The American Journal of Management and Economics Innovations
99
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TYPE
Original Research
PAGE NO.
99-106
10.37547/tajmei/Volume07Issue05-12
OPEN ACCESS
SUBMITED
28 March 2025
ACCEPTED
21 April 2025
PUBLISHED
28 May 2025
VOLUME
Vol.07 Issue 05 2025
CITATION
Trofimov Semen Valerevich. (2025). Customer Retention Methods in
Automated Self-Service Technologies. The American Journal of
Management and Economics Innovations, 7(05), 99
–
106.
https://doi.org/10.37547/tajmei/Volume07Issue05-12
COPYRIGHT
© 2025 Original content from this work may be used under the terms
of the creative commons attributes 4.0 License.
Customer Retention
Methods in Automated
Self-Service Technologies
Trofimov Semen Valerevich
Individual entrepreneur Khabarovsk, Russia
Abstract:
This study aims to systematize existing
theoretical and empirical data on customer retention
methods in SSTs, focusing on a range of factors
(convenience, trust, technological readiness, control,
customer-to-customer interactions, and service
recovery). Automated self-service technologies (SSTs)
are becoming increasingly prevalent across various
industries, yet ensuring long-term customer retention
in these channels remains a significant challenge for
businesses. The research was conducted as a
systematic review of scholarly sources, including peer-
reviewed articles indexed in international scientific
databases. The analysis indicates that isolated
measures (such as interface improvements or faster
transaction speeds) rarely yield sustainable effects
unless supported by mechanisms that foster trust,
ensure security, and provide prompt compensation in
the event of failures. The identified interdependence
between convenience and trust underscores the need
for a comprehensive approach to customer retention:
even when convenience is high, users may abandon
SST if they harbor doubts about the system’s security.
A novel and important contribution of this work is its
detailed examination of the role of customer-to-
customer interactions, wherein positive and negative
feedback from other consumers significantly
influences the behavior of potential users.
Practical implications include the opportunity for
companies to optimally allocate resources: investing not
only in technological upgrades but also in developing
training programs, increasing transparency in data
handling, and responding swiftly to disruptions. When
the appropriate conditions are met, social outcomes
include increased user satisfaction and engagement,
though this also heightens demands for the accessibility
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of digital services to diverse population groups.
Consequently, this work contributes to confirming and
detailing the multifaceted nature of customer retention
in
automated
self-service
environments
while
identifying factors that can enhance customer loyalty
and trust in such technologies.
This article will be valuable to professionals and
managers in the retail, banking, aviation, and hospitality
sectors seeking to optimize self-service processes and
increase customer loyalty by analyzing the impact of
convenience, control, trust, technological readiness, and
service recovery.
Keywords:
automated self-service technologies,
customer retention, trust, technological readiness,
service
recovery,
customer-to-customer
interactions, loyalty, automated service channels.
Introduction:
In recent decades, there has been a steady
increase in interest in self-service technologies (SSTs),
which are being implemented across a variety of sectors,
ranging from retail and banking to aviation and
hospitality. The
primary
advantage
of these
technologies lies in their ability to automate routine
operations, save time and resources, and enhance
customer satisfaction by providing rapid access to
services. However, one of the major challenges facing
companies is not only attracting users to the new service
format but also retaining them over the long term,
ensuring loyalty to automated channels.
Existing research has suggested that a range of factors
influence a customer’s decision to continue using SSTs,
including convenience, control, trust, technological
readiness, as well as additional elements such as
customer-to-customer interactions and recovery
mechanisms after failures. Nevertheless, several studies
note that the impact of each of these factors may vary
depending on the specific industry and consumer
category. There is also a hypothesis that the absence of
one fundamental factor (such as security or a clear
interface) can negate all other advantages of the
technology.
The present study was conducted to consolidate and
systematize existing theoretical and empirical data on
customer retention methods in automated self-service
environments, as well as to test the hypothesis of the
dominant role of multiple factors (convenience, trust,
technological readiness, and service recovery) in
fostering user loyalty. To achieve this goal, a systematic
review of academic literature was undertaken,
comparing findings from different researchers,
identifying common trends, and analyzing the statistical
contributions of individual variables to customer
retention.
Thus, this introduction highlights the relevance of the
topic and justifies the need for studying SSTs from the
perspective of long-term loyalty development. The
initial information provided demonstrates why interest
in customer retention emerged and how the literature
substantiates the importance of individual factors.
Testing the aforementioned hypothesis (regarding the
multifaceted nature of retention) and examining the
synergistic effects of multiple variables formed the basis
for further exploration of this topic in the study.
MATERIALS AND METHODS
In preparing this article, the works of various authors
focusing on different aspects of the functioning of
automated self-service technologies (SSTs) and the
formation of customer loyalty to these technologies
were utilized. For example, J. Collier and S. Kimes [1] as
well as J. Collier and D. Sherrell [2] conducted a detailed
analysis of how convenience and control influence SST
evaluations, providing empirical data on how speed and
sim
plicity affect customers’ decisions to reuse the
service. In turn, A. De Keyser et al. [3] highlighted the
role of service robots and emphasized the importance of
considering users’ technological readiness when
introducing innovative self-service formats. Research by
S. Dimitradas and N. Kyrezis [4], along with that of J. Kim
et al. [5], focused on issues of trust, transaction security,
and the transparency of personal data usage
—
factors
that are critically important when dealing with
automated service channels. V. Liljander et al. [6]
demonstrated that technological readiness correlates
directly with SST usage intensity, while M. Meuter and
colleagues [7] examined customer satisfaction in the
context of self-service technology interactions,
identifying key points that influence repeat usage. N.
Robertson et al. [8] stressed the significance of
customer-to-customer interactions, where reviews and
recommendations from other users substantially impact
potential clients’ loyalty. Meanwhile, C. Wang et al. [9]
explored long-term SST retention through the lens of
technological readiness and an elaborate system of
“rewards” for repeat use. Z. Zhu and colleagues [10]
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devoted particular attention to loyalty recovery
mechanisms following system failures, describing
compensation practices and rapid customer feedback.
The article’s methodology included a systematic search
and selection of relevant publications in scientific
databases (Scopus, Web of Science, EBSCO),
comparative analysis of theoretical propositions,
synthesis of statistical data from primary studies, and
critical evaluation of the obtained results. In the first
stage, scientific articles addressing issues of
convenience, control, trust, technological readiness, and
service recovery in SSTs were collected. After a detailed
examination, the selected sources underwent content
analysis to identify key customer retention factors and
strategies that enhance loyalty to automated channels.
In the final stage, the information was integrated into a
unified
framework,
allowing
the
systematic
presentation of approaches to user retention described
in the literature and the identification of the most
promising directions for further research in SSTs.
RESULTS
Analysis of the selected sources [1-10] revealed that all
of these studies in some form address the use of
automated self-service systems (SSTs) and the factors
influencing satisfaction, loyalty, and repeated use of
such services. Most authors focus on issues such as
convenience, control, technological readiness, trust,
intercustomer interactions, and service recovery
mechanisms for SST failures. Since maintaining and
strengthening long-term relationships with customers is
a crucial goal for any business, these studies provide
empirical
and
conceptual
evidence
that
a
comprehensive approach aimed at supporting these
factors is directly tied to successful SST user retention.
The analysis identified several key factors that recur
across various studies and influence the extent to which
customers remain loyal to automated service channels.
For clarity, these factors are summarized in Table 1,
which provides a brief description of each factor along
with the sources in which they are most thoroughly
discussed:
Table 1
–
Summary of Key Customer Retention Factors and Relevant Sources (source: compiled by the author
based on [1; 2; 4; 5; 6; 7; 8; 9; 10])
Factor
Brief Description
Main
Sources
Convenience
Simplicity and speed of completing transactions in SST
[1], [2]
Control
The customer’s ability to independently manage the self
-service
process and select interaction methods
[2]
Technological
Readiness
Users’ willingness to accept and adopt innovations, as well as their
skills and psychological preparedness
[6], [9]
Trust
Confidence in the technology’s security, privacy, and reliability
[4], [5]
Intercustomer
Interactions
The influence of other SST users’ behavior on satisfaction and loyalty
[8]
Service Recovery Mechanisms for addressing errors and compensating for
inconveniences during SST failures
[7], [10]
This table illustrates that the development of effective
retention methods requires attention to multiple factors
simultaneously. For example, convenience is most
frequently mentioned in the context of reducing wait
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times and simplifying the user interface [1; 2; 6; 7; 9]. In
the studies [2] and others, control is understood as the
ability of the customer to set the pace of service, input
data independently, and manage personal account
settings. Technological readiness, as a collective
concept, encompasses both the customer’s technical
skills and their overall openness to innovation [6; 9].
Trust in the system, according to [4; 5], is built through
transparent security policies, data protection, and the
stable performance of the service. Intercustomer
interactions, as noted in [8], are increasingly discussed
in the context of sharing reviews and recommendations,
where the experience of other users can either increase
or decrease trust in SST. Finally, recovery is examined in
[7; 10] as a critical mechanism that helps compensate for
negative user experiences and prevent churn to
competitors.
The next step in the material’s systematization was to
determine how frequently different factors are
mentioned in the sources. The goal was to identify which
aspects of SST are of the greatest interest to researchers
in the context of customer retention. Each article was
reviewed for mentions of these factors, and the final
results are presented in Table 2. Some studies [3] discuss
the introduction of service robots, which partly address
issues related to technological readiness and
intercustomer interactions.
Table 2
–
Frequency of Retention Factors Mentioned in the Reviewed Studies (source: compiled by the author
based on [1-10])
Factor
Number of Mentions*
Sources
Convenience
5
[1], [2], [6], [7], [9]
Control
3
[2], [7], [8]
Technological readiness
3
[6], [9], [3]**
Trust
4
[4], [5], [6], [9]
Intercustomer interactions
2
[8], [3]**
Recovery
3
[7], [9], [10]
* Multiple factors could be mentioned in a single article.
** De Keyser and coauthors [3] examine service robots
but also address technological readiness and
intercustomer interactions.
Table 2 indicates that convenience is the most
frequently
mentioned
factor
(five
mentions),
highlighting its critical importance for customer
retention. At the same time, control, technological
readiness, trust, intercustomer interactions, and
recovery appear with varying frequencies, but their
interplay is also considered significant. In particular,
convenience cannot be viewed in isolation from trust (if
a customer does not feel the system is secure, they are
unlikely to continue using it even if the interface is very
convenient), and technological readiness correlates with
user satisfaction and the likelihood of returning to SST
[6; 9].
In addition to identifying factors, a comparative analysis
of methods proposed by the authors to increase loyalty
and retain customers at automated self-service points
was conducted. Broadly, these practices are grouped
under the same six factors, as each method targets
strengthening one or more aspects of user interaction
with SST. For instance, in improving convenience, the
focus is on reducing wait times, simplifying the interface,
and providing round-the-clock access [1; 2]. To build
trust, the emphasis is on transparent use of personal
data, heightened security, and targeted communication
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with the customer [4; 5]. Research [6; 9] notes that low
technological readiness can be mitigated through
educational materials, a demo version of the service,
and incentive programs encouraging customers to use
SST more frequently. All the studies stress that a single
factor is rarely sufficient; retaining customers requires a
holistic approach that harmoniously combines
convenience and trust while ensuring effective system
recovery in case of failures.
Some of the reviewed works [1; 6; 9] include statistical
data confirming a positive relationship between these
factors and customer retention. Table 3 below presents
examples of correlations and regression coefficients (r
and β) reported by the authors. These numerical values
illustrate how factors like convenience, trust, and
technological readiness may impact retention rates.
However, each study employed its analytical methods
(regression models, surveys, satisfaction scales), so the
figures provided in the columns reflect only a general
trend and do not claim universality.
Table 3
–
Examples of Statistical Relationships Between Factors and Customer Retention (Based on Author
Data) (Source: compiled by the author based on [1; 6; 9])
Source and Indicator
Convenience
Trust
Technological Readiness
Retention
Collier & Kimes [1]: r
0.42
0.25
–
0.50
Liljander et al. [6]: β
–
–
0.33
0.39
Wang et al. [9]: β
0.29
0.22
0.35
0.44
Here, the “–” symbol indicates that the given metric was
not analyzed or reported by the authors. Whether the
correlations (r) or standardized regression weights (β)
are shown, the general trend is clear: convenience, trust,
and technological readiness have a statistically
significant positive effect on customer retention. For
example, in [9], the combined influence of these three
factors in the regression model can be expressed as:
Retention = 0.29 × Convenience + 0.35 × Technological
Readiness + 0.22 × Tr
ust + ε,
where ε is the random error term. All coefficients in this
model have a positive sign, indicating a direct
relationship between these factors and retention.
Similar patterns were noted by other authors [1; 6],
suggesting that comprehensive support of these aspects
contributes to increased user loyalty.
A closer examination of individual aspects highlighted in
the reviewed works reveals three significant additions.
First, [3] draws attention to the integration of service
robots, which appears to be a logical progression in the
evolution of SST. However, their study indicates that
without adequate customer technological readiness and
an established trust framework, such solutions may
prove ineffective. Second, [8] closely examined the
impact of intercustomer interactions, noting that while
positive reviews and recommendations enhance
engagement, the spread of negative comments can lead
to a sudden user exodus. Third, [10] and [7] both
emphasize the importance of swift responses to
disruptions; when a service promptly compensates for
inconveniences (e.g., through bonus points or discounts)
and provides clear instructions for problem resolution,
customer loyalty is retained even after significant
technical failures.
Synthesizing all these findings, it can be concluded that
customer retention in automated self-service points is
inherently multifaceted. Each factor
—
convenience,
control, trust, technological readiness, intercustomer
interactions, and recovery mechanisms
—
contributes to
the user’s ultimate deci
sion to continue or discontinue
using SST. Convenience is the most frequently cited
factor in the literature [1; 2; 6; 7; 9], but researchers
emphasize that its role is closely tied to trust in the
technology and customers’ readiness to engage with
automated services. While intercustomer interactions
are mentioned less frequently [8; 3], their significance
grows as digital communications expand and real-time
reviews and recommendations become more prevalent.
Additionally, the issues of security (privacy, data
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protection), repeatedly emphasized in [9; 4; 5], directly
influence trust and repeat usage. Meanwhile, rapid and
well-considered recovery measures, highlighted by [7;
10], are identified as key tools for mitigating potential
customer attrition.
Based on the statistical data presented in Table 3 and
the methodological recommendations (some of which
are noted in [1; 6; 9]), it is evident that the most effective
strategies simultaneously address multiple parameters.
For example, simplifying the SST interface should be
paired with a clear security policy and educational
initiatives that bolster technological readiness. In the
event of disruptions, the service must have a well-
established compensation and support system to ensure
that customers do not equate a single negative
experience with the overall failure of the technology.
Several authors [3; 8] suggest that shortly, all these
factors may gain additional importance as robotic
solutions become more popular and the “digital
ecosystem” expands, where custom
ers themselves help
shape the reputation and reliability of services.
Thus, the results of the systematization demonstrate
that retaining customers at automated self-service
points critically depends on a comprehensive approach
that integrates convenience, control, technological
readiness, trust, inter customer interactions, and well-
planned recovery processes. The relative significance of
each factor may vary depending on the market specifics
or customer categories, yet together, they form the
“user perception” that directly influences repeat visits to
SST and long-term loyalty. The data and descriptions
presented in Tables 1
–
3 reflect the theoretical and
empirical aspects of how these factors affect retention.
The methodologies proposed by the authors
—
from
simplifying interfaces to introducing innovative robots
and error compensation systems
—
offer a broad range
of tools that companies can employ to develop their
loyalty strategies. All the statistical results presented
(correlation coefficients and regression weights)
confirm the existence of meaningful positive
relationships between these parameters and client
behavior. However, a detailed interpretation and critical
analysis of these results in specific contexts falls outside
the scope of the “Results” sec
tion and is traditionally
included in the “Discussion.”
DISCUSSION
The results of the systematic review (see the “Results”
section) indicated that customer retention in automated
self-service points is influenced by a combination of
factors, most commonly including convenience, control,
technological
readiness,
trust,
inter
customer
interactions,
and
recovery
mechanisms.
This
multifactorial nature is confirmed by numerous authors
(e.g., [1; 2; 9]), who emphasize that isolated measures
(e.g., merely simplifying the interface or only enhancing
security) rarely achieve long-term effects. Instead, the
best results are obtained through a combination of
multiple tools. The systematization revealed that
convenience is indeed the most frequently mentioned
factor, but convenience alone does not guarantee user
loyalty if trust in the system and channel reliability are
not ensured. This finding aligns with studies [4; 5] that
highlight the importance of data security and
transaction transparency.
The trends identified in the review are generally
consistent with studies conducted in the context of retail
networks and banking services (e.g., [2; 6]). For instance,
recent research on self-service in retail (particularly in
the grocery sector) notes that simplifying the interface,
promptly responding to errors, and providing well-
planned customer support increase the likelihood of
repeat customer interactions with an electronic kiosk
rather than a staffed checkout. This is also reflected in
findings related to technological readiness, showing that
customers with even minimal technical skills are more
confident using SST if the system offers clear
instructional content [6]. Regarding recovery from
failures, the findings align with studies [7; 10], which
claim that timely compensation (discounts, bonuses)
and 24/7 support substantially reduce the risk of
immediate churn in the event of technical disruptions.
The review highlights that positive feedback from other
users can not only increase trust in the self-service
system but also encourage new customers to try SST.
Conversely, negative feedback
—
especially detailed
accounts of system failures
—
can lead to a rapid loss of
a significant portion of the audience. This conclusion is
consistent with
studies
that
consider
online
intercustomer communication as a key factor in shaping
the reputation of automated systems [3].
The practical value and significance of these findings lie
in their potential application by companies developing
or implementing SST to create more targeted retention
strategies. The multi-component structure of factors
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(convenience,
trust,
readiness,
inter
customer
interaction, control, and service recovery) suggests that
effective retention efforts require not only technical
improvements (such as faster terminal performance)
but
also
enhanced
“human”
elements
like
communication, feedback, and security transparency.
This supports the theory of loyalty as a complex
phenomenon, where satisfaction with the transactional
process is only one part, while emotional perception,
trust, and social influence also play substantial roles [1].
The results generally aligned with initial expectations, as
previous research has repeatedly highlighted the
importance of convenience, trust, and user readiness for
technology [4; 9]. However, clearer data structuring
revealed that trust and convenience are more closely
interconnected than initially assumed: it was expected
that trust would be secondary to the functional features
of SST, but several studies indicate that even a highly
convenient system is not perceived as reliable if users
have doubts about its security. Thus, if a company does
not invest in measures to build trust, improvements in
interface design and speed may have limited impact.
This shift in emphasis may reflect growing consumer
awareness of information security issues and
heightened demands for data protection [6].
The consistency of these findings with established
principles on the multifaceted nature of loyalty (see [2;
5]) indicates that traditional theories of user behavior in
the self-service context
—
relying on technological
readiness and perceived risk
—
remain relevant.
Empirical results demonstrate a statistically positive
relationship between convenience, trust, technological
readiness, and overall retention rates. Additionally, the
importance of service recovery as a tool for
“rehabilitating” customers after service disruptions
support the concept that the quality of post-incident
support directly influences subsequent user behavior [7;
10].
This interpretation of the collected and analyzed data
underscores that customer retention strategies for
automated self-service points must consider multiple
interconnected factors. The findings are applicable
across various industries (retail, banking, services,
aviation, and others), as the underlying principles
(comfort, security, rapid incident response) are broadly
relevant to most consumer segments. However, the
question remains as to how retention factors vary
among specific target groups (for example, customers
with low technological readiness or advanced users
seeking high-tech features). Future studies could focus
on identifying the distinct characteristics of different
customer types and developing personalized retention
strategies accordingly.
CONCLUSION
The results of the systematic review and their
interpretation allow for several conclusions regarding
the mechanisms and tools that contribute to customer
retention in automated self-service points. The analysis
of literature sources confirmed that the multifactorial
nature of retention plays a key role: convenience, trust
in the technology, technological readiness, control over
the process, inter customer interaction, and service
recovery from failures collectively create a positive user
experience and encourage repeated use of SST.
The primary contribution of this study to the div of
research is that the conducted systematization not only
reaffirmed the existing approaches in the literature for
identifying retention factors but also highlighted their
interdependence. It was found that companies focusing
solely on simplifying the interface and accelerating
transactions may face insufficient loyalty levels if they
do not simultaneously address trust and security (such
as data protection). Furthermore, it was established that
proper service recovery can significantly mitigate
negative experiences caused by technical failures and
prevent customer churn.
From an economic standpoint, the obtained results are
important as they enable optimization of SST
development costs. Businesses that consider the
complexity of the underlying causes of loyalty can
allocate resources more effectively, focusing not only on
the technological modernization of devices and
applications but also on programs to build trust, educate
users, and respond quickly to incidents. This contributes
to more sustainable customer retention, reduced
operating costs for traditional service channels, and
increased company competitiveness.
In conclusion, the study demonstrates that customer
retention methods in automated self-service points are
of significant scientific and practical value, requiring
further interdisciplinary research and refinement of
loyalty management approaches. Their implementation
and the correct combination of factors can provide
companies with additional advantages in the
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increasingly digitalized market environment.
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