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Douglas, 1972) which subsequently assists in better matching customer requirementswith the firm’s offerings (McDonald & Dunbar, 1995).

Despite the acknowledged importance of market segmentation for businesspractice, most literature on the topic is conceptual or normative in nature, dealingwith how market segmentation should be conducted (e.g. Kreutzer, 1988; Piercy &Morgan, 1993; Sausen, Tomczak, & Herrmann, 2005; Wind & Douglas, 1972),rather than with how segmentation is actually performed in practice. Moreover, as isalso evident in previous literature reviews on segmentation (e.g. see Beane & Ennis,1987; Plank, 1985; Steenkamp & Ter Hofstede, 2002; Tynan & Drayton, 1987;Walters, 1997), the main focus has been on the choice of segmentation variables(bases) at the expense of other stages of the segmentation process (e.g. marketdefinition, segment formation, evaluation, etc.). Lastly, rather than reviewingempirical findings on firms’ actual segmentation practices, several previous literaturereviews describe applications (i.e. examples and illustrations) of different segmenta-tion schemes (e.g. Choffray & Lilien, 1978; Laughlin & Taylor, 1991; Ter Hofstede,Steenkamp, & Wedel, 1999). As a result of the above, many of the guidelines offeredto practitioners in the market segmentation literature are grounded more onanecdotal evidence and ‘common sense’ rather than on a solid empirical base. AsJenkins and McDonald (1997, p. 18) observe, ‘conventional theory has […] beenfounded on conceptual, rather than empirical evidence’ and this despite the fact that‘anecdotal data is not ideal … to aid in understanding the phenomenon’ (Craft,2004b, p. 87).

Against this background, the purpose of the present paper is to review criticallythe existing empirical literature on firms’ actual market segmentation practices inorder to (a) provide a critical state-of-the-art review of relevant studies, and (b)

develop an agenda for future research based on the identified knowledge gaps. Morespecifically, the added-value of this review is three-fold: First, the identified empiricalstudies are assessed in terms of their methodological characteristics – somethingwhich has been neglected in previous reviews – in an attempt to establish thesoundness of the empirical evidence on market segmentation practices. Whereappropriate, suggestions are also provided on how to achieve methodologicalimprovements in future empirical studies on firms’ actual segmentation practices.Second, findings relating to all stages making up the market segmentation processare reviewed. Such findings are subsequently contrasted with the normativesegmentation literature and points of agreement and divergence identified. In

particular, discrepancies in the application of normative guidelines into actualsegmentation practice are highlighted. Third, based on the identified research gapsrelating to each stage of the market segmentation process, a navigation chart forfuture research efforts is developed. Given that ‘there are big gaps in currentknowledge relating to segmentation practice’ (Walters, 1997, p. 174), this chartshould aid researchers in selecting topics for further study that have beeninsufficiently addressed by extant research.

In the section that follows, we describe our literature review approach in terms of identifying and classifying relevant empirical studies on market segmentationpractices. We then undertake a thorough review of the methodological character-istics of the identified studies and relate their findings to theoretical and normativeliterature bearing on the nature and the stages of the market segmentation process.We conclude the paper by developing a navigation chart for further research.

224 E.K. Foedermayr and A. Diamantopoulos



Empirical research on segmentation practices

Overview of extant research

Based on a thorough search of extant literature, 1 by the time of writing, nineteenempirical studies could be identified which specifically investigated the actual

segmentation practices of firms. To provide an overview of the identified studies,Table 1 classifies them according to their setting (i.e. domestic vs international, andB2C vs B2B) as well as according to the stage(s) of the market segmentation processto which they relate. Several authors (e.g. Croft, 1994; Dibb & Simkin, 1996;McDonald & Dunbar, 1995; Myers, 1996; Wedel & Kamakura, 2000) have provideddescriptions of the stages of the market segmentation process, and the sequenceshown in Table 1 represents a consensus of the various segmentation schemes:market definition, segmentation variable selection, segmentation method selection,segment formation, segment profiling/evaluation/selection, implementation issuesand finally, segmentation strategy evaluation.

Ten of the nineteen studies in Table 1 focus explicitly on international/exportmarket segmentation, whereas nine studies look at segmentation decisions relating toa firm’s domestic market. With respect to their settings, five studies investigate botha B2C and a B2B setting, another eight a B2C environment only, and six focus solelyon the B2B market.

In terms of focus, as Table 1 shows, the majority of the studies (thirteen in all)only deals with a single stage of the market segmentation process. Of those studiesthat consider several stages of the market segmentation process simultaneously,practically all of them also deal with the segmentation variable selection stage, whichis, by far, the most heavily investigated stage.

Having provided a brief overview of empirical research on segmentationpractices, we now undertake a methodological assessment of the identified studiesand follow this with an examination of their key findings (Table 2); while doing this,important gaps in knowledge calling for further research are also identified.

Methodological assessment

Research design / data collectionWe classify the research approaches and designs employed in the empirical studiesinto qualitative versus quantitative (Creswell, 2003) and exploratory versusdescriptive versus explanatory (Pinsonneault & Kraemer, 1993). In terms of the

overall research approach adopted, six studies are qualitative in nature and rely onin-depth (face-to-face or telephone) interviews and case study approaches as datacollection methods. Nine studies are quantitative, all of them involving a mailsurvey. Four studies represent a combination of qualitative and quantitative researchdesigns by carrying out either a combination of unstructured with structuredinterviews or parts of an online survey, or a combination of case studies with asurvey (without specifying the type of the latter).

With respect to research designs, eight studies are exploratory in nature, fivedescriptive and only four explanatory. One study is both exploratory and descriptive(Badgett & Stone, 2005) and another one is both descriptive and explanatory (Erem& Menguc, 1997).

In future research, greater adoption of explanatory research designs would helpidentify key linkages between the various stages of the market segmentation process

Journal of Strategic Marketing 225



Table 1. Overview of empirical research on market segmentation practices.

Market segmentationstage

Number of studies

Domestic studies

B2C B2B

Market definition 1 1(Jenkins, le Cerf,& Cole, 1994)

Segmentation variableselection

13 3(Cross, Belich,

& Rudelius, 1990;Danneels, 1996;

Meadows & Dibb,1998)

4(Abratt, 1993; Crosset al., 1990; Kalafatis

& Cheston, 1997; Wind& Cardozo, 1974)

(BadgCraft, 202006; H

Hassan, C

Segmentation methodselection

1 1(Spring, Verhoef,

Hoekstra, & Leeflang,2000)Segment formation 2 1

(Cross et al., 1990)2

(Abratt, 1993; Crosset al., 1990)

Segment profiling,evaluation and selectionof final target segments

5 3(Callaghan & Morley,

2002; Cross et al.,1990; Danneels, 1996)

3(Abratt, 1993; Callaghan& Morley, 2002; Cross

et al., 1990)

(Simk

Implementation issues 5 3(Cross et al., 1990;

Danneels, 1996;Meadows & Dibb, 1998)

2(Abratt, 1993; Cross

et al., 1990)

Segmentation strategyevaluation

3 1(Wind & Cardozo, 1974)



Table 2. Actual segmentation practices of firms.

Author(s) Focus Product type Country/International Research design/data collection Unit of analysis

Wind &Cardozo(1974)

Use of segmentationbases andevaluation of segmentation-basedmarketingstrategies

B2B (goodsand services):Manu-facturers of industrialgoods andservices

US(Minneapolismetropolitanarea) Notinternational

ExploratoryQualitative +

quantitative(unstructured +

structuredinterviews)

Marketingmanagers

Schuster& Bodkin(1987)

Use of segmentationbases andevaluation of segmentation

B2B (goods):Industrialgoodscompanies

US (Virginia)International

ExploratoryQualitative(telephoneinterviews)

Marketingmanagers



Table 2. continued

Author(s) Marketdefinition

Segmentation variables Segmentationmethod

Segmentformation

Segment profievaluationand selection

Wind &Cardozo(1974)

Three clusters of bases of segmentation:N organization characteristics: industry type,

size of firm, geographic locationN product characteristics: frequency and size

of purchase, end use, specification of product

N DMU (decision- making unit)characteristics: buyer’s identity, sourceloyalty, buyer’s personality

Schuster& Bodkin

(1987)

Macro and micro criteria (in descendingorder):N geographicalN attitudesN criteriaN size of companyN end marketN usage ratesN importanceN buying strategyN decision-making stageN personal characteristicsN buying unitsN buying situationN SIC codeN conflictN organizational innovativenessN financial information



Table 2. continued

Author(s) Focus Product type Country/International

Research design/data collection

Unit of analysis

Crosset al.(1990)

Selection of segmentationbases andinvestigation of criteria appliedto formsegments andselect targets;

marketingactions used toreach the chosensegments

B2C (goods andservices) andB2B (goods andservices):Consumergoods and/orservices firmsand industrial

goods and/orservicescompanies

US (largemetropolitanarea) Notinternational

ExploratoryQualitative andquantitative(telephoneinterviews)

Marketingand productmanagers

Abratt(1993)

Selection of segmentationbases andinvestigation of criteria appliedto formsegments andselect targets;marketingactions used toreach the chosensegments

B2B: Industrialcompanies (noindicationwhether goodsand/or services)

South AfricaNotinternational

DescriptiveQuantitative(mail survey)

Marketingmanagers andmarketingdirectors



Table 2. continued



Segmentformation


Crosset al.(1990)

N Firm’s characteristicsN DemographicsN GeographicN Application/useN Benefits to buyerN Usage rateN PsychographicsN Buying situation

N Feasibilityof marketingaction

N Potentialfor increasedprofit/ROI

N Similarityof needswithinsegment

N Differenceof needs

betweensegments

N Simplicityof assigningto segments

N Stabilitythrough time

N Size of marksegment

N Compatibilitwith objectivresources

N ProfitabilityN Expected gr

of segmentN Ability to re

buyersN Competitive

in segmentN Cost to reac

Abratt(1993)

N GeographicN DemographicsN Usage rateN Buying situationN Application/useN

PsychographicsN ValuesN BenefitsN Other Purchasing

organization

Criteriaapplied fromCross et al.(1990)

Criteria appliefrom Cross et(1990)



Table 2. continued



Unit of analysis

Jenkinset al.(1994)

Investigationof conceptcategoriesapplied fordefining the

market

B2C (goods):Consumergoods firms

UK Notinternational

ExploratoryQualitative(semi-structuredin-depth interviews)

Marketingmanagers

Danneels(1996)

Application of segmentationbases andselection of target segments;identification of implementationproblems

B2C (goods):Consumergoods firms

Belgium Notinternational

ExploratoryQualitative(semi-structuredin-depth interviews)

Owners ormarketingmanagers





Segmentformation


Jenkinset al. (1994)

Conceptcategories fordefining themarket:N ProductN ChannelN ConsumerN BrandsN GeographyN Consumer

functionN Product

volumeN Packaging

Danneels(1996)

Socio-demographics; socio-culturalvariables gain importance; ‘reference age’(i.e. consumers’ mental age – the age theyidentify with and feel and act like)

Target marketemerges in agradual proces(STP not linkin a uni-directprocess butconnected in aiterative feedbprocess)

Table 2. continued



Table 2. continued



Unit of analysis

Erem &Menguc(1997)

Investigationof thesignificance of common exportmarketsegmentation

bases

B2B (goods):Manufacturersof industrialgoods

TurkeyInternational

Descriptive/explanatoryQuantitative(mail survey)

Exportmanagers

Kalafatis&Cheston(1997)

Application of segmentationbases

B2B (goods):Industrialgoods firms

UK Notinternational


Pharmaceuticalcompanies (nofurtherinformation)





Segmentformation


Erem &

Menguc(1997)

Classification of 50 market segmentation

criteria into 17 conceptual categories (indecreasing order of perceived importance):N Market potential/profitability/

attractivenessN Political/legal considerations and riskN Demand/behavioural characteristics of

buyersN Socio-economic environmentN Economic/legal constraints in a marketN Competition and new competitorsN Demographic environmentN Long/short term goals, objectives and

resources of firmN

Geographic position and regionalcharacteristicsN Structural characteristics of marketN Competitiveness of firmN SubstitutesN Strength/weakness of firmN Marketing channelsN Cultural characteristics of productN Cultural environmentN Industrial/technological infrastructure of

market

Kalafatis &Cheston(1997)

17 macro and micro segmentation variableswere classified into four groups:

N Type of industryN Organizational characteristicsN Characteristics of the DMUN Product related benefits

Table 2. continued



Table 2. continued



Unit of analysis

Meadows& Dibb(1998)

Usage of segmentationbases andidentificationof implementationbarriers

B2C (services):Consumerservices firms

UK Notinternational

Exploratory Qualitative(case study approach)

Well reputedbanks (nofurtherinformation)

Simkin &Dibb(1998)

Usage of attractivenesscriteria toevaluate andselect targetmarkets

B2C and B2B:Consumer andindustrial firms(no indicationwhether goodsand/or services)

UKInternational

Descriptive Quantitative(mail survey)

Marketingdirectors



Table 2. continued



Segmentformation


Meadows &Dibb (1998)

Mostly demographic variables (e.g. age,income social class). Only one bank collectsattitudinal data and behaviouristicsVariables proposed: customer attitude data

Simkin &Dibb (1998)

23 marketattractiveness (derived fromliterature and idiscussions wimarketing manMost heavily u

criteria: profitamarket growthmarket size



Table 2. continued



Unit of analysis

Spring etal. (2000)

Usage andselection of segmentationtechniques

B2C: Consumerfirms (noindicationwhether goodsand/or services)

TheNetherlandsNotinternational


Marketingmanagers

Dibb &Simkin(2001)

Identification of implementationbarriers andsuggestion of ways to

diagnose andtreat them

B2B (goodsand services):Industrial goodsmanufacturersand industrial

service firms

UKInternational

ExploratoryQualitative(case studyapproach)

Seniormanagers



Table 2. continued



Segmentformation


Springet al. (2000)

Usage of techniques forsegmentation:Cross-tabulations,RFM, linearregression,cluster analysis,factor analysis,chaid orCART,discriminantanalysis, logit-probit analysis,neuralnetworks,geneticalgorithms

Dibb &Simkin(2001)



Table 2. continued



Unit of analysis

Callaghan& Morley(2002)

Usage of criteria toevaluate andselect targetsegments


Australia Notinternational


Marketingdirectors

Hassanet al.(2003)

Usage of segmentationbases


USInternational

ExplanatoryQuantitative(mail survey)

Managers

Craft(2004a)

Usage of segmentationbases andformation of customersegments

B2C (goods):Consumer goodsfirms

USInternational

ExploratoryQualitative(case studyapproach)

Executive-levelkey informants



Table 2. continued



Segmentformation


Callaghan &Morley(2002)

40 criteria fromliterature (mosimportant onedecreasing ordrating):N Profitability

segmentN Sales volume

potentialN Competitive

intensity insegment(s)

N Reputation wcustomers insegment

N Current/potenmarket share

N Ability of buprovide addeto the segme

N Size of segmN Fit with busi

strategyN Ease of acce

through distrchannel

N Firm’s abilitydeliver adifferentiatedproduct offer

Hassan et al.(2003)

14 macro- and 22 micro- level variables

Craft(2004a)

Macro variables (for country selection) andmicro variables (for selecting specificconsumer segments within target countries)



Table 2. continued



Unit of analysis

Craft(2004b)

Identification of internationalsegmentationperformancemeasures forevaluatingsegmentationstrategies

B2C (goods):Consumer goodsfirms for casestudies; however,no informationprovided on 62companies

USInternational

Explanatory Qualitative(case studies with sample1) Quantitative (surveywith sample 2; sort of survey not specified)

Keysegmentationdecision maker(identifiedaccording totheirqualification torespond and

not their formarole in theorganization)

Badgett& Stone(2005)


B2C (goodsand services):Consumergoods andservicesfirms

International(with themajority of firmsinterviewedbases in theUSA)

Exploratory/descriptiveQualitative andquantitative part (of online survey)

Executives inmarketing andsales



Table 2. continued



Segmentformation


Craft(2004b)

Badgett &Stone (2005)

Usage of segmentation variables(relative frequencies)N

Demographic (77)N Needs-based (66)N Profitability/value (63)N Behaviour-based (37)N Life-stage (34)N Occasion-based (21)N Attitudinal (20)N Other (1)





Unit of analysis

Hassan &Craft(2005)

Determiningthe majormacro andmicrosegmentationbases andlinking themwith differentialpositioningstrategies


USInternational


Managers

Craft &Hassan(2006)


B2C: Consumerfirms (noindicationwhether goodsand/or services)

USInternational


Segmentationdecision maker(identifiedaccording totheirqualification torespond and

not their formarole in theorganization)

Table 2. continued





Segmentformation

Segment profevaluationand selection

Hassan &Craft (2005)

14 macro- and 22 micro-evelvariables

Craft &Hassan(2006)

17 country attractiveness and22 within-country segment variablesdrawn from literature

a The sampling method is not specified in the study but based on the authors’ read of the samples.

Table 2. continued



and building comprehensive models of market segmentation practice; unfortunately,to date, neither of these issues has been systematically examined in extant empiricalresearch.

Unit of analysis / respondentsThe unit of analysis in all studies is the individual firm and the respondents are keydecision makers (mainly marketing directors/managers) directly involved in marketsegmentation decisions. In most studies, the ‘key informant’ approach (Seidler, 1974)to selecting respondents is prevalent, whereby respondents are chosen on the basis of their possession of in-depth knowledge and experience specific to the topic of interest(Kumar, Stern, & Anderson, 1993). With the exception of Danneels (1996), allrespondents in the empirical studies are solely ‘internal’ informants, 2 thus, in futurestudies external experts (e.g. marketing research agencies, marketing consultancies,advertising agencies) who are often consulted by firms for assistance when

developing and implementing segmentation strategies (Dibb, 1998) should addition-ally be considered as respondents to obtain a more comprehensive picture of marketsegmentation expertise (Marschan-Piekkari, Welch, Penttinen, & Tahvanainen,2004).

In three studies, multiple informants were used in combination with a case studyapproach as the data collection method. Apart from two studies that do not provideany information on their respondents, 3 the remaining fourteen studies rely on singleinformants as their respondents. The difficulty with single informants is that insightsare obtained from one source only and may thus be potentially biased (e.g.marketing managers may have particular preferences for specific target segments,product lines or brands and thus provide a subjective view which need not fullyreflect the company perspective). In contrast, with multiple informants, company-wide market segmentation expertise can be pooled and a more objective and cross-departmental view reflecting the company perspective can be obtained. However,potential drawbacks related to a multiple informant approach may be a clash of views between several respondents within a firm.

As all extant studies focus on the individual firm as a single entity but lack aninvestigation of several alternative units of analysis within a firm, a more detailedpicture of a company’s segmentation practices can be obtained by paying greaterattention to simultaneously investigating alternative units of analysis within the samefirm such as various strategic business units (SBUs), different countries of operationor specific brands offered. The reason behind this is that different segmentationdecisions may be applied to different SBUs, countries and brands according to theirspecific characteristics and their strategic importance to the firm.

Sampling In about half of the studies (namely nine) the sampling frame from which the samplewas drawn is indicated to be a listing/directory of firms (e.g. Kompass Directory,Exporters Directory, Directory of Key British Enterprises, UK Times 1,000Companies). As such sampling frames are more accurate and complete than self-compiled lists of companies, sampling frame error is reduced (Malhotra & Birks,2003). In the rest of the studies, no information is provided about the samplingframes applied.




The sampling methods used to draw the samples are mainly non-probabilistic innature, which may be due to pragmatic reasons (i.e. being more convenient andquicker as well as less expensive and more accessible than probability methods).More specifically, in most cases (i.e. eight studies) a purposive sample was drawn, 4

followed by judgemental sampling (i.e. six studies). 5 Convenience sampling wasrelied on twice and quota sampling once. In contrast, a probability method (randomsampling) was used only in two studies. 6 The main drawback faced with non-probabilistic sampling methods is that they do not permit statistical evaluation of sampling error (Lohr, 1999). Furthermore, it is problematic to estimate populationparameters or test hypotheses with non-probabilistic samples because inferentialstatistics make use of estimates of sampling error (Henry, 1990).

With regard to sample size, the sample sizes utilized are generally small, rangingfrom only four (Dibb & Simkin, 2001; Meadows & Dibb, 1998) to one hundred andninety-eight (Spring et al., 2000), with an average sample size of sixty-fourrespondents. With small sample sizes, the results obtained only from a limitednumber of firms are subsequently attributed to firms in general in order to providean overview of segmentation practices in a certain industry or country (see, forexample, Cross et al. (1990) who differentiate between consumer and industrialmarkets, as well as between product and service offerings within each of the twomarkets with an overall sample size of only thirty-two companies).

The fundamental problem with small sample sizes is that sampling error tends tobe higher (Henry, 1990), thus negatively impacting on the precision of populationparameter estimates (given a certain level of confidence) (Barnett, 1991). Hence, theresulting confidence intervals tend to be wider and significance tests less powerfulthan is the case with large samples (Kalton, 1983). Accordingly, use of larger sample

sizes in future studies would offer higher degrees of precision and confidence in theresults which, in turn, would enable more meaningful generalizations of segmenta-tion practices.

Sample sizes also need to be considered in light of the (expected) response rate. Inthe studies where response rates were specified, they range from a very low 6% withan online-survey (Badgett & Stone, 2005) to exceptionally high 74% with a mailsurvey (Erem & Menguc, 1997). In general, however, studies achieved satisfactoryresponse rates (on average 27%); thus the small sample sizes observed above cannotbe (only) attributed to low response rates.

Validity and reliability

A critical issue highlighted by Table 2 is the general lack of validity and reliabilityassessments in empirical research on segmentation practices. All in all, only three outof nineteen studies explicitly reported on validity assessment approaches and onlytwo on reliability assessment procedures.

With respect to validity, two studies (i.e. Craft, 2004b; Cross et al., 1990) dealtwith the assessment of content validity, which captures the extent to which a specificset of items reflects a content domain (DeVellis, 2003). In both studies, marketingmanagers were solicited to screen the initial items. A third study (Jenkins et al., 1994)reported on face validity, which indicates the extent to which a set of items appearsto measure what it is supposed to measure, as judged by key segmentation decisionmakers (DeVellis, 2003).




Although criterion validity (i.e. concurrent and/or predictive validity) was notexplicitly mentioned in the studies, predictive validity can be reasonably inferred intwo of the studies: Hassan and Craft (2005) conducted a regression analysisconstructing four regression models where seven underlying segmentation bases(three macro-level and four micro-level) identified in a previous study (Hassan et al.,2003) were utilized as predictor variables and each of four strategic positioningoptions as the criterion variable. Craft and Hassan (2006) also ran a regressionmodel using the factor scores of ten underlying segmentation bases and three factorson scale of segment management as independent variables and a performancemeasure labelled ‘success of the firm’s segmentation strategy’ as the dependentvariable. Thus in both studies predictive validity can be inferred for the segmentationbases linked to the respective outcome variables.

Since none of the studies in Table 2 reported on an assessment of any form of construct validity (i.e. convergent, discriminant and nomological validity) thetheoretical soundness of the measures used in empirical research on segmentationpractice cannot be taken for granted.

Regarding the reliability of the studies under consideration, only two studies (i.e.Hassan & Craft, 2005; Hassan et al., 2003) assessed internal consistency reliabilityusing Cronbach’s alpha for a set of 14 macro-level ( a 5 0.904) and 22 micro-levelsegmentation variables ( a 5 0.923). 7 While the obtained alpha values well exceed thecommonly used threshold of 0.7 (Nunnally, 1978), it should be born in mind thatcoefficient alpha is not only a function of the magnitude of intercorrelation of theitems in a scale but also of their number (i.e. scale length); thus a may also be partlydue to the high number of items (i.e. 14 and 22, respectively) comprising the assessedmeasures.

The general lack of validity and reliability assessments in the empirical studies onfirms’ actual segmentation practices puts into question the psychometric propertiesof the measures utilized and, hence, the robustness of the reported findings. Thus,greater attention to different types of validity (i.e. content, criterion and constructvalidity) and reliability (i.e. internal consistency as well as test–retest reliability andsplit-sample reliability) assessment should be a top priority in future research onsegmentation practices.

Method of analysis

With respect to the methods used to analyse the collected data, content analysis(applied in eleven studies) and descriptive statistics (thirteen studies) were the mostpopular analytical methods. Inferential statistics (involving hypotheses tests orconstruction of confidence intervals) were only applied in six studies (see Table 2).

With content analysis, in-depth interviews were generally conducted, taped(Craft, 2004a, 2004b), transcribed (Craft, 2004a, 2004b; Danneels, 1996; Jenkins etal., 1994), sometimes coded (Jenkins et al., 1994), and protocols were first reviewedcase by case and then cases were compared (Danneels, 1996). Although not explicitlyindicated, this analysis roughly corresponds to the two-pronged analysis strategy of Miles and Huberman (1994), that is, within-case analysis is followed by cross-casecomparisons to draw meaningful conclusions. With descriptive statistics, mainlyabsolute and relative frequencies were calculated and modes reported. In a fewstudies, means were also calculated and, very rarely, standard deviations. Finally, the




inferential statistics applied were – with the exception of ANOVA (Erem & Menguc,1997) – all multivariate, namely cluster analysis (Erem & Menguc, 1997),multidimensional scaling (Wind & Cardozo, 1974), regression (Craft & Hassan,2006; Hassan & Craft, 2005) and most frequently factor analysis (Craft, 2004b; Craft& Hassan, 2006; Hassan & Craft, 2005; Hassan et al., 2003).

More sophisticated data analysis techniques such as structural equationmodelling which would allow testing complex theoretical models with severalconstructs have not been used in the studies listed in Table 2.

In summary, our methodological assessment of empirical studies on marketsegmentation practices has revealed a preponderance of exploratory and descriptiveresearch designs; a heavy reliance on non-probabilistic sampling methods; relativelysmall sample sizes; lack of adequate psychometric assessment of the measuresemployed; and, with few exceptions, rather basic statistical analyses of the collecteddata. These limitations need to be born in mind when considering the findings of thestudies in Table 2, a discussion of which now follows.

The market segmentation process: empirical findings

Market definition

According to the conceptual literature, defining the market is the first stage of themarket segmentation process (Croft, 1994) and one of the most crucial decisions forits success (Weinstein, 2006) because ‘effective strategy analysis hinges on the properdefinition of the market’ (Day, 1981, p. 281). Therefore, it is essential to find ameaningful balance between a broad and a manageable market definition, since toonarrow a definition can restrict the range of new opportunities segmentation could

open up for a firm, whereas too broad a definition might result in overwhelming thesegmentation exercise (McDonald & Dunbar, 1995). In this context, a market shouldnot simply be viewed in terms of a geographic area, product (what is often the casewith small firms), industry, state-of-action (e.g. frequent flyers) or state-of-mind (e.g.‘techies’); instead, defining the market should integrate several dimensions – customer needs, customer groups, competition, products and technologies(Weinstein, 2006).

Only one empirical study (Jenkins et al., 1994) could be identified on howmanagers actually define their markets. Its findings reveal that marketing managersof fast moving consumer goods organizations rely on the market as a collection of

products rather than customers because ‘all the respondents included a product-based concept in their definition’ (Jenkins et al., 1994, p. 185); only three out of theeighteen firms investigated considered a ‘consumer concept category’ and two a‘consumer function market concept’. These results are contrary to the viewdominating the marketing literature whereby markets should be defined as groupsof customers who acquire products to satisfy their needs and wants (Kotler & Keller,2006). Companies which ‘organize their marketing effort principally around the products they make, [miss] many opportunities for creating competitive advantage’(McDonald & Dunbar, 1995, p. 9, emphasis in original).

Given that several ways of defining the market have been proposed in theliterature (see Day, 1981; McDonald & Dunbar, 1995; Weinstein 1998, 2006 foralternative schemes) and bearing in mind that ‘different market definitions areneeded for different strategic purposes’ (Day, 1981, p. 281), future research should




investigate the underlying objectives which drive firms in their market definitions.For instance, an organization of which the main concern is short-run marketingplanning is supposed to emphasize a narrow market definition which reflects thepresently served markets because these are the markets where customer needs arecurrently satisfied and marketing planning is undertaken. In contrast, when theobjective is to analyse environmental threats and opportunities for new ventures, amuch broader market definition would be required comprising not only currentcustomer needs and firm capabilities but also competitors’ products, resources, likelyreactions and technological developments (Day, 1981). In this context, the specificobjective(s) underlying the market definition could well explain why the firmsinvestigated by Jenkins et al. (1994) mainly relied on a product concept whendefining their markets. Future research should also investigate whether smaller firmswhich are more constrained in terms of financial resources than their largercounterparts tend to define their markets from a narrower perspective byconcentrating on manageable niches where financial risks tend to be more easilycontrollable or whether highly customer-oriented firms which strongly focus on theircustomers’ preferences and needs (Brady & Cronin, 2001; Saxe & Weitz, 1982) tendto rely more on a customer- versus a product-based market definition than lesscustomer-oriented firms.

Segmentation variable selection

After the market has been defined, segmentation variables (bases) have to be selectedat the next stage of the market segmentation process. Segmentation variables are‘set[s] of characteristics that [are] used to assign [customers] to segments’ (Steenkamp

& Ter Hofstede, 2002, p. 196). Thus, segmentation variables indicate why segmentsdiffer, as they partition the market in such a way that those customers are aggregatedwho are similar along the chosen segmentation variable(s) (Dibb, 1995) and thusexhibit relatively similar responses to marketing stimuli (Baalbaki & Malhotra, 1993;Jain, 1994; Rudelius, Walton, & Cross, 1985). Since different variables naturallyresult in different classifications/segments (Cheron & Kleinschmidt, 1985), theirappropriate selection is of crucial importance in market segmentation tasks(Nachum & Ayal, 1994).

As Frank, Massy and Wind (1972) and Wedel and Kamakura (2000) discuss,segmentation variables can be classified into general (i.e. independent of products,

services and circumstances) and product-specific variables (i.e. specifically relating tothe customer and the product). Furthermore, segmentation variables can be eitherobservable (i.e. they can be measured directly, as, for example, customer demographicsor usage frequencies) or they have to be inferred (as is the case with psychographics andperceived benefits). They can further be classified into macro- and micro-levelindicators. Macro-level indicators such as economic factors (e.g. level of economicdevelopment), technological characteristics (e.g. internet penetration), geographicalfactors (e.g. location), cultural dimensions (e.g. language) or demographics (e.g. agedistribution) are typically applied when countries constitute the unit of analysis.However, macro-level indicators do not provide sufficient detailed information formanagerial decisions because they do not explicitly focus on individual customerspecificities but on country aggregates (Steenkamp & Ter Hofstede, 2002). In contrast,micro-level indicators can be directly linked to specific customer needs, characteristics




and customers’ desired benefits (Bonoma & Shapiro, 1984) and are thus used when theindividual customer (either a consumer or an industrial organization) is to be explored.In the case of segmenting consumer markets, consumer demographics (e.g. age, gender,income), psychographics (e.g. values, lifestyles, personality), behavioural characteristics(e.g. usage rate, loyalty status, benefits sought) can be used, whereas in B2B marketsindustrial segmentation criteria include firm demographics (e.g. firm size, industry type)and purchasing approaches (e.g. centralized or decentralized purchasing organization,user status, order size).

Our analysis of empirical studies on actual segmentation practices of firms (seeTable2) reveals widespread use of several segmentation bases simultaneously. 8 Mostfrequently applied are demographics, geographic and economic variables (e.g. Erem& Menguc, 1997; Hassan et al., 2003) and also psychographics and values/attitudes(e.g. Abratt, 1993; Badgett & Stone, 2005; Craft, 2004a; Schuster & Bodkin, 1987).In this context, more importance tends to be attached to general (rather thanproduct-specific) variables although product-specific unobservables (e.g. benefits,attributes, perceptions, preferences, intentions) are considered to be most effectivefor future marketing instrument and marketing mix developments (Wedel &Kamakura, 2000). Furthermore, micro indicators are preferred over macroindicators. The latter, if applied at all, are always used in combination with microcharacteristics (which is always the case in B2B markets). This is particularlyimportant in an international segmentation context, where macro-level indicators arefirst applied to select countries and micro-level criteria are subsequently employed toform customer segments within those target countries (see Craft, 2004a and Hassanet al., 2003 in Table 2) so as to derive cross-national segments, that is, inter-marketand global segments (Agarwal, 2003; Ter Hofstede, Wedel, & Steenkamp, 2002;

Yavas, Bronislaw, & Green, 1992).9

Erem and Menguc (1997) found significant differences among industries 10 interms of the importance attached to different political/legal considerations and risk,market potential/profitability/attractiveness, structural characteristics of the marketand industrial/technological infrastructure of the market as segmentation variables;however, no significant differences could be found across industries in terms of therelative ranking of these segmentation variable categories. Erem and Menguc (1997)also identified significant differences in the perceived importance of marketsegmentation categories across principal export destinations. 11 However, again,exporters’ importance ranking of market segmentation categories revealed no

significant differences across principal export destinations.Strong support for a hybrid/integrated approach to international segmentation isprovided by Hassan et al. (2003) when investigating the impact of identified macro-and micro-level factors of segmentation variables on targeting and positioningdecisions. By running a regression analysis to capture the influence of these factorson positioning strategies (standardization vs adaptation), they aimed to identifyconsumers who share the same expectations and requirements towards products,irrespective of their cultural and national differences, thus enabling the targeting of global consumers with standardized products.

Similarly, in a more recent study, Hassan and Craft (2005) examined the effect of each of the previously defined macro- and micro-level factors (see Hassan et al.,2003), on each of four different positioning options 12 and revealed/confirmed that acombination of macro- and micro-level variables is required when a similar strategic




positioning is to be leveraged across global markets, whereas micro-level bases aresuggested for differential positioning strategies.

In the most recent empirical study identified, Craft and Hassan (2006) developedten factors capturing different segmentation dimensions by means of factor analysisbased on seventeen country attractiveness and twenty-two within-country indicatorsdrawn from literature. Running a regression model they revealed that firms canincrease their performance by utilizing within-country segmentation bases as adecision element in segmentation strategy (significant results were obtained forwithin-country factors only, i.e. market potential, culture and socio-economic level).

Interestingly, only a single study (Wind & Cardozo, 1974) reports on howsegmentation variables are actually evaluated by marketers. The segmentationvariables used to segment industrial markets were grouped into three clusters bymarketers (organization characteristics, characteristics of decision making units andproduct characteristics) and evaluated on two dimensions, 13 the first one being madeup of several aspects (namely costs, ease of identifying segments and differentiatingmarketing programmes, and acceptance of bases by the marketing personnel) andthe second dimension assessing the appropriateness of a segmentation variable, withthe appropriateness criterion being ‘construed as a global evaluation, one which hadnormative futuristic implications’ (Wind & Cardozo, 1974, p. 162). The findingsreveal that ‘characteristics of decision-making units’ is evaluated as the mostappropriate cluster of segmentation variables, while being also considered as mostcostly to identify and least acceptable to marketing management! More generally,the same cluster of variables was evaluated highly positively on one dimension (i.e.appropriateness), but not so on the other dimension (i.e. costs, acceptance bymarketing personnel). This suggests that ‘often, a trade-off between the costs and

applicability of the segmentation basis is made’ (Verhallen, Frambach, & Prabhu,1998, p. 306) because ‘management often faces segmentation tensions between thetheoretically desirable and the managerially possible’ (Bonoma & Shapiro, 1983,p. 258). However, care has to be taken since the study of Wind and Cardozo (1974)was undertaken more than thirty years ago and, therefore, its results may not stillhold today.

Although the selection of segmentation bases is that stage of the marketsegmentation process which has been most heavily investigated (see Table1 earlier),further research should go beyond investigating which variables are applied andfocus on why and under which circumstances particular segmentation variables are

chosen. The rationale behind is that different firms may select the same variables fordifferent reasons (e.g. ease of use due to being easily observable, being internallyavailable and/or less costly). Furthermore, future research should investigate theimpact of likely antecedents (e.g. firm size, international involvement/experience,product type, customer orientation) on the choice of different types of segmentationvariables as well as the number of different segmentation variables used.

Moreover, as the stages of the market segmentation process are interrelated(Danneels, 1996; Goller, Hogg, & Kalafatis, 2002), the choice of the number and/ortypes of segmentation variables directly impacts on subsequent stages (e.g. onsegment formation) and is itself influenced by how broadly/narrowly the marketboundaries are defined. Thus future research should examine the linkages betweensegmentation variable selection and usage and decisions related to earlier/subsequentstages of the market segmentation process.




Segmentation method(s) selection

Deciding on the segmentation method(s) is the third stage of the segmentationprocess. Segmentation methods can be classified into a-priori versus post hocmethods and into descriptive versus predictive methods (Wedel & Kamakura, 2000;

Wind, 1978). When the number and type (e.g. customer-characteristics-based orproduct-related) of segments is determined in advance (i.e. without performing anystatistical analysis) and is mainly based on judgement/prior experience and/orsecondary data, the segmentation approach is called a-priori. In contrast, with posthoc approaches the number and type of segments are determined based on the resultsof data analysis, that is, segments are defined by grouping customers on a set of relevant characteristics, not knowing the type and resulting number of segmentsbeforehand (Rudelius et al., 1985; Wedel & Kamakura, 2000).

With respect to the descriptive versus predictive distinction, with descriptivesegmentation methods, no distinction is undertaken between dependent andindependent variables because the aim is to identify relations between variablesand the units of analysis (Wedel & Kamakura, 2000). For instance, cluster analysis isapplied to group customers according to similarities in lifestyle and/or purchasebehaviour. Application of predictive methods, on the other hand, involves linking aparticular dependent variable (e.g. usage rate) to a set of independent variables (e.g.socio-demographic and psychographic characteristics) and using the latter assegmentation criteria (Backhaus, Erichson, Plinke, & Weiber, 2003).

Although ‘researchers do not appear to have agreed on the most suitabletechnique to use in a given situation’ (Hoek, Gendall, & Esslemont, 1996, p. 25),‘post hoc segments are often much more useful than a priori segments, because theymore directly reveal how people view a specific type of product/service category’(Myers, 1996, p. 67). More specifically, post hoc predictive techniques are the mostpowerful algorithms for market segmentation because they allow a simultaneousprediction and classification. For instance, by means of clusterwise logit models,customer segments can be identified which are homogeneous in their brandpreferences and in their response to price and sales promotions; hence, a directlinkage between actual behaviour in the marketplace and managerially actionablevariables of the marketing mix is provided (Wedel & Kamakura, 2000). However,more sophisticated techniques require specific software programs, technical expertiseand more experience (Dibb, 1998); thus lack of firm resources may be a barrier totheir adoption.

Empirical studies on actual segmentation practices of firms provide hardly anyinformation about the segmentation methods selected by practitioners. The onlyempirical study that could be identified (Spring et al., 2000) revealed that thetechniques applied by far most frequently are cross-tabulation, followed by RFM(recency–frequency–monetary value), 14 linear regression and cluster analysis. Incontrast, more sophisticated techniques such as logit–probit analysis, neuralnetworks and genetic algorithms were least frequently employed, which Spring etal. (2000, p. 5) explained by the fact that ‘managers are faced with time problems andtherefore still rely on techniques or rules used for many years’. What is perhaps mostsurprising, however, is that about one-third of respondents did not use any of thesegmentation techniques listed by the authors but instead relied on intuition or gutfeeling, due to their unfamiliarity with the techniques (almost half of the non-users




were not even aware of the more sophisticated techniques) and/or difficulties tounderstand and apply them.

Against this background, future research should investigate whether marketersstill rely on intuition and relatively simple segmentation techniques and identifyspecific barriers that prevent practitioners from using more sophisticated andeffective methods. In this context, while such barriers as lack of familiarity withsegmentation techniques and associated software can be overcome by buying inassistance from external experts, resource constraints may prevent some firms(particularly smaller ones) from taking such steps.

Future research should also explore the impact of the segmentation variableschosen by the firm (see previous section) on its selection of segmentation methods;for example, if demographic variables are used to group consumers, basicdescriptive statistics may be sufficient in order to identify distinct segments. Onthe other hand, if, say, psychographic segmentation bases are applied, the use of more sophisticated methods (e.g. factor and/or cluster analysis) may be unavoid-able.

Finally, future research should examine whether the application of moresophisticated segmentation methods has a greater impact on the success of segmentation efforts than simple methods. Since more sophisticated techniquesrequire more resources (e.g. bearing acquisition costs of specialized programmes,internal and/or external expertise and know-how), the trade-off between extra costs/efforts and a supposed higher success of sophisticated techniques has to be weighted;thus providing an empirically based justification whether sophisticated methodsshould increasingly be applied in business practice or whether simpler segmentationtechniques are good enough.

Segment formation

The fourth stage of the market segmentation process deals with the formation of market segments, that is, segments are created without considering their attractive-ness (Dibb, 1999).

When forming segments, two general aspects need to be considered: first, eachsegment needs to be made up by an economical minimum number of customers tooffer an economical value or volume of sales; second, the number of segmentsformed needs to be manageable to be handled by the firm (McDonald & Dunbar,

1995). While too many segments will lead to difficulties in terms of inter-segmentheterogeneity, too few segments may hinder the success of the segmentation processdue to lacking intra-segment homogeneity (Rudelius et al., 1985). In this vein, ‘thebiggest problem for the analyst is that of deciding which of several possiblelegitimate solutions makes the most sense’ (Myers, 1996, p. 21).

Empirical knowledge on the segment formation stage is rather limited.Specifically, only two empirical studies investigate which decision criteria areapplied to form segments. Cross et al. (1990) find out that US managers prefer‘feasibility of a marketing action’ and ‘potential for increased profit/return oninvestment’ over ‘similarity of needs within a segment’ and ‘differences of needsbetween segments’, although the latter two criteria are proposed in academicliterature as being most appropriate to use when forming segments (e.g. Dickson &Ginter, 1987; Grover & Srinivasan, 1987). Abratt (1993), in contrast, reveals that




South-African managers ascribe more importance to ‘similarity of needs within asegment’, followed by ‘feasibility of marketing action’.

Abratt (1993) attributes the difference in results compared with Cross et al.(1990) to differences in market conditions in the two countries but does not explorewhether underlying factors such as environmental factors (e.g. competitive intensity,technological turbulence, industry specificities) lead to these market-specificdiscrepancies. Since the decision criteria for forming segments may also be shapedby management characteristics (e.g. highly customer-oriented firms may considersimilarity of needs within segments as more important than, say, potential forincreased profit), future research should investigate the impact of contextual factorson the decision of segment formation criteria.

Future research should also investigate the implications of segment formationfor subsequent stages such as implementation issues. For instance, firms which focusstrongly on feasibility of marketing action (as opposed to, say, potential forincreased profit) as a segment formation criterion already take into consideration thepracticability of marketing mix decisions for the formed segments, which directlyimpacts on implementing marketing programmes.

Profiling, evaluation and final selection of target segments

Six criteria have frequently been suggested in literature in order to evaluate theattractiveness of the segments formed (Baker, 2003; Frank et al., 1972; Kotler &Keller, 2006, Wedel & Kamakura, 2000): identifiability is the extent to whichmanagers can recognize distinct groups of customers in the marketplace by usingspecific segmentation bases; the substantiability criterion is satisfied if the segments

represent a large enough portion of the market to ensure the profitability of targetedmarketing programmes; accessibility is the degree to which managers are able toreach the targeted segments through promotional or distributional efforts;responsiveness is satisfied if segments respond uniquely to marketing efforts targetedat them; stability signifies segments that are stable over time and do not change theircomposition or behaviour during the implementation of a targeted marketingstrategy; finally, segments are actionable if their identification provides guidance fordecisions on the effective specification of marketing instruments.

In addition to these six criteria, Piercy and Morgan (1993) add that theevaluation of the formed segments should moreover focus on the internal capability

of the firm, namely the extent to which both its structure and processes are consistentand compatible with the proposed segments. Furthermore, when finally selecting thetarget segments, it would be essential to also consider whether the selected segmentscan create and sustain competitive differentiation and advantage, are compatiblewith the company mission and are consistent with corporate values and cultures.

For profiling segments, Rudelius et al. (1985) propose that both customerdescriptors (e.g. demographics, attitude variables) and behavioural correlates (e.g.product use situations, media exposure, price preferences) should be used. While theformer characterize the typical customer in each segment, the latter have directrelevance for marketing strategy development as they are situation specific andconstitute important inputs to marketing mix decisions.

While profiling segments is not considered by any of the studies in Table 2, fivestudies address how to evaluate segments in order subsequently to select final target




segments. Cross et al. (1990) identified a total of seven criteria which managers of USfirms use to evaluate and select segments (in decreasing order of usage byrespondents), which constitute a combination of several of the six conventionalsegment attractiveness criteria and the additional criteria indicated by Piercy andMorgan (1993): segment size; compatibility with objectives and resources; profit-ability; growth expectations; ability to reach buyers in the segment; competitiveposition of the company in the segment; and cost to reach buyers. Abratt (1993)simply adopted and applied these criteria to his empirical investigation in SouthAfrica. He revealed that firms assign different priorities to the various criteria, thatis, those which Cross et al. (1990) discovered to be least important for target segmentselection in the USA were precisely those criteria which South African companiesconsidered to be most important (namely ability to reach buyers in the market andcompetitive position in the market). He again explained his findings in terms of thedifferences in the markets in South Africa and the USA.

Simkin and Dibb (1998) largely confirmed the results by Cross et al. (1990) thatthe most heavily used criteria were profitability, growth and segment size. While thefirms investigated by Simkin and Dibb (1998) focused primarily on financial returnaspects, they did not draw on the six segment attractiveness criteria. Accordingly, theauthors concluded that companies over-emphasize company-internal considerationsand short-term goals instead of equally considering external environmental forcesand market trends when evaluating and selecting final target segments.

Similar to Simkin and Dibb (1998), Callaghan and Morley (2002) empiricallyconfirmed the high importance attributed to profitability and growth criteria.However, ‘growth, size and profit will not encapsulate the requirements of allorganizations’ (McDonald & Dunbar, 1995, p. 111). So they argued that companies

need increasingly to consider internal organizational issues (e.g. fit with businessstrategy, ability to deliver a differentiated product offer, the organization’s currentposition with customers), which relate to their business’ strengths and weaknessesmore directly and are less marketplace oriented.

Finally, Danneels (1996) revealed that in the apparel market target segments‘emerge’ based mainly on intuition instead of well-thought criteria and are derivedfrom the retailer’s offer, i.e. the retail mix is determined first and the target market issubsequently derived as the group of customers that is attracted by the offering.Accordingly, the conventional stages of segmenting, targeting and positioning arenot linked in a unidirectional process sequence as suggested in literature (e.g.

Bonoma & Shapiro, 1984) but are connected in an iterative feedback process wherethey are rearranged and repeated.In view of the complete absence of empirical investigations into how firms

actually profile their formed segments, an obvious future research priority is toexplore which criteria (e.g. demographics, behaviouristics) are employed to developsegment profiles and how such criteria are subsequently linked to marketing mixdecisions relating to the four P’s. ‘Profiling all segments from each separate analysiscan be of great help in defining each segment and selecting a target segment that hasthe best ‘fit’ with present company offerings, offers the most opportunity, or can bereached by the media most effectively’ (Myers, 1996, p. 23).

Moreover, extant empirical studies do not reveal any insights into how many of the (initially) formed segments are ultimately selected as final target segments. In thiscontext, the choice on the number of final target segments may, for instance, depend




on the financial resources of a company since the more resources available, the moresegments a firm can, in principle, afford to serve. Similarly, firms which are wellestablished in the market and highly experienced can draw on their expertise inpreviously served markets and benefit from economies of scale and scope byselecting those target customer segments which are similar to already servedcustomers. Accordingly, future research should investigate which contextual factorsdrive and how they can impact on the selection of final target segments.

Finally, although highly recommended in segmentation literature as basicconditions for successful segmentation (e.g. Piercy & Morgan, 1993), criteria such ascompatibility of segments with a company’s mission, its corporate values andcultures have not been raised in the empirical studies as criteria applied whenselecting final target segments; thus, the influence of a firm’s internal organizationalframework (in which segmentation decisions are embedded) on the choice of targetsegments needs to be investigated in further research.

Implementation issues

Surprisingly, and despite the importance of segmentation decisions (Rao & Wang,1995; Steenkamp & Ter Hofstede, 2002), literature offers little practical help andguidance to marketers who are seeking to implement the market segmentationprocess in their firms (Simkin & Dibb, 1998). Although ‘increasing evidence suggeststhat businesses have problems operationalizing segmentation’ (Dibb, 1998, p. 394),‘the sophistication of implementation guidance remains surprisingly static’ (Dibb,1999, p. 109). Dibb (1998) relates the discrepancies in research needs betweenacademics and practitioners to the fact that the priorities of practitioners clearly

differ from those of academics. Specifically, whereas academics mainly focus onsegmentation variable selection and segmentation techniques in order to achievesegmentation schemes that are statistically robust, practitioners emphasize targetsegments for which it is possible to develop precise marketing programmes.Accordingly, ‘a market segmentation strategy must have the potential to be used’(Choffray & Lilien, 1978, p. 17). Therefore, great emphasis has to be placed on theability to tie tangible marketing actions to the segments formed in order to ensuretheir value to marketing managers (Rudelius et al., 1985).

In early empirical studies on firms’ segmentation practices (Schuster & Bodkin,1987; Wind & Cardozo, 1974), implementation issues were not considered at all.

Cross et al. (1990) only touched on the topic of implementation by consideringdifferent marketing actions to reach different segments namely different advertisingappeals/media, offerings (products/services), sales promotion programmes, prices,sales forces and distribution systems. Variations in the importance of such actionswere observed between consumer and business markets and further between the typeof offering (i.e. product or service). Abratt (1993) confined himself to stating that themost difficult stage in market segmentation is the translation of results into aneffective implementation strategy, but no empirical analysis is undertaken to identifypotential difficulties, nor are guidelines offered how to put segmentation efforts intopractice successfully. Similarly, Danneels (1996) does not provide hints forimplementation either, although he reports that retailers face problems whentranslating segmentation findings into real marketing decisions, irrespective of whether supporting market research has been conducted beforehand. The first




authors who do not only empirically identify implementation barriers but also offerinsights on how to deal with them are Meadows and Dibb (1998), followed by amore thorough diagnosis of segmentation barriers and ways to treat them by Dibband Simkin (2001). Dibb and Simkin (2001) differentiate between infrastructurebarriers, process issues and implementation barriers. Infrastructure barriers (such asweak communication channels, lack of culture of data collection, lack of customerfocus, lack of marketing expertise) inhibit firms right from the start since anorganization’s infrastructure is not appropriate or too inflexible to deal with thesegmentation process. To overcome them, companies need to audit and updatemarket and customer data continuously and, more importantly, improve commu-nication within the firm and develop an organization-wide understanding of segmentation principles and benefits.

Process issues indicate a lack of a systematic process (i.e. a clearly definedsequence of steps to follow) in order to carry out segmentation projects. Also, a clearidentification of skill gaps of marketing personnel is required to avoid problems withunderstanding the market segmentation process itself as well as uncertainties abouthow best to proceed with segmentation-related tasks. Buying-in external advice andoffering segmentation trainings helps to overcome process issues. Finally, it isrequired to ensure that proposed segmentation strategies and segment solutions fitwith the overall corporate strategy of the company (Dibb & Simkin, 2001) to foster amore credible and positive image of a company, entailing that customers are moreconvinced to purchase a firm’s offering (Jenkins & McDonald, 1997).

Ultimately, implementation barriers (e.g. inflexibility, product focus in distribu-tion, poor alignment of resources for implementation) hinder managers fromoperationalizing the segments. As firms frequently organize their segments based on

certain product or customer sector dimensions instead of focusing on customer needsand buying processes, 15 companies have to undergo a reorientation process in termsof modifying their organizational culture, distribution, sales force and to re-allocatecontinuously appropriate personnel and resources so as finally to match the activitiesand needs of the customers in each segment. Also, segment solutions need to becommunicated around the business to key internal and external (e.g. dealers,distributors) audiences to ensure that the segmentation process is understoodcompany wide as well as by external partners’ businesses so as to foster theaudiences’ conviction to operationalize the chosen segmentation scheme (Dibb &Simkin, 2001).

Bearing in mind that firms often seek assistance and guidance whenimplementing the stages of the market segmentation process (Dibb, 1998; Dibb &Simkin, 2001), an issue worthy of future research concerns the role of externalexperts, that is, which services related to tasks of the market segmentation processare bought in (e.g. collection of customer data, application of segmentation methodsto form segments, development of an appropriate marketing mix for each targetsegment selected) and which benefits are obtained by relying on such externalexpertise.

Segmentation strategy evaluation

Although the majority of companies investigated in the empirical studies onsegmentation practices of firms indicate that they do use a segmentation strategy, 16




only three (i.e. Craft, 2004b; Schuster & Bodkin, 1987; Wind & Cardozo, 1974) of the nineteen empirical studies in Table 2 consider the important task of how firmsevaluate their segmentation efforts. This lack of shortage of empirical studiesexamining the success of segmentation decisions is surprising since ‘marketsegmentation is widely accepted as an effective strategy for enhancing marketingperformance’ (Craft & Hassan, 2006, p. 26).

Schuster and Bodkin (1987) reported that just about two out of five firms in theirsample evaluate their segmentation strategy, which appears to be due to the fact thatcompanies consider measuring the success of segmentation efforts to be the biggestchallenge they face (Badgett & Stone, 2005). Accordingly, the criteria most commonlyapplied are financial performance measures such as sales volume/growth, profit, costand market share (Craft, 2004b; Wind & Cardozo, 1974), which can be measured easilyand are internally available from the balance sheet and profit & loss account. Inaddition, successful brand building, reputation as successful (Craft, 2004b), intuition,feedback (Schuster & Bodkin, 1987) and the ability to meet customers’ needs (Wind &Cardozo, 1974) are sometimes applied for evaluation purposes.

Craft (2004b) analysed the measures applied to assess segmentation success usingprincipal components analysis and found four underlying factors: long-termfinancial success; relationship building; market position; and immediate financialreturns. However, it is important to note in this context that segmentation activitiesdo not necessarily directly result in increased performance in terms of higher sales,profits or market shares. This is because bottom-line performance measures are alsoinfluenced by a host of other variables (such as environmental factors, firmcharacteristics), which makes the isolation of the unique impact of segmentationdecisions on such performance measures very difficult (Lenz, 1981). In other words,

segmentation activities only indirectly influence the financial performance of a firm,thus bottom-line measures are not adequate for isolating the contribution of marketsegmentation decisions on firm performance. Therefore, future research needs toidentify measures that capture the effectiveness of segmentation decisions and theirspecific impact on firm success. This, in turn, necessitates the development of a clearconceptualization of the segmentation effectiveness construct, which captures thedirect outcomes of segmentation decisions; such outcomes can then be linked withindicators of overall market performance.

Conclusion

In the previous sections, a thorough review of the findings of the nineteen identifiedempirical studies on market segmentation practices was undertaken and correspond-ing areas for future research were raised within each subsection. Table 3 summarizesthe identified research gaps relating to each stage of the market segmentation processand, thus, offers a navigation chart for future efforts.

In addition to the research suggestions listed in Table3, two broader issuesdeserve attention in future studies as discussed below.

First, as already mentioned, the various stages of the market segmentationprocess have not been equally subjected to empirical investigation. As shown inTable1, the most frequently covered stage deals with the selection of segmentationvariables whereas market definition, as well as segmentation method selection haveonly been investigated in a single study each, thus calling for further research.




Table 3. Agenda for future research.

Future research issue

Market definition N Investigation of underlying strategic objectives which drive fiN

Investigation of the impact of situational factors (e.g. firm sizmarket definition

Segmentation variable selection N Underlying rationale why specific segmentation variables are sfor different reasons)

N Investigation of the impact of likely antecedents (e.g. firm sizcustomer orientation, type of industry, product type) on the chvariables

N Investigation of links and dependencies of segmentation variaband impact on subsequent stages of the market segmentation

Segmentation method(s) selection N Identification of barriers which prevent usage of sophisticated low adoption of the latter

N Influence of type of segmentation variables applied on segmeN Investigation of the impact of more/less sophisticated techniqu

Segment formation N Exploring underlying factors (e.g. environmental issues, manaindustry) which drive the choice of criteria for segment forma

N Investigation of the impact of segment formation stage on subsprocess (e.g. implementation issues)

Profiling, evaluation and finalselection of target segments

N Exploration of segment profiling criteria and investigation of N Investigation of which factors influence the decision on the num

segmentsN Investigation of the influence of a firm’s mission, values and

Implementation issues N Role of external experts in supporting firms with their segmeoffered and which benefits do firms obtain from buying in ex

Evaluation of segmentation strategies N Identification of measures to capture the effectiveness of segmeon a firm’s success

N Development of a clear conceptualization of the segmentationN Investigation of the linkage of segmentation effectiveness/suc



Furthermore, in view of the general interrelatedness of the stages of the marketsegmentation process, future studies should focus on the implications of differentmarket segmentation practices on decisions related to subsequent stages of themarket segmentation process (e.g. positioning decisions).

Second, additional research should also investigate firms that operate in B2C andB2B markets simultaneously with the aim of obtaining insights on whether (and, if so, how) such firms segment their markets differently in different marketenvironments. In addition to the general and acknowledged structural differenceswhich impact on segmentation efforts in consumer and business markets, futureresearch should also incorporate the maturity and competitive dynamics of variousindustries typical of either consumer or business settings in order to account equallyfor differences within (as opposed to between) both settings. In general, matureindustries show a higher concentration, which, in turn, facilitates to monitorcompetitors more easily (due to a lower number of active firms). Additionally,regardless of how the market structure changes over time, customer response isevolving as industries/markets mature (Soberman & Gatignon, 2005): so-calledinnovators are less price sensitive and more risk taking than followers or laggards,and they are more sensitive to advertising or marketing activities because theirgeneral level of knowledge about a product category is rather low. Accordingly, in-depth knowledge about the maturity of a particular industry (whether in a B2C orB2B setting) allows to segment and target customers more accurately by thoroughlyselecting segmentation bases, descriptors for profiling segments and selecting targetsand develop marketing programmes.

To conclude, the state-of-the-art picture of research on actual marketsegmentation practices reveals important knowledge gaps related to the various

stages of the market segmentation process as well as more general issues thatdeserve future attention. In seeking to address these gaps, future studies onsegmentation practices should simultaneously seek to implement methodologicalimprovements so as to derive psychometrically robust results, which would allowfor confident generalizations regarding the way in which firms go about segmentingtheir markets.

Acknowledgements

The authors thank the JSM co-editor Carolyn Strong and two anonymous reviewers for useful

feedback on an earlier version of this article.

Notes

1. This was based on a combination of bibliographic database searches (ProQuest andEBSCO), online searches (Google Scholar), manual searches of conference proceedingsand authors’ websites and examination of reference lists of relevant articles.

2. Daneels (1996) conducted six interviews with external experts in the apparel industry inaddition to his interviews with twenty-two retailers.

3. Kalafatis and Cheston (1997) only indicate that their unit of analysis is pharmaceuticalcompanies and Meadows and Dibb (1998) just state that ‘well-reputed banks’ were

chosen.4. The study by Craft (2004b) relies on two samples of which the first (smaller) sample istaken from a previous study by Craft (2004a); thus it is counted only once.




5. Also the study by Simkin and Dibb (1998) relies on two samples of which the method fordrawing the first sample is judgemental, whereas no information is provided about thesecond sample.

6. In the majority of studies in Table 2, the sampling method was not clearly described. Theclassification provided here is based on the authors’ impressions based on whatever

information was disclosed in the relevant studies.7. Both studies used the same database in their analyses.8. The number of segmentation variables appears to be increasing over time. For example,

Wind and Cardozo (1974) identified a total of nine variables, whereas thirty-nine arereported in the study by Craft and Hassan (2006). This can probably be explained in termsof the increasing use of computers and more extended access to data, which leads toimprovements in data collection and analysis (Meadows & Dibb, 1998; Schuster &Bodkin, 1987).

9. Such cross-national segments account for both within-country customer heterogeneityand commonalities between customers in different countries (Ter Hofstede et al., 2002).

10. These cover four groups of industries: textile; steel and iron; mixed; and more than one

product.11. Three groups of export destinations are distinguished: EU countries; Islamic countries;more than one country.

12. The four different positioning options were: focused strategy option; optimizationstrategy; geo-centric strategy; and localization option.

13. It is not specified how these dimensions were derived.14. RFM is a descriptive method that does not require specialized statistical software. It relies

on applying either a certain business rule or a statistical technique such as decision treetechniques.

15. This mirrors the findings of Jenkins et al. (1994) that companies mainly rely on a productconcept and much less on a consumer or consumer function concept when defining their

markets.16. Cross et al. (1990) found out that 94% of the surveyed companies segment their markets;Kalafatis and Cheston (1997) identified 72% of the pharmaceutical companies to segmenttheir markets; Spring et al. (2000) found out that 69.2% actually perform segmentation;and Danneels (1996) discovered that all 22 retailers studied segment their market.

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