Measuring the consumer-based equity of financial services brands Professor Leslie de Chernatony Birmingham University Business School The University of Birmingham Winterbourne 58 Edgbaston Park Road Edgbaston Birmingham B15 2RT Tel: Int Code + 44-121-414-2299 Fax: Int Code + 44-121-414-7791 e-mail: [email protected] Author for correspondence Dr Fiona J. Harris Open University Business School The Open University Walton Hall Milton Keynes MK7 6AA Tel: Int Code + 44-1908-654096 Fax: Int Code + 44-1908-655898 e-mail: [email protected] October 2001

Biographies Leslie de Chernatony Leslie de Chernatony is Professor of Brand Marketing and Director of the Centre for Research in Brand Marketing at Birmingham University Business School.

With a

doctorate in brand marketing, he has a substantial number of publications in American and European journals and is a regular presenter at international conferences. He has several books on brand marketing, the two most recent being Creating Powerful Brands and From Brand Vision to Brand Evaluation, both published by ButterworthHeinemann.

A winner of several research grants, his two most recent grants have

supported research into factors associated with high performance brands and research into services branding. He was Visiting Professor at Madrid Business School and is currently Visiting Professor at Thammasat University, Bangkok.

He acts as an

international consultant to organisations seeking more effective brand strategies and has run acclaimed branding seminars throughout Europe, Asia and the Far East.

Fiona Harris Fiona Harris is Research Fellow in Brand Management and Acting Director of the Marketing & Strategy Research Unit at the Open University Business School. Her current research interests include factors affecting brand performance, brand identity and reputation and financial services branding. Her research has been published in leading refereed journals and at international conferences. With a background in applied psychology Fiona has undertaken a range of applied research. Prior to joining The Open University in 1997, Fiona worked as a Research Scientist at Xerox Research Centre Europe. She also held research posts at the Defence Research Agency and Loughborough University, where she was responsible for researching a range of future aircraft cockpit displays and advanced in-vehicle systems.

Measuring the consumer-based equity of financial services brands Abstract As there is no universal approach for measuring brand performance, this paper shows how a consumer-based brand equity measure was developed for corporate financial services brands.

Churchill’s (1979) paradigm was adopted and a literature review

suggested that brand loyalty, consumer satisfaction and brand reputation be the components of consumer-based brand equity.

Ten financial services organisations

provided access to their consumers, from whom, using a postal questionnaire, data were collected.

Based on the 664 usable returned questionnaires, principal

components analysis enabled the consumer-based equity measure to be identified. Further testing revealed this to be a valid and reliable measure.

The measure

represents an easily administered tool for managers and researchers to assess consumer-based equity amongst financial services brands and its strategic applications are considered.

Introduction One of the most important constructs for managers is that of brand performance, yet just as there are numerous interpretations of “brand” (e.g. de Chernatony 2001) so a review of the literature shows a plethora of ways of interpreting brand performance (e.g. Ambler 2000; Aaker 1996). To talk about a brand performing “well” or “badly” is not only imprecise, but it focuses on having one measure of brand performance. The significant interest in brand valuation (e.g. Perrier 1997) has in part encouraged managers to focus on a single measure of brand performance. However, this output perspective overlooks the richness of information available from some of the intermediate indicators which show why a brand has a particular financial value (Feldwick

1996).

Through

knowledge 1

of

the

attributes

constituting

brand

performance, managers are better equipped to develop more effective brand strategies. To draw an analogy, just as a doctor assesses a patient’s health by measuring various parameters, for example blood pressure, height, weight, body temperature, so brand marketers are more informed by having data on the characterising dimensions of their brand (cf Mitchell, 2001).

The idea of a universal approach to the measurement of brand performance is appealing, but the actual metrics that are used vary between business sectors (Ambler 2000) and according to the brand marketing objectives that were set (Srivastava, Shervani and Fahey 1998).

The purpose of this paper is to appreciate how the

literature advocates brand performance should be measured and explain how a brand performance metric was operationalised in the light of the existing literature. In view of the limited research that has been undertaken on services branding (van Riel, Lemmink and Ouwersloot 2001), it further seeks to advance knowledge by focusing on financial services brands.

The paper opens by reviewing the literature on measurements of brand performance. It considers why there is no standard measurement procedure and proposes that when assessing brand performance, a measure of consumer-based equity be employed. Focusing on financial services corporate brands, the paper draws on Churchill’s (1979) paradigm about how to devise this construct, and explains why we selected brand loyalty, satisfaction and reputation as the constituents of consumer-based equity.

The data collection procedure is clarified and, following the use of principal

component analysis, the specific operationalisation of consumer-based equity is presented. The paper shows how this was found to be a reliable and valid measure, and draws managerial implications and conclusions.

2

Literature review The problems selecting a brand performance metric Business success is due, in no insignificant part, to the performance of brands (Doyle 2000).

Thus, one might anticipate that an examination of the business performance

literature would unearth a consensus view about measuring performance.

However

this reveals that researchers have conceptualised and measured performance using a variety of metrics (Venkatraman and Ramanujam 1986; Day and Fahey 1988; Srivastava, Shervani and Fahey 1998; Doyle 2000). this.

There are several reasons for

The first problem is that business performance is a multi-dimensional and

complex phenomenon (Lenz 1981; Ogbonna and Harris 2000).

The nature of the

environment and the strategy being followed influence managers’ choice of performance measures (Day and Nedungadi 1994), as does the function within which the manager operates (Deshpande and Webster 1989).

A preference for different

types of performance measures is likely to exist between managers working for the same corporation since, as Cyert and March (1963) argued, managers have conflicting goals and do not seek optimal, but rather satisfactory solutions, often with only partial information.

Furthermore, as different managers employ different mental models to

make sense of the competitive environment (de Chernatony, Daniels and Johnson 1993), preferences vary between managers in the same organisation for performance measures (Day and Nedungadi 1994).

The type of market within which a brand competes impacts upon the type of performance measure used (Ambler 2000; Rust, Zeithaml and Lemon 2000). Thus, a relationship-centred bank, such as a Swiss private bank for high net worth individuals,

3

would be more concerned with measures of client satisfaction and client assessment of relationships, since these influence retention rates, which form the basis for their business model.

By contrast, an insurance company operating in a highly

competitive, price sensitive market needs to keep control of its costs and would focus more on the number and levels of claims being made, since its business model would fail if its proportion of accident prone consumers increased.

One of the fundamental tenets of marketing planning is that once an objective has been set and a suitable strategy devised and enacted, a measurement system is then needed to identify how close the firm came to meeting that objective. Differences can be detected amongst researchers about the central objective of marketing which is a further reason for different performance measures being used. For example, Ambler (2000), Doyle (2000) and Srivastava, Shervani and Fahey (1998) share similar views that the objective of marketing is to generate healthy returns to shareholders by creating and managing market-based assets.

This leads to more emphasis being

placed on measuring the contribution of market-based assets, net present value of cash flow and shareholder value.

Rust, Zeithaml and Lemon (2000) concur with these

objectives for marketing, but because they believe the route to achieving this is through maximising the lifetime value of a firm’s consumer base, they place more emphasis on a consumer equity metric.

Different consultancies have developed their individual philosophies about how brands should be managed, thus particular consultancies offer individual ways of monitoring brand performance. For example, Millward Brown advocate performance measures based on their BrandDynamicsT M pyramid (Dyson, Farr and Hollis 1996) while Young & Rubicam (1994) have a different set of performance measures based

4

on their BrandAssetT M Valuator.

Ambler (2000) so succinctly summaries the

dilemma managers face, noting “they (market research agencies) begin with what they already have and proceed incrementally” (p57).

When looking at the literature about the measures researchers employ to assess performance, a plethora of measures have been used (e.g. Blattberg and Deighton 1996; Pitta and Katsanis 1995; Barwise and Ehrenberg 1985). As Venkatraman and Ramanujam (1987) observe, the use of different measures of performance is due to the variety of research questions being studied, the discipline focus and the pragmatic issue of data availability.

As there is no standard way of measuring brand performance, a process had to be followed to develop a brand performance metric. This is explored in the next part of this paper.

Developing a measure of consumer-based equity The starting point for this process to develop a measure of brand performance is Ambler’s (2000) contention that a performance measure splits into two parts, i.e. the short-term results and an element that shows how the brand’s equity has changed. The short-term component relates to data in the profit and loss account. As Aaker and Joachimsthaler (2000) argue though, there is a shift away from focusing on short-term financials to brand equity measurements.

In part, this may be due to the fact that

brands require investment over the long-term (Kendall 1999). Our problem is that we needed to measure brand performance across a variety of organisations involved in the marketing of a very broad range of financial services.

Within the financial

services sector there is no standard short-term measure that is suitable for all firms.

5

Part of the reason relates to the fact that financial services encompasses such a broad variety of services (e.g. insurance, consumer banking services, assurance, mortgages, tax efficient savings schemes, buying and selling shares) which are underpinned by different business models and thus managers in different sectors focus on different metrics.

While they may share a commonality of reporting key parameters, such as

profitability or shareholder dividends, managers operating in different categories place reliance on different assessment measures.

In view of these issues, we did not include any short term financials in our measure of brand performance.

Without this component, we were, in effect faced with the

challenge of developing a measure of the consumer-based equity of corporate financial services brands.

Aligning with the contention of Yoo and Donthu (2001),

measuring consumer-based equity equates with evaluating cognitive and behavioural brand

equity

through

consumer

interviews.

We

followed

Churchill’s

(1979)

recommendations about how we could operationalise a reliable and valid measure of this construct, and this part of the paper is concerned with the first two stages of Churchill’s (1979) procedure, i.e. specifying the domain of the construct and selecting the items that capture the domain.

One of the earlier researchers popularising interest in brand equity was Aaker (1991) who defined brand equity as “a set of brand assets and liabilities linked to a brand, its name and symbol, that add to or subtract from the value provided by a product or service to a firm and/or to that firm’s customers” (p15).

While he subsequently

contributed to knowledge by postulating the components of brand equity, he did not develop a valid and reliable metric to measure this concept. Partly because of this, and also partly because of the significant interest in brand valuation (Aaker and Biel

6

1993), no universally accepted method was devised to measure brand equity (Barwise 1993; Mackay 2001).

Rather, several different definitions were devised for brand

equity (e.g. Keller 1993, Srivastava and Shocker 1991) spawning different measuring procedures (Agarwal and Rao 1996; Clark 1999).

We do not wish to enter the debate about the relative merits of different definitions of brand equity, since this has already been covered in the literature (Mackay, Romaniuk and Sharp 1998). Furthermore we did not wish to follow Aaker’s (1991) or Keller’s (1993) definitions since these narrow the options for selecting the components of consumer-based brand equity, and we wished to select components suitable for services.

Instead we adopted the widely accepted Marketing Science Institute

interpretation of brand equity as it ties in closest with our understanding of a successful brand as “an identifiable produce, service, person or place, augmented in such a way that the buyer or user perceives relevant, unique added values which match their needs most closely” (de Chernatony and McDonald 1998, p.20).

The

Marketing Science Institute regards brand equity as being a set of associations and behaviours on the part of a brand’s consumers, channel members and parent corporation that enables a brand to earn greater volume or greater margins than it could without the brand name and, in addition, provides a strong, sustainable and differential advantage.

Reflecting the multi-dimensional nature of the brand equity concept, we scanned the literature to appreciate the components of brand equity that other researchers had employed, and would be suitable for financial services corporate brands.

Agarwal

and Rao (1996) and Mackay (2001) advocate using a variety of components, but when we considered brand awareness as one of the components, cf Aaker (1991), since this

7

did not correlate with market share (cf increasing volume in the Marketing Science Institute definition) we rejected this variable. We also rejected the use of perceived quality and relative price because many of these intangible financial services are high in credence qualities and customers have difficulty evaluating competing brands on these dimensions (Crosby and Stephens 1987; Zeithaml and Bitner 1996).

The

components that we selected are brand loyalty, satisfaction and reputation and the rest of this section explores these three components.

Brand loyalty is included in many of the approaches advocated by other researchers (e.g. Aaker and Joachimsthaler 2000; Ambler 2000; Rust, Zeithaml and Lemon 2000; Blackston 1992).

Loyalty/retention was the second most frequently reported metric

that was presented by managers to their Board of Directors and it was rated as being the most important metric for assessing marketing performance in Ambler’s (2000) study of UK firms.

In a study amongst consultancies specialising in branding, it was

the most frequently cited consumer-based criteria for evaluating brand success (de Chernatony, Dall’Olmo Riley and Harris, 1998). Having a loyal consumer base can significantly enhance the profitability of a brand.

Reichheld (1996) reported that the

net present value increase in profit from a 5% increase in consumer retention varies between 25% and 95% depending on the sector. In an era that stresses relationship marketing (Gummesson 1999), brand strategies (e.g. Dowling and Uncles 1997) are seeking to capitalise on the significantly lower costs of consumer retention compared with consumer acquisition (Fornell and Wernerfelt 1987).

Having a group of consumers who regularly purchase a brand as part of their repertoire brand buying behaviour in a category (Ehrenberg 1993; Gordon 1994) represents a valuable asset.

A brand’s positive associations engender a sense of

8

bonding with consumers (Dyson, Farr and Hollis 1996) and can act as a barrier against the overtones of potential competitors.

Work using the metaphor of

interpersonal relationships (Fournier 1998) shows consumers as having different intensities of bonding with brands. the same strength.

Not all types of relationships with a brand have

For example some brands give rise to a fling type relationship,

which results in a shorter term attachment, while other brands give rise to committed partner relationship resulting in strong, long term unions. This is due to the brand-self connection forming at either a superficial or significant level with a consumer’s life theme (Fournier and Yao 1997).

When seeking to operationalise the construct of loyalty, the work of researchers such as Jacoby and Chestnut (1978) show that it would be unwise to infer loyalty solely from repetitive purchase patterns.

Preference for convenience, novelty, chance

encounters and repertoire buying behaviour are but some reasons for this.

Oliver

(1999) argues that consumers become loyal by progressing from a cognitive phase, to an affective stage and finally onto a conative phase. The first phase, that of cognitive loyalty is shallow. In view of this and the fact that others have focused on the latter two phases (e.g. Feldwick 1996), we operationalised loyalty by questioning consumers about affective and conative loyalty.

Following the tradition of other

researchers (e.g. Dall’Olmo Riley, Ehrenberg, Castleberry, Barwise and Barnard 1997) we asked consumers about how much they like the corporate brand (affective loyalty) then questioned whether they would consider using other products from the corporation and whether they would recommend the corporate brand to others (conative loyalty).

9

One of the problems using repeated buying behaviour as a metric is that it does not provide a full picture of brand equity, particularly since it does not imply commitment (Ambler 2000).

Commitment to a brand results from satisfaction.

For example, a

consumer may make repeated use of their bank, yet show little commitment, because they perceive the other banks to be equally unsatisfactory and the switching costs do not warrant an action.

To open the window more fully on consumer-based brand

equity it is therefore appropriate to measure satisfaction with the brand. It is incorrect to assume that satisfaction is subsumed within loyalty.

Stewart (1997) and Oliver

(1999) argue that satisfaction and loyalty do not move in a synchronous manner.

The outcomes of consumer satisfaction with brands are a willingness to pay a price premium, use more of the brand, provide positive referrals (Srivastava, Shervani and Fahey 1998), and have a positive financial impact (Ittner and Larcher 1998; Yeung and Ennew 2000).

Reflecting these significant benefits, there has been a notable

increase in the use of consumer satisfaction studies (Piercy 1997).

Satisfaction is conceptualised in the literature as an attitude-like judgement after a purchase, or an interaction with a services provider (Fournier and Mick 1999). There has been a notable amount of research into the antecedents of satisfaction, i.e. expectations,

disconfirmation

of

expectations,

performance,

affect

and

equity

(Szymanski and Henard 2001). Following the tradition of other services researchers, we adopted the methodology employed by Crosby and Stephens (1987).

A gestalt

approach was used (cf Oliver, Rust and Varki 1997), asking respondents about their overall degree of satisfaction on a five point semantic differential scale.

Drawing an

analogy with the view of Gronroos (2000) that service quality consists of

person-

person interactions, plus a technical outcome, we followed Crosby and Stephens

10

(1987) approach and also asked about consumers’ degree of satisfaction regarding the sales/service staff and their purchase satisfaction, together with their overall degree of satisfaction with the brand. Each satisfaction rating was made on a five point semantic differential scale.

A brand’s reputation is a perceptual asset in the mind of stakeholders about a performance.

It attracts consumers and can be a key consideration when choosing

between apparently similar brands (Dowling 1994).

A brand’s reputation engenders

loyalty (Hall 1992) and enhances the likelihood of high profits (Fombrun 1996). While there is growing interest in this construct (Schultz, Hatch and Larsen 2000), there are a number of interpretations (Frombrun and van Riel 1997). The integrative definition by Fombrun and Rindova (1996) is adopted in this study, i.e. “a collective representation of a firm’s past behaviour and outcomes that depict the firm’s ability to render valued results to multiple stakeholders”.

Both Aaker (1996) and Keller (1993) advocate incorporating brand associations into measures of brand equity.

Having an image component in any measure of brand

equity is wise since under the traditional view of brand management, when the gap between a brand’s identity and its image become notable, this triggers actions (Dutton and Dukerich 1991).

However image relates to the most recent perception and

fluctuates over time; by contrast reputation is about perceptions of the brand over time and is more stable (Fombrun and van Riel 1997).

Image is overly focused on

consumers, and in view of the new models of brand management adopting a more balanced, stakeholder perspective (e.g. Mitchell 1997), brand reputation has the further advantage that it addresses stakeholders’ views (Smythe, Dorward and Jerome 1992).

11

The reputation construct has been operationalised in a variety of ways (Fombrun 1996).

Some studies assess reputation by asking respondents to assess corporate

brands on criteria thought to describe reputation, and these responses are aggregated into overall ratings (Fombrun 1998). However researchers are critical of this type of approach, in particular because they lack content validity (Fryxell and Wang 1994). An alternative approach is to ask respondents directly about their evaluation of a corporate brand’s reputation (Fombrun, Gardberg and Sever 2000). While researchers are starting to focus attention on the content validity of the items constituting reputation, we were concerned by this limitation. We were also mindful of Drolet and Morrison’s (2001) contention that if services researchers develop multi-item measures these can lead to participant fatigue, boredom and inattention, which in turn can lead to

inappropriate

behaviour,

inflating

across-item

error

term

correlation

and

undermining respondent reliability. Instead, we adopted a gestalt approach and used a five point semantic differential scale, asking respondents to rate the favourability of their evaluation of the corporate brand’s reputation.

Having drawn on the literature to specify the domain of the consumer-based brand equity of financial services brands, and identified suitable dimensions to characterise it, following Churchill’s (1979) paradigm we then collected data to purify our measure as well as assessing reliability and validity.

Data collection This study on the consumer-based equity of financial services brands, was part of a bigger project to investigate perceptions of financial services brands.

Fifty two

financial services organisations were identified in the UK and were approached.

12

Twelve of these agreed to participate.

Rejections were received from the other

organisations for reasons such as they perceived some of the data as being commercially sensitive or were under time pressure and could not spare the time. To collect the consumer data we needed to send questionnaires to the participating organisations’ consumers.

One firm was a business-to-business operation and was

unable to participate in the consumer-based equity data collection process. One further firm was unable to participate in the entire research owing to resource constraints.

Based on Chisnall (2001), we anticipated a 30% response rate from a postal questionnaire.

We therefore aimed for a contact sample of 330 consumers per

organisation in the hope of achieving 100 consumer replies for each corporate brand. The organisations supplied contact details for a random sample of approximately 330 of their consumers who had direct contact with the financial services provider (rather than through an intermediary) and had a sufficient level of contact to be able to answer questions about the brand. As far as possible, the consumer samples were drawn in proportion to the number of consumers per product in an organisation’s product portfolio.

Each consumer received an envelope containing a letter from the financial services provider, a letter on university headed paper signed by the lead researcher, a questionnaire, instructions for completing the questionnaire and a reply paid envelope addressed back to the university. identities would be kept confidential.

It was stressed in the letters that participants’ Consumers were also offered an incentive to

participate in the research. This was in the form of a donation of 50 pence to their

13

choice of charity from a list of four charities spanning a range of concerns (health, poverty, child welfare and animal welfare).

The number of returned questionnaires was plotted over time and follow-up questionnaires sent to non-respondents when the chart indicated that the number of returned questionnaires had reached a plateau. In total, 748 replies were received from the 3210 questionnaires mailed out, a 27.6% response rate.

Some of the

questionnaires had to be discarded, as they were incorrectly completed, resulting in 664 usable questionnaires.

The achieved response rate was lower than anticipated,

but may be attributable to consumers’ low level of interest in financial services (Levy, 1996).

Consumer-based equity measures As discussed earlier in this paper, three categories of consumer-based equity were employed: brand loyalty, consumer satisfaction and brand reputation. The questions are reproduced in Appendix A.

(i)

Brand loyalty

Brand loyalty was assessed in terms of both conative (or behavioural) loyalty and affective (or attitudinal) loyalty. Conative loyalty was assessed as whether or not consumers would consider using other products from the same financial services provider and whether they would recommend the brand to other people (see Questions 1 and 2 in Appendix A). Affective loyalty was assessed as the degree of liking consumers had for the brand rated on a 5-point scale with verbal anchors of ‘not at all’ and ‘very much’ (see Question 3 in Appendix A). The descriptive statistics for the brand loyalty scales are shown in Table 1.

14

Table 1. Descriptive statistics for the brand loyalty scales Brand loyalty scales

Mean score

Standard deviation

Conative brand loyalty: consider using other products

0.76

0.42

Conative brand loyalty: prepared to recommend brand to other people

0.87

0.34

Affective brand

3.79

0.90

(ii)

brand

loyalty:

liking

for

Consumer satisfaction

Three measures of consumer satisfaction were employed: (i) consumers’ overall satisfaction with the brand; (ii) consumers’ satisfaction with staff; and (iii) consumers’ satisfaction with the product(s) (see Questions 4-6 in Appendix A). Responses were made on 5-point scales with verbal anchors of ‘very dissatisfied’ and ‘very satisfied’. A similar approach has been used by other authors (e.g. Crosby and Stephens, 1987; Czepiel, Rosenberg and Akerle, 1974; Westbrook, 1981) in assessing overall satisfaction and satisfaction with components that are deemed to drive overall satisfaction. The descriptive statistics for the satisfaction scales are shown in Table 2.

Table 2. Descriptive statistics for the satisfaction scales Satisfaction scales

Mean score

Standard deviation

Overall satisfaction

3.87

0.91

Satisfaction with staff

3.95

0.96

Satisfaction with product(s)

3.95

0.93

(iii)

Brand reputation

15

Brand reputation was assessed by asking consumers to evaluate the favourability of the financial services brand’s reputation on a 5-point scale with verbal anchors of ‘very unfavourable’ through to ‘very favourable’ (see Question 7 in Appendix A). The descriptive statistics for the reputation scale are shown in Table 3.

Table 3. Descriptive statistics for the reputation scale Reputation scale Favourability of reputation

Mean score

Standard deviation

3.94

0.83

Purifying the measure A principal components analysis with varimax rotation was performed on the seven consumer-based performance measures. The number of consumers who contributed usable data to this analysis was 600. Both a criterion of eigenvalues of greater than 1.00 and the scree plot indicated a one factor solution. This single factor accounted for 60.8% of the variance, a level deemed acceptable in the social sciences (Hair, Anderson, Tatham and Black, 1998). Table 4 presents the component score coefficient matrix and enables researchers to measure the consumer-based equity of financial services brands. This can be done by multiplying consumers’ assessments of the first characteristic in table 4 by 0.107, adding to that 0.167 times consumers’ assessment of the second characteristic, adding to that 0.211 times consumers’ assessment of the third characteristic, etc. for all seven characteristics.

Having developed this measure, its reliability and validity then needed assessing, as is explained in the next section.

16

Table 4. Component score coefficient matrix for principal components analysis of the consumer-based equity measure. Consumer-based equity

Component 1

Conative brand loyalty: consider using other products

0.107

Conative brand loyalty: prepared to recommend brand to other people

0.167

Affective brand loyalty: liking for brand

0.211

Overall satisfaction with the brand

0.211

Satisfaction with staff

0.188

Satisfaction with the product(s)

0.195

Brand reputation

0.183

Assessing reliability and validity The reliability of the consumer-based equity measure was assessed by calculating Cronbach’s alpha for the 7-item scale. The Cronbach’s alpha value of 0.88 exceeded the generally accepted lower limit of 0.7 (Robinson and Shaver, 1973; Robinson, Shaver and Wrightsman, 1991). Furthermore, the inter-item correlations were all 0.3 or above, as recommended in the rule-of-thumb described by Hair et al. (1998). The consumer-based equity measure was therefore deemed to demonstrate satisfactory reliability.

Hair et al. (1998) recommended that the results be validated by performing a confirmatory factor analysis on either a split sample or a new sample of data. However, given that the principal components analysis suggested a single factor solution, performing a confirmatory factor analysis was not appropriate. Nevertheless, the stability of the factor model results was tested by splitting the sample and performing a separate principal components analysis on each. Comparison of the two factor matrices from the analyses was used to assess the robustness of the factor 17

solution across the overall sample (cf. Hair et al., 1998). The sample was split into two equal samples using the random sample function of SPSS. This generated samples of usable data from 299 and 301 consumers respectively. Principal components analysis of the two samples yielded comparable results, both between the split samples and with the original combined sample. The scree plots all indicated a single factor solution, which accounted for 58.3% and 63.2% of the variance in the two split sample analyses (60.8% of the variance was accounted for in the combined sample). The component score coefficient matrix in each of the analyses was very similar, as shown in Table 5. These results suggested that the obtained solution was robust across the sample.

Table 5. Comparison of the component score coefficient matrix for principal components analysis of the consumer-based equity measure between the combined and split samples.

Consumer-based equity

Component 1 (combined sample)

Component 1 (split sample A)

Component 1 (split sample B)

Conative brand loyalty: consider using other products

0.107

0.092

0.119

Conative brand loyalty: prepared recommend brand to other people

0.167

0.169

0.164

Affective brand loyalty: liking for brand

0.211

0.217

0.204

Overall satisfaction with the brand

0.211

0.217

0.206

Satisfaction with staff

0.188

0.198

0.180

Satisfaction with the product(s)

0.195

0.200

0.190

Brand reputation

0.183

0.186

0.180

to

In addition to assessing the stability of the factor model results, as a further validation check the principal components analysis on the full sample was re-run with outliers on 18

the seven scales omitted, as recommended by Hair et al. (1999). The results of this reanalysis proved comparable to the original principal components analysis. Again, both the eigenvalues greater than 1 criterion and scree plot indicated a one factor solution, which accounted for 58.4% of the variance. As Table 6 shows, the component score coefficient matrix was similar to those obtained previously.

Table 6. Component score coefficient matrix for the re-run principal components analysis of the consumer-based equity measure with outliers omitted. Consumer-based equity

Component 1

Conative brand loyalty: consider using other products

0.094

Conative brand loyalty: prepared to recommend brand to other people

0.159

Affective brand loyalty: liking for brand

0.217

Overall satisfaction with the brand

0.217

Satisfaction with staff

0.194

Satisfaction with the product(s)

0.203

Brand reputation

0.192

Other issues in assessing the validity of the measure include consideration of various types of validity: content or face validity (the extent to which the scale represents the concept it is intended to measure); convergent validity (the extent to which the scale values correspond to other similar measures); discriminant validity (the extent to which the scale values diverge from dissimilar measures) and nomological validity (the accuracy with which the scale is able to predict other concepts in a theoretical model) (Hair et al., 1998).

As care was taken to ensure that all seven scales represent types of consumer-based equity, the measure may be considered to have adequate content validity. 19

The measure’s convergent validity was assessed by correlating the corporate brands’ consumer-based equity scores produced by the measure with the mean consumer ratings of the extent to which the corporate brand’s personality characteristics were like (i) their ideal self-concept, and (ii) their actual self-concept (measured on 5-point scales with verbal anchors of ‘very much unlike my ideal (actual) self’ and ‘very much like my ideal (actual) self’). This consumer data was collected as part of the survey.

When people choose between competing brands, they prefer brands whose

perceived personality match their own personality since this allows consumers to express their actual self (Belk 1988) or ideal self (Malhotra 1988).

One would

therefore expect a positive significant correlation between the consumer-based equity scores and the two measures of the corporate brand’s personality characteristics. In both cases, significant correlations were obtained. The consumer-based equity measure was significantly correlated with consumers’ mean rating for ideal selfconcept (r=0.942; N=10; p=0.000). The better the consumer-based equity score, the more consumers rated the corporate brand’s personality characteristics as being similar to their ideal self-concept. Similarly, the consumer-based equity measure was significantly correlated with consumers’ mean rating for actual self-concept (r=0.942; N=10; p=0.000). The better the consumer-based equity score, the more consumers rated the corporate brand’s personality characteristics as being similar to their actual self-concept. These results suggest that the measure demonstrated acceptable convergent validity.

The data collected did not enable the measure’s discriminant validity to be assessed.

20

Nomological validity was assessed by correlating the corporate brands’ consumerbased equity scores produced by the measure with the increase in sales for the corporate brands between 1998 and 1999, when that data were collected. The Marketing Science Institute definition of brand equity specifically relates to the way that a set of associations and behaviours enables a brand to achieve higher levels of sales. Thus, if the consumer-based equity measure has nomological validity, it should be able to predict increased sales. Comparable sales data were obtained from the FAME financial database and the increase in sales between 1998 and 1999 calculated. A significant correlation was obtained between the measure of consumer-based equity and the increase in sales data (r=0.912; N=10; p=0.004). The better the consumerbased equity, the greater the increase in sales. This suggests that the measure provides satisfactory nomological validity.

Discussion and managerial implications Services branding has attracted less interest than product branding and this paper contributes to the paucity of services branding literature through describing the procedure, and the resulting consumer-based brand equity measure, that may be used to assess financial services brands’ performance.

We have shown that the measure

has satisfactory reliability and validity.

The measure represents an easily administered tool for managers and researchers to assess consumers’ evaluations of financial services brands. It encourages managers to consider how changes in their brand strategies will impact on brand ol yalty, consumer satisfaction and brand reputation, and through becoming more vigilant about these antecedents, have a more rounded insight to changes in their brand’s equity. By using this measurement tool on a regular basis across its portfolio of financial services

21

brands, an organisation will be able to appreciate how their brands are performing on a relative basis, and by building an historical database, can better decide how resources should be allocated.

Through including competing brands in the tracking monitor, managers should be better equipped to identify any competitive threats.

By collecting data about the

impact on the antecedents of consumer-based equity from changes in competitors’ strategies, managers can assess the likely severity of competitors’ activities and plan to better protect their brand.

Furthermore, by understanding the weaknesses of

competitors’ brands, in terms of the three antecedents of consumer-based equity, strategies could be devised to enhance the attractiveness of the firm’s brands over its competitors.

Were firms to use their databases to monitor the relationship between its consumerbased equity and corporate performance outcomes, such as market share movements, it could develop more realistic brand objectives in its planning documents.

One of the trends in financial services is the merger of companies.

This leads to

considerable debate amongst management teams about the most appropriate naming strategy. The measure developed in this paper enables the consumer-based equity of each of the corporate brands to be assessed and provides further guidance as to which of the existing brand names is the most appropriate, based on the strengths of the separate financial services brands.

It also enables the senior managers of the newly

merged financial services organisation to consider which of the three equity components will demand their early attention.

22

This study has focused on the financial services sector. measure to other sectors has not been investigated.

The generalisability of the Furthermore, in view of the

interest and impact of different stakeholders on a brand’s well-being, the concentration of this study on consumers makes it difficult to comment about other stakeholders.

Researchers are encouraged to extend this study to other sectors and

stakeholders.

Conclusions This paper has shown how a valid and reliable measure has been devised to assess the consumer-based equity of financial services brands.

Adopting Churchill’s (1979)

paradigm has provided a sound basis for developing a consumer-based equity measure.

It has identified three key variables that constitute brand equity, and it

enables researchers and managers to appreciate from changes in these variables why movements are occurring in a brand’s equity.

This research has been specific to

financial services and researchers are encouraged to extend this research into other service and product sectors.

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APPENDX A

Consumer-based equity items collected in the consumer questionnaire

Q1

Q2

Q3

Would you consider using other products by [insert brand name]?

Yes…………………..

o

No……………………

o

1

2

3

4

5

Very much

1

2

3

4

5

Very satisfied

5

Very satisfied

5

Very satisfied

How satisfied are you with the [insert brand name]’s sales/service staff? 1

2

3

4

How satisfied are you with [insert brand name]’s product(s) that you have? Very dissatisfied

Q7

o

How satisfied are you overall with the [insert brand name] brand?

Very dissatisfied

Q6

No……………………

How much do you like [insert brand name]? (Please circle the appropriate number on the scale below.)

Very dissatisfied

Q5

o

Would you recommend [insert brand name] to other people?

Not at all

Q4

Yes…………………..

1

2

3

4

What is your evaluation of the [insert brand name] brand’s reputation? (Please circle the appropriate number on the scale below.) Very unfavourable

1

2

34

3

4

5

Very favourable