TOTAL QUALITY MANAGEMENT, VOL. 11, NOS. 4/5&6, 2000, S509± S514
The relationship between customer
satisfaction and loyalty: cross-industry
diVerences
Lars Grønholdt,1 Anne Martensen2 & Kai Kristensen 2
1
Department of Marketing, Copenhagen Business School, Solbjerg Plads 3, DK-2000
Frederiksberg, Denmark & 2Department of Information Science, The Aarhus School of Business,
Fuglesangs Alle 4,DK-8210 Aarhus V, Denmark
Introduction
Customer satisfaction is a key issue for every company wishing to increase customer loyalty
and thereby create a better business performance.
An important question is therefore: What is the relationship between customer satisfaction and loyalty? The purpose of this paper is to answer this question and to investigate
diVerences across industries. An empirical study is conducted, based on data obtained from
the Danish part of the recently introduced European Customer Satisfaction Index (ECSI), a
Pan-European customer satisfaction measurement instrument. Thirty major companies were
investigated within various industries in Denmark.
First, the paper presents the methodology behind the ECSI. Second, the Danish part of
the ECSI pilot phase is described. Third, the empirical study and results are presented to
improve the understanding of how customer satisfaction aVects loyalty, and to investigate
diVerences across industries. The results have important implications for companies’ marketing strategy used to create customer satisfaction and loyalty.
The ECSI model and methodology
In 1989, Sweden became the ® rst country in the world to have a harmonized cross-company,
cross-industry national measurement instrument of customer satisfaction and evaluations of
quality of products and services, the Swedish Customer Satisfaction Barometer (SCSB)
(Fornell, 1992). SCSB has been adopted and adapted for use in the American Customer
Satisfaction Index (ACSI) (Fornell et al., 1996).
The successful experiences of the Swedish and US customer satisfaction indices have
inspired the creation of ECSI, founded by the European Organization for Quality (EOQ),
the European Foundation for Quality Management (EFQM) and the European Academic
Network for Customer-oriented Quality Analysis, and supported by the European Commission (DG III). A pilot study during 1999 was implemented in 12 European countries,
including Denmark.
ISSN 0954-4127 print/ISSN 1360-0613 online/00/04S509-06
€ 2000 Taylor & Francis Ltd
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L. GRé NHOLDT ET AL.
Image
Expectations
Perceived
value
Customer
satisfaction
Customer
loyalty
Perceived
quality of
ªhard wareº
Perceived
quality of
ºhuman wareº
Figure 1. The basic ECSI model.
European experts have developed the ECSI methodology, based on a set of requirements
(ECSI Technical Committee, 1998), e.g. comparability, reliability, robustness and structural
modelling approach.
The basic ECSI model (see Fig. 1) is a structural equation model with latent variables.
The model links customer satisfaction to its determinants and, in turn, to its consequence,
namely customer loyalty. The determinants of customer satisfaction are perceived company
image, customer expectations, perceived quality and perceived value (`value for money’).
Perceived quality is conceptually divided into two elements: `hard ware’, which consists of
the quality of the product/service attributes, and `human ware’ , which represents the
associated customer interactive elements in service, i.e. the personal behaviour and atmosphere of the service environment. Main causal relationships are indicated; actually there can
exist many more points of dependence between the variables.
These seven variables are seen as latent, i.e. non-observable. Each of the latent variables
is operationalized by two to six measurement variables (indicators), observed by survey
questions to customers.
The latent variable customer satisfaction is measured through three indicators, empirically observed by the three questions, that have dominated theory and practice within customer
satisfaction measurement (Ryan et al., 1995, pp. 11± 12).
First, overall satisfaction is measured as the answer to a question such as ``Considering
all your experience of company X, how satis® ed are you, in general?’’ on a scale from
`completely dissatis® ed’ to `completely satis® ed’. This approach is perhaps the most common
in customer satisfaction measurement practice (Ryan et al., 1995, p. 12).
Second, satisfaction is measured by a question of this type: ``To what degree did
RELATIONSHIP BETWEEN CUSTOMER SATISFACTION AND LOYALTY
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company X ful® l your expectations?’’ on a scale from `much less than expected’ to `much
more than expected’.
Third, there is used an ideal-point scale asking. ``Imagine a company which is perfect in
all aspects. How close to this ideal do you consider the company X to be?’’ on a scale from
`very far away’ to `very close’.
Each question captures diVerent facets of an underlying satisfaction perception. In
combination, the answers to these three questions give a reasonably accurate measure of the
latent variable for an individual. A customer satisfaction index is calculated by a weighted
average of scores from the three questions, and this approach will be more useful that a single
measure from any of the three questions. The use of multiple questions for each latent
variable increases the precision of the estimate, compared to use of a single question, and
there is empirical support for using such an approach within satisfaction measurements
(Fornell & Cha, 1994; Fornell et al., 1996; Ryan et al., 1995).
The latent variable customer loyalty is operationalized by four indicators: the customer’s
intention to repurchase; intention of cross-buying (buy another product from the same
company); intention to switch to a competitor (price tolerance); and intention to recommend
the brand/company to other consumers.
Data for the model estimation come from data collected through telephone interviews
from a national, representative sample of customers who are recent buyers and/or users of
speci® c products and services. For most companies interviews are conducted with about 250
of their customers. The sample size is determined by a precision requirement: a 95%
con® dence interval for customer satisfaction (on a 0± 100-point scale) should not be wider
that + 2 points. Another accuracy requirement is that R2 of customer satisfaction should be
at least 0.65, i.e. the model must be able to explain at least 65% of what drives customer
satisfaction (ECSI Technical Committee, 1998, pp. 20± 21).
The entire model is estimated using partial least squares (PLS) (Fornell & Cha, 1994).
The latent variables are operationalized as weighted indices of their measurement variables,
and the PLS estimation method weights the survey measures such that the resulting
model has maximum explanatory power, i.e. maximum prediction accuracy of the ultimate
dependent variable customer loyalty. The loyalty measure is a survey-based proxy for
economic results, and therefore the estimated measure for customer satisfaction should be a
forward-looking indicator of economic performance. Many empirical studies have demonstrated that customer satisfaction, based on the ACSI/SCSB approach, has an impact on
economic results (EkloÈf et al., 1999; Fornell, 1999), and therefore the ECSI measure of
customer satisfaction also has a linkage to economic performance.
For each company in the sample, the PLS method estimates indices for all the seven
latent variables, i.e. customer satisfaction, loyalty and their drivers. Furthermore, the PLS
method estimates the relationships within the entire model, i.e. the impacts between the
latent variables (inner coeYcients in the structural model) and the weights for each
measurement variable associated with a latent variable (outer coeYcients in the measurement
model).
All seven latent variables are transformed from the original 1± 10-point survey measures
to 0± 100-point scales, where zero means lowest possible (for example completely dissatis® ed)
and 100 means highest possible (for example completely satis® ed).
Measuring and estimation are made at the company level. Latent variable indices and
impact scores at industry level are calculated by aggregating company-level estimates,
weighted by market share.
A major advantage of the ECSI is the use of generic questions, which are suYciently
¯ exible to be used across a wide variety of products, services and public sector services, such
as education, healthcare, etc.
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L. GRé NHOLDT ET AL.
Data from the Danish part of the ECSI pilot study
Twelve European countries participated in the ECSI pilot study, and across Europe nearly
55 000 interviews were carried out during the spring of 1999. Telecommunication was
covered by all participating countries, and retail banks and supermarkets were covered by
nearly all the countries.
In Denmark, 30 companies within eight speci® c industries were included in the study,
namely four telecommunication industries (® xed net, mobile phones, the Internet and cable
television), retail banks, supermarkets, the soft drink industry and fast food restaurants.
During the spring of 1999, data were collected for the Danish ECSI pilot study. Nearly 9000
customers were interviewed regarding their perceptions of quality and satisfaction with
products and services in these industries.
Comparative results of these co-ordinated studies in 11 European countries have been
reported (ECSI, 1999), and the authors have presented Danish results and cross-industry
® ndings (Martensen et al., 2000).
Our experiences with the application of the ECSI model have been very good. The
model ® ts well and seems to be suYciently ¯ exible for diVerent industries.
Comparability has been highlighted by the ECSI Technical Committee (1998, pp. 7,
11). The ECSI methodology, i.e. the structural model approach, the questionnaire and the
estimation technique will allow comparisons between companies and organizations not only
at national levels but also at Pan-European and global levels. It is possible to make meaningful
comparisons with companies located outside Europe where similar customer satisfaction
indices are already produced, including the US and East Asia. As national customer
satisfaction indices reliably and consistently measure customer satisfaction and quality
perceptions for many companies within a variety of industries, the ECSI has the potential to
be an excellent platform for benchmarking.
Empirical ® ndings
Based on the results of Danish ECSI pilot study, we have analysed the relationship between
company-level customer satisfaction indices and loyalty indices. Figure 2 illustrates the
relationship, where the eight aggregated indices for the eight industries are also marked. The
® gure shows that customer satisfaction has a positive eVect on customer loyalty. This ® nding
comes as no surprise, since it is well supported in the literature. However, in our study the
relationship is estimated with a high explanatory power across the 30 companies plus `all
other’ companies within six industries.
Regression analysis shows that the relationship between customer satisfaction and loyalty
is strongly signi® cant: the estimated regression coeYcient is 1.14, i.e. for every point change
in satisfaction, loyalty changes by 1.14 point, on average (n 5 36, R2 5 0.691, t 5 8,71,
p-value < 0.0005).
Looking at the individual companies as they are positioned in Fig. 2, a very interesting
pattern appears. Very large positive residuals are found for companies with a low price
strategy. The supermarkets Netto and Fakta and Saltum/Rù rkjñ r Brewery (and the gas
stations Uno-X, also measured according to the ECSI methodology) are all companies that
have made price their main competitive weapon. These companies have a much larger loyalty
than expected from their customer satisfaction. On the other hand, we ® nd that companies
that have used a lot of energy on branding indeed have a high customer satisfaction but they
do not have a correspondingly high loyalty. This holds good for, for example, McDonald’s,
PepsiCo and Coca-Cola Company from the international scene and Faxe Brewery and Tele
Denmark from the Danish scene.
RELATIONSHIP BETWEEN CUSTOMER SATISFACTION AND LOYALTY
Customer loyalty
90
88
86
84
82
80
78
76
74
72
70
68
66
64
62
60
58
56
54
52
50
S513
Other banks
Other supermarkets
Tele2
Sydbank
Netto
Cola
Jyske
Bank Coca
Fù tex
Others,
soft drinks
SUPERMARKETS
SOFT DRINKS
Telia Fixed net
Saltum/Rù rkjñ r
Kvickly SuperBrugsen
Irma Faxe
get2net BANKS
Harboe
Fakta
Unibank
Bilka Pepsi
Den Danske Bank
Albani
Others,Sonofon
fast food
Tele Denmark
Internet
Aldi
BG Bank
FAST FOOD
Tele Denmark Cable TV Stofa OBS!
TELE, CABLE TV TELE, MOBILE TELE, INTERNET
Tele Denmark Mobile
Others, tele, mobile
Others, tele, internet
TELE, FIXED NET
McDonald© s
Tele Denmark Fixed net
50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80 82 84 86 88 90
Customer satisfaction
Figure 2. Customer satisfaction versus loyalty by companies and industries.
This may be a coincidence but it could also indicate that a given loyalty could be
obtained in many diVerent ways. One way is to increase customer satisfaction by branding
and similar activities, another is to be price eYcient. Which strategy is the better one is
impossible to say without further research into the generated income. The price strategy is
controlling loyalty by reducing revenue while the branding strategy is controlling loyalty by
increasing costs.
Similar regression analyses were carried out for each of four industry groupings. In all
four cases there is again a positive linear eVect of satisfaction on loyalty, but the regression
slopes are diVerent in an interesting pattern: for telecommunication industries (® xed net,
mobile phones and the Internet) the regression coeYcient is 1.64 (n 5 9, R2 5 0.908, t 5 8,30,
p-value <0.0005), for banks 1.42 (n 5 6, R2 5 0.990, t 5 19,81, p-value <0.0005), for
supermarkets 0.910 (n 5 10, R2 5 0.478, t 5 2,71, p-value 5 0.027) and for the soft drinks
industry 0.453 (n 5 7, R2 5 0.213, t 5 1,16, p-value 5 0.297). The eVect of satisfaction on
loyalty is signi® cant in the ® rst three cases and non-signi® cant in the last case. This pattern
for the regression coeYcients supports the hypothesis that the positive eVect of customer
satisfaction on loyalty increases with the degree of competition in the market, i.e. the more
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L. GRé NHOLDT ET AL.
competitive a market is, the more sensitive changes in loyalty are to changes in customer
satisfaction. In recent years, there has been great competition in the telecommunication and
bank markets in Denmark, where product diVerentiation and number of suppliers have
increased. This situation is still valid.
The relationship between market share and customer satisfaction was found to be negative
by Anderson et al. (1994) in Sweden and by GriYn and Hauser (1993) in the US. The same
relationship is also signi® cant for the 30 Danish companies measured. Thus, there is evidence
that increasing market share may decrease customer satisfaction. The argument is that it is
more diYcult to satisfy a large customer base, often consisting of multiple segments, compared
to a smaller one. Of the 30 companies only one (the Coca-Cola Company) achieved both
high customer satisfaction and high market share.
Conclusion
The newly developed methodology behind the Pan-European customer satisfaction measurement instrument ECSI has been applied in Denmark, and there are interesting results
providing insight about how customer satisfaction aVects customer loyalty; and diVerences
across industries have been investigated. Our experiences with the Danish applications of the
ECSI model have been very good. The model ® ts well and seems to be suYciently ¯ exible
for diVerent industries.
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