand. Frank (1968) noted that the "heavy half" is already the "heavyhalf" and may offer little scope for expansion. A study by Barker and Trost(1973) has revealed that volume purchased |>er given time span should beused in preference to purchase frequency as a measure of user rate. Theyfound that either purchase frequency, or size purchased together withnumber of units purchased at one time can be deceptive when used alone.

An interesting paper by Dickson (1982) makes an excellent case for theadoption of the usage situation in market segmentation. He redefinesmarkets and demand in terms of people and usage situations offering thefollowing "Sjjeculative Person Situation Segmentation Matrix for SuntanLotion" as an example of his segmentation framework. (See Figure 8)

Alternatively, many markets can be segmented into non-users, potentialusers, first time users, regular usere, intermittent users or ex-users. Adifferent marketing approach will be required for each of these groups.Little research has been conducted on this topic but at a pragmatic levelmany companies with a high market share will attempt to convert potentialusers into actual users, whereas smaller firms would be more likely toencourage users to switch to their brand.

6. Industrial segmentatioiiAs mentioned in the introduction to this section on Bases for SegmentingMarkets, the majority of segmentation approaches are equally applicable toconsumer and industrial markets (Webster and Wind 1972, Nicosia andWind 1977). Clearly some situational variables are specific to either the


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MARKET SEGMENTATION 327consumer market or to the industrial market, but it should be noted thatthe industrial market can be segmented by geograpfiic, demographic,psychological, psychographic and behavioural variables in just the sameway as the consumer market,

A two stage approach to industrial market segmentation was developedby Wind and Cardozo in 1974, The first sUge is macro-segmentation wherethe market is segmented by bases including industry demographics, size,indtistrial sector (i.e, commercial firm or public sector), SIC (StandardIndustrial ClassiOcation) code and product usage. The second stage calledmicro-segmentation is based on the demographic and behavioural character-istics of decision making units or buying centres. Subsequently ChofTrayand Lillien (1978) attempted to operationalize this second stage of Windand Cardozo's model.

Since this early work much of the academic research has "unfortunatelyattempted to transpose literature on the industrial buying process to explainindustrial market segmentation" (Hlavacek and Reddy 1986, p, 13),Segmentation based on industrial end use, buying power and industrialconcentration are recommended (Chisnall 1986), with insufficient emphasisbeing placed on the development of an understanding of buyers needs.

6. Product segmentationIt should be mentioned for the sake of completeness that it is possible tocluster products rather than consumers by using product segmentation,Bamett (1969), an enthusiastic proponent of tfiis approach, has argued thatresearchers should abandon consumer segmentation and concentrate insteadon deriving product field speciGc criteria by which consumers themselvesdistinguish between brands and products. However "it is just as valuable tocluster consumers in terms of their requirements from product field specificvariables as it is to cluster products in terms of the extent to which they areperceived to satisfy these requirements" (Lunn 1978, p, 366-7),

A full description and critical appraisal of the different methodologicalapproaches to product segmentation can be found in Beazley (1973).Product segmentation has proved especially useful in identifying gajK fornew product oppwrtunities, and in checking which brands or products arecompeting with each other.

REQUIREMENTS FOR EFFECTIVE SEGMENTATIONThere is general agreement in the literature on factors which affect thefeasibility of market segmentation, Kotler (1984) originally cited threefactors namely, measurability, accessibility and substantiality. In laterrevisions he has added a fourth factor, i,e, actionability, A brief^ descriptionof these factors follows:

328 A. CAROLINE TYNAN AND JENNIFER DRAYTONMeasurability This refers to the effective size and purchasing power of asubmarket. It is dependent on the availability of suitable market researchdata concerning the segmentation variable chosen.

Accessibility This is the degree to which a segment can be effectivelyreached and served. It largely rests upon the ability of a firm to direct itsmarketing effort at a particular segment. Media coverage, distribution andthe influence of behavioural factors, all need to be evaluated. It isimportant to choose a media mix which will reach the target segment botheconomically and efficiently. Likewise the distribution network chosen mustbe effective in reaching the sub-segment. Chisnall {1985, p. 265) alsorecommends that "reference should be made to group behaviour, opinionleadership, family life styles" for the sub-segment under consideration.

Substantialitj The segment must be sufficiently large and profitable to beeconomically viable for the firm. Kotler (1984, p. 265) maintains "asegment should be the largest jKJSsible homogeneous group worth goingafter with a tailored program".

Actionability The degree to which a firm can develop and manage effectiveprogrammes for attracting and serving segments. This factor relates to therequirements and capabilities of particular firms.

To these four factors Thomas (1980) adds another, that of "stability" i.e.can you predict the segment's behaviour in the future.

Clearly there are many ways to segment a market, although they are notall equally effective. In order to select an appropriate method of segmentinga particular market, the segment (s) identified must exhibit the fourcharacteristics explained above. If the segment chosen is measurable,accessible, substantial and actionable then in Kotler's words it should be"maximally useful".

CRinCSSMS OF THE THEORY OF MARKET SEGMENTATION

The concept of market segmentation, and most market segmentationstudies, is "based on the premise that the given market is heterogeneous andcan be segmented" (Wind 1978, p. 327). Chisnall {1985, p. 262) goesfurther, he maintains that "practically every market is capable of refine-ment into significant sub-markets". Young et al. (1978) disagree, they havesuggested three occasions in which market segmentation is not useful.

(a) where the market is so small that marketing to a small pwrtion of itmay not be profitable.

(b) where heavy users constitute such a high proportion of the salesvolume that they comprise the only relevant targets.

MARKET SEGMENTATION 329(c) where a brand is the dominant brand in the market. (However, even

here, segmentation provides information about the consumers whoconstitute the target market which will enable the marketing man-ager to "taiior" tbe marketing mix to their needs).

Collins (1971) has argued that the traditional assumption of all marketingstudies that a product can be placed in a market segment is an over-simplification. He considers not all consumers can be placed in a segmentand that most brands of products do not operate within a definablesegment. His hypothesis is that a brand's sales depends on its penetrationand buying rate rather than on the segment size. Collins accepts theconcept of market segmentation in the case of what he calls the "segmentbrands", which he defines as appealing to some relatively restricted sectionof the market and having more heavy than normal buyers. Resruk et al.(1979) have drawn attention to their belief that segmentation has gone toofar. They have identified markets which are hyper-segmented, a conditionthey define in cases where increasingly smaller market segments areidentified and targeted, thus causing corresponding increases in productionand marketing costs. These authors have postulated the strategy of "countersegmentation" as an appropriate response to hyper-segmentation. In countersegmentation market segments are aggregated or clustered so that a simplerproduct is offered, with lower production and marketing costs, and some ofthe savings are passed on to the consumer through lower prices. In spite ofthe interest this paper initially generated the strategy of counter segmentationdoes not appear to have been widely adopted.

While all these criticisms are valid in a small number of cases they arenot universally applicable and thus do not seriously limit the theory orpractice of market segmentation.

CONCLUSION

Market segmentation is clearly a crucial marketing strategy. It enables themarketing manager to divide total demand into relatively homogeneoussegments identified by geographic, demographic, psychological orbehavioural variables. These characteristics are relevant in explaining andin predicting the response of consumers, in a given segment, to marketingstimuli. Once a segment has been identified which fulfils the requirements ofmeasurability, accessibility, substantiality and actionability it is possible todevelop a product or service to meet the needs of the segment. A marketingmix can then be devised to reach the segment identified efficiently andeconomically.

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Barker, S. M. and Trost, J . F. (1973), "Cultivate the high-volume consunier". HarvardBusiness Review , 51(2), pp. 118-122.

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