Conference PaperPDF Available

Customer experience in retail banking: what touchpoints matter for customer loyalty?

Authors:

Abstract and Figures

The availability of new online channels has led to an explosion in the number of different touchpoints. This is putting pressure on retailers to design omni-channel Customer Experiences (CE). To develop CE, practitioners have started to adopt Customer Experience Management (CEM), that is a firm-wide management approach for designing CE (Homburg, Jozić, and Kuehnl 2015). The final goal of CEM is achieving long-term customer loyalty by designing and continually renewing touchpoint journeys (Homburg, Jozić, and Kuehnl 2015). Hence, it is key to measure the role of each touchpoint within the customer journey and its contribution to develop the relationship between the customer and the company (Baxendale, MacDonald and Wilson 2015). To date, however, few studies have performed comparisons among touchpoints and no study has explored the relative touchpoint contribution to customer loyalty. The present study addresses this issue and focuses on the reach and the relative contribution of touchpoints to customer loyalty in a multichannel retail banking setting. Touchpoint contribution to loyalty is evaluated separately by considering reach-i.e. customer exposure to each touchpoint in the period of reference-and positivity-i.e. the valence of the customer's affective response to each touchpoint (Kahn & Isen 1993). By means of a survey on almost five thousand consumers this study aims to provide an examination of the relative importance of twenty-two touchpoints in contributing to customer loyalty to retail banks. Our findings suggest that thirteen touchpoints out of the twenty-two analysed play a significant role for customer loyalty to the bank in terms of reach, positivity or both. Findings reveal relevant managerial implications. Special focus should be devoted, in terms of investment and effort, to a specific set of offline and online touchpoints to enhance their potential to achieve long-term customer loyalty within an omni-channel perspective.
Content may be subject to copyright.
Customer experience in retail banking:
what touchpoints matter for customer loyalty?
Dr. Marco Ieva, University of Parma
Prof. Cristina Ziliani, University of Parma
The availability of new online channels has led to an explosion in the number of
different touchpoints. This is putting pressure on retailers to design omni-channel
Customer Experiences (CE). To develop CE, practitioners have started to adopt
Customer Experience Management (CEM), that is a firm-wide management
approach for designing CE (Homburg, Jozić, and Kuehnl 2015). The final goal of
CEM is achieving long-term customer loyalty by designing and continually
renewing touchpoint journeys (Homburg, Jozić, and Kuehnl 2015). Hence, it is
key to measure the role of each touchpoint within the customer journey and its
contribution to develop the relationship between the customer and the company
(Baxendale, MacDonald and Wilson 2015). To date, however, few studies have
performed comparisons among touchpoints and no study has explored the relative
touchpoint contribution to customer loyalty. The present study addresses this
issue and focuses on the reach and the relative contribution of touchpoints to
customer loyalty in a multichannel retail banking setting. Touchpoint
contribution to loyalty is evaluated separately by considering reach - i.e.
customer exposure to each touchpoint in the period of reference - and positivity -
i.e. the valence of the customer’s affective response to each touchpoint (Kahn &
Isen 1993). By means of a survey on almost five thousand consumers this study
aims to provide an examination of the relative importance of twenty-two
touchpoints in contributing to customer loyalty to retail banks. Our findings
suggest that thirteen touchpoints out of the twenty-two analysed play a significant
role for customer loyalty to the bank in terms of reach, positivity or both.
Findings reveal relevant managerial implications. Special focus should be
devoted, in terms of investment and effort, to a specific set of offline and online
touchpoints to enhance their potential to achieve long-term customer loyalty
within an omni-channel perspective.
Keywords: customer experience; customer loyalty; touchpoints; retail bank.
Introduction
The availability of new online channels has led to an explosion in the number of
different touchpoints (Pantano and Viassone 2015), - i.e. the number of verbal or
nonverbal incidents a person perceives and consciously relates to a given firm or brand
(Duncan and Moriarty 2006) - within the customer journey. New touchpoints are
putting pressure on retailers to design an omni-channel Customer Experience (CE)
(Verhoef, Kannan, and Inman 2015). “CE is the evolvement of a person’s sensorial,
affective, cognitive, relational, and behavioural responses to a firm or brand by living
through a journey of touchpoints along pre-purchase, purchase, and post-purchase
situations…” (Homburg, Jozie, and Kuehnl 2015, 8). A seamless experience across
online and offline touchpoints will deliver a stronger overall CE (Lemon and Verhoef
2016).
To develop CE, practitioners have started to adopt Customer Experience
Management (CEM) (Homburg, Jozić, and Kuehnl 2015). The CEM framework is a
firm-wide management approach for designing CE. The final goal of CEM is achieving
long-term customer loyalty by designing and continually renewing touchpoint journeys
(Homburg, Jozić, and Kuehnl 2015). However, the (re)design of customer journeys
forces companies to choose how they should allocate investment and efforts across
touchpoints (Court et al. 2009). Hence, it is key to measure the role of each touchpoint
within the customer journey and its contribution to develop the relationship between the
customer and the company (Baxendale, MacDonald, and Wilson 2015). Few studies
perform comparisons among touchpoints: the topic of touchpoint journey and
touchpoint effectiveness remains largely unexplored (Lemon and Verhoef 2016).
Moreover, no studies focus on the relative contribution of touchpoints with respect to
customer loyalty, which has been regarded as the ultimate objective of CEM (Homburg,
Jozić, and Kuehnl 2015). Therefore, providing a linkage between touchpoints and
customer loyalty has been recently included as a key element of the updated research
agenda for CE (Lemon and Verhoef 2016).
The present study focuses on the reach and the relative contribution of
touchpoints to customer loyalty in a multichannel retail banking setting. Touchpoint
contribution to loyalty is evaluated separately by considering touchpoint reach - i.e. the
exposure to each touchpoint in the period of reference - and touchpoint positivity - i.e.
the valence of the customer’s affective response to each touchpoint (Kahn and Isen
1993). By means of a survey on almost five thousand customers, this study aims to
provide a holistic examination of the relative importance of twenty-two touchpoints in
contributing to customer loyalty to retail banks.
Our findings suggest that thirteen touchpoints out of the twenty-two analysed
play a significant role for customer loyalty to the bank in terms of reach, positivity or
both. Results provide guidance for banks, service providers and retailers on how to
improve their CEM and their investment allocation across touchpoints. In the following
sections, we review key literature on the topic, present the methodology for the study,
show findings, and discuss implications for practice as well as research directions.
Theoretical background
CE develops throughout all touchpoints encountered during the service delivery process
(Jüttner et al. 2013). This study adopts a broad definition of touchpoints, including all
verbal or nonverbal incidents a person perceives and consciously relates to a given firm
or brand (Duncan and Moriarty 2006). This definition is wider than the definitions of
channel or media touchpoints as specified respectively in Neslin et al. (2006) and in
Sundar et al. (1998). Touchpoints have been classified into four main groups (Lemon
and Verhoef 2016): brand owned touchpoints, partner owned touchpoints, customer
owned touchpoint and social/external touchpoints. Even though this classification
entails some overlap across the defined categories, it helps companies identify which
touchpoints they can own or influence and which are not under their control. Most
academic research on touchpoints has focussed on a category of touchpoints in
isolation, i.e. on a group of similar touchpoints involved in a part of the customer
journey (Baxendale, MacDonald, and Wilson 2015). For instance, many studies have
analysed the role of touchpoints in the online setting, which is characterized by higher
availability of data at the individual level (e.g., Li and Kannan 2014; Xu, Duan, and
Whinston 2014). Such studies employ attribution models and provide insights on some
portions of the customer journey. However, further studies are needed to complement
these findings with a wider perspective on the relative role of each touchpoint within the
customer journey.
The present study considers a wide range of touchpoints, and includes
touchpoints that have been ignored in previous studies (i.e., loyalty programs). The role
of touchpoints is evaluated in terms of reach and positivity. Touchpoints might reach
different customer segments. Reaching consumers in the right segment with the right
message is essential for media placement (Romaniuk, Beal, and Uncles 2013).
Romaniuk, Beal, and Uncles (2013) found that touchpoints such as television
advertising, gift-pack, in store displays/promotion and outdoor advertisements reach the
average category and brand user, in a grocery setting. Social media and word of mouth
skew the heavy category and brand users. Frequency of exposure to touchpoints may
also differ across customer segments and has been found to influence brand attitudes
(Cambpell and Keller 2003) and brand consideration changes (Baxendale, MacDonald,
and Wilson 2015).
Positivity of interactions with touchpoints is a key aspect that should be
measured to evaluate the importance of touchpoints in the customer journey
(Baxendale, MacDonald, and Wilson 2015). Positivity, which is the valence of the
affective response to a touchpoint encounter, has been shown to have an impact on
spending and repeat purchase intentions (Arnold and Reynolds 2009). In fact, affect
coming from an experience with a touchpoint is believed to be embodied in the
customer’s evaluative response (Westbrook and Oliver 1991), influencing future brand-
related cognitions (Baumeister et al. 2007). Baxendale, MacDonald, and Wilson (2015)
have evaluated the impact of multiple touchpoints in terms of frequency and positivity
on brand consideration changes. Brand consideration has been defined as the extent to
which the customer would consider buying the brand in the future (Roberts and Lattin
1997) and it is closely related to purchase intention. They show that frequency and
positivity of interactions with touchpoints influence brand consideration changes.
However, their study leaves unexplored the issue of the relative contributions of
touchpoints to customer loyalty, which is the ultimate goal of CEM (Homburg, Jozic,
and Kuehnl 2015). Other studies show that positivity is associated with satisfaction
(Westbrook and Oliver 1991) and commitment (Ahluwalia, Burnkrant, and Unnava
2000), that have been identified as drivers of customer loyalty (e.g. Shankar, Smith, and
Rangaswamy 2003). A positive experience with a touchpoint could be a significant
predictor of customer loyalty.
The conceptualization of loyalty ranges from a behavioural approach - defining
loyalty as repeated purchase behaviour and probability of product repurchase (Lipstein
1959; McConnell 1968) - and a cognitive approach - highlighting the attitudinal
dimensions of loyalty (Lalaberba and Marzusky 1973) As customer loyalty includes
multiple dimensions rather than the sole purchase intention (Ngobo 2016; Gremler
1995) previously mentioned findings on brand consideration cannot be extended to it.
Although it is a challenging task, it is key to identify critical touchpoints
throughout the customer journey, that are most influential on the relevant customer
attitudes and behaviours (Lemon and Verhoef 2016). This could lead to a better
theoretical understanding of the customer journey and it would help practitioners to
improve design and measurement of customer experience and related investment in
retailing and consumer services. Drawing from the abovementioned theoretical
background, we argue that both the reach and the valence of the affective response to a
touchpoint may explain customer loyalty toward a company. Hence, we formulate the
following research questions:
RQ1: How do the audiences reached by different touchpoints compare in terms
of customer loyalty to the company?
RQ2: Does touchpoint positivity contribute to customer loyalty to the company?
We address these questions in the retail banking context, which is undergoing a
fast-digital transformation.
Methodology and results
To answer the above research questions data were collected by means of an online
cross-sectional survey conducted in one European country by means of the Nielsen
consumer panel. The panel includes 6,233 subjects over 14 years old. Among these,
4,963 complete responses were collected from subjects who own a bank account. We
asked respondents to answer the survey with reference to the bank that attains the
highest share of their wallet for financial activities. A list of 22 touchpoints was
identified with reference to retail banking by considering and integrating lists of
touchpoints employed in previous studies (e.g., Romaniuk, Beal, and Uncles 2013).
Respondents were asked to indicate the frequency of interaction with each touchpoint in
the previous three months on a single Likert-scale item (7-point scale) anchored by
“never” and “very often”. Touchpoint reach was computed as a dummy variable from
touchpoint frequency, assuming value equal to one in case of touchpoint exposure in the
period of reference. Touchpoint frequency has been further transformed by employing
its natural logarithm: it is assumed that communication wears out through over-
exposure (Bass et al. 2007). Positivity was measured by means of the single Likert-scale
item “How did it make you feel about the retailer?” on a 5-point scale anchored by
“very positive” and “very negative”, from Baxendale, MacDonald, and Wilson (2015).
This variable was then re-centered around zero and if the participant did not report any
interactions with a touchpoint (i.e., frequency is zero), positivity was imputed as zero as
well, following the procedure from Baxendale, MacDonald, and Wilson (2015). The
touchpoint list was randomized per each respondent to avoid any order bias in the
responses. We also cleaned the data to ensure that careless responses were identified
and removed from the analysis. Loyalty to the bank was measured by means of the 7-
point Likert-scale from Zeithaml and Barry (1996), which was developed by the authors
within a behavioural-intentions battery. The scale has been adapted in order to be
referred to the bank of reference and has been proved to be reliable as its Cronbach’s
Alpha is equal to 0.91.
We run two OLS regression models with clustered standard errors taking into
account that observations nested within the same family are not independent. As a
matter of fact, customers belonging to the same family might influence each other as far
as their experience with the relative bank is concerned. We clustered standard errors for
the 2834 families to which respondents belonged to. In the first model (Model 1) loyalty
to the bank was regressed on touchpoint reach included at the single touchpoint level. In
the second model (Model 2) loyalty to the bank was regressed on touchpoint positivity,
and touchpoint frequency was included as a control variable both touchpoint positivity
and frequency were included at the single touchpoint level. VIF values were below or
equal to 3 for both models, thus multicollinearity was not a concern. Socio-demographic
information per each respondent was also available and it has been included in both
Model 1 and Model 2 in terms of several control variables. Standardized coefficients
were computed in Model 2 and compared to highlight the relative importance of each
touchpoint in terms of positivity. Analyses were conducted by means of SAS 9.4. Table
1 shows descriptive results as far as touchpoint reach, frequency and positivity are
concerned. ATM machine, bank branch, bank associates and bank website display the
highest reach, frequency and positivity. Model 1 (see Table 2), shows that touchpoints
reach has a significant relationship with loyalty to the bank for 9 touchpoints.
Table 1. Descriptive statistics on reach, frequency and positivity across touchpoints
Variable
Reach
Frequency
score
Positivity
score
TV and cinema advertising
23%
1.60
0.02
Radio advertising
18%
1.44
0.01
Newspaper advertising
23%
1.56
0.01
Customer magazine
15%
1.39
0.01
Direct mailing
56%
2.74
0.20
Billboards
21%
1.51
0.01
Online advertising
24%
1.64
0.02
Social networks
14%
1.37
0.02
Bank website
67%
4.04
0.68
Bank branch
67%
3.21
0.48
Special events
16%
1.44
0.04
ATM machine
79%
4.37
0.78
Branch associates
64%
3.15
0.57
Word of mouth
27%
1.70
0.06
E-mailing
41%
2.30
0.17
Loyalty program
18%
1.49
0.02
Mobile app
33%
2.39
0.31
Special promotions
15%
1.40
0.01
Mobile messaging
36%
2.14
0.20
Customer service
45%
2.33
0.32
Customer satisfaction
surveys
23%
1.58
0.05
Telemarketing
13%
1.32
-0.01
N=4963
Table 2. Model 1: customer loyalty to the bank regressed on touchpoint reach and
control variables
Variable
Coefficient
Intercept
3.6851
REACH
TV and cinema advertising
0.0439
Radio advertising
-0.1836*
Newspaper advertising
-0.0253
Customer magazine
0.0057
Direct mailing
-0.09
Billboards
-0.0156
Online advertising
0.0267
Social networks
0.0812
Bank website
0.2296***
Bank branch
-0.1686**
Special events
0.1257
ATM machine
0.0657
Branch associates
0.0798
Word of mouth
0.4837***
E-mailing
0.2202***
Loyalty program
-0.0115
Mobile app
0.291***
Special promotions
0.0519
Mobile messaging
0.0636
Customer service
0.1864***
Customer satisfaction surveys
0.1449***
Telemarketing
-0.4755***
Number of household
members
-0.041
Age
0.0032*
Affluency (Low)
-0.0264
Affluency (Low-to-average)
0.0009
Affluency (Average-to-high)
0.0316
City (Very small)
0.2374**
City (Small)
0.2284**
City (Medium)
0.2314**
Gender (Female)
-0.0653*
*p<.05; **p<.01;***<.001 High affluency and large cities are employed as a term of reference for
respectively, affluency and city.
Results for RQ1: Out of twenty-two touchpoints, the reach of the following six
touchpoints is positively related to loyalty to the bank: bank website, word of mouth, e-
mailing, mobile app, customer service and customer satisfaction surveys. On the other
hand, the reach of the following three touchpoints is negatively related with loyalty to
the bank: bank branch, telemarketing and radio advertising.
Table 3 shows results as far as Model 2 is concerned: when controlling for
touchpoint frequency, positivity has a significant relationship with loyalty to the bank as
far as 9 touchpoints are concerned.
Table 3. Model 2: customer loyalty to the bank regressed on touchpoint positivity and
control variables
Variable
Coefficient
Standardized
coefficient
Standardized
coefficient rank
Intercept
3.5067
POSITIVITY
Positivity
ranking
TV and cinema advertising
0.0347
Radio advertising
0.0516
Newspaper advertising
0.0518
Customer magazine
-0.1155*
-0.0318
9
Direct mailing
0.1302***
0.0712
6
Billboards
-0.0646
Online advertising
0.0505
Social networks
-0.0191
Bank website
0.1647***
0.1100
3
Bank branch
0.2123***
0.1359
2
Special events
0.032
ATM machine
0.268***
0.1791
1
Branch associates
0.1364***
0.0899
5
Word of mouth
0.1236***
0.0485
8
E-mailing
0.1081***
0.0523
7
Loyalty program
-0.093
Mobile app
0.037
Special promotions
0.0155
Mobile messaging
0.0593
Customer service
0.1942***
0.1078
4
Customer satisfaction
surveys
-0.0193
Telemarketing
-0.0606
FREQUENCY
TV and cinema advertising
0.0208
Radio advertising
-0.0827
Newspaper advertising
0.0459
Customer magazine
0.046
Direct mailing
-0.0548
Billboards
-0.0083
Online advertising
0.0084
Social networks
0.245**
Bank website
-0.0032
Bank branch
-0.1962***
Special events
0.0771
ATM machine
-0.1841***
Branch associates
0.0017
Word of mouth
0.4669***
E-mailing
0.1113*
Loyalty program
0.0758
Mobile app
0.1492**
Special promotions
0.0412
Mobile messaging
-0.0073
Customer service
-0.0046
Customer satisfaction
surveys
0.1072
Telemarketing
-0.3895***
Number of household
members
-0.0141
Age
0.0004
Affluency (Low)
-0.0258
Affluency (Low-to-
average)
-0.034
Affluency (Average-to-
high)
-0.0488
City (Very small)
0.152***
City (Small)
0.1242*
City (Medium)
0.1215
Gender (Female)
-0.0971***
*p<.05; **p<.01;***<.001 High affluency and large cities are employed as a term of reference for
respectively, affluency and city.
Results for RQ2: Nine touchpoints out of twenty-two are significantly related to
customer loyalty as far as positivity is concerned: ATM machine, bank branch, bank
website, customer service, branch associates, direct mailing, e-mail, word of mouth,
customer magazine.
Discussion and conclusions
This study compares the relative importance of different touchpoints in their
relationship with customer loyalty to the bank. Results on almost five thousand
respondents show that only thirteen out of the twenty-two touchpoints considered in this
study are significantly related to customer loyalty. This reveals that it is important to
measure the role of touchpoints at the individual touchpoint level to avoid mis-
attribution or dilution of the relative touchpoint contribution.
The study shows that six touchpoints reach those customers who display higher
loyalty to the bank: bank website, word of mouth, e-mailing, mobile app, customer
service and customer satisfaction surveys. As most of these are “brand-owned”
touchpoints, banks might have higher control and flexibility to develop and manage
cross-up selling strategies through these touchpoints. Word of mouth is a touchpoint
that is not controllable by the company, but banks should devote efforts to closely
monitor it: word of mouth reaches high loyal customers and - as it will be discussed
below - also contributes positively to customer loyalty. On the other hand, three
touchpoints reach customers who display lower loyalty to the bank: radio advertising,
bank branch and telemarketing. Bank branch may reach customers whose behavioural
loyalty is only driven by location convenience. A customer could use a bank branch
close to his house or office just for convenience and not because he/she appreciates the
service. Telemarketing might be specifically addressed to reach customers that are at
risk of churn. Knowing what touchpoints reach different audiences help companies to
avoid duplication of investment. At the same time, knowing what touchpoints have
higher overlap points managers’ attention to what set of touchpoints should be
thoroughly orchestrated to always look and feel consistent and connected to customers.
Eight touchpoints contribute positively to customer loyalty to the bank: ATM
machine, bank branch, bank website, customer service, branch associates, direct
mailing, e-mailing and word of mouth. Out of this list, the top seven contributors in
terms of positivity are all “brand-owned” touchpoints. Both physical and digital
touchpoints are present among the most important touchpoints: this provides evidence
on the need for banks and financial companies to embrace an omni-channel perspective
across touchpoints in order to manage customer experience in an effective way. The
customer magazine is the only touchpoint that shows a barely significant negative
relationship between positivity and loyalty to the bank. This finding should be
complemented with additional evidence in order to provide conclusive results on the
role of customer magazine. It is also interesting to focus on the touchpoints that do not
contribute to customer loyalty, such as Tv advertising. Given the high amount of
investment devoted to Tv, banks might consider shifting some funds from Tv to other
touchpoints that are related to customer loyalty.
Fourth, it is interesting to compare each touchpoint in terms of reach and
positivity. Only four touchpoints can both (i) reach loyal customers and (ii) contribute
positively to customer loyalty: bank website, word of mouth, emailing and customer
service. Interestingly, while bank branch reaches customers displaying lower loyalty, its
relationship with customer loyalty to the bank is positive. Hence, the bank branch could
be a key touchpoint for customer retention as it allows to reach customers displaying
lower loyalty and it provides a positive contribution to customer loyalty. Mobile app,
customer satisfaction surveys, direct mailing and bank associates can reach loyal
customers but do not seem to contribute to their customer loyalty. From our results, we
might hypothesize that customers reached by these touchpoints already display high
levels of customer loyalty. Generally, consumers who already hold a very positive
attitude are more likely to move down the scale or stay where they are rather than
further increase their opinion (Baxendale, MacDonald, and Wilson 2015). Hence, this
might explain why these touchpoints contribute less to increase customer loyalty.
The results of this study have implications for marketing strategy in retail
banking. First, banks should be concerned with the specific reach of each touchpoint,
both in terms of number and type of customers reached. This could help them to address
the right message through the right touchpoint to the right audience and to better
evaluate the relative customer response. Second, special focus should be devoted, in
terms of investment and effort, to a set of both offline and online touchpoints to enhance
their potential to achieve long-term customer loyalty within an omni-channel
perspective. In particular, three touchpoints - website, emailing and mobile app - that
have been found to reach highly loyal customers and positively contribute to store
loyalty should receive attention and investment to provide an integrated consistent CE.
Their digital nature allows for this and makes them precious to CEM for the customer
data collection. Third, the ATM is the most important touchpoint both in terms of reach
and positivity: this should guide banks to focus on the quality of experience with this
touchpoint by conducting marketing research and developing improvements. Fourth,
promotional activities, both in terms of loyalty programs and special promotions have
been found not to matter in terms of frequency nor positivity. This should lead banks to
think about redesigning or innovating promotional activities to better match their related
objectives in terms of customer relationship management.
This study entails two main limitations. First, customers self-selected themselves
in the interaction with touchpoints. This issue is relevant when assessing the
relationship between touchpoint positivity and customer loyalty to the bank: self-
selection and reverse causality do not allow to draw causal inference statements on the
effect of positivity on customer loyalty. Second, even though surveys are commonly
employed for academic and practitioner studies on touchpoint interactions (e.g.,
Romaniuk, Beal, and Uncles 2013), respondents might find hard to remember the
experience with touchpoints they had some time ago (Wind and Lerner 1979). Future
studies should estimate the relative impact of different touchpoints on customer loyalty
and discover synergies across touchpoints by adopting different research designs.
Further research is needed on the identification and profiling of customer segments
based on exposure to touchpoints, rather than medium or channel preference (e.g.,
Konus, Verhoef, and Neslin 2008). Comparing and coupling a touchpoint-based
segmentation with the classic demographic segmentations could provide academic and
managerial insights on how to effectively segment consumers in an omni-channel
scenario.
References
Ahluwalia, R., R. E. Burnkrant, and H.R. Unnava. 2000. “Consumer response to
negative publicity: The moderating role of commitment.” Journal of Marketing
Research 37 (2): 203-214. doi: http://dx.doi.org/10.1509/jmkr.37.2.203.18734.
Arnold, M. J., and K.E. Reynolds. 2009. “Affect and retail shopping behavior:
Understanding the role of mood regulation and regulatory focus.” Journal of
Retailing 85 (3): 308-320. doi: http://dx.doi.org/10.1016/j.jretai.2009.05.004.
Bass, F. M., N. Bruce, S. Majumdar, and B.P.S. Murthi. 2007. “Wearout effects
of different advertising themes: A dynamic Bayesian model of the advertising-sales
relationship.” Marketing Science 26 (2): 179-195. doi:
http://dx.doi.org/10.1287/mksc.1060.0208.
Baxendale, S., E. K. Macdonald, amd H.N. Wilson. 2015. “The impact of
different touchpoints on brand consideration.” Journal of Retailing 91 (2): 235-253. doi:
http://dx.doi.org/10.1016/j.jretai.2014.12.008.
Baumeister, R. F., D. V. Kathleen, C. N. DeWall, and L. Zhang. 2007. “How
Emotion Shapes Behavior: Feedback, Anticipation, and Reflection, Rather Than Direct
Causation,” Personality and Social Psychology Review, 11: 167203. doi:
https://doi.org/10.1177/1088868307301033.
Campbell, M. C., and K.L. Keller. 2003. “Brand familiarity and advertising
repetition effects.” Journal of Consumer Research 30 (2): 292-304. doi:
https://doi.org/10.1086/376800.
Court, D., D. Elzinga, S. Mulder, and O. J. Vetvik. 2009. “The Consumer
Decision Journey,” McKinsey Quarterly, (3): 96107.
Duncan, T., and S. Moriarty. 2006. “How integrated marketing communication’s
‘touchpoints’ can operationalize the service-dominant logic.” Chap. 18 in The service-
dominant logic of marketing: Dialog, debate, and directions edited by Lusch, R. F., and
S. L. Vargo, 236-249. Armonk: Sharpe.
Gremler, D. D. 1995. The effect of satisfaction, switching costs, and
interpersonal bonds on service loyalty” Doctoral dissertation, Arizona State University.
Homburg, C., D. Jozić, and C. Kuehnl. 2015. “Customer experience
management: toward implementing an evolving marketing concept.” Journal of the
Academy of Marketing Science 1-25. doi:10.1007/s11747-015-0460-7.
Jüttner, U., D. Schaffner, K. Windler, and S. Maklan. 2013. “Customer service
experiences: Developing and applying a sequential incident laddering
technique.” European Journal of Marketing 47 (5/6): 738-769. doi:
http://dx.doi.org/10.1108/03090561311306769.
Kahn, B. E., and A. M. Isen. 1993. “The influence of positive affect on variety
seeking among safe, enjoyable products.” Journal of Consumer Research 20 (2): 257-
270. doi: https://doi.org/10.1086/209347.
Konuş, U., P.C. Verhoef, and S. A. Neslin. 2008. “Multichannel shopper
segments and their covariates.” Journal of Retailing, 84 (4): 398-413. doi:
http://dx.doi.org/10.1016/j.jretai.2008.09.002.
Lalaberba, P., and D. Marzusky. 1973. “A longitudinal assessment of consumer
satisfaction/dissatisfaction: The dynamic aspect of the cognitive process.” Journal of
Marketing Research 20: 393-404. doi: 10.2307/3151443.
Lemon, K. N., and P.C. Verhoef. 2016. “Understanding customer experience
throughout the customer journey.” Journal of Marketing 80 (6): 69-96. doi:
http://dx.doi.org/10.1509/jm.15.0420.
Li, H., and P.K. Kannan. 2014. “Attributing conversions in a multichannel
online marketing environment: An empirical model and a field experiment.” Journal of
Marketing Research 51 (1): 40-56. doi: http://dx.doi.org/10.1509/jmr.13.0050.
Lipstein, B. 1959. “The dynamics of brand loyalty and brand switching”
in Proceedings of the fifth annual conference of the advertising research foundation,
101-108. New York: Advertising Research Foundation.
McConnell, J. D. 1968. “The development of brand loyalty: an experimental
study.” Journal of Marketing Research, 13-19. doi: 10.2307/3149788.
Neslin, S. A., D. Grewal, R. Leghorn, V. Shankar, M. Teerling, J.S. Thomas,
and P.C. Verhoef. 2006. “Challenges and opportunities in multichannel customer
management.” Journal of Service Research 9 (2): 95-112. doi:
10.1177/1094670506293559.
Ngobo, P. V. 2016. “The trajectory of customer loyalty: an empirical test of
Dick and Basu’s loyalty framework.” Journal of the Academy of Marketing Science 1-
22. doi:10.1007/s11747-016-0493-6.
Pantano, E., and Viassone M. 2015. Engaging consumers on new integrated
multichannel retail settings: Challenges for retailers.” Journal of Retailing and
Consumer Services 25: 106-114. doi:
http://dx.doi.org/10.1016/j.jretconser.2015.04.003.
Roberts, J. H., and J. M. Lattin. 1997. “Consideration: Review of research and
prospects for future insights.” Journal of Marketing Research 406-410. doi:
10.2307/3151902.
Romaniuk, J., V. Beal, and M. Uncles. 2013. “Achieving Reach in a Multi-
Media Environment.” Journal of Advertising Research 53 (2): 221-230. doi:
10.2307/3151902.
Shankar, V., A. K. Smith, and A. Rangaswamy. 2003. “Customer satisfaction
and loyalty in online and offline environments.” International Journal of Research in
Marketing 20 (2): 153-175. doi: http://dx.doi.org/10.1016/S0167-8116(03)00016-8.
Sundar, S. S., S. Narayan, R. Obregon, and C. Uppal. 1998. “Does web
advertising work? Memory for print vs. online media.” Journalism & Mass
Communication Quarterly 75 (4): 822-835. doi:
https://doi.org/10.1177/107769909807500414.
Verhoef, P. C., P.K. Kannan, and J.J. Inman. 2015. “From multi-channel
retailing to omni-channel retailing: introduction to the special issue on multi-channel
retailing.” Journal of Retailing, 91 (2): 174-181. doi:
http://dx.doi.org/10.1016/j.jretai.2015.02.005.
Westbrook, R. A., and R. L. Oliver. 1991. “The dimensionality of consumption
emotion patterns and consumer satisfaction.” Journal of Consumer Research 18 (1): 84-
91. doi: https://doi.org/10.1086/209243.
Wind, Y., and D. Lerner. 1979. “On the measurement of purchase data: surveys
versus purchase diaries.” Journal of Marketing Research 39-47. doi: 10.2307/3150872.
Xu, L., J.A. Duan, and A. Whinston. 2014. “Path to purchase: A mutually
exciting point process model for online advertising and conversion.” Management
Science 60 (6): 1392-1412. doi: http://dx.doi.org/10.1287/mnsc.2014.1952.
Zeithaml, V. A., L. L. Berry, and A. Parasuraman. 1996. “The behavioral
consequences of service quality.” Journal of Marketing 31-46. doi: 10.2307/1251929.
... Researchers argue that customer satisfaction as well as a positive experience with a touchpoint could be significant antecedents of customer loyalty (Anderson and Sullivan, 1993;Homburg and Giering, 2001;Shankar et al., 2003;Ieva and Ziliani, 2017). Loyalty is defined as repeated purchase behavior and probability of product repurchase by Lipstein (1959) and McConnell (1968). ...
... International Journal of Business and Management Vol. 13, No. 1; omnichannel perspective, retailers will need to combine all the different touchpoints in order to reach highly loyal customers. Thanks to their digital nature, digital touch points allow for a better customer experience as well as advanced customer data collections (Ieva and Ziliani, 2017). ...
Article
Full-text available
The rise of the Internet, mobile technologies and digital disruption have changed the retail business as well as the implementation of the levers of retail mix and the behavior of shoppers. Online channel has become an appealing channel where retailers can sell their products and services. The proliferation of channels and touch points has affected not only consumer behavior but also companies' business models. Many retailers have started to develop multichannel and omnichannel strategies by adding new channels through which interact with the customers. Retailers are now concentrating on how shoppers are influenced by new technologies and how they switch across channels during their research and buying process. Omnichannel retailing, defined as the conceptualization of the complete integration of all channels, with no distinction between the online and the physical channel, is the new retailing paradigm of today. The topic itself is particularly relevant as technological development continue to disrupt retail strategies and practitioners are debating as to how to respond. Particularly, managers are worried about how to manage the several touch points, which are now simultaneously available to customers. Concerning with the present research, we attempt to describe this development by analyzing the existing literature about topics that we can classify within the omnichannel paradigm. In order to explain how both literature and business models are moving from multichannel retailing towards the implementation of omnichannel strategies, we follow a blended approach based on literature review, theoretical background as well as some interesting managerial insights resulting from business’ case histories. To address the concerns of managers and retailers about the new challenges they will need to face in implementing an omnichannel retailing approach, we present a theoretical framework, concerning with the adoption of the omnichannel as an innovative strategy in the overall marketing strategies. To deal with the topic we start from three research questions that guide our literature review as well as our theoretical framework. We investigate what are the key drivers that have stimulated retailers to develop an omnichannel retailing strategy, what are the new challenges that retailers will need to face when they decide to implement an omnichannel strategy in their overall marketing strategy and finally what are the possible outcomes of a correct and successful implementation of an omnichannel retailing strategy. Therefore, our theoretical framework explains key drivers, new challenges and potential outcomes coming from the adoption of the omnichannel retailing in order to help managers and practitioners who might decide to enter the omnichannel retailing.
Article
Full-text available
Technology enables a firm to produce a granular record of every touchpoint consumers make in their online purchase journey before they convert at the firm's website. However, firms still depend on aggregate measures to guide their marketing investments in multiple online channels (e.g., display, paid search, referral, e-mail). This article introduces a methodology to attribute the incremental value of each marketing channel in an online environment using individual-level data of customers' touches. The authors propose a measurement model to analyze customers' (1) consideration of online channels, (2) visits through these channels over time, and (3) subsequent purchases at the website to estimate the carryover and spillover effects of prior touches at both the visit and purchase stages. The authors use the estimated carryover and spillover effects to attribute the conversion credit to different channels and find that these channels' relative contributions are significantly different from those found by other currently used metrics. A field study validates the proposed model's ability to estimate the incremental impact of a channel on conversions. In targeting customers with different patterns of touches in their purchase funnel, these estimates help identify cases in which retargeting strategies may actually decrease conversion probabilities.
Article
Full-text available
The world of retailing has changed dramatically in the past decade. The advent of the online channel and new additional digital channels such as mobile channels and social media have changed retail business models, the execution of the retail mix, and shopper behavior. Whereas multi-channel was in vogue in the last decade in retailing, we now observe a move to so-called omni-channel retailing. Omni-channel retailing is taking a broader perspective on channels and how shoppers are influenced and move through channels in their search and buying process. We discuss this development conceptually and subsequently discuss existing research in this multi-channel retailing. We also introduce the articles in this special issue on multi-channel retailing and position these articles in the new omni-channel movement. We end with putting forward a research agenda to further guide future research in this area.
Article
Full-text available
Marketers face the challenge of resource allocation across a range of touchpoints. Hence understanding their relative impact is important, but previous research tends to examine brand advertising, retailer touchpoints, word-of-mouth, and traditional earned touchpoints separately. This article presents an approach to understanding the relative impact of multiple touchpoints. It exemplifies this approach with six touchpoint types: brand advertising, retailer advertising, in-store communications, word-of-mouth, peer observation (seeing other customers), and traditional earned media such as editorial. Using the real-time experience tracking (RET) method by which respondents report on touchpoints by contemporaneous text message, the impact of touchpoints on change in brand consideration is studied in four consumer categories: electrical goods, technology products, mobile handsets, and soft drinks. Both touchpoint frequency and touchpoint positivity, the valence of the customer's affective response to the touchpoint, are modeled. While relative touchpoint effects vary somewhat by category, a pooled model suggests the positivity of in-store communication is in general more influential than that of other touchpoints including brand advertising. An almost entirely neglected touchpoint, peer observation, is consistently significant. Overall, findings evidence the relative impact of retailers, social effects and third party endorsement in addition to brand advertising. Touchpoint positivity adds explanatory power to the prediction of change in consideration as compared with touchpoint frequency alone. This suggests the importance of methods that track touchpoint perceptual response as well as frequency, to complement current analytic approaches such as media mix modeling based on media spend or exposure alone.
Article
A simplified cognitive model is proposed to assess the dynamic aspect of consumer satisfaction/dissatisfaction in consecutive purchase behavior. Satisfaction is found to have a significant role in mediating intentions and actual behavior for five product classes that were analyzed in the context of a three-stage longitudinal field study. The asymmetric effect found demonstrates that repurchase of a given brand is affected by lagged intention whereas switching behavior is more sensitive to dissatisfaction with brand consumption. An attempt to predict repurchase behavior on the basis of the investigated cognitive variables yielded weak results. However, repurchase predictions were improved when the model was extended to a multipurchase setting in which prior experience with the brand was taken into account.
Article
The classic model of loyalty proposed by Dick and Basu (1994) assumes that customers can be naturally classified in four loyalty conditions. This model has been tested with cross-sectional data and measures of recalled or retrospective consumer loyalty. Therefore, these studies could not examine whether and why customers move across different loyalty conditions over time, and offer guidance to managers on how to shift customers to the more desirable loyalty conditions. In this paper, we conduct an empirical test of this model and examine the key drivers of shifts in consumers’ loyalty conditions over six annual time periods. Based on data from 6,109 households and 23 stores, we find customers can be classified in three loyalty conditions only: (1) the no-loyalty, (2) the latent loyalty, and (3) the true loyalty conditions. The spurious loyalty condition is not supported probably because switching costs are negligible in the grocery retailing industry. However, we find that marketing actions, i.e. private label policy, feature advertising, end-of-aisle product display, and store pricing policy, influence customer transition across loyalty conditions.
Article
Understanding customer experience and the customer journey over time is critical for firms. Customers now interact with firms through myriad touch points in multiple channels and media, and customer experiences are more social in nature. These changes require firms to integrate multiple business functions, and even external partners, in creating and delivering positive customer experiences. In this article, the authors aim to develop a stronger understanding of customer experience and the customer journey in this era of increasingly complex customer behavior. To achieve this goal, they examine existing definitions and conceptualizations of customer experience as a construct and provide a historical perspective of the roots of customer experience within marketing. Next, they attempt to bring together what is currently known about customer experience, customer journeys, and customer experience management. Finally, they identify critical areas for future research on this important topic.
The rapid diffusion of more channels for shopping posits new challenges for retailers, who need to compete in a complex environment for avoiding the problem of consumer cross-channel free riding. To discourage this behaviour, we propose a new environment where one retailer simultaneously handles more channels. The emerging integrated environment would engage more consumers if compared to the single handled channel, which in turn would avoid switching behaviours towards competitors' channels. Our empirical research, based on the stimulus–organism–response paradigm, involves a sample of 237 consumers who were asked to explore the new retail settings simulated in a university lab. The results lead us to suggest the effective combination of multiple channels managed by one retailer as the new challenge for scholars and practitioners. We note that our participants showed positive emotional reactions towards the environment, which lead them to choose this environment for purchases.
Article
A field experiment with a factorial design showed that consumers developed preferences for three brands of a physically homogeneous product (beer), identical except for brand name and price. With price used as a cue to brand quality and time measured by total purchase trials, strength of brand loyalty could be explained by perceived quality and a time trend.