Jurnal Administrasi Bisnis Vol.
No.
April 2025 ISSN 3047-0005 (Onlin.
Digital Service Innovation in Enhancing Customer Satisfaction: An Analysis of Service and Product Quality in the Banking Industry (Inovasi Layanan Digital dalam Meningkatkan Kepuasan Nasabah: Analisis Kualitas Layanan dan Produk pada Industri Perbanka.
Agung Prastyo.
Kevin Ewaldo*.
Marselinus.
Aira Putri E D Department of Business Administration.
Universitas Jakarta.
Jl.
Pulomas Barat No.
East Jakarta.
Indonesia.
* Corresponding Author.
E-mail: kevinewaldooffice@gmail.
Abstract This study aims to analyze the influence of service quality and product quality on customer satisfaction through digital service innovation at BNI Agen46 Menteng Main Branch and to propose strategic recommendations for developing digital services that enhance customer satisfaction and A quantitative approach was applied using a survey method with a five-point Likert scale The collected data were analyzed using multiple linear regression to examine the relationships among variables, supported by validity, reliability, and classical assumption tests to ensure the robustness of the findings.
The results indicate that both service quality and product quality have a positive and significant impact on customer satisfaction.
These findings highlight that improving service and product quality is crucial for strengthening customer loyalty and fostering sustainable long-term Furthermore, based on SWOT and TOWS analyses, this study proposes strategic recommendations that leverage internal strengths and external opportunities, such as optimizing brand reputation, fostering collaboration with fintech companies, and enhancing digital service features to be more responsive to customer needs.
Keywords: Customer satisfaction, digital services, service quality.
SWOT, product quality.
Abstrak Penelitian ini bertujuan untuk menganalisis pengaruh kualitas layanan dan kualitas produk terhadap kepuasan nasabah melalui inovasi layanan digital pada Agen46 BNI Kantor Cabang Utama Menteng, serta merumuskan rekomendasi strategis untuk pengembangan layanan digital yang dapat meningkatkan kepuasan dan loyalitas nasabah.
Pendekatan kuantitatif digunakan dengan metode survei melalui kuesioner yang disusun menggunakan skala Likert lima poin.
Data yang diperoleh dianalisis menggunakan regresi linier berganda untuk menguji pengaruh antarvariabel, disertai uji validitas, reliabilitas, dan asumsi klasik guna memastikan keandalan hasil penelitian.
Hasil analisis menunjukkan bahwa baik kualitas layanan maupun kualitas produk berpengaruh positif dan signifikan terhadap kepuasan nasabah.
Temuan ini menegaskan bahwa peningkatan kualitas layanan dan produk merupakan faktor penting dalam memperkuat loyalitas nasabah dan menciptakan hubungan jangka panjang yang berkelanjutan.
Selanjutnya, melalui analisis SWOT dan TOWS, penelitian ini merekomendasikan strategi pengembangan layanan digital berbasis kekuatan internal dan peluang eksternal, seperti optimalisasi reputasi merek, kolaborasi dengan fintech, serta peningkatan fitur digital yang responsif terhadap kebutuhan nasabah.
Kata kunci: kepuasan nasabah, kualitas layanan, kualitas produk, layanan digital.
SWOT.
INTRODUCTION
The rapid development of digital technology has brought significant changes across various sectors, including the financial In the banking sector, technological advancement represents a strategic opportunity to expand access to financial services, improve operational efficiency, and strengthen customer Banks that can optimally leverage digital innovation will gain a competitive advantage and better meet the financial needs of Agung Prastyo.
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society in a faster, safer, and more practical To remain competitive in an increasingly dynamic market, banks must adapt by implementing digital-based service innovations.
Such innovations not only aim to attract customers but also to enhance their transaction experience through services that are efficient, accessible, and reliable.
Therefore, a bankAos ability to develop high-quality digital services and products has become a crucial factor in achieving customer satisfaction.
One notable example of digital service innovation in Indonesia is Agen46, an initiative by PT Bank Negara Indonesia (Perser.
Tbk.
This program represents a form of inclusive financial transformation that enables individuals and business entities to access a wide range of banking services through authorized agents.
Agen46 offers various services such as Laku Pandai, digital financial transactions, epayments, e-commerce, and micro-loans.
Through Electronic Data Capture (EDC) devices and a mobile application.
Agen46 extends BNIAos reach even to areas not covered by branch offices.
However, despite the continuous growth in the number of agents, data indicate a decline in transaction volume and fee-based income in several branches, including the Kantor Cabang Utama Menteng.
In 2020, the number of agents reached 535 with approximately 33,000 transactions, but in 2023, even though the number of agents increased to 616, transaction volume and income decreased.
Moreover, 86 agents terminated their operations during 2023, mainly due to switching to competitors.
This phenomenon shows that the increase in the number of agents has not been followed by improved performance and customer satisfaction.
Interviews with the Branch Manager of BNI Menteng Branch revealed several customer complaints regarding service quality, less competitive transaction fees, and technical issues with the Agen46 mobile application.
These findings indicate that the quality of digital services and products plays a vital role in maintaining customer satisfaction and loyalty.
Previous studies on the influence of service quality and product quality on customer satisfaction have been widely conducted, such as those by Laili & Rahman .
, who emphasized the importance of customer satisfaction in maintaining loyalty, and Atmaja .
, who highlighted the role of product quality in shaping customersAo positive perceptions of banks.
However, most of these studies focused on conventional banking services and have not thoroughly examined the implementation of digital service innovations as a strategic approach to improving service quality, product quality, and customer satisfaction in the era of banking digitalization.
With the rapid development of digital banking, there is a need for more specific studies to understand how digital innovation contributes to enhancing customer satisfaction and experience.
Based on the background and the problems identified, this study aims to analyze the influence of service quality and product quality on customer satisfaction through digital service innovation at Kantor Cabang Utama BNI Menteng, recommendations for the development of digital services that can enhance customer satisfaction and loyalty.
This research is expected to provide valuable insights for BNIAos management in optimizing the implementation of digital innovations and serve as a practical reference for advancing the banking industry in the digital transformation era.
LITERATURE REVIEW
Marketing Management Marketing management is a strategic process that involves analyzing market opportunities, selecting target segments, and designing integrated marketing programs to attract, retain, and grow customers.
It focuses on creating superior value for customers through promotion, and distribution strategies.
In the modern business landscape, marketing management plays a critical role in aligning company objectives with customer It emphasizes understanding consumer behavior, delivering consistent value, and building long-term relationships that contribute to customer loyalty and sustainable business growth (Agu et al.
, 2.
In the context of digital banking, marketing management is not limited to traditional promotional efforts but also includes managing digital platforms, enhancing customer experience, and ensuring service innovation that Agung Prastyo.
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meets the evolving expectations of tech-savvy customers (Athaide et al.
, 2.
Therefore, marketing management serves as the foundation for designing customercentered strategies that integrate both technological innosvation and service excellence to enhance satisfaction and competitiveness in the banking industry (Cakir et al.
, 2.
Customer Satisfaction Customer satisfaction refers to the feeling of pleasure or disappointment that arises when comparing perceived product or service performance with customer expectations (Fadhillah & Simanjuntak, 2.
If performance falls short of expectations, customers are if it meets expectations, they are and if it exceeds expectations, they experience delight.
Customer satisfaction is critical for fostering loyalty, enhancing corporate reputation, reducing price sensitivity, and improving overall efficiency (Akanbi & Obafemi, 2.
Satisfied customers are more likely to engage in repeat transactions, provide positive word-of-mouth recommendations, and become long-term users of a companyAos products and services.
Several methods can be used to measure customer satisfaction, including complaint and suggestion systems, mystery shopping, lost customer analysis, and customer surveys.
There are five key factors commonly associated with customer satisfaction, including product quality, service quality, emotional factors, price, and cost considerations (Ifedi et al.
, 2024.
Marselinus & Rudianto, 2.
These factors demonstrate that customer satisfaction serves as a key outcome of marketing and service strategies, closely influenced by how well the company delivers quality in both products and services.
Product Quality Product quality refers to a productAos ability to meet customer needs and expectations by delivering performance that matches or exceeds what is desired (Sambo et al.
, 2.
Yusuf & Matiin .
describe a product as anything offered to a market for attention, acquisition, use, or consumption that satisfies consumer wants or Understanding product quality dimensions helps firms differentiate their offerings from Key performance, durability, conformance to specifications, features, reliability, aesthetics, and perceived quality.
In the digital banking industry, product quality can be reflected through the stability of the digital platform, the completeness of its features, the design appeal of its interface, and the reliability of its transaction systems.
High product quality not only strengthens customer trust but also enhances satisfaction and long-term While product quality emphasizes the tangible and technical aspects of digital banking services, service quality focuses on the experiential and relational elements that shape customer perceptions and loyalty.
Service Quality Service quality is defined as a companyAos ability to fulfill customer needs and expectations by delivering services accurately, promptly, and reliably (Setiono & Hidayat, 2022.
Singh et al.
(Setiono & Hidayat, 2022.
Singh et al.
In essence, services represent intangible exchanges between parties that emphasize experience and value creation rather than physical ownership.
Baek et al.
identifies several intangibility, inseparability, and customization.
Service quality is often measured through the SERVQUAL model, which includes five key Tangibles, physical facilities, tools, and appearance of personnel.
Reliability, the ability to perform promised service dependably and accurately.
Responsiveness, willingness to help and provide prompt service.
Assurance, employee knowledge, courtesy, and ability to inspire trust.
Empathy, individualized attention and genuine concern for customers.
In the context of digital banking, service quality is reflected in the reliability of digital platforms, the responsiveness of customer service, and the ease of accessing banking features through applications or agent networks such as BNIAos Agen46.
Together with product quality, service quality forms the foundation for customer satisfaction, which in turn determines loyalty and Agung Prastyo.
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competitive sustainability in the era of digital CONCEPTUAL FRAMEWORK This study is based on the assumption that customer satisfaction is influenced by the quality of services and products provided by the bank.
Digital service innovation plays a crucial role in enhancing both aspects by improving efficiency, accessibility, and transaction convenience.
The better the quality of digital products and services offered, the higher the level of customer satisfaction with the bank.
Digital service innovation enhances both product and service quality by improving efficiency, accessibility, and customer experience.
As product and service quality improve, customer satisfaction increases accordingly (Figure .
Product Quality (X.
Service Quality (X.
Customer Satisfaction (Y) Figure 1.
Conceptual Framework Based on the theoretical framework and previous studies related to service quality, product quality, and customer satisfaction, the hypotheses in this research are formulated as follows:
Service quality (XCA) has a significant effect on customer satisfaction (Y).
Product quality (XCC) has a significant effect on customer satisfaction (Y).
Service quality (XCA) and product quality (XCC) simultaneously have a significant effect on customer satisfaction (Y).
METHODS
This study employs a quantitative approach aimed at analyzing the influence of service quality and product quality on customer satisfaction within BNIAos digital service platform.
Agen46.
The research was conducted at PT Bank Negara Indonesia (Perser.
Tbk.
Kantor Cabang Utama Menteng, located at Jl.
Menteng Raya No.
Kebon Sirih Sub-district.
Menteng District.
Central Jakarta.
The study was carried out over the period of March to August 2024.
The population in this research consists of all Agen46 partners under the supervision of Kantor Cabang Utama BNI Menteng.
Due to the dynamic and fluctuating nature of the population, the exact number could not be determined.
Therefore, the sample size was determined based on the rule of thumb principle proposed by VanVoorhis & Morgan .
, to ensure that the representativeness and sufficiency for statistical The sample size formulation was adapted from the approach suggested by Hair Jr et al.
, as shown in the following equation:
ycumin = yco y ycy .
Where:
ycumin = minimum sample size = limiting factor of 10 .
s suggested by Hair et al.
= number of independent variables in the analytical model Based on this calculation, a total of 43 respondents were selected as the research sample.
The sampling technique used was accidental sampling, which selects respondents based on accessibility and availability during the data collection process (Sugiyono, 2.
The research utilized both primary and secondary data.
Primary data were obtained directly through questionnaires distributed to respondents, while secondary data were collected from documented sources such as company reports, academic publications, and other relevant literature that support the study.
The research instrument employed was a structured questionnaire designed using the Likert scale This method was used to measure respondentsAo attitudes, and evaluations toward each research variable.
Each variable was operationalized into several indicators that were then formulated into questionnaire items, allowing for systematic and measurable assessment of the phenomena being Before conducting data analysis, the research instrument was tested to ensure that the questionnaire met the criteria of validity and The validity test aims to assess the extent to which the questionnaire items Agung Prastyo.
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accurately and appropriately measure the intended variables (Dasli & Achmad, 2.
The test was conducted using a statistical data processing application by comparing the r-count value with the r-table value at a 5% significance A questionnaire item is considered valid if the r-count value is greater than the r-table value, and invalid if otherwise (Isnardono & Nicholas.
A reliability test was then performed to evaluate the consistency of the research Reliability reflects the extent to which a measurement tool produces stable and consistent results when applied at different times (Puspita & Arisandi, 2.
The reliability test in this study employed the CronbachAos Alpha method, where an instrument is considered reliable if the Alpha value exceeds 0.
(Bungatang & Reynel, 2.
This method was used to assess the internal consistency reliability of the questionnaire items.
Data analysis in this study was carried out quantitatively using statistical analysis tools to process and interpret the collected data.
The analytical procedures included descriptive analysis, classical assumption testing, and hypothesis testing.
Descriptive analysis was conducted to present the characteristics of respondents and to provide an overview of their perceptions of each research variable.
The descriptive statistics employed included measures of central tendency .
ean, median, and mod.
and measures of dispersion .
ange and standard deviatio.
Prior to regression analysis, basic assumption tests were conducted, including normality and linearity tests.
The normality test aimed to determine whether the data were normally distributed, using the KolmogorovSmirnov method with a significance level of 0.
(Jasin & Firmansyah, 2.
The data are considered normally distributed if the significance value exceeds 0.
05 (Naulibasa et al.
The linearity test was conducted to determine whether the relationship between independent and dependent variables was linear (James et al.
, 2.
The relationship is considered linear if the significance value is greater than 0.
05 (Arini et al.
, 2.
Subsequently, classical assumption tests were performed, including multicollinearity, heteroskedasticity, and autocorrelation tests (Nyoman et al.
, 2.
The multicollinearity test aimed to ensure that there was no high correlation among the independent variables, with the criterion that the Variance Inflation Factor (VIF) values should fall between 1 and 10 (Saehu & Hutabarat, 2.
The heteroskedasticity test used to detect variance inequality among residuals, where no heteroskedasticity is indicated if the significance value is greater than 05 (Musa et al.
, 2.
The autocorrelation test was conducted using the Durbin-Watson method, where no autocorrelation is indicated if the value satisfies du < d < 4 Ae du (Kumar, 2.
The primary analysis of this research employed multiple linear regression to examine the influence of service quality and product quality on customer satisfaction.
Multiple linear regression was chosen because the study involved more than one independent variable (Aras et al.
, 2.
with the following formula:
Y=a b1 X1 b2X2 .
bnXn Where:
XCA.
XCC.
XCo bCA, bCC.
A, bCo = Dependent variable = Constant = Independent variables = Regression coefficients Hypothesis testing was conducted through the t-test and F-test.
The t-test was used to measure the partial effect of each independent variable on the dependent variable at a 0.
significance level (Puspita & Arisandi, 2.
the t-count value exceeds the t-table value, the alternative hypothesis is accepted (Sugiyono.
Meanwhile, the F-test was used to examine the simultaneous effect of all independent variables on the dependent variable (Sugiyono, 2.
The hypothesis is accepted if the F-count value exceeds the F-table value or if the significance value is less than 0.
Furthermore, determination (RA) was used to determine the proportion of variance in the dependent variable explained by the independent variables (Dasli & Achmad, 2.
A higher RA value indicates that the independent variables have a greater ability to explain variations in customer satisfaction as the dependent variable (Isnardono & Nicholas.
Subsequently, to formulate strategies for the development of digital services, the SWOT method was employed, taking into account Agung Prastyo.
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internal factors .
trengths and weaknesse.
as well as external factors .
pportunities and threat.
relevant to enhancing customer satisfaction and loyalty.
RCount
Information CS6
Valid
CS7
Valid
RESULT AND DISCUSSION
CS8
Valid Validity and Reliability Test Validity testing aims to ensure that the questionnaire items accurately measure the intended research variables.
In this study, the Pearson Product Moment correlation method was An item is considered valid if its r-count
exceeds the r-table value at a 5% significance CS9
Valid
CS10
Valid Table 1.
Validity Test Result Variable Service Quality (SQ) Product Quality (PQ) Customer Satisfaction (CS) Item RTable Source: Primary Data .
As shown in Table 1, the research variables include Service Quality .
Product Quality .
, and Customer Satisfaction .
All items have r-count values greater than r-table, indicating that each item is capable of accurately measuring the construct it represents.
This confirms the validity of the instrument, ensuring the data collected from respondents is suitable for further analysis.
Reliability consistency of an instrument in measuring the same construct over time.
In this study.
CronbachAos Alpha was used, with a threshold of 60 as the minimum requirement for reliability.
RCount
Information SQ1
Valid
SQ2
Valid
SQ3
Valid
SQ4
Valid
SQ5
Valid
Valid
SQ7
Valid
Variable SQ8
Valid
Service Quality Cronbach's Alpha
0,933
SQ9
Valid
Product Quality 0,926 Reliable SQ10
0,953
Reliable Valid
Customer Satisfaction SQ11
Valid
PQ1
Valid
PQ2
Valid
PQ3
Valid
Valid
Valid
PQ6
Valid
PQ7
Valid
PQ8
Valid
CS1
Valid
CS2
Valid
Valid
CS4
Valid
CS5
Valid
Item
SQ6
RTable Variable 0,294 PQ4
PQ5
CS3
0,294
0,294
Table 2.
Reliability Test Result Information Reliable Source: Primary Data .
The results indicate that all variables have CronbachAos Alpha values exceeding 0.
60 (Table This demonstrates that the questionnaire items are reliable and capable of producing consistent data, providing a solid foundation for subsequent statistical analyses.
Classical Assumption Test The normality test aims to verify whether the residuals in the regression model are normally This is essential because parametric statistical tests assume normality of residuals.
The KolmogorovAeSmirnov (KAeS) test was applied, producing an Asymp.
Sig.
value of 200, which is greater than 0.
05 (Table .
Therefore, it can be concluded that the data are normally distributed.
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Table 3.
KolmogorovAeSmirnov Normality Test One-sample Kolmogorov-Smirnov Test Unstandardized Residual Normal Parameters Mean Std.
Deviation Absolute Positive Negative Most Extreme Differences Test Statistic Asymp.
Sig.
Monte Carlo Sig.
-taile.
e Sig Condidence Interval Lower Bound Upper Bound Test distribution is Normal.
Calculated from data.
Lilliefors Significance Correction This is a lower bound of the true significance.
LillieforsAo method based on 10000 Monte Carlo sample with starting seed 2000000 Source: Primary Data .
The multicollinearity test evaluates whether independent variables are highly correlated with one another.
Excessive correlation can distort regression estimates.
The results (Table .
indicate that the Tolerance values are above 0.
1 and VIF values are below 10, suggesting that multicollinearity is not present in the regression model.
Table 4.
Multicollinearity Test Results Coefficientsa Model (Constan.
Service Quality Product Quality Std.
Beta Sig.
VIF
Error
959 <,001
012 <,000
Dependent Variable: Customer Satisfaction Source: Primary Data .
Heteroscedasticity testing checks whether the variance of residuals is constant across Using the Glejser test, the significance values for Service Quality and Product Quality exceed 0.
05, indicating the model does not exhibit heteroscedasticity.
This confirms that the regression estimates are reliable and unbiased.
Autocorrelation testing examines whether residuals from one observation are correlated with residuals from previous observations.
The DurbinAeWatson (DW) test yielded a value of 173, with decision criteria du = 1.
6091 and 4Ae du = 2.
Since du < DW < 4Aedu, it is concluded that the model does not experience autocorrelation, ensuring the independence of observations (Table .
Table 5.
Autocorrelation Test Results (DurbinAeWatso.
Mode Summaryb Adj R Model Square Square Source: Primary Data .
Std Error Multiple linear regression analysis was conducted to determine the effect of Service Quality (XCA) and Product Quality (XCC) on Customer Satisfaction (Y).
The regression equation is as follows:
Y = -2,376 0,713 X1 0,274 X2 e Table 6.
Multiple Linear Regression Results Coefficientsa Coef Std.
Error (Constan.
-2,376 10.
Service Quality Product Quality Model Coef Beta Sig.
Dependent Variable: Customer Satisfaction Source: Primary Data .
The negative constant (-2.
suggests that if both independent variables are zero.
Customer Satisfaction is predicted to decrease by 376 units (Table .
The positive coefficient for Service Quality .
indicates that higher service quality is associated with increased Agung Prastyo.
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customer satisfaction, reflecting the critical role of service in customer perception.
The positive coefficient for Product Quality .
shows that improvements in product quality contribute positively to customer satisfaction.
This finding aligns with the theory that product quality is a key determinant of consumer satisfaction.
The results of the t-test indicate that both service quality and product quality have a positive and significant effect on customer satisfaction with Agen46.
The significance values for each variable were below 0.
suggesting that any improvement in these variables is likely to be followed by an increase in customer satisfaction.
This implies that efforts to enhance service quality, such as improving response speed, information clarity, and digital interaction comfort, as well as strengthening product quality through more functional and reliable features, will have a direct impact on customer satisfaction levels.
Furthermore, the F-test results show that simultaneously have a significant influence on customer satisfaction, with a significance value smaller than 0.
05 (Table .
This finding confirms that both variables complement each other in shaping customersAo positive perceptions of Agen46.
Table 7.
F-Test Results Model Regression Residual Total Sum of Mean Square Sig.
<,000
Dependent Variable: Customer Satisfaction Predictors: (Connstan.
Service Quality,Product Quality Source: Primary Data .
The coefficient of determination (Adjusted RA) value of 0.
315 indicates that 31.
5 percent of the variation in customer satisfaction can be explained by the combination of service and product quality (Table .
, while the remaining 5 percent is influenced by other factors outside the model, such as brand trust, digital experience, and emotional or social factors.
Therefore, simultaneous improvement in service and product quality should be considered a strategic priority to strengthen customer satisfaction and loyalty in Agen46.
Table 8.
Coefficient of Determination (RA) Results Model Summaryb Model Adjusted Std.
Error of Square R Square the Estimate Dependent Variable: Customer Satisfaction Predictors: (Connstan.
Service Quality,Product Quality Source: Primary Data .
Strategic Analysis for Digital Service Development To propose strategic recommendations for enhancing customer satisfaction and loyalty in Agen46 digital services, a SWOT analysis was This method evaluates internal and external factors that influence service The findings are summarized as Strengths (Internal Positive Factor.
A Strong brand recognition of BNI and the Agen46 network.
A Historical base of loyal customers with consistent engagement.
A Integration of digital platforms with an easyto-use interface.
A Experienced and well-trained workforce supporting digital services.
Weaknesses (Internal Negative Factor.
A Limited customization of digital services to meet specific customer needs.
A Occasional delays in service response for some transactions.
A Digital features are still incomplete compared to competitors.
Opportunities (External Positive Factor.
A Rapid digital transformation among the A Increasing adoption of digital banking services among Indonesian customers.
A Growing demand for remote and practical financial solutions.
A Opportunities to collaborate with fintech companies to expand services.
Threats (External Negative Factor.
A Intense competition from other digital banking platforms and e-wallets.
A Rapid technological changes requiring continuous platform updates.
A Security and privacy concerns that may affect customer trust.
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Based on the results of the TOWS analysis, several strategic recommendations can be formulated to support the development of Agen46Aos digital services in enhancing customer satisfaction and loyalty.
These strategies were derived by integrating internal factors .
trengths and weaknesse.
and external factors .
pportunities and threat.
, aiming to provide realistic and sustainable directions for improving the competitiveness of BNIAos digital services.
First, the SO (StrengthAeOpportunit.
strategy emphasizes leveraging internal strengths to capitalize on the growing opportunities in the digital market.
BNI can strengthen the synergy between its online and offline channels by developing more user-friendly digital features, promoting accessibility, and collaborating with fintech companies to expand financial inclusion among unbanked communities.
Second, the WO (WeaknessAeOpportunit.
strategy focuses on addressing internal For instance, enhancing service responsiveness and adding personalized digital features can better meet the diverse needs of BNI can also introduce continuous digital training programs for Agen46 partners to improve their understanding and use of digital tools, thereby ensuring a consistent and satisfying customer experience across all service points.
Third, the ST (StrengthAeThrea.
strategy aims to use internal strengths to mitigate external In the face of intense competition and rapid technological changes.
BNI should pursue continuous innovation by leveraging its digital Strengthening ensuring transparency in data management, and proactively communicating privacy policies will be crucial to maintaining customer trust and reinforcing confidence in the Agen46 digital Fourth, the WT (WeaknessAeThrea.
strategy highlights defensive actions to minimize the impact of weaknesses and external threats.
BNI should conduct regular performance evaluations of its digital applications, develop a data-driven customer feedback monitoring system, and benchmark against key competitors to identify and address service gaps.
This approach enables the organization to maintain operational stability while remaining responsive to dynamic market conditions.
Overall, the TOWS analysis suggests that the development of Agen46Aos digital services should prioritize customer-oriented innovation, the improvement of digital interaction quality, and the strengthening of cross-sector Implementing these strategies is expected to enhance the value proposition of BNIAos digital services, foster customer trust, and build a sustainable competitive advantage in the era of digital banking transformation.
Discussion The results of the multiple linear regression analysis conducted in this study indicate that both service quality and product quality have a significant and positive effect on customer satisfaction with Agen46Aos digital The positive coefficients for both variables demonstrate that an improvement in either service or product quality directly contributes to higher customer satisfaction levels.
This finding reinforces the theoretical framework suggesting that customer satisfaction is primarily determined by the degree to which expectations are met through high-quality products and superior service delivery.
Furthermore, the results of the classical assumption tests, along with the validity and reliability analyses, confirm that the data used in this study are valid and consistent.
The Adjusted R Square value of 0.
315 indicates that 31.
5% of the variation in customer satisfaction can be explained by service and product quality, while the remaining 68.
5% is influenced by other factors beyond the scope of this study.
This finding highlights that service and product quality remain central determinants of satisfaction, but complementary aspects may also play an essential role in shaping long-term customer relationships.
The results of the t-test further reveal that both service quality and product quality individually have significant effects on customer Meanwhile, the F-test confirms that these variables jointly exert a meaningful influence on satisfaction, demonstrating their The determination (RA) value further supports this by showing a moderate explanatory power, which suggests the presence of other contributing variables that could be explored in future studies, such as digital convenience, system reliability, and perceived security.
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These findings are consistent with previous research by Noivyanti et al.
Mimi and Ekawati .
, as well as Panjaitan and Yuliati .
, all of which found that service quality positively and significantly affects customer satisfaction.
Similarly, the current study supports the work of previous researchers, which demonstrated that product quality has a significant and measurable impact on customer satisfaction (Tanjung et al.
, 2.
This alignment with earlier studies strengthens the empirical validity of the present findings and underscores the importance of continuous service and product improvement as strategic levers for enhancing satisfaction and loyalty.
Given the significant influence of these variables, the findings suggest that improving digital service and product quality should become a strategic priority for Agen46.
Enhancing the efficiency and responsiveness of digital platforms, expanding the range of product offerings, and ensuring consistency in service quality across all digital touchpoints will help reinforce customer trust and foster loyalty.
In this context, digital transformation is not merely a technological initiative but a comprehensive approach to strengthening the overall customer recommendations for the enhancement of digital services, a SWOT and TOWS analysis was conducted to identify key internal and external factors influencing Agen46Aos performance.
The integration of these analytical results allows for the development of actionable strategies, including leveraging BNIAos strong brand recognition, expanding collaboration with fintech partners, and continuously innovating digital features to remain competitive in a rapidly evolving financial landscape.
By aligning internal strengths with market opportunities while addressing existing weaknesses and mitigating threats.
Agen46 can build a sustainable digital ecosystem that enhances both customer satisfaction and loyalty in the long
CONCLUSION
This study concludes that service quality and product quality have a positive and significant influence on customer satisfaction with BNI Agen46 digital services at the Kantor Cabang Utama Menteng.
Improvements in both aspects have been shown to make a tangible contribution to increasing customer satisfaction, which in turn plays an essential role in building loyalty and strengthening long-term relationships between customers and the bank.
These findings reinforce the notion that customer satisfaction results from the effective and continuous management of service and product strategies.
recommendations formulated through SWOT and TOWS analyses emphasize the importance of leveraging BNIAos internal strengths, such as its strong brand reputation and digital capabilities, to capture external opportunities arising from the growing adoption of digital banking services in The development of more responsive digital features tailored to customer needs should be prioritized, along with optimizing collaborations with fintech partners and enhancing the reliability of digital systems to strengthen customer trust and loyalty.
REFERENCES