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Segmenting FinancialServices Markets forCustomer Relationships: APortfolio-Based ApproachGregory Elliott & WILLIAM GLYNNPublished online: 28 Jul 2006.

To cite this article: Gregory Elliott & WILLIAM GLYNN (1998) SegmentingFinancial Services Markets for Customer Relationships: A Portfolio-Based Approach, The Service Industries Journal, 18:3, 38-54, DOI:10.1080/02642069800000031

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Segmenting Financial Services Markets for Customer Relationships:

A Portfolio-Based Approach

G R E G O R Y ELLTOI'T a n d W I L L I A M G L Y N N

In the marketing process, the generlc process of 'target marketing' plays a central role [Kotler, 19971. As a part o f this process, the tasks of, tirst, the identification of the appropriate market scgmcnts and, second, the evaluation of, and choice between, possible market segments present some operational issues and challenges \vhich, somewhat surprisingly, receive little attention in the literature. This issue is compounded in the service industries context in which the issue of 'relationships' assumes greater salience. This paper addresses tlie fundamental problem of market segmentation in the service context and employs a portfolio approach to the operational problem of segmenting financial services customers on the basis of the likely value over time of their relationship with the financial services provider. Resolving tlie probleni in this way .srrnztltcrtieo~isI~~ tachles the tasks of identirying desirable market segnlents and the evaluating among possible segments.' The model presented herein thus offers considerable benefits, pr.ima,fac~e, although the demands in opcrationalising the model are not inconsequential.

T H E CI-IAI-1 ,ENGE IN M A R K E T S E C M E N 1 ' A ' I ' I O N

The origins of the term market segmentation can be traced back to Wendel Smith's trail-blazing article in the 1950s which introduced the concept as 'based upon developments on the demand side of the market and represents a rational and more precise ad,justmcnt of product and marketing effort to consumer and user requirements' [Smith, 1956). In support of his position, Smith pointed to the variety inherent in contemporary markets among users and suppliers of products. Market segmentation was identified as a prerequisite for any organisation endeavouring to create products to fit customers' needs. Smith's market segtncntation concept was rapidly adopted in theory and practice and was furthcr developed by a number of researchers [Yankelovich, 1964; Bamett, 1969; Myers and Tauber, 1977; Wilkie and Cohen, 19771. By the end of the 1970s several authors were able

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S E G M E N T I N G FINANCIAI, S E R V I C E S M A R K E T S 3 9

confidently to assert generalised market segmentation principles. In a key summary article, Wind declared market segmentation to be 'a dominant concept in marketing literature and practice' [Wind, 19781.

The concept of market segmentation remains a central tenet of modem marketing and, arguably, is linked inextricably to the marketing concept itself [Neidell, 19831. As organisations move from serving individual customers to addressing larger markets, the focus shifts from identifying and satisfying the needs of individual customers to the task of satisfying the needs of target market segments. This is inevitable as a firm typically has only a limited ability to match the variety of demand with a corresponding variety of supply. Put simply, most organisations serving mass markets have only a limited ability to vary their offer before production or cost constraints p r e ~ a i l . ~ Beyond that point, the increased costs of proliferating the variety in their offerings are not recoverable through the price.

S E G M E N T A T I O N C R I T E R I A

Whilst market segmentation is an intuitively simple concept, its operationalisation is not self-evident. Several authors have complained that there is no generally accepted and validated way to segment markets [Beane and Ennis, 1987; Schauerman, 19901. However, four popular forms of market segmentation have emerged:

Geographic Segmentation. Demographic Segmentation. The validity of using demographic variables is well supported in the literature [Frank, Massey and Wind, 19721. Clearly defined segments can be identified using demographic segmentation, but entire markets cannot usually be segmented by this method alone [Beane and Ennis, 19871. Psychographic Market Segmentation. This involves the less easily measured social class and way of living or lifestyle variables. Psychographic segmentation has proved superior to demographic segmentation alone [Plummer, 1974; Wells, 19751. Behavioural Market Segmentation. This form of segmentation includes variables such as purchase occasion, benefits sought, user status, degree of usage and loyalty, buyer readiness stage, and marketing focus sensitivity. Knowledge of product, attitude and response to the product are used to segment consumers [McDonald and Goldman, 19791. A combination of psychographic and behavioural segmentation has also been proposed as a means of segmenting markets on the basis of the consumer's self-image or self-concept and its relationship to the image of the product [Sirgy, 19821.

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40 S E K V I C C I N C ) I J S T K I F S M A K K I : T I N G

A number of useful criteria liavc bccn identified to help guide researchcrs in selecting appropriate market segments [Plummer, 1974; Kotler, 1980; Martin, 1986; Zeithaml and Bitner, 199Gl including 'mcasurability', 'accessibility', 'substantiality', 'actionability', 'determinancc', 'appropriatencss' and 'predictive ability'.

S E G M E N T I N G SERVICES MARKETS

The treatment of the central concept of market segmentation in thc services literature is noticeably light\svight. To date, researchcrs have tended to concentrate on the segmentation of external customer marhcts in tlie targeting and positioning of services [Gilmour, 1977; Easingwood and Mahajan, 1989; Payne, 1993; Gavin ct nl., 1996; and Zeitliaml arid Bitner, 19961. Customer servicc cost reduction, customer retention and scrvice level improvements have been cited as reasons to segment external servicc markets [Payne and Clarke, 1995; Zeithaiiil and Bitner, 19961. Scrvicc organisations have also tended to adopt an unsophisticated approach to segmentation. For the most part, scrvice organisations have concentrated on demographic and geographic data to segment markets [Palmer 19941. One author comniented that many organications and rescarchers are currently paying only lip servicc to the conccpt of market segmentation IPayne, 19931. In view of the ilnportarice of the financial serviccs sector and the fundamentally distinctivc charactertstic\ of services, this finding is both surprising and disappointing.

H E H A V I O U K A L S E G M I S N I-ATION

Whilst, in practice, the financial institutions, Icd by the banks, have run the full gamut of segmentation critcria from dcniograpliics, including family life cycle, to psychographics (lifestyles), it is clear that, as for all such ~egmentation exercises, tlic use of 'bcliavioural' dimensions appears to offer the best prospect of establishing thc link between segments and financial 'purchasing' behaviour. That is, thc process of identifying market segments should logically begin from the observed differences in behrrviour-, and, through understanding this behaviour, develop an understanding of customers' differing rcquiremcnts through the study of such variables as 'perceived benefits' or siniilarly 'cilstomcr needs'. '?'he belief underlying this (benefit) segmentation strategy is that tlie benefits which people are seeking in consuming a given product are thc basic reasons for thc existence of true market segments. Experience with this approach has shown that benetits sought by consumers dctcrmine their bchavior much more accurately than do demographic characteristics or

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S E G M E N T I N G F I N A N C I A L S E R V I C E S M A R K E T S 4 1

volume of consumption' [Haley, 1995: 601. 'I'his 'behavioural' approach contrasts with the process of segmentation

based on custolner characteristics, such as demographics, including fanlily life cycle or even 'psychographics' (or 'lifestyles') in which it is presumed that such characteristics are reliable indicators of the underlying requircments, needs or benefits. Such an approach, however, is likely to be more 'descriptive' than 'predictive'. By focusing on behavioural indicators, such as 'customer needs', in contrast with customer characteristics, it is more probable that the segments which are consequently identified will be ultimately predictive of the purchase behaviour. Furthermore, it is also manifestly true that 'needs-based' or 'benefits-based' segmentation in Haley's terms comes closest to fulfilling the dictum of the 'marketing concept' in that the focus of segmentation is the customers' wants, needs andlor benefits.

It should be further emphasised that such a 'bchavioural', needs or benefits-bascd approach, however, is likely to be specific to a product or product category and, as such, more difficult and time-consuming than an a priori approach INeidell, 19831 to scgmentation which simply classifies segments in terms of customer characteristics. The inherent shortcoming of the latter approach is that it is likely to produce segments that are plausible and even vividly descriptive, as are the 'VALS' segments, but which are unlikely to be predictive of actual purchase behaviour - the ultimate objective of the analysis.

E V A L U A T I N G M A R K E T S E G M E N T S

Beyond identifying segments there is the further task of evaluating and choosing between segments. This process of selecting among available segments will frequently revolve around an assessment of the value of the various segments (most commonly their salcs potential in the case of tangible goods) and the degree of fit with the organisation's marketing activities.

In the context of financial services, especially retail banking, the choice of segments will need to recognize that customers should be targeted on the basis oS the likely value of the relafionshiy - not only according to their present vulue but also their furtire worth or value to the institution. This latter concept is analogous to the financial concept of 'net present value'.

Combining these two general problems of behavioural segmentation and some measure of customer value (to the bank) suggests that segmentation should logically be based on the joint combination of 'customer needs' (or 'benefits'), as a means of properly understanding the customer and rcsponding to the precepts of the marketing concept, and some analysis of

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42 S E R V I C E I N D U S T K I E S M A R K E T I N G

'usage' as a means of understanding their current and future value. It can be further argued that, whilst 'needs' reflects what the custonler is lookilig for in their bank, the complementary process of estimating 'value' represents what the bank is looking for in its customer mix. Thus, for the process of' segmentation to be complete requires both types of analysis.

An additional operational problem is thus suggested: namely, which analysis should be conducted first? While fundamental marketing principles would seem to suggest that customers' needs should be the first concern, this raises the prospect that tlie search will lack focus and may conceivably result in the identification of a range of custoliier 'needs-based' segments which are unattractive or infeasible from the bank's perspective. This suggests that it may be more efficient first to identify the segments on the basis of their value to the batik and then in turn look to i~ndcrstand the range of segments of needs +t;it/7i17 the chosen value-based segments. Whilst this suggests a time-consuming process of identifying segments within segments, it also provides a focused approach which results in both customers' and the bank's interests being colnprchensively identified, analysed and ultimately satisfied. Such an iterative process is an already well understood requirement for effective segmentation:

This docs not mean that the kinds of data gathcrcd in more traditional types of segmentation are not useful. Once peoplc have been classiticd into segments in accordance with the Benefit, they are seeking, each segment is contrastcd with all of thc other segmcnts in terms of its demography, its volun~e of con~iilr~/>tion, [emphasis added] its brand perceptions, its media habits, its personality and lifestyle, and so forth.

In this way, a reasonably decp understanding o f the people who make up each segment can be obtained. And, by capitalizing on this understanding, it is possible to reach them, to talk to them in their own terms, and to prcsent a product in tlie most favorable light possible. [I-laley, 1995: 601.

A further key issue in this process is tlie concept of'the ~.elc~tiond~ip, over time, between the bank and its individual custorncrs. This relationship over time recognizes that it is not sufficient to evaluate new custonicrs solely in tcrnis of their present worth but also their likely future worth and, further, that customers should be evaluated not simply on tlic basis of a static value or the profitability of an individual transaction, but also on the basis of the future value of the relationship. This is analogous to the concept of 'net prcsent value'.

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SEGMENTING FINANCIAL SERVICES M A R K E T S 43

This is also not a new proposition to bankers, who have long placed emphasis on the value of the customer 'connection' and the expected growth in the value of the customer's future banking business. In this sense, bankers have anticipated the current concerns of marketing theorists with 'relationship marketing' as evidenced in Kotler's conclusion [quoted by Gronroos, 1994: 91 that 'companies must move from a short-term transaction-oriented goal to a long-term I-el~~tion~ship-building goal'. Many bankers would agree that viewing customer exchanges as a revenue stream, as opposed to a compendium of isolated transactions, enables cross-selling of related sertices over time and potentially supports premium pricing for the increased customer confidence [Reichheld and Sasser, 1990; Congram, 19911.

Furthermore, it is also important from the retail financial organisation's point of view, as with all organisations, that there exists an optimal blend of customers who provide current cash flow and profits together with growth and predictable cash flows and profits over time.

C U S T O M E R I 'ORTFOLIOS

Having identified potentially attractive market segments, the further task is that of evaluating and choosing between segments (what Kotler [I9971 terms of 'market targeting'). In this process, a valuable role can be played by 'portfolio analysis', by which it is possible to analyse customer segments in terns their value in the present and over time. An additional benetit of the portfolio concept derives from the accepted principle that organisations should maintain balanced product, business or customer portfolios. (In the current context, such a 'balance' would be based on the 'mix' of relationships in the range of chosen market segments.)

The concept of the desirability of looking at the customer base as a portfolio is not new. Lovelock, for example, advocates:

The fact is that not all customer relationships are worth keeping. So~iie customers no longer fit the firm's positioning strategy, either because that strategy has changed or because the nature of the customer's behaviour and needs has changed. Careful analysis may show that many relationships are no longer profitable for the firm: they cost more to maintain than the revenue they generate. Just as investors need to dispose of poor investments and banks need to write off bad loans, so each service firm needs to regularly evaluate its czrslonier yorrfolio (en~phasis added) and to consider terminating unsuccessful relationships. [Lovelock, 1996: 1871

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44 SI:KVICE 1NI)IISI 'KIES M A R K E T I N G

In earlier research, Shapiro et 01. [I9871 classify customers in two dimensions based on their sensitivity to price and the cost to the organisation to service the customer. Customers fall into four resultant cells of their matrix, labelled as 'passive', 'carriage trade', bargain basement' and 'aggressive' and there are clear parallels with the segments proposed in the current paper. More recently, other authors [Krapfel et ul., 1991 ; Yorke and Droussiotis, 19941 have further illustrated the importance of viewing the customer base from the perspective of a portfolio.

With these considerations in mind, the authors propose a portfolio-based approach to the evaluation and selection of target market segments, wherein the portfolio co~nprises a mix of customer segments which yield to the bank an optimal blend of current profit and future growth and economic value. The focus on valuing the relationship over lime is the crucial issue and the incorporation of this in a custorner portl'olio model is, to the authors' knowledge, a new approach.

The use of the product portl'olio models is, of course, \videspread in practice and widely discussed in the literature (although not always critically). The general purpose of the commonly disci~ssed marketing portfolio models is to be able to represent in a single niodcl, the range of a firm's products or businesses comnionly within a two-dimensional matrix. The dimensions of the matrices are typically indicative of both 'industry or market attractiveness' and the firm's 'competitive position'. Within the matrix are identified the entire range of products, product groups or businesses spanned by an organisation. The clear ob.jective is to be able to measure and represent the position of all products at one time and to see the contribution and competitive position of individual products to the total product or business portfolio.

In common with the widely disci~sscd portfolio models (BCG, Directional Policy Matrix, GE Business Screen) the proposed model is t ~ v o dimensional. These dimensions are proposcd as current profitability and long-term value. They are closely indicative of tlie 'transaction' and 'relationship' values of individual customers, witli these indications further linked to the previously discussed needs-based segmentation structure. Both these dimensions, in common with DPM and G E Business Screen arc multivariate dimensions (and in stark contrast with tlie BCG Matrix). This suggests that current and long-term attractiveness 01' market scgments will be a function of several variables.

E S T I M A T I N G CIJSTOMER VAI,UE

The task of establishing tlie value to the bank of each customer and customer segment is a forniidablc operational challenge, although the

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S E G M E N T I N G F I N A N C I A L SERVICES M A R K E T S 4 5

principles guiding such a task can be discussed broadly. In Barnes and Cumby's view the estimation of true customer valuc requires five stages of analysis in order fully to account for all costs and benefits relevant to individual customers and, by extension, customer segments. These comprise allocatable and non-allocatable; monetary and non-monetary costs and benefits [Barnes and Cumby, 19951. Benefits would include conventional income through sales, fees and charges, intcrcst, and so on, but would also encompass measures such as customer satisfaction, referral sales, repeat business, loyalty and goodwill. Similarly, costs include the usual direct labour charges but also training, compensation, motivation, service quality expenses, and so forth. 'The objective is to link revenues with the appropriate customer or market segmcnt, and to match costs with their related revenucs, in some systematic and rational manner' [Barnes and Cumby, 19951.

The infor~nation requirements of such a system are formidable, although not beyond the capacity of most banks. Equally, the payoffs of such a system would reward the bank handsomely. For example, Banc One in the United States 'conducts quarterly measures of customer retention; the number of services used by each customer, or depth of relationship; and the level of customer satisfaction. The strategies derived from this information help explain why Banc One has achieved a return on assets morc than double that of its competitors in recent years' [Heskett, Jones, Loveman, Sasser and Schlesinger, 1994 quoted in Barnes and Cumby , 19951.

It is beyond the scope of this paper to iternise the co~nponcnts (and further the relativc importance of the individual items) in such a system. However, in general, the following factors would commonly be relevant:

Short-term cashflow income, assets, indebtedness, transaction activity: Demographics age, sex, family size, employment profile, Financial behaviour savings, mortgage, other loans, investment and

loan activity and history, interest and charges, transaction volumes, propensity to use plastic cards and new technology, ctc.

Collateral relationshi/~s family, employer and social connections.

These short-term variables are frequently readily accessible and their value readily calculable for individual customers from the bank's customer information file.

Long-term value a future view of current position together with such additional variables as length of customer connection, loyalty, history of family and employer connections, employment stability, occupational stability and prospects etc.

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4 6 S E R V I C E INDUSTRIES M A R K E T I N G

Calculation of this value for indivtdual custorncrs is frequently tilore difficult and relies typically on the analysis of a representative samplc of longitudinal customer historics cxtending pcrliaps ovcr ten years or morc. Moreover, such a value will be probabilistic as there is a finite and calculable probability that the customer will remain a customer over the span of the chosen period. (Thc identification of this period is also important, especially in light of thc widely acccpted vicw that banh- customer relationships with some key custotner groups have bcconie appreciably shorter in recent years as these key segments display an incrcasing willingness to 'shop around'.)

A vital component of this value is, of course, loyalty. The profitability of loyal customers is well recognised and is the key to the concept of 'relationship marketing'. Whilst the value of loyal customers is widely appreciated, the prior identification of such customers is morc difficult, since loyalty can only be obscrved oncc a relationship has had sullicient time to develop. This is, of course, impossiblc with ncw or prospective custorncrs. The isolation of demographic, psychographic and behavioural indicators of loyalty remains a major challenge for analysts and researchers. Whilst the approach proposed broadly Sollows the logic of 'net present value' the approach proposed for thc banking (and othcr linancial services) context should result in an algorithm which is riot as driven by cash flow as is NPV, because of the fundamental importance of relationships and the link to loyalty and profitability in financial services marketing. ' lb niaximise profitability, relationship building should be forward looking, not entrenched in historic monetary revenue patterns' IBarnes and Cumby, 1995: 18 I]. The computational problcni is formidable although the issues are generically common with actuarial issues in life assurance. In the case of banking relationships, the variables cxtend f i r beyond simple 'premium income' and the independent variables more complcx than those predicting life expectancies.

Conceptually then, the value of individual customers and custotner segments, in turn, can be represented on a two-dimensional matrix and a portfolio approach adopted to view the customer niix of a bank. In common with DPM and Business Screen, a 3 x 3 matrix, in contrast to thc 2 x 2 matrix of BCG, is favoured. Suggcsted appropriate strategies are also shown in brackets.

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S E G M E N T I N G F I N A N C I A L S E R V I C E S M A R K E T S

T A B L E I CUS'I'OMER VAI-UE I'OK'I'k'01,lO M A T R I X

1-ong-term Attractiveness ('Relationship' Value)

High Medium I+ow

High (I) (2) ( 3 ) 'Prime Cii.storner.s ' 'Highlv Vulired Clrstorners ' 'Pro.spemu.s hilt MohrIe '

I'rotect and Nurture Reward Loyalty Masimise Inconle c Reward Build Kelationship Avoid Over-management 5 - r" Develop 'Partnerships' . Monitor Closely

c Avoid 'Milking' 0 .- .d

Medium (4) ( 5 ) (6)

2 - 'Pririle PIVS~~ECIS ' 'Middle Mujoritj~ ' 'I'ricc Shoppers' - I'rc~tect and I<ncourage Manage for Long-term . Short-term Yield >, .- - .- Manage for I:uture Yields management

f 1lel:itionship Cost Containment Cost Minimisation 5 Defend againw Modest Revenue Short-tern1 Revenue e

n. I'redatory Competitors Opportunities Opportunities - 5

Low (7) (8-) (9) 'Tomorrnx~:~ Vilrred 'No Fri1l.s ' 'Social Res~1ornihi1itie.s ' Cii.stomer.s '

Lower Costs Minimise Short-term - Divest where Ethically Invest in the Relationship Costs Possible

Recognise and Rc\rJard . Cost Recovery Potential

These cells and the recommended business developmcnt strategies are described below.

Cell I ('Prime Customers 7 . This group represents the bank's most desirable target customers. In some instances, whilst it may comprise less than 25 per cent of the customer base, there may also exist a most extreme 'Pareto's Principle' with this group contributing a major share of current profits (and with cells 1, 2 and 3 together accounting for more than 100 per cent!). Whilst this group might be regarded as a 'cash cow' in the sense of the BCG matrix, there is a danger in excessively 'milking' this group for current profits as it will also represent a valuable target market for competitors and they may become 'at risk'.

Cell 2 ('Highly Valued Customers 7 . This group, while currently very profitable, is 'at risk' in the longer term. Efforts should be directed towards enhancing the current realtionship and at lowering the likelihood of losing the customer. A danger here is that a short-term focus will only accelerate the.loss of the relationship. While such customers will be 'at risk', the focus should be in adding value to the relationship and removing any incentives

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48 SI:RVICE I N D ~ J S T R I E S M A R K E T I N G

to switch. One approach is to masiniise the number of bonds in the relationship through cross-selling of services.

Cell 3 ('Prospero~rs b~rt Mohlle 3. This group represents the familiar 'high net worth' but, at thc samc time, highly tilobile customcr (most c01iin101ily young, well educated and socially mobilc). This group is generally aware of its prospects; is not loyal and will frequently shop around for the best deal and will move readily to take advantage of thc bcst oft'er. 'I'his group will also be highly demanding but will not have strong feelings ol'loyalty. It will expect much, but give little in return. As this group has rather short-term, oppol-tunistic objectives, then it should be ~iianagcd to lnaximise current income.

Cell 4 ('Prrme Pr.ospec/., 7 . fhis group, while potcntially profitable, is currently less profitable commonly due to high transaction activity and low average savings and deposit levels. Whilst it is naturally desirable to improve the profitability of this group, to do so by cmphasising revenue through higher charges may threaten the potentially profitable relationship. Only modest rcvcnue gains through pricing should be attempted here. A more desirable strategy to increase profitability of this group would bc to contain costs to the extent that this is possible while ensuring that the relationship is actively cultivated. Significant ilnprovements will accrue through a prudent combination of cost and revenue measures. Incentives through differential pricing and service levcls should recognise thc potential of these customers.

Cell 5 ('The Middle Mqor.rty '). Whilst niembcrs of'this group arc unlikely to ever reach the status of 'prime customers', they should still receive careful attention as they provide important 'volunie' in both transactions and customer numbers. They thcrefore play an important role in 'spreading the base' of the bank's overheads. Short-term strategies should probably bc devoted to managing variable costs, while, in the longer term there may be selective opportunities to improvc the revenue stream. The risks in these relationsliips arc 'over-nianage~iient' or the danger of breaking tlic relationship through aggressive pricing.

Cell 6 ('Prrce Shopper-.s '). I'his group is of some short-term interest in that it provides volume base. Its long-term attractiveness is low, howcvcr. This is most likely to bc due to members' propensity to 'shop around' and to switch based on short-term gains. Such customers are pricc-driven and seem little interested in longer-term relationships. Some gains can be expected in trying to 'migrate' this group to Cell 5 ('middle ma.jority') through modest, price-based, incentive and loyalty programmes.

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S E G M E N T I N G 1:INANCIAL S E R V I C E S M A R K E T S 49

Cell 7 ('Totnorro~vj. Valtred Ctatotners 7 . This group is difficult to manage in the short term as they are currently high cost low value customers. However, their long-term potential would justify a strategy of 'investing in the relationship'. (The concept of 'student loans' is evidence of the attractiveness of this segment, although the long-term rewards are not guaranteed.) Minimising switching is the key to the profitability of this segment.

Cell 8 ('No Frills y . The key to the management of this group lies in 'cost containment', as members' long-term revenue prospects are doubtful. However, providing costs can be managed, these customers can provide some volume base, especially for 'plain vanilla' products, although the likelihood that they can be 'migrated' into more profitable segments over time seems modest at best.

Cell 9 ('Socicrl Responsibilitiesy. This group is labelled somewhat irreverently 'social responsibilitics' in recognition of the fact that, through the combination of low account balances, high transaction volumes and few prospects of improvement, they typically cost the bank more to maintain than they currently, or potentially, generate in earnings. As Storbacka [cited in Gronroos, 19941 has demonstrated, some bank-customer relationships are not profitable, even in the long run, notwithstanding the level of satisfaction enjoyed by the customer. It is hard to see an economically viable role for members of this group although they could be managed more profitably through lowering costs and modestly increasing charges. (This is not to dcny that there are significant ethical and 'social responsibility' issues involved in the management of thcse customers, although a full discussion of these issues is beyond the scope of this papcr.)

C U S T O M E R P O R 1 ' F O L I O S A N D TI-IE AI , I ,OCATION 01: O V E R I - I E A D S

This lack of profitability of certain customer segments raises the issue which is consistent with the widely accepted position, encompassed in Gronroos' view, that 'segmentation based on customer relationship profitability is a prerequisite for customer retention decisions' [Gronroos, 1994: 91. An important issue relevant to this latter group of customers in particular, and also the general issue of the nature of portfolio models, is worth exploring. That concerns the allocation of overheads. The general 'Pareto's Principle' when applied to the customer base will frequently find that 20 per cent of customers will contribute 80 per cent of profits (or of that order). This is frequently invoked to further question the value of the remaining 80 per cent of the customer base. Whilst the authors do not

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5 0 SERVICE INDIJSTKII'S MARKETING

question that customers will contribute unequally to costs and revenuc, an olten overlooked matter implicit in the observation is thc unrevealed issue of the allocation of overlicads. In most retail banks, the niost significant single overhead is thc branch network. By fhllowing the logical conclusion of the Parcto observation, banks would be tcmpted to eliminate a significant proportion of the current custonier basc. 'The implication of such a stcp would be to force the diminished customer base to absorb the unchanged overhead, with the unfortunate consequence that a proportion of the forinerly profitable customcr base would itself now be unprofitable. A downward spiral in size and profitability is set in process.

Thc inevitable end-point of such a process would be to eventually have more branches than custotncrs! Whilst such a scenario is patently implausible, it does suggest that thc reason why a high proportion of current customers are deemed to be unprofitable is becausc they are absorbing their full share of overheads, which are fixcd by definition. Shrinking the customer base in the short term can only scrvc to exacerbate the problem. This problem is made more intractable by the fact that profitable customers are likely to be randomly distributed across the branch network and thercfore only limited rationalisation of the network will be possible without eroding the base of profitable customers.

C I J R R E N T L Y IJNKESO1,VED I S S U E S

Whilst the logic of the portfolio-based niodel of customer segmentation described above is undoubtedly sound, there remain several important and outstanding issues which stand in the way of tlie practical development and i~nplementation of the model as described above.

First, while the classification of customer segments according to current and future value to the bank is,p~.imu/i-rcie, appealing, much more and richer data are required to 'flesh out' the characteristics of such customer segments. For example, what demographic (and even psychographic) variables correlate with these measures of value and the range of financial needs? As discussed previously, this is a necessary task in any segmentation exercise based on behavioural (benefits- or nceds-based) segmentation. Thus, \vitIiin the matrix described above, it will be necessary to perfortn further analysis to identify the dominant clusters or segments ~c!ifl?iri each of the cells of tlie model. Within the 'valued customers' cell, for example, it seems likely that there will be several modal clusters sharing common demographic, psychographic attributes and common financial needs. The identification of the constituent members of tlie cells and the important clusters within the cells will present a formidable challenge to bank niarket researchers, although the appropriate nlultivariatc tnethodologies are well understood.

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S E G M E N T I N G F I N A N C I A L S E R V I C E S M A R K E T S 5 1

Second, implicit in the concept of 'bank-customer relationships' is the assumption that such relationships should be symmetrical or reciprocal [Holmlund and Tornroos, 19971. The current focus of banks, in common with all sellers, is to consider the value of the relationship from the seller's perspective alone. However, clearly, any appreciation of basic marketing tenets would suggest that it is equally important to understand the value which the individual custonler places on the relationship. Focusing solely on the value to the bank is potentially misleading as there is no reason to presume that the relationship is symmetrical and reciprocal (as with any relationship) and that customer holds the institution in equivalent esteem.' The value of the relationship from the customer's perspective is, therefore, a further important variable in the segmentation process, a point endorsed by Gronroos [1994]: 'marketing is to establish, maintain, and enhance relationships with customers and other partners, at a profit, so that the objectives of both (inference added) the parties involved are met. This is achieved by a mutual exchange and fulfillment of promises.'

Thus, beyond the customers' needs, it is necessary to examine the level of customer satisfaction; that is, to what extent are the needs of individual customer segments currently being satisfied. How likely are such identified valuable customer segments to be loyal or, alternatively, to be mobile between institutions? Conceptually, the task of identifying indicators of mobility, therefore poses a further important challenge. Again, some indicators, such as the conventional demographics, are likely to able to be drawn from the banks' customer information files although behavioural or attitudinal indicators are likely to prove less readily identifiable. In this context, the current preoccupation of the banks and their information systems suppliers with thc process of 'data mining' may prove fruitful.

Finally, within the literature the general empirical predictors of the value of btisinesses are either known (or, at least, knowable) through such techniques as Valuc Based Management [Reimann, 19891 or Shareholder Value Analysis [Rappaport, 19861. Further, there are also undoubtedly important and valid generalisations which can be made about the value a priori of certain market segments (for example, customers with substantial personal assets are likely to be more valuable than those with few assets). I-lowever, the widely variable nature of individual banks' traditional customer bases would suggest that market segmentation based around the concept of value of segments over time will need to be empirically estimated for each individual bank, at least until some reliable indicators are published. In view of the vast sums spent by banks with consultants in endeavouring to estimate such value, it is most unlikely that the consultants will rush to publish their findings!

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S E R V I C E I N D I J S T K I E S MAI<Kl-.I INCi

C O N C L U S I O N S

As can be seen, the area is one which is ripe for further data gathering and theory building. At this stage, as this discussion has demonstrated, such segmentation based on the concepts of thc 'customer value' and of a 'portfolio' of customer segments seems lihely to result in segmentation tied to profitability, customer behaviour and value over time. Once established, high value segments can be targeted with marketing campaigns and appropriate levels of customer service can be determined which reflect the bank's short- and long-term priorities. Fostering increased loyalty among the chosen target segments and establishing and deliver~ng appropriate levels of customer service for the chosen target scgmcnts then become the challenges.

Barnes, J.G. and J.A. Cumbp, 1995, 'The Cost of Service Quality: Estending the Boundaries of Accounting Systems to Enhance Custonier Value'. in W.J. Glynn and J.G. Barnes, Ur~c/er:~rrrridirig Sendcev Muriugc.r~rer~r 1rrtlrgr.utirrg Mt~rkelirrg. Orgcrr~i.scrtior~trl Be/itn:iorr~: 0percrtio11.s orrcl Humtnl Re.solr,~:e.v Mrrrrcrgrnterit. Chicl~es~er : \hliley, pp. 178-202.

Barnett, N.I,., 1969, 'Beyond Market Segmentation', Htrr~~cr~d Hrrsirres.s Revic,iv, Vol.47. No.1, pp. 152-66.

Beane, T.P. and D.M. Ennis, 1987. 'Market Segmentation: A Revie\\.'. EJrrrc~l~eurr Jotrrrrcrl qf' Mcrrke~ing, Vo1.2 1, No.5, pp .2042 .

Congram, C.A., 1991, 'Building Relationships that Last,' in C. A. Congram and M.I.. I7riedman (eds.), Tlie AMA Horidbook ofiMc~rketirig,fnr //re Sc~rilicc, lrrc/~r.vtrie.s, New York: AMACOM. American Management Association, pp.263-79.

Co\vles, D. L., 1997, 'The Role of l'rust in Customer Relationships: Asking the Right Questions', Muriogetneri/ Vecisiorr, Vo1.35, No.4, pp.27.3-82.

Easing\vood, C. J . and V. Mahajan, 1989, 'Positioning of Financial Services for Competitive Advantage', Jorrrriol (!fPm~d~rcl / 1 1 1 1 0 1 ~ 1 ~ ~ 0 1 1 ~~~lcrr~crgerr~er~t, Vo1.6. August. pp.207-19.

Frank, K., W.F. Massy, and Y. Wind. 1972, !\,lcrrker Se~yrrrerr/trtiorr. Engle\vood CliKs. New J c r s q : Prentice-l.lall.

Gavin. K. , J. Con\vay, W.J. Glynn, M. Turner and -1'. 13rannick, 1996. 'Designing a Measurement Instrument Ibr Evaluating Quality in the Maternity Services: A Composite Vie\+$ Involving Internal and External Customers', Proceedings. Qrtcrlin; ir~ Ser~~ice (QUIS 5) Corfirerlce. University of Karlstad, Sweden, pp.143-53.

Gilniour, P., 1977, 'Customer Senzice: Dilferentiating hy Market Segment', Irrterricr/ioricrl .I~~~r~~~l o f Pliysiccrl Visrrihrrriorr, Vo1.7. No.3, pp. 141-8.

Gronroos, C.. 1994, 'From Marketing Mis to I<elationship Marketing: .I-owards a Paradigm Shift in Marketing', Murioger~ient Decisiorr. Vo1.32, No.2, pp.4-20.

Haley, R.I., 1995, 'Benefit Segmentation: A Decision-Oriented Research Tool'. Mur.ke/irrg hfc~ricrgemen/. Vol.4, No. I, pp.59-62.

I-lolmlund, M. and I'ornroos, J.-A,, 1997, 'What are Relationships in Business Networks?', Mcrricrgerrien/ Deci.sio11, Vo1.35, No.4. pp.304-9.

Kotler, P., 1997, Murketing Manoger~~erit: Arrcr/j:~is. I'lc~rrriing urrcl Corr/,nl, Upper Saddle River, New Jersey: Prentice-I.lall, 9th Edition.

Krapl'el, R.E. Jr., D. Salmond and R. Speknian, 1991, 'A Strategic Approach to Managing Buyer - Seller Relationships', ~llropeirrl Jorrrr~nl r!fMcrrketirrg. Vo1.25. No.9, pp.22-37.

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Martin J., 1986, 'I'roblem Segmentation', Internatiorial Jorirnal of Bank Marketing, Vo1.4, No.2, pp.35-57.

McDonald, S.S. and A.E. Goldman, 1979, 'Strategies of Segmentation Research', in G. B. Hafer (ed.), A Look Back, A Look Ahead, Chicago: American Marketing Association, pp.30-42.

Myers, J.H. and E. Tauber, 1977, Market Strrrcture Ano!~ai.s, Chicago: American Marketing Association, pp.68-90.

Neidell, L.A., 1983, Strrrlegic Marketing A4~1iugernen1, New York: Macmillan. Palmer, A., 1994, Princij11e.s ofServices Marketing, London: McGraw-Hill, 1994. Payne, A,, 1993, The Essence of Services Murke~ing, I-lertfordshire: Prentice-I-lall International

(UK). Payne, A. and M. Clarke, 1995, 'Marketing Services to External Markets', in W. J. Glynn and

J.G. Barnes (eds.), Understanc/ing Services Managemeril: I~itegrcrting Mclrkefing. Orgc~niscrtional Behaviour; Opera~ioris and Hu~ncrtz Resource Munagement, Dublin: Oak Tree Press and Chichester: John Wiley and Sons, pp.322-69.

Peppers, D. and M. Rogers, 1993, The One to One Frr/ure: Brrildirlg Relc~tiorwhips 01ie Cr~.stor~ter at u nrne, New York: The Free Press.

Plummer, J.T., 1974, 'The Concept and Application of I,ifestyle Segmentation', Jorrrnal of Marketing, Vo1.38, No.1, pp.33-7.

Rappaport, A,, 1986, Creating Shareholcler Kiltre, New York: The Free Press. Reichheld, F. F. and W.E. Sasser, 1990, 'Zero Defections: Quality Comes to Services', Hrrrvad

Business Review, SeptemberIOctober, pp. 105-1 1. Reimann, R.F., 1989, Manogi~ig for Valrre: A Guide to Value-Based Strategic Matiugernerit,

Oxford: Blackwell. Schauerman, J., 1990, 'A New Basis for Segmenting the Corporate Banking Market', in R. Teare,

L. Moutinhoand and N. Morgan (eds.), Managing and Marketing Sen1ice.s iri the 1990:s, London: Cassell, pp. 169-83.

Shapiro, B.P., V.R. Rangan, R.T Moriarty and E.T. Ross, 1987, 'Manage Customers for Profits (not Just Sales)', I-larvard Brrsiness Revie~t! September-October , pp. I0 1-8.

Sirgy, M.J., 1982, 'Self-concept in Consumer Behaviour: A Critical Review', Joirrncrl of Consrmier Re.sertr.ch, Vo1.9, December, pp.287-300.

Smith, W.R., 1956, 'Product Diflerentiation and Market Segmentation as Alternative Marketing Strategies', Jozrnial r$Marketirig, Vo1.21, July, pp.3-8.

Yankelovich, D., 1964, 'New Criteria for Market Segmentation', FIarvu,d Btisiness Revie~v, Vo1.42, No.2, pp.83-90.

Yorke, D.A. and G. Droussiotis, 1994, 'The Use of Customer Portfolio Theory: An Empirical Survey', Jotmicrl ofBusine.s.s arid In(/tr.strial Marketing, Vo1.9, No.3, pp.6-18.

Wells, W.D., 1975, 'Psychographics: A Critical Review', Jotrr~iul of Murketirig Resecrrch, Vol. 12, May, pp.196-2 13.

Wilkie, W.J. and J.B. Cohen, 1977, Ari Overvie,v of Mcrrket Segr,ientcrlion: Behc~viotrrc~l Concel11.s arid Research Apytoachw, Cambridge, Massachusetts: Marketing Science Institute, Report Number 77-105.

Wind, Y.J., 1978, 'Issues and Advances in Segmentation Research', Jot~rrial of Mc~rkethig, Vol. 15, August, pp.3 17-37.

Zeitharnl, V.A. and M.J. Bitner, 1996, Sen~ices Marketi~ig. New York: McGraw-Hill.

NOTES

I. Kotler 119971 labels these tasks 'market segmentation' and 'market targeting' respectively. Other authors, however, simply describe this process under the 'market segmentation' label. Thankfully, Kotler's 1997 edition drops the use of the term 'market targeting' (of which 'target marketing' was a constituent part) - almost a spoonerism and certainly an unnecessary confusion!

2. This situation may not apply in all cases, however, The characteristics of professional services, and, in particular, their almost infinite heterogeneity, provide an obvious example. Furthermore, as industry commentators, often with vested interests, are fond of proclaiming,

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54 SEIIVICIZ I N D U S I ' R I E S M A R K E T I N G

the concept o f the niass market may he a thing of the past with the developnient o f such technology as the Internet and the growth ofdirect marketing. (See, for example. Peppers and Rogers, 1993.) Whilst their arguments have some face \,alidity, the proposition that all l irms wi l l be able to custo~nise their offer for each individual customer is patently unrealistic. as, for example, the prospect o f negotiating your individual train journey with the engine driver! Notwithstanding these limitations, the potential payoffs o f such an approach are attracting greater attention from the hanks, i n part spurred by the developing concept o f 'data mining' which pro~ni.sc~.s to provide the nccessar? methodologies and, ultimately, the profirability algorithms.

3 . The concept o f 'trust' has recently entered the services marketing literature and reflects the necessity to see relationships as ~\rco-sidcd and spanning a vnriahle period o f time. See. for example, Cowles 119971 and Ambler (19971. Whctlicr 'trust' encompasses crll that both parties seek in the relationship is douhtl i~l . IFor csaniplc, I may i r ~ s t the Tax Office or the Police Service (and they me), but this would not guarantee that I \vould \,oluntarily enter a long-term relationship with them! tlolmlund and 'l'oniroos [I9071 see 'trust' as only one a component of the 'social' dimension o f relationships.

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