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ORIGINAL EMPIRICAL RESEARCH
Customer win-back: the role of attributions and perceptionsin customerswillingness to return
Doren Pick1 &Jacquelyn S. Thomas2&Sebastian Tillmanns
3&Manfred Krafft
3
Received: 9 January 2014 /Accepted: 28 May 2015 /Published online: 16 June 2015# Academy of Marketing Science 2015
Abstract Interest in customer reacquisition has increased as
firms embrace the concept of customer relationship manage-ment. Using survey and transactional data from defected sub-
scribers of a publishing company, we investigate how defected
customers evaluate their propensity to return to the company
prior to any win-back offer. We introduce a new variable for
relationship marketing, general willingness to return (GWR),
and show that it is strongly and positively related to the actual
return decision and the duration of the restarted relationship.
Combining attribution theory elements with existing win-back
explanations, which focus on economic, social, and emotional
value perceptions, provides a more comprehensive understand-
ing of the factors that influence the GWR to a former relation-
ship. Importantly, we learn that regardless of whose fault it is, if
the reasons for the relationship termination can change or are
preventable and the firm can control those changes, then the
defected customer has a higher general willingness to return to
the former relationship. Also, we show that the duration of time
absence before relationship revival moderates the impact of
GWR on second relationship duration. Furthermore, we dem-
onstrate that satisfaction prior to defection and the length oftime absence provide a reasonable basis for distinguishing
defected customers who differ in their GWR. By applying
our findings, we derive recommendations for firms on how to
position marketing communications to recapture defected
customers according to their general willingness to return.
Keywords Customerrelationship management. Relationship
revival . Consumer attributions
Introduction
Win-back, or customer reacquisition, is the process of revital-
izing relationships with customers with whom the company
has failed to maintain an active relationship (Thomas et al.
2004). As reacquisition becomes a more prominent part of a
firms customer marketing strategy, it is important to under-
stand the mechanisms that drive customer return and assess
the process with relevant metrics. Consequently, metrics that
are analogous to the popular measures applied to customer
acquisition or retention have been extended to the win-back
context. For example, Bsecond lifetime value^ (SLTV), de-
fined as the expected LTV of a customer who has returned to
a former relationship, has been discussed as a valuable metric
for targeting and assessing the quality of a recaptured custom-
er (Griffin and Lowenstein 2001; Stauss and Friege 1999;
Thomas et al. 2004). Using SLTV as an objective, Thomas
et al. (2004) present a two-stage econometric model to devel-
op a pricing strategy for recapturing lost customers. In addi-
tion to SLTV, there is a long history in direct marketing for
firms to use recency, frequency, and monetary value (RFM)
models when determining who to target for reacquisition or
repurchase (e.g., Elsner et al. 2004; Hughes 1996) or to
* Manfred Krafft
Doren Pick
Jacquelyn S. [email protected]
Sebastian Tillmanns
1 Freie Universitt Berlin, Boltzmannstr. 20, 14195 Berlin, Germany
2 Cox School of Business, Southern Methodist University,
P.O. Box 750333, Dallas, TX, USA
3 Institute of Marketing, University of Mnster, Am Stadtgraben
13-15, 48143 Mnster, Germany
J. of the Acad. Mark. Sci. (2016) 44:218240
DOI 10.1007/s11747-015-0453-6
http://crossmark.crossref.org/dialog/?doi=10.1007/s11747-015-0453-6&domain=pdfhttp://orcid.org/0000-0002-9394-95197/26/2019 Customer Win Back Role of Attributions and Perceptions in Customers 2
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determine the allocation of marketing expenditure on cus-
tomers (Reinartz and Kumar2000).
A common strength of all of these metrics is that they are
objective assessments of customerspast behaviors, or objec-
tive predictions of future behavior and economic value, based
on past interactions with a firm. Additionally, a notable limi-
tation of these measures is that they do not reflect or measure
the customers cognitivestate or disposition at defection, northe development of a return decision. This distinction high-
lights an opportunity to consider the behavioral and cognitive
aspects of customers as they progress from defection to an
actual return decision.
A review of the customer win-back literature shows that
research has focused on the defection intention or decision
(e.g., Capraro et al.2003), has taken the firms point of view,
has focused on the conceptual aspects of winning customers
back (e.g., Reichheld and Sasser Jr.1990; Stauss and Friege
1999), has considered customers return intentions (Tokman
et al. 2007) and the classification of revocable relationships
(Roos1999), has investigated customersperceptions of spe-cific win-back offers or activities (Homburg et al. 2007;
Tokman et al.2007), and has paid attention to behaviors after
win-back (Thomas et al. 2004). In general, these streams of
research reveal that researchers usually choose to address a
specific phase of the customer defection to win-back process.
Unifying these disparate examinations of customer win-back,
we posit that customer win-back can be conceptualized into
stages that represent the interplay between external customer
actions, internal customer processing, and firm actions toward
the customer. This approach is particularly relevant for con-
tractual relationships where customer defection can be deter-
mined by firms. To frame this research, we present the follow-
ing stages of win-back:
Stage 1: customer defection decision and relationship
termination
Stage 2: customer rationalization of the defection decision
Stage 3: win-back offer extended
Stage 4: customer processing of win-back offer
Stage 5: customer return decision
Stage 6: second lifetime relationship
We seek to expand research that relates to customers ra-
tionalization resulting from internal processing of the defec-
tion decision (stage 2). In this research on contractual relation-
ships, the defection involves an action and some involvement
on the part of the consumer. Thus when rationalizing the de-
cision, customers might evaluate the effort involved with the
relationship termination and also consider their willingness to
return independent of a win-back offer by the firm. This con-
templation reflects their affinity to return after a defection.
This reasoning is in line with the theory of cognitive disso-
nance that argues that individuals generally assess former
decisions and their implementation and might revise a prior
decision. Accordingly, in this study we focus on the willing-
ness to return withouta given win-back offer by the prior firm.
In order to support our assertions and findings we also exam-
ine actual outcomes (i.e., stages 5 and 6). To our knowledge,
the re-examination and rationalizing that occurs in stage 2
represents an opportunity in the literature that warrants addi-
tional research. Through this research, we will demonstratehow insights at this stage 2 can form future firm actions and
potentially enhance the probability of successful win-back.
Rationalizing defection and relationship revival
Consumer perceptions reflect the consumers understanding
or interpretation of a situation or information. Thus percep-
tions inform how the consumer rationalizes the defection de-
cision before any (potential) win-back offer is provided. While
focused on a different stage of the process, Tokman et al.
(2007) study the drivers of consumers perceptions of thevalue of an actual win-back offer. Specifically, these authors
leverage the theory of social capital to explain how consumers
think about reacquisition actions. This theory describes an
individuals sense of obligation to an organization, which is
based on past experiences with the organization, and special
treatment received from them (Coleman1990). Tokman et al.
(2007) maintain that this social capital influences consumers
when they evaluate a win-back offers value. They find that
while the characteristics of an offer affect consumers per-
ceived value of a win-back offer, the perceived importance
of the service and the social capital in the customerfirm rela-
tionship moderate consumers value perception. Thus, these
authorsresearch demonstrates that value perceptions are crit-
ical in the reacquisition process.
Similar to Tokman et al. (2007), Homburg et al. (2007)
investigate relationship revival activities. Their research is dis-
tinct in that it references equity theory to explain consumers
perceptions of revival activities and links this to actual revival
performance. According to equity theory, individuals evaluate
outcomes and inputs of both the relationship partners and seek
a balanced relationship (Adams 1963, 1965). These authors
empirically demonstrate that a perception of equity or fairness
affects customer satisfaction, which is ultimately linked to
customer win-back. Their analysis also shows that customer
characteristics (e.g., age and variety seeking) and relationship
characteristics (e.g., the duration of the relationship prior to
termination) also predict the actual relationship revival.
Thus, using different theories, Tokman et al. (2007) and
Homburg et al. (2007) investigate how consumers interpret
actual win-back actions, finding that consumers consider the
value and equity of a win-back offer. Interestingly, the notion
of value perception has been conceptualized as a multi-
dimensional construct in other literature (Sheth et al. 1991a,
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b). Sweeney and Soutar (2001), for example, believe that sev-
eral dimensions of value may be simultaneously considered.
While their context is not specific to customer return or win-
back, these authors focus on how consumers assess an actual
product on the basis of the following value dimensions: qual-
ity, emotional value, price, and social value. They find that
each dimension affects a persons willingness to buy. Howev-
er, the emotional value dimension has a particularly strongeffect on willingness to buy. Their findings are consistent with
Gassenheimer et al.s(1998) argument that asserts that eco-
nomic and social values are both critical for successful ex-
change relationships.
Jointly, all of these research streams suggest that the study
of how consumers rationalize the possibility of rejuvenating
pas t rela tions hips cou ld be enhance d by inves tigat ing
economic-oriented value perceptions in the same framework
as social- or emotional-oriented value perceptions. Attribution
theory, which focuses on how individuals evaluate or assess
circumstances, has also been suggested as a possible theoret-
ical framework that might explain defected customers pro-pensity to reactivate former relationships, (e.g., by how cus-
tomers attribute their defection reasons to the firm or them-
selves, i.e., locus) (Homburg et al.2007).
In this research, we make use of these suggestions by
integrating different theoretical perspectives. Specifically,
we integrate attribution theory and prior theories on custom-
er win-back into a systematic study, using both survey and
transactional data from defected subscribers of a publishing
house, and test the appropriateness of our theoretical frame-
work. Theory combination is therefore an important aspect
of our research. However, since we primarily focus on the
neglected effects of attribution theory on customerswilling-
ness to return, phenomena identified in other theoretical con-
cepts such as equity theory will be addressed only to a
limited degree.
This research differs from prior work on switchback inten-
tions in that we do not examine intentions in light of a specific
win-back offer (i.e., stage 4). Instead, we focus on consumers
willingness to returnprior to a potential win-back attempt or
specific offer (i.e., stage 2). We refer to this attitude as a
defected clients general willingness to return (GWR) to a
former supplier, which is independent of expectations of a
specific offer from such a firm. Specifically, we define GWR
as the unconditionalwillingness of a customer to return to a
former supplier.
While there clearly is an overlap between GWR and mea-
sures of intentions, we posit that GWR is distinct from tradi-
tional constructs of customer intention, namely repurchase
intentions, revisit intentions, and loyalty. First, an important
distinction of the GWR measure is that it pertains to the
revision of a previously established decision, which may or
may not be the case with a measure of intention to repurchase.
This is a significant distinction because changing a prior
decision, which was contractually binding in our case, is more
involving than stating a desire or intention to continue a prior
behavior such as repurchase. Thus, one can conceptualize in-
tentions as a broad concept and GWR as a specific concept
that is highly relevant for contexts in which a customer must
actively revise a prior decision or behavior.
Additionally, unlike GWR, measures of repurchase and
revisit intentions often capture only the current relationshipsand thus are void of the defected customers perspective.
GWR is also distinct from loyalty measures because loyalty
often relates not only to purchase-related behaviors but also to
WOM (e.g., Zeithaml et al.1996) and entails multiple cogni-
tive sentiments and behavioral actions that may or may not be
in response to firm actions. Thus, GWR is a measure of a
specific disposition that is relevant for customers who have
explicitly terminated their relationship.
Understanding the rationalization of defected customers
and investigating their disposition or GWR to a former rela-
tionship has several benefits. Specifically, if firms know the
drivers of GWR, they might be better able to influence thosedrivers and increase the odds of customer return. For example,
some customers might return without any win-back offer but
are more interested in an apology and thus this knowledge can
help to reduce investments in win-back activities. Related to
this, by understanding defectorsrationales and their motivat-
ing factors, firms can more effectively design win-back activ-
ities. We further elaborate on this in our section on managerial
implications. Understanding how customers differ in their
willingness to return could allow firms to prioritize customers
for reacquisition activities. Thus, this paper advances market-
ing theory and practice in three key areas:
(1) We propose the new construct, GWR, and show that it is
strongly and positively related to both aspects of revival
performance of firms, i.e., return decision and second
relationship duration. This construct can be used to mea-
sure a defected customers generalpropensity to return
and thus assist firms in targeting customers for reacqui-
sition and developing win-back offers.
(2) We provide evidence for several antecedents of GWR to
a prior contractual relationship and show how the dura-
tion of time absence moderates the relationship between
GWR and second relationship duration. This is very rel-
evant for managers in optimizing marketing win-back
measures.
(3) By integrating theoretical explanations, we demonstrate
the importance of defected customers perceptions and
attributions on their GWR that drives their return behav-
ior. Applying the results from our model we provide
distinct implications for customer groups that differ in
their status (prior satisfaction and duration of time ab-
sence). For managers, these insights can help to refine
and target win-back marketing communications.
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Drivers of general willingness to return
Economic value perceptions
Two main economic arguments have been suggested in the
context of customer win-back. The first relates to customers
perceptions of switching costs when changing providers (or, in
terms of this research, reactivation costs) (Ping 1993; Sharmaand Patterson2000). The perception ofreactivation costsmight
emerge in a variety of monetary or non-monetary ways. For
example, returning to a former relationship might necessitate
the termination of a current relationship, spending time, money,
and cognitive effort. Furthermore, defectors might rationalize
that reactivating a former relationship is risky due to the fear
of incurring additional costs if the relationship once again fails.
Accordingly, we suggest that if defected customers perceive the
costs of reactivating a relationship as high, it is unlikely that they
would be willing to return to their former supplier. Thus, we
assume that the costs of reactivating a former relationship de-
crease customersgeneral willingness to return.Theattractiveness of alternatives has also been conceived
as an economic consideration in the context of how consumers
assess the equity of alternatives. Specifically, the attractive-
ness of alternatives refers to customersperception of the de-
gree to which the products or services that competitors offer
are more interesting, beneficial, and valuable. Several studies
indicate that the attractiveness of alternatives drives cus-
tomers decisions to maintain or leave a relationship (e.g.,
Sharma and Patterson 2000; Bansal et al. 2005; Pick and
Eisend 2014). Accordingly, a lack of attractive alternatives
could stimulate defected customers willingness to return to
their former supplier. Hence, we suggest that the attractiveness
of the alternatives that competitors offer decreases customers
general willingness to return.
Emotional and social value perceptions
Prior literature has also suggested that commitment, switching
experiences, and variety seeking are central drivers of cus-
tomers intention and behavior (Garbarino and Johnson
1999; Homburg et al. 2007; Sheth and Parvatiyar 1995;
Snchez-Garca et al.2012). We assert that affective commit-
ment, switching experiences, and variety seeking are reflec-
tions of consumers assessments and perceptions of an emo-
tional or a social value that they derive from relationships.
Although we focus on the emotional and social components
of variety seeking and switching experience, we have to em-
phasize that they also entail some economic facets, such as
risk and benefit considerations.
In the context of our study, affective commitmentcan be
defined as defected customersemotional attachment to a sup-
plier. It has been empirically shown that commitment is one of
the main drivers of intention to repurchase (Johnson et al.
2006), of retention (Verhoef 2003), or of the propensity to
leave a firm (Morgan and Hunt1994). If a former relationship
with a supplier was emotionally important for customers, this
commitment may exacerbate or ignite post-relationship disso-
nance, since these customers behavior (i.e., defection) and
attitude (i.e., commitment) do not fit (Thomas et al. 2004).
Applying this line of thought to our study, we argue that cus-
tomers who perceive themselves as strongly and affectivelycommitted to a former supplier would be more willing to
return in order to eliminate or reduce the cognitive dissonance
resulting from their defection.
Lam et al. (2010) propose that customersswitching deci-
sions might be based on sociopsychological rather than func-
tional utility. Accordingly, an important facet of social value
perceptions is the extent to which consumers have accumulat-
edswitching experiences over time. Switching experiences are
intensive if customers have often changed suppliers. Addition-
ally, by accumulating these experiences, customers are be-
lieved to have obtained greater knowledge and expertise of
the quality of suppliers in the marketplace (Burt1997). Ingeneral, the more experienced consumers are with switching,
the lower they might perceive the risks related to dealing with
a product, service, or person. Thus, consumers with more
switching experiences may feel more confident about their
behavior when terminating their current relationships and
returning to their former suppliers. Accordingly, consumers
are more likely to return to their former relationship if they
have switching experience.
Finally, emotional value perceptions are also reflected in
customers tendency toward variety seeking. Prior research
argues that satiety with a product can lead to variety seeking
behavior on subsequent purchases (Inman2001). Interesting-
ly, variety seeking is considered a major driver of customers
tendency to abandon relationships, even if those relationships
are satisfactory (Bansal et al.2005). In general, variety seek-
ing affects customer loyalty negatively. However, this gener-
ally negative effect of variety seeking (Homburg et al.2007)
changes in the context of defected customers. For defected
customers, their former supplier can become attractive again
if it can demonstrate new orBnovel^differentiated products or
services. Accordingly, Snchez-Garca et al. (2012) find that
variety seeking customers develop higherrevisitintentions in
the long run (in a non-contractual setting). Since customers
who are prone to variety seeking search actively for new of-
fers, a former supplier can again become relevant and thus
customers are more willing to return.
Attribution theory
How consumers make attributions can affect their perceptions,
rationalization of the defection decision, and propensity to
reactivate former relationships (Homburg et al. 2007). Attri-
bution the ory des cribe s peo ple as rationa l inf orm ation
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processors whose causal inferences influence their attitude
and behavior (Bettman1979; Weiner2000). To date, attribu-
tion research has been applied to help understand the drivers
of customersattitudes and behaviors in theircurrentrelation-
ships (e.g., customer satisfaction and word-of-mouth) (Tsiros
et al.2004) but, to the best of our knowledge, not to contrac-
tual relationships with a prior firm.
Attribution theory suggests that judgments are based onthree major dimensions of causal attributions: locus, stability,
and controllability (Weiner1985).
Locus The locus of causality is the consumers perception of
where the responsibility for an incident lies. From a customer
perspective, this involves answering the following questions: Is
defection due to a factoroutside the customer, such as compe-
tition or the former supplier (external locus), ordue to the
customer(internal locus)? There is evidence that attribution to
an external locus leads to lower loyalty intentions toward the
former supplier (Wagner et al. 2009). Therefore, customers who
perceive and rationalize the defection as company-related, suchas a service failure, should have a lower willingness to return.
However, research also indicates that people tend to be
biased by attributing their own failings to external factors
(e.g., Folkes1988). Once a relationship has been terminated,
the expectation is that defected customers will generally avoid
attributing the relationships termination reasons to them-
selves. This might also hold true in cases where the firm has
no locus on the defection reasons. In addition, as customers
perceive that they have power or influence, it can be argued
that customers expect a company to deal with their defection
reasons in its customer orientation strategy, or customer reten-
tion strategy. And, if a business relationship takes a negative
development, customers are more likely to externalize the
reasons to their provider than to themselves, also known as
the self-serving bias (Heider1958). Additionally, arguments
from cognitive dissonance theory further emphasize that cus-
tomers will attribute the reasons for their defection to external
objects rather than to themselves (Festinger1962). Therefore,
companies may be seen as mostly responsible for customer
defection. For example, the firm should have lowered product
prices if the customers did not have the financial resources to
maintain their subscription. Thus, when defection occurs, the
resulting rationalization can lead to a negative attitude toward
the firm due to the necessity to terminate the relationship.
Consequently, we offer the following hypothesis:
H1: The more customers perceive the causes of defection as
the former suppliers fault (external locus), the lower
their willingness to return to this prior relationship.
Stability Stability refers to the perception that the circum-
stances of a relationship termination will either be fairly
permanent (stable), or relatively temporary (unstable). Stable
outcomes are presumed to reoccur in the future, while un-
stable conditions create uncertainty about future outcomes. If
customers perceive the major reasons for their defection as
rather permanent and unchangeable, i.e., stable over time,
their willingness to revive a former relationship with a sup-
plier will be low (Folkes et al.1987; Homburg et al. 2007).
This reasoning can be expanded: if customers defection isattributed to an own locus (e.g., a low budget for buying a
product or service) or external locus (e.g., the prices of the
supplier are perceived as too high) and these reasons are
perceived to be stable, customers willingness to return will
be low. Therefore, in both situations, the willingness to re-
turn is expected to be low. The underlying reason for this is
that customers find no changes in the companys offerings
and there is consequently no improvement in the relation-
ship value. Their return would represent losing emotional,
cognitive, and social value in their relationship with the
former supplier. While the proposed directional relationship
between stability and GWR is reasonable, establishing thelink between stability and GWR is important because its
significance reveals whether defectors are predisposed to
reevaluating their defection decision early on in the return
process and not simply after an offer is made. A lack of
significance would suggest that defectors are less open to
reexamining the conditions that lead to their defection and
may only be open to reexamination after a win-back offer is
made. Under these circumstances, the offer and its perceived
value becomes the focal point and increases the importance
of the actual offer in the win-back process. Therefore, we
hypothesize about stability to formally establish the link to
GWR and propose the following:
H2: The more customers perceive the circumstances of de-
fection as stable (stability), the lower their general will-
ingness to return to this prior relationship.
Controllability Controllability is a third dimension that
needs to be analyzed with regard to customer attributions.
The causes of defection can involve choice (controlled), or
are constrained and/or non-volitional (uncontrolled). From a
customers point of view, the perception of whether a supplier
could control a cause, or prevent its consequences, is pivotal
for their attitude and behavior (Wagner et al. 2009). For ex-
ample, it can be argued that customers will be relatively more
willing to reactivate a former relationship if the causes of their
defection are under the suppliers control (Folkes et al.1987).
With such a controllability perception, a defected customer
might expect that the firm is able to prevent and change as-
pects that refer to the defection reason (e.g., price). If these
aspects are changed, the customer will be more willing to
return. Hence, we hypothesize:
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H3: The more customers perceive the causes of defection as
being under the control of the former supplier (control-
lability), the higher their general willingness to reacti-
vate this prior relationship.
In summary, the synthesis of the antecedents to general
willingness to return that are derived from attribution theory
dimensions, as well as from economic, emotional, and socialvalue perceptions, serves as the perceptual model in this re-
search. Supplementing our perceptual model, we also develop
a transactional model of actual return behavior. The purpose of
the transactional model in this research is to demonstrate the
link between GWR and actual return behavior of defected
customers. By establishing this linkage we can support the
use of GWR as a crucial measure in the win-back process.
Figure 1 depicts the perceptual and transactional models.
The next section hypothesizes about the factors that impact
actual return behavior. This set of hypotheses will be tested in
our transactional model.
Drivers of customer return behavior
General willingness to return
Because people seek consistency in their attitudes, intentions,
and behavior (see Fishbein and Ajzen 1975), we expect that
GWR will be linked to actual return behavior. By investigating
the relationship of GWR with two types of customer behavior,
we respond to the concern that attitudes or intentions may not
always be related to the behavior of customers. More specifi-
cally, in our study we investigate whether general willingness
to return is related to both, the actual return to the former
relationship and the duration of the reactivated relationship.
We therefore hypothesize:
H4: General willingness to return has a positive effect on (a)
the actual return to the former relationship and (b) the
duration of the second relationship.
In our transactional model, we relate measures from our
survey to actual customer behavior before and after the survey.
Time absenceafterthe survey is the measure of the amount of
time elapsed from when a defected customer was surveyed
and his/her return to the firm. A long time absence after the
survey suggests that the customer might be doubtful or facing
impediments to returning. Additionally, these customers mayevaluate benefits and costs of a potentially renewed relation-
ship more thoroughly. However, if a customer returns after
such a long consideration time, it suggests that the impedi-
ments or possible cognitive dissonance may have been satis-
factorily resolved after sufficient efforts were exerted. Given
the efforts required to get to the favorable return decision, one
might expect that the customers may be more convicted in
Emotional and social valueperceptions
Affective CommitmentSwitching experiencesVariety seeking
Perception of behavior: Attribution
Theory
LocusStabilityControllability
Economic value perceptions
Reactivation costsAttractiveness of alternatives
Explaining general willingness to return
(Perceptual model)
Explaining customer return behavior
(Transactional model)
Relationship characteristics
Number of trial subscriptions
Number of regular subscriptions
Relationship duration beforedefection
Differentiation variables
SatisfactionTime absence before the survey
Time absenceafter the survey
Generalwillingness to
return
Customerwin-back
Secondrelationship
duration
Fig. 1 Research framework containing the perceptual and transactional model
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their return decision and as a result the second relationship
duration would be longer than if the return process was shorter
and the return process was easier. We therefore state:
H5: Time absenceafterthe survey has a positive effect on
the duration of the second relationship.
The effect of GWR on customers actual return behaviormight be attenuated by the temporal distance between cus-
tomers expression of their GWR and their actual return
behavior. In a similar vein, Mittal and Kamakura (2001) claim
that there is likely an attenuation of the relationship between a
satisfaction rating and the repurchase behavior of a customer
as the time lag increases.
Following from the argument that the length of time ab-
sence after the survey is an indicator of the efforts necessary to
return to the former relationship, then one might expect that
the length of the time absence might moderate the association
of GWR with second relationship duration. We have argued in
H4b that GWR is positively related to second relationshipduration. However, when defectors have a high GWR, a lon-
ger time absence after the survey reflects a contrast to the
defectors return propensity and therefore could indicate a
deep reconsideration process. Though this finally leads to
returning to the supplier, doubts can remain, leading to aver-
age durations of second lifetime.
This same argument can apply to the case when defectors
have a low GWR and a long time absence. Specifically, the
decision of low GWR defectors to recommit after a long time
absence may reflect thoughtful reconsideration and result in
stronger convictions about this reversal of the decision and a
longer second lifetime. Therefore we hypothesize:
H6: Time absenceafter the survey and before relationship
revival moderates the impact of general willingness to
return (GWR) on second relationship duration such that
the effect of GWR is attenuated when the duration of
absence after the survey is long.
Transactional model control variables
Our first control variable in the transactional model is custom-
er satisfaction prior to defection. Homburg et al. (2007) and
Tokman et al. (2007) find empirical support for defected cus-
tomers who were satisfied with a prior relationship being more
likely to revive this relationship. Moreover, Tokman et al.
(2007) find that satisfaction interacts with some antecedents
of switch-back intentions (e.g., price attitude) and not with
others (e.g., service benefits). Thus, customer satisfaction
can be considered one of the most important factors in a cus-
tomer retention strategy. Nevertheless, even the most satisfied
customers might defect for reasons beyond the firms control,
or even that of the customers themselves (Ganesh et al.2000).
For example, the customers financial situation might have
changed, or there is simply no longer a need for a firms
products and services. Furthermore, customers might defect
because a competitors specific offer might generate greater
benefits. In specific contexts such as internet or cable TV
providers, clients may defect because services by the current
provider are not available in their new location. Accordingly,some studies question the link between customer satisfaction
and customer retention (Jones and Sasser Jr.1995), or cannot
verify this empirically (Verhoef2003).
Ganesh et al. (2000) propose that customers who switched
from their former supplier for reasons other than dissatisfac-
tion are less likely to have negative attitudes and feelings
toward this supplier. Accordingly, we expect that customers
who were satisfied with their former relationship are more
likely to return and stay for a longer period of time.
The second control variable is the recency of the last
purchase. This is considered one of the most important mea-
sures in customer relationship value estimation (Reinartz andKumar2000; Neslin et al.2013). Neslin et al. (2013) find that
recency (i.e., time since last purchase) is negatively related to
purchase probability. Thomas et al. (2004) find empirical sup-
port that the probability of recapturing a defected customer
lessens with the time being absent. However, Tokman et al.
(2007) find that time absence has no significant direct effect
on switch-back intentions. Nevertheless, in the context of
defected contractual relationships, a former suppliers chance
of retrieving customers is higher as long as the customer does
not enter into an alternative contract.
The third control variable isrelationship duration prior to
defection. Some studies find that relationship duration is pos-
itively related to the social and financial bonds between the
customer and the firm (e.g., Chiu et al. 2005; Reinartz and
Kumar 2003), and could increase positive behavioral inten-
tions (van Birgelen et al.2006). In spite of the termination of a
relationship, customers with a long relationship duration
might specifically feel they have a bond with their former
supplier. Processes and interactions learned in a previous re-
lationship with a firm might support customers return deci-
sions. Furthermore, lapsed customers with long prior relation-
ship durations might be relationship prone and thus have lon-
ger second relationship durations.
Given that our research context is for subscriptions (i.e.,
contractual relationships), we attempt to account for the con-
sumers prior use of trial and regular subscriptions. Trial sub-
scriptions are a common means of customer acquisition in the
publishing industry (Picard and Brody1997). These subscrip-
tions might be highly attractive due to reduced prices or re-
duced contract durations. Accordingly, customers might feel
more flexible and therefore return more easily in the near future.
In line with the social exchange theory, customers who often
make use of trial subscriptions might have a higher likelihood
224 J. of the Acad. Mark. Sci. (2016) 44:218240
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of returning to a relationship because they might feel an obli-
gation to give the firm something back (Bagozzi 1995). Ac-
cordingly, these customers might subscribe for a longer period
of time and thus have longer second lifetime durations.
One can also argue that customers with a long history of
defecting from and returning to regular subscriptions might
get used to the processes of canceling and renewing their sub-
scriptions. Accordingly, these customers should have much ex-perience with switching suppliers. In accordance with our as-
sumptions about switching experience in our perceptual model,
we expect that customers who are highly experienced with
switching or renewing their contracts have a higher probability
of returning to their former relationship after they have
defected. Given these contextual considerations, we introduce
number of prior trial subscriptions and number of prior regular
subscriptionsas control variables in our transactional model.
Methodology
Data collection
To test our research hypotheses, we surveyed subscription
customers of a publishing house that sells a variety of ro-
mance novels in Germany. A survey of 600 regular romance
readers found that they mirror the general population in terms
of age, education, and marital and socioeconomic status
(Thurston 1983).
Specifically, we surveyed customers who had canceled
their subscriptions and had been inactive for at least
12 months. The firms database contained about 25,000
defected customers, from which we drew a random sample
of 6411 individuals. We sent each individual a questionnaire
and incentivized their participation by offering them an oppor-
tunity to win one of 20 vouchers worth EUR 20 for a purchase
from a major retailer. Two weeks after our initial mailing,
reminder postcards were sent to the non-responding defectors.
Those who responded after our reminder postcard were
marked as late respondents. A comparison between the early
and late respondents regarding all the key variables indicated
that they were similar (p>.10). Accordingly, non-response
bias does not seem to be an issue in the study.
A total of 748 questionnaires were returned, yielding a
response rate of 12%. After eliminating 205 surveys due to
incomplete answers and removing three participants as out-
liers in the subsequent cluster analysis, we achieved a final
sample of 540 respondents. We are aware of higher re-
sponse rates in other study contexts and attribute this to
the home mailing procedure and the specific context of
defected customers in our study.
Of these respondents, 99.6% were female and 56% were
married. Our participantsmean age was 40 years (range: 17
to 82 years), and the median annual household income was
EUR 12,000 to EUR 18,000. Because our sample is not rep-
resentative of the German population in gender and income,
our findings may not be generalized to the overall population.
However, this is not unusual as magazine subscriptions are
typically targeted to specific customer groups.
In addition to our survey data, we obtained transactional
data about the surveyed customers from the cooperating
publishing house. Hence, we were able to derive whetherour respondents actually returned and when they did, the
duration of their second relationship. Information on two
surveyed customers in the cooperation partners database
was missing. Hence our transactional model accounts for
538 out of 540 customers we examined in the perceptual
model. We also obtained transactional data from 789 cus-
tomers who did not receive the survey but did defect in the
same manner as the customers who did participate in our
survey in order to account for a potential measurement bias.
Despite our attempt to rigorously collect both survey data
and post-defection transactional data from defected cus-
tomers, the product category of this research presented anatural limitation. This limitation is a result of the fact that
some customers could purchase the novels at retail locations
without a subscription. While executives of the publishing
house judged that the impact of the retail sales on the sub-
scription sales were minimal, we acknowledge this as a
potential limitation of our data.
Statistical analysis overview
To test our hypotheses, we took several steps in our statistical
analyses. First, in order to deeply understand the value of inte-
grating attribution theory with existing theories on customer
return and win-back, we sought to identify differences in
defected customers that may blur interesting insights. Thus we
decided to perform a cluster analysis to account for heterogene-
ity among defectors. Second, we tested the proposed anteced-
ents of the general willingness to return with regression analysis
(perceptual model). Finally, we set up regression models to
derive how the general willingness to return related to the actual
return of defected customers and, if they did return, how long
they maintained the relationship (transactional model).
Perceptual model
Measures and validation
With the exception of a measure for GWR, we made use of
established measures, which we either applied directly or
adapted for our survey. Details about the exact items, their load-
ing, the construct composite reliability, and the source of the
scale are described in the Appendix. All the scales were assessed
using a seven-point Likert scale. Their respective means, stan-
dard deviations, and correlations are provided in Table1.
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Table1
Descriptivestatisticsandcorrelations
Variables
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Constructs
1.Generalwillingnesstoreturn
2.Priorsatisfaction
0.25*
3.AffectiveCommitment
0.39*
0.42*
4.Varietyseeking
0.07
0.03
0.08
5.Switchingexperiences
0.15*
0.04
0.04
0.39*
6.Locus
0.05
0.51*
0.11*
0.13*
0.12*
7.Stability
0.45*
0.17*
0.22*
0.17*
0.16*
0.13*
8.Controllability
0.11*
0.18*
0.04
0.08
0.13*
0.37*
0.05
9.Reactivationcosts
0.27*
0.37*
0.09*
0.12*
0.13*
0.39*
0.19*
0.20*
10.Attractivenessofalternatives
0.05
0.22*
0.10*
0.26*
0.38*
0.25*
0.00
0.05
0.23*
Transactionalmeasures
11.Timeabsencebeforethesurvey0.12*
0.06
0.03
0.14*
0.17
0.05
0.06
0.03
0.08
0.07
12.Timeabsenceafterthesurvey
0.03
0.02
0.09
0.08
0.06
0.06
0.03
0.50
0.03
0.01
0.02
13.Trialsubscriptions
0.08
0.02
0.07
0.04
0.19*
0.01
0.10*
0.04
0.00
0.06
0.04
0.06
14.Regularsubscriptions
0.03
0.00
0.03
0.13*
0.21*
0.03
0.09*
0.09*
0.03
0.04
0.15
0.02
0.46*
15.Priorrelationshipduration
0.02
0.04
0.05
0.14*
0.19*
0.07
0.11*
0.06
0.07
0.12*
0.14*
0.01
0.34*
0.65*
16.Secondrelationshipduration
0.13*
0.03
0.13*
0.01
0.00
0.08
0.05
0.02
0.07
0.05
0.04
0.10
0.10
0.10
0.07
Mean
3.62
6.16
4.29
3.91
3.91
1.66
3.91
3.23
2.22
2.58
970.30
256.78
0.85
0.66
738.54
631.02
StandardDeviation
1.66
0.91
1.70
1.54
1.53
1.21
1.53
1.81
1.17
1.22
277.86
312.86
0.91
0.75
1,151.11
972.44
*p.05). We find that the number of trial
subscriptions in which customers were enrolled before their
defection showed a strong positive effect (=0.84, p .05). The number
of regular subscriptions neither showed an effect on the return
decision (=0.33, p>.05), nor on the relationship duration
after returning (=54.49,p >.05).
Discussion
This research investigates the perceptions and rationalizations
of defected customers in order to understand the factors that
influence their revival of former relationships. An important
characteristic of the current research is that we investigate the
customer evaluations priorto any of the firms win-back ac-
tions. We refer to the disposition of the consumer at this stage
as the consumers GWR, or general willingness to return to
their former supplier. The investigation of such a variable is of
interest because it can reveal customers overall affinity and
relationship evaluations indicating their propensity to revise a
previous decision and return to a firm from which they have
defected. Importantly, identifying GWR and understanding its
impact shows thatactual return behavior is NOT simply areflection of the firms offers that are extended to revive the
relationship. Rather, GWR is a major driver of relationship
revival and potentially instrumental in designing and targeting
revival offers to defected customers. Thus, our finding that
GWR impacts actual return behavior is not only a critical
support for the usage of our GWR measure and our research
findings, but it also is a notable contribution to the existing
knowledge in customer win-back research as will be ex-
plained in the following.
Theoretical implications
Combining theories improves our understanding of cus-
tomer willingness to return Given that customer win-back is
arguably one of the least researched areas of CRM, integrating
theories and then testing the applicability of hypotheses de-
rived from those theories contributes to a better understanding
of this important field of research. In detail, we draw upon a
theory that has not been applied in a customer win-back con-
text (i.e., attribution theory) and compare our model to abase-
line model that reflects individual theories that are focused on
Table 5 Logistic regression and censored normal regression explaining revival performance
Return Second relationship duration
b SE b SE
Intercept 0.33 0.55 238.54 267.60
General willingness to return (GWR) 0.17* 0.10 266.84*** 70.45
Prior satisfaction 0.14 0.10
34.93 68.67Time absence before the survey 0.00 0.00 0.07 0.23
Time absence after the survey 0.50 0.31
GWR x Time absence after the survey 0.50* 0.24
Relationship duration before defection 0.00 0.00 0.02 0.06
Number of trial subscriptions 0.84*** 0.17 23.60 75.85
Number of regular subscriptions 0.33 0.19 54.49 108.64
Brand subscribed to before defection (categorical)
Several Brands 1.58* 0.78 32.95 280.93
Brand 1 0.44 0.38 255.86 159.65
Brand 2 0.19 0.43 59.52 176.04
Brand 3 0.57 0.43 113.51 179.89
Brand 4
0.84 0.47 845.71* 359.78
Brand 5 1.83* 0.72 113.28 208.61
Brand 6 1.48** 0.47 723.67* 329.21
N 538 292
*p
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value perceptions and which have been shown to relate to
customersreturn decisions.
When comparing the models without attribution variables
(i.e., the baseline models) with the respective models with
attribution variables, we see a substantial improvement of
the explanatory power and model fit (see Table 3). This sug-
gests that consumerswillingness to reinitiate former relation-
ships is only partially explained by their perceptions of therelationships value (economic or social value) and, thus, em-
phasizes the value of integrating attribution theory proposi-
tions in research as requested by Homburg et al. (2007). By
summarizing the findings we derive from investigating attri-
bution theory in this context, we gather the novel insight that
the defectors rationalization for leaving and consideration to
return can be characterized as follows: Regardless of whose
fault it is, if the reasons for the relationship termination can
change or are preventable and the firm can control those
changes, then the defector has a higher general willingness
to return to the former relationship.
While attribution theory adds to our understanding of thewin-back process, we acknowledge that all of the theoret-
ical explanations help explain customers willingness to
return. However, the following is a logical question: does
one theory consistently explain the top factor(s) that have
an impact on the GWR? Our empirical analysis of custom-
er segments suggests that one dominant theoretical frame-
w o r k d o e s n o t e x p l a i n c u s t o m er s p e rc e p tio n s ,
rationalizations, and subsequent motivations for revitalizing
a relationship. However, if we were to focus on the most
important factor that affects reactivation, we find that
stability, a variable derived from attribution theory, has
the greatest influence (i.e., elasticity) on reactivation if (1)
the consumer has a low level of satisfaction or (2) if the
defection occurred recently (i.e., a short time absence be-
fore survey) (see Fig. 2). Thus, it is important to defected
customers who are considering a return to know that things
can change. For another subset of defectors (i.e., moderate
to high satisfaction and less recent defection), the most
influential factor is affective commitment, which reflects
consumers perception of the emotional value. This factor
is associated with the theory of social capital (Mathwick
et al. 2008). The importance of commitment is consistent
with prior research that finds that perceptions of emotional
value have a great impact (Sweeney and Soutar 2001).
The impact of time absence on gwr and second relation-
ship performance Time absence plays an important role in
relationship revival. For those who have had a recent defec-
tion (i.e., short time absence before the survey), their general
willingness to return is driven mostly by how the consumers
rationalize thepermanence(i.e., stability) of their reasons for
defection. This is not the case for those who have been
absent for a while. The contrast is seen by comparing
clusters 1 and 4 in Fig. 2. Both of these clusters report a
medium satisfaction level prior to defection. Yet, by tearing
apart the duration of their time absence we can see that the
top two drivers of GWR among the more recent defectors
(cluster 4) are first stability and second affective commit-
ment (elasticities are -0.437 for stability and 0.392 for com-
mitment). For the defected customers who have been absent
for a long time (cluster 1), the impact is the exact opposite(elasticities are 0.466 for commitment and -0.376 for stabil-
ity). Thus, over time, a defectors mindset shifts, leading to
different motives driving his/her willingness for relationship
revival. Hence, theory integration helps to better understand
the return propensities for defectors who have been absent
for varying lengths of time.
Another important and novel finding from our analysis is
the moderating effect of time absenceafterthe survey on the
relationship between GWR and the second relationship du-
ration. Such a moderating effect goes beyond direct effects
identified by attribution theory or any value perception the-
ory. Yet, one can conjecture that high GWR defectors mightestablish a longer second relationship if they return and that
the reverse is true for low GWR defectors, particularly if the
return happens shortly after the survey and possibly with
less contemplation. However, the fact that a low GWR de-
fector can behave similar to a high GWR defector if enough
time passes before the second relationship ensues is an in-
teresting new finding. It suggests that firms should carefully
consider the timing and how aggressively they pursue defec-
tors.Allowing time to Bheal a wound or for contemplation
can improve the quality of the second relationship in terms
of its duration.
Explanations of customerswillingness to reactivate a re-
lationship may not align with crm practices From the
firms perspective, CRM research has focused significantly
on customers economic value (see, e.g., Gupta et al.2006).
Monetizing customers and measuring their lifetime value
have been the guideposts of many of the recommendations
that firms have received (e.g., Blattberg et al. 2001). When
firms think about customers second lifetime value, they
generally consider incentives that they could offer the cus-
tomer to reactivate their relationship. From a companys per-
spective these incentives translate into costs while they add
to the perceived economic value of a relationship from the
customers perspective.
However, our research, which is undertaken from a cus-
tomers perspective, offers an interesting contradiction to
the firms thinking: on the whole, consumer perceptions
of economic value are less important for their willingness
to return than perceptions of emotional value (see Table4).
The only case in which this is not true, is in the low
satisfaction cluster. In this group (cluster 3), perceptions
of the economic value are the second most influential
234 J. of the Acad. Mark. Sci. (2016) 44:218240
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factor, but a distant second behind the most influential fac-
tor of stability (elasticities for stability are -0.73, and -0.39
for perceived reactivation costs).
Based on these results, and the economic practices that
firms typically use to win customers back, firms could very
easily focus on the wrong activities, namely those that do
not drive the GWR. For example, a firm may focus on
devising promotions and economic incentives to recapturevaluable lost customers who have switched suppliers, when
the defected customers may actually be more concerned
with the bonds that they had with their former supplier, or
with special treatments that they previously received (Lam
et al. 2010; Tokman et al. 2007). A recent study supports
this rationale by finding that the efficacy of some marketing
activities such as advertising are quite low and even negative
in the long term (Ataman et al. 2010).
General willingness to return is a relevant and measurable
win-back metric Our focal measure, GWR, is new in the
CRM research domain. Prior research in this domainaccounted for demographics (e.g., the duration of the rela-
tionship prior to defection), emotion-based customer charac-
teristics such as customers overall satisfaction prior to their
defection (Homburg et al. 2007), and their intentions to re-
activate a (non-contractual) relationship given a specific
win-back offer (Tokman et al. 2007). To our knowledge,
prior research has not fully investigated the rationalization
and disposition of defected customers prior to any win-back
offer. While the GWR concept has similarities to the concept
of consumers affinity for a firm, product, or brand, we
emphasize that a key distinction between GWR and general
intention is that GWR measures the inclination to revise a
prior decision without any firm offered incentives. Thus
GWR is not a broad measure of repurchase intentions but
instead it is a specific measure of a customers disposition
toward relationship revival.
Managerial implications
Leveraging GWR and its antecedents to position win-back
communications Because the consumers defection reasons
can influence GWR and win-back performance, effective
marketing communications should address the consumers
concerns. The antecedents to GWR and how they vary
across customer groups can help CRM managers to position
their win-back communications. For example, if controlla-
bility is a key explanation for a specific customers GWR, a
firm could approach such a defected customer with a state-
ment that communicates, Bthis incident can be prevented.^
With such a statement, the firm is tapping into the cus-
tomers perception that it can change the situation for the
better. If stability drives the consumers GWR, the firm can
position its marketing communications so that the former
customer knows that Bthings have changed.^ Consumers
who emphasize that commitment to their relationship affects
their willingness to return could be approached with market-
ing communications that acknowledge that Bthe relationship
is important or Bis valued.^ This type of remark would
resonate with consumers who have an emotional connectionto the firm. In contrast, marketing communications directed
at defected customers who focus on factors that drive the
economic value of the relationship would require a differ-
ently positioned message. For example, customers who are
driven by reactivation costs would want a message from the
firm that communicates that Bcoming back can be easy^ or
Bis not expensive.^ To implement this, for example, in con-
tractual relationships, a firm can offer a pre-printed contract,
or a sufficient number of customer touchpoints for contract
renewal. These examples show that knowledge of the
drivers of the GWR can help a firm position its win-back
communications.Interestingly, one way to characterize these themed
talking points is based on whether they are grounded in
a rational appeal (i.e., a persuasive message that focuses
on facts and product/service attributes), or in an emotional
appeal (i.e., a persuasive message that taps into the con-
sumer sentiment and emotional or social value derived
from the exchange). Given the theories that we examine,
this is an appealing characterization, because it is consis-
tent with the emotional and subjective aspects of some of
our GWR drivers (e.g., affective commitment), as well as
with the more objective or fact-based aspect of our drivers
(e.g., reactivation costs).
We present a simplified demonstration that only focuses
on the top drivers of GWR in each cluster to apply the idea
of a rational communication appeal versus an emotional
communication appeal to our specific clusters. First, we note
that clusters 1 and 2 differ with respect to the intensity of
their effects, but are similar with respect to the relative im-
portance of the factors that affect GWR, i.e., affective com-
mitment and stability. Consequently, the main theme behind
marketing communications for these clusters would be the
same. Specifically, the theme should combine a strong emo-
tional appeal that perhaps emphasizes loyalty and commit-
ment. Settings that highlight families, parents and children,
or good friends interacting together are examples that may
be appropriate because they typically evoke a strong sense
of commitment. Within these contexts, a marketing commu-
nication may refer to statements such as: BWe value our
relationship and are committed to doing what it takes to
make it work.^ Through this type of statement, the firm
addresses the clusters emotional bond with the relationship
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and their perception that the circumstances leading to their
defection can change.
In contrast to clusters 1 and 2, a marketing communica-
tion targeted at cluster 3 (Bdisillusioned^ customers) should
possibly comprise a far more rational appeal, because the
top two factors associated with this clusters GWR are (1)
stability and (2) perceived reactivation costs. The firm may
consider citing facts or statistics pertaining to the reasons forthe defection having been minimized or eliminated, and that
revitalizing the relationship will not be risky or costly. Thus,
a message theme that communicates Bthings have changed
and we can make it easy for you^ might motivate them to
consider returning to a relationship. A firm may try using
the familiar phrase Bunder new management for these types
of consumers. Using significant price promotions or finan-
cial incentives to stimulate return are also reasonable mar-
keting tactics that may resonate with this cluster.
Finally, cluster 4 (the Bremorseful customers, medium
satisfaction and short time absence) values the relationship,
but is most concerned with whether the factors that causedtheir defection have been addressed (i.e., stability). There-
fore, a rational appeal may be most persuasive and resonate
with these customers. Elaborating on the specific details of
changes is consistent with the idea of presenting a rational
appeal, and could strengthen the message. Examples of plau-
sible changes that the firm may want to communicate are: a
new web site, a new (re)ordering system, or a new distribu-
tion partner. Hence, a message theme that communicates
Bthings have changed and our relationship with you is
important may motivate these customers to reactivate a
relationship.
In summary, these examples show that by knowing and
understanding the key factors that drive the GWR, firms can
tailor specific messages that have a higher chance of resonat-
ing with defected customers. Notably, these examples can be
easily linked to the theoretical frameworks that were investi-
gated in this research. Further, the examples and frameworks
that we presented align easily with the concept of a rational
versus an emotional message appeal, which is a concept used
to guide firmsmarketing communications.
Clustering defected customers for win-backPractitioners
rely upon various methods and variables for segmenting
current customers. Adding to this practice, this research
demonstrates the value of clustering defected customers
based on combining metrics that capture their relationship
before and after their defection. Specifically, we show that
the time elapsed since the relationships termination and
before the survey along with a customers satisfaction lev-
el prior to the termination can delineate between defected
customers who vary in their general willingness to return
to prior relationships (see Table 2). The time elapsed can
easily be measured in a contract setting, as is the case
with this research. In non-contractual settings statistical
models can be used to predict lifetime durations and from
that estimates of time absence can be derived. Thus, time
absence is a practical clustering measure for defected
customers.
Customer satisfaction has repeatedly been linked to cus-tomer retention (e.g., Mittal and Kamakura2001), and numer-
ous firms frequently measure this at an individual level
(Reichheld 2003). Although many firms may presume that
all defectors are dissatisfied, we show that this is not neces-
sarily the case (see Table 2). Thus, we posit that satisfaction
prior to defection is also an appropriate clustering measure to
consider for defectors. In this research, the measure was taken
after the defection and thus did not require a survey of an
entire customer database.
Combining these two metrics to form clusters reveals an
interesting group of defected customers whom some man-
agers may have difficulty understanding or identifying. Forexample, if the firm were to only use satisfaction as a cluster-
ing variable, they would likely combine clusters 1 (Bmigrant
birds,^ long time absence) and 4 (Bremorseful, short time
absence) because they have the same level of satisfaction. This
would be detrimental from a managerial implementation per-
spective because, as our research shows, these two clusters are
motivated by very different factors.
The time since the last purchase, which is analogous to our
time absence before the survey variable, is a common metric
that database marketers use for targeting (Hughes 1996).If our
time absence variable were used without the satisfaction var-
iable, firms would find it hard to differentiate consumers in
cluster 3 (low satisfaction) and cluster 2 (high satisfaction).
Managerially, this could also cause significant problems when
implementing a win-back campaign because commitment is
the biggest driver of cluster 2s GWR, while commitment is
only the fifth most significant driver of cluster 3s GWR. In
general, the relative importance of the factors that drive GWR
differs greatly from the least satisfied to the most satisfied
clusters. Thus, the customer satisfaction level is an important
profiling factor for firms to consider when developing a win-
back strategy.
Proxy measurement Given the high level nature of many
of the constructs in our study, firms may try to use proxy
variables from their customer database that mirror those
constructs. By using such proxies, managers can avoid
conducting large scale surveys. For example, because they
also had relationships with other suppliers, one might de-
duce that customers with high degrees of variety seeking
behavior and switching experience are characterized by
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short prior relationship durations. This is also reflected in
Table 1, where prior relationship duration is negatively
associated with variety seeking and switching experience.
Thus, prior relationship duration might serve as a good
pr ox y me as ur e fo r va ri et y se ek in g an d sw it ch in g
experience.
Relying solely on transactional measures might be insuf-
ficient when searching for proxy measures for e.g., attribu-tional variables. Nevertheless, with the availability of rich
data, managers might even be able to identify customer
characteristics or individual behavior, such as complaints,
interaction with frontline employees, or social media conver-
sations that strongly correlate with constructs such as prior
satisfaction, locus, stability, or controllability. The impor-
tance of measuring complaints to gain substantial insights
into the quality of the relationship has been highlighted in
several studies (e.g., van Oest and Knox 2011). Neverthe-
less, firms need to be aware that most customers do not
complain (e.g., Voorhees et al. 2006). Hence, customers
should be stimulated to raise their complaints (e.g., by ask-ing customers for their defection reasons during relationship
termination). Additionally, service employees often dispose
of in-depth knowledge of customer attitudes. Thus, their
feedback and evaluation of attributional variables might
serve as another proxy measure.
Firms may also find that they need to consider alterna-
tive variables for deriving clusters. Previous customers can
be segmented based on time absence and satisfaction prior
to defection to target them with specific win-back offers.
Both of these factors have been shown to be relevant for
customer reacquisition (Homburg et al. 2007; Thomas et al.
2004; Tokman et al. 2007). As we show in Fig. 2, in our
study only extremely low or high levels of these two fac-
tors had to be known to identify the four clusters. So even
if, for example, satisfaction is not known, proxies such as
product returns or customer complaints could suffice for the
purpose of segmentation. Our study also emphasizes the
benefits of collecting customer satisfaction scores or prox-
ies to be able to effectively segment defected customers for
win-back purposes.
Conclusion and limitations
Our research explores the perceptions and rationalizations
of defected customers to gain a deeper understanding of
their willingness to return to a contractual relationship
with a firm. While we are confident that our survey-
based research generates novel preliminary insights into
effects of attitudes and intentions on relationship revival,
we are aware of its incremental contribution to our field
and therefore encourage future research to conduct neuro-
scientific studies to validate or qualify our findings on the
outcomes of the internal mental workings of customers.
We further suggest conducting experimental studies to
broaden our knowledge on the impact of concrete win-
back offers (besides pricing issues) on customer return
behavior. Further, experimental studies might also help to
further enlighten the cognitive processes that a defectedcustomer goes through while forming her or his general
willingness to return.
Our theoretical framework and empirical findings can
provide managers with very specific guidance and sug-
gestions on how to segment defected customers and
engage them through specific communication messages.
Hence, additional research on proxy measures will be
helpful to translate the high level constructs studied in
this research into actionable insight. Future studies
might also consider the important revenue, cost, and
profit implications of new customer acquisition and re-
tention vis--vis win-back of former clients. Finally, fu-ture research might also reveal how characteristics of a
prior relationship other than prior satisfaction or affec-
tive commitment might influence customer responses to-
ward the firm.
While we are not aware of any win-back activities by
the firm before the survey, the possibility of this is a
potential limitation of this research. We also note that
the subscription context is another potential limitation to
the generalizability of this research. It would be fruitful
if the theoretical framework presented here were to be
examined in a non-subscription context and contexts
that have a higher risk associated with the purchase
(e.g., prepaid legal service or medical insurance) than
the one studied in this research (i.e., novels, media
content).
Another possible limitation of this research is the
ratio of women to men in the data sample. The study
participants were mostly women. It is possible that atti-
tudes could differ if the sample was more balanced. For
example, Melnyk et al. (2009) find that men are more
loyal to groups (e.g., companies), whereas women tend
to be more loyal to individuals, such as certain service
employees.
Despite the potential limitations and several ways to
extend this study, this research can be viewed as a cat-
alyst to expand our knowledge of customer reactivation.
Specifically, this research contributes to the literature by
expanding our theoretical knowledge about customer re-
vitalization and provides recommendations that are high-
ly relevant to practitioners responsible for managing
customer relationships.
J. of the Acad. Mark. Sci. (2016) 44:218240 237
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Appendix
Table 6 Measurement items (1= I do not agree at allto 7=I fully agree; r=reverse coded)
Constructs and items Loadings Composite reliabilities
Prior Satisfaction (Maxham III2001; Ping1993,1995):
As a whole, I am satisfied with the products and services offered by your publishing house. 0.82 0.93In general, I am pretty satisfied with my relationship with your publishing house. 0.91
Overall, you and your staff treated me fairly. 0.88
How satisfied are you with the quality of our performance? 0.87
Affective Commitment (adapted from Ganesh et al.2000):
The relationship I shared with your publishing house was very important to me. 0.90 0.89
Since the termination of my subscription, I still feel very committed to your publishing house. 0.90
Variety Seeking (Van Trijp et al. 1996):
I enjoy taking chances by trying out unfamiliar companies, products/contracts to provide variety to my life. 0.85 0.93
I like trying things out that I am not familiar with. 0.89
I always try something different. 0.86
I like to try something I am not very sure of. 0.80
I enjoy trying out new products. 0.83
Switching Experiences (Burnham et al.2003):
I occasionally try new subscriptions from competing publishing houses. 0.87 0.90
In the past, I often switched between different subscriptions. 0.83
I occasionally try other subscriptions. 0.89
Locus (Tsiros et al.2004):
Your publishing house is responsible for my decision to terminate the relationship. 0.87 0.92
Your staff is responsible for my decision to terminate the relationship. 0.90
The strategies and orientation of your publishing house are responsible for my decision to terminate the relationship. 0.89
Stability (Russell1982):
My reasons for terminating the relationship are
Permanent/temporary 0.86 0.86
Changeable/Unchanging (r) 0.76
Stable over time / variable over time 0.85Controllability (Hess et al.2003):
My reasons for terminating the relationship are
Controllable by your company. 0.91 0.91
Preventable by your company. 0.91
Reactivation costs (adapted from Ping1993):
I think the costs in time, money and effort to return to the publishing house would be high. 0.59 0.86
Overall, I could lose a lot if I return to your publishing house. 0.62
Returning to your company is too risky/insecure for me. 0.81
It is too complicated to renew my former subscription with you. 0.86
Returning to your publishing house is too cumbersome to me. 0.83
Attractiveness of alternatives (Ping1993):
Products and services available from alternative publishing houses offer exactly what I need. 0.83 0.89
Overall, alternative publishing houses would benefit me more than your publishing house.I am interested in many publishing houses.
0.82
Other publishing houses provide a bigger assortment of subscriptions than your publishing house. 0.83
Other publishing houses keep me better informed about attractive offers. 0.70
General willingness to return:
I am generally willing to return to you (publishing house) and to close a new contract. 0.91 0.92
I am generally willing to revise former decisions. 0.77
In the future I would like to close subscriptions with your publishing house again. 0.89
The renewal of my former relationship, e.g., a new subscription, is very probable/ not very probable. 0.86
238 J. of the Acad. Mark. Sci. (2016) 44:218240
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