INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue VIII, August 2025

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Customer Relationship Management (CRM) Practices in the SBI
Bank: An Analytical Study in Darjeeling, West Bengal

Dr. Jyotirmoy Koley, WBES

Assistant Professor of Commerce, Darjeeling Government College, Darjeeling, West Bengal, India.

DOI: https://doi.org/10.51583/IJLTEMAS.2025.1408000185

Abstract: This analytical study investigates Customer Relationship Management (CRM) practices at the State Bank of India (SBI)
branch in Darjeeling, West Bengal. The study's objectives are to evaluate CRM strategies, assess their impact on customer
satisfaction and loyalty, and identify the challenges encountered during implementation. A combination of primary and secondary
data was used, with primary data collected through a structured questionnaire administered to 75 SBI customers using convenience
sampling. This study examined several key variables related to CRM, including customer awareness of CRM policies, perceptions
of CRM practices, e-CRM strategies, and customer service. Statistical tools such as ANOVA, correlation analysis, multiple
regression analysis, and one-sample t-test were used for data analysis. The findings reveal significant differences between
customers' demographic profiles and their awareness of CRM policies. Strong positive correlations were found between CRM
awareness, perception, and satisfaction. Customer service significantly influences perceptions of CRM practices, and e-CRM
strategies have a substantial impact on customer satisfaction. This study underscores the importance of tailored CRM strategies,
effective communication, service quality, and digital banking services in enhancing customer relationships and satisfaction. The
findings provide valuable insights for SBI and other banks operating in similar contexts to improve CRM practices and customer
satisfaction in the banking industry.

Keywords: Customer Relationship Management (CRM), E-CRM, Customer Satisfaction, Customer Loyalty, Service Quality, State
Bank of India (SBI), Banking Industry, etc.

I. Introduction:

Customer Relationship Management (CRM) is an essential strategy for banks aiming to enhance customer satisfaction, loyalty, and
overall organizational performance. In the competitive banking sector, effective management of customer relationships has emerged
as a critical determinant of success (Blery & Michalakopoulos, 2006). The State Bank of India (SBI), a prominent banking
institution in India, has been at the forefront of implementing CRM practices to strengthen customer relationships. This analytical
study focuses on examining CRM practices at the SBI branch in Darjeeling, West Bengal. The banking industry has recognized
CRM as a strategic tool that facilitates the management of existing customer relationships and the acquisition and retention of new
customers. The implementation of effective CRM strategies can enhance customer service quality, thereby improving organizational
performance (Lebdaoui & Chetioui, 2020). Technological advancements have enabled banks to adopt electronic CRM (e-CRM)
systems, allowing them to provide personalized services and improve customer satisfaction (Kumar et al., 2021). SBI's CRM
practices in Darjeeling exemplify a unique integration of traditional and electronic customer relationship management efforts. The
bank's emphasis on leveraging CRM systems aims to foster a more responsive and customer-centric approach to service. This study
explores the intricacies of CRM implementation at SBI in Darjeeling, examining the benefits and challenges encountered during
the process. By analysing these aspects, this study seeks to provide valuable insights into the effectiveness of CRM strategies in
enhancing customer satisfaction and loyalty within the banking industry context (Blery & Michalakopoulos, 2006; Kumar et al.,
2021).

Concept of Customer Relationship Management (CRM):

Customer Relationship Management (CRM) in Indian banks is important for keeping customers happy and loyal. It includes
strategies and technologies for managing interactions with customers. The main goal is to improve customer relationships by
providing better services and personalized experiences. Electronic Customer Relationship Management (E-CRM) is a key
component of CRM in banks. E-CRM improves customer satisfaction by enhancing their experience, which leads to increased
loyalty. Studies show that E-CRM not only improves customer experience but also helps build satisfaction and loyalty (Kumar et
al., 2021; Mokha & Kumar, 2021). Indian banks face challenges owing to competition and changing customer behaviour. CRM
strategies are essential for meeting customer expectations and improving services. Banks can gain an edge by offering both
technology-driven and traditional services to meet the changing needs of customers (Kamath et al., 2003). Customer satisfaction in
Indian banks depends on service quality, customer involvement, and the bank's physical environment. A study found that service
quality and customer involvement are key factors in customer satisfaction. This implies that banks should focus on these areas to
retain and attract customers (Gupta & Dev, 2012). Indian banks also use corporate social responsibility (CSR) in their CRM
strategies to improve satisfaction and performance. These initiatives focus on education, health, the environment, and societal
growth, which help the community and improve the bank's image and performance (Narwal, 2007). In summary, CRM in Indian
banks uses both traditional and electronic methods to improve customer experience, satisfaction, and loyalty. To succeed in a
competitive market, banks must use technology and focus on high-quality services.

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Problem Statement:

This study examines how the State Bank of India (SBI) branch in Darjeeling, West Bengal, uses Customer Relationship
Management (CRM). The main goal is to determine how CRM strategies are used at this branch, check if they help make customers
happier and more loyal, and find any problems faced during this process. SBI is one of India's largest banks and operates in a highly
competitive market where retaining customers is crucial. Banks worldwide now see CRM as the key to building strong customer
relationships and making more money (Blery & Michalakopoulos, 2006). However, using CRM effectively is not just about
technology; it requires the right organization, change management, and support from top leaders to work well (Alt & Puschmann,
2004). Past studies have shown that CRM is very important in banking for increasing customer loyalty and staying ahead of
competitors by using customer knowledge (Bhat & Darzi, 2016). However, there can be challenges in CRM due to local business
conditions, customer expectations, and the extent to which technology is used, which can vary in places like Darjeeling. This study
aims to examine these aspects by checking the current CRM setup at SBI's Darjeeling branch, seeing if it meets customer
expectations, how well it works in keeping customers happy and loyal, and finding areas to improve so that CRM helps the bank
meet its goals.

II. Literature Review:

Numerous articles and research papers have been published by researchers and academics on various aspects of the role of customer
relationship management in the Indian banking sector. The most recent and pertinent research articles were selected for this review.
These articles are critically reviewed and presented in this section.

Ahad (2022) examined Customer Relationship Management (CRM) in Indian banking, studying its implementation across three
banks using within-case and cross-case methodologies. Data were collected from the branch managers and academic journals. This
study analyzed CRM in ICICI Bank, HDFC Bank, and IDBI Bank, examining their definitions, processes, technology, and
structures. The analysis revealed that while CRM definitions varied, banks prioritized long-term customer relationships and
effectively utilized CRM technology, with organizational structures that supported communication. The study recommends broader
CRM implementation, continuous learning, customer information gathering, organizational alignment and clear implementation
goals.

Dash and Nayak (2022) examined Customer Relationship Management (CRM) in banking using Machine Learning (ML). This
study shows how information technology has transformed Indian banking and highlights CRM's role of CRM in sales and service
automation. Data were collected through questionnaires from public and private bank customers in Odisha, India, using a five-point
Likert scale. Using the x-means clustering algorithm, the analysis revealed that the Individual Customer Program (ICP) had the
strongest effect on customer retention, whereas employees’ understanding of specific customer needs (ESC) had the most impact
on service quality. The study recommends that banks improve service quality and adopt innovative strategies that focus on
customers, processes, and technology.

Nisha (2023) examined how banks use Customer Relationship Management (CRM). This study views CRM as a way for banks to
maintain good relationships with clients, moving away from traditional marketing methods. It focuses on how CRM affects the
Indian banking sector. CRM started in the 1970s and helped banks collect customer data to offer better services to customers. This
study examines CRM's benefits of CRM, how technology affects banks, and the challenges in dealing with customers. It uses
existing data to divide CRM into three types: Operational, Analytical, and Collaborative. These include Human Resource
Management, Customer Service, Sales Force Automation, and Marketing. Research shows that CRM helps banks understand
customers better and improve sales. However, it also highlights challenges, such as measuring customer views and the costs of
maintaining customer loyalty. The study concludes that CRM is important for attracting and retaining customers in Indian banks,
stressing the need for employee training and a shift from a task-focused to a result-focused work culture.

Verma et al. (2024) investigated Customer Relationship Management (CRM) in Indian banking. This study examines CRM's
potential of CRM to enhance customer satisfaction and business performance through a literature review and analysis. This study
explores CRM implementation challenges, including training and technology adoption. The findings indicate that CRM strategies
improve service quality and customer relationships, leading to higher retention rates. The study outlines CRM tools such as customer
databases, EPOS, Sales Force Automation, and Call Centers. Comparing public and private banks, the study shows that private
banks implement CRM more effectively. The study concludes that CRM adoption is vital for Indian banks' success in achieving
customer satisfaction and loyalty in the banking sector.

Putney and Puney (2013) examined Customer Relationship Management (CRM) in Indian banking. CRM is vital for banks in India
to maintain their competitiveness and involves customer data collection, profile creation, and targeted marketing. This study
emphasizes CRM's importance of CRM as the Indian banking market becomes more competitive, noting it as essential for market
share and growth. The factors driving CRM implementation include competition, customer contact points, information security,
customer expectations, and marketing opportunities. Banks that use CRM receive favorable customer perceptions based on
reliability, responsiveness, empathy, tangibility, and satisfaction. The study concludes that Indian banks are increasingly adopting
CRM to build customer relationships for competitive advantage.

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Yadav and Singh (2018) created a framework to study Customer Relationship Management (CRM), relationship quality, and
customer loyalty in Indian banks. They developed a model to explore CRM, relationship quality, and customer loyalty. CRM
includes communication, conflict handling, responsiveness, personalization, and customer focus. Relationship quality includes
trust, commitment, and relationship satisfaction. Customer loyalty is examined through customers’ behavior, thoughts, and attitudes.
The authors used previous studies to develop a model linking these parts. This study provides ideas for academics and professionals
regarding CRM in Indian banks. The identified parts can help professionals use CRM to improve relationship quality and loyalty.
However, focusing only on Indian banks limits the applicability of these findings. Future studies could examine other financial
areas and add more factors, such as service quality and switching costs.

Valetvakar et al. (2025) investigated CRM systems' effectiveness and loyalty in banking, examining their impact on customer
satisfaction and retention. The research objectives included assessing CRM's impact on satisfaction, identifying loyalty-enhancing
features, measuring the correlation between CRM effectiveness and loyalty, and examining implementation challenges. The study
collected data through questionnaires and research papers, with respondents from Vadodara, India. The findings revealed a balanced
gender distribution, with students as the primary respondents. Mobile banking was the main interaction method, and customer
service was crucial for selecting a bank. Of the respondents, 45.8% were satisfied with the banking services. The study concludes
that CRM systems enhance satisfaction and loyalty, requiring effective implementation and employee training to gain a competitive
advantage.

Karunasree and Sudhakar (2018) studied Customer Relationship Management (CRM) practices and strategies in ICICI and HDFC
banks in Hyderabad and Secunderabad, India. This study examined the perceptions of business and non-business customers
regarding CRM practices and strategies. Using a descriptive research design, they surveyed 945 customers with a questionnaire.
The analysis covered five CRM practices: Customer Acquisition, Customer Response, Customer Knowledge, Customer
Information System, and Customer Value Evaluation, along with four CRM strategies: Customer Focus, Knowledge Management,
CRM Organization, and Technology-based CRM. The findings show significant differences between non-business and business
customers' perceptions. The study recommends that banks develop differentiated CRM approaches for different customer segments,
considering demographic profiles, and establish departments to monitor CRM effectiveness.

Veni and Gayathri (2016) studied customer relationship management (CRM) practices in State Bank of India (SBI) branches in
Virudhunagar. This study examined customer demographics, CRM policy awareness, practices in Tamil Nadu branches, and the
role of electronic CRM in satisfaction. Data were collected from 100 SBI customers through questionnaires and were analyzed
using statistical tools. The results showed that demographics did not affect CRM awareness, and customers approved most CRM
practices, with physical services having the strongest influence. E-CRM services, especially Internet banking and ATMs, enhance
customer satisfaction. The study found SBI's CRM practices to be satisfactory, highlighting the importance of customer-oriented
relationships in the banking sector.

Chaudhari (2020) examined Customer Relationship Management (CRM) in Indian banking. This study presents CRM as vital in
contemporary banking, highlighting its importance in the competitive global context. This study investigates CRM's significance,
technology's role, and CRM processes in Indian banking using secondary data from newspapers, books, journals, and other sources.
The findings show that CRM helps banks identify profitable customers by integrating technology with human resources to acquire
and retain them. CRM enables banks to build relationships and maximize profits while providing customers access to new
technologies and improved services. At the national level, CRM advances the banking sector, aids global competition, and enhances
quality. The study concludes that CRM is essential in the era of globalization, emphasizing the importance of technology in Indian
banking for achieving objectives cost-effectively.

Research Gap:

Numerous studies have examined various aspects of customer relationship management (CRM) practices and their effects on
customer awareness, perception, and satisfaction in the Indian banking sector. However, there is a notable lack of substantial
research specifically focused on Darjeeling, West Bengal. This study addresses this gap by investigating CRM practices and
electronic CRM (e-CRM) strategies at SBI Bank and their influence on customer satisfaction, perception, and awareness in
Darjeeling. The present study endeavors to explore this previously unexamined area.

Significance of the Study:

The study of Customer Relationship Management (CRM) at the State Bank of India (SBI) in Darjeeling, West Bengal, is important.
This affects both academic research and real banking operations. This research helps us understand customer satisfaction and
engagement. By knowing CRM practices well, banks can improve their strategies to better meet customer needs. As banking
changes and customer expectations grow, this study can help SBI improve customer satisfaction and loyalty, which are key to
retaining and attracting customers (Parameswar et al., 2016; Tiwary et al., 2015). In addition, CRM's impact on financial
performance is important. By checking how well CRM works, banks can link customer satisfaction to financial results, aligning
CRM efforts with financial goals. Good CRM systems can make operations more efficient and reduce costs, thereby boosting profits
(Mbama & Ezepue, 2018). In Darjeeling, understanding the local banking needs is crucial. The area's unique social and cultural
environment requires CRM practices to effectively serve different customer groups. This study offers a local view that can help SBI
adapt its CRM strategies to fit the region, possibly using digital banking for easier access (Rai & Das, 2024). Finally, this study

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adds to the academic literature by providing data and insights useful for other researchers and banks looking to improve CRM
practices in India and worldwide. This can lead to more research and innovation in banking CRM, promoting a customer-focused
approach in the industry (Tiwary et al., 2015).

Objectives of the Study:

This study has been initiated with the following objectives: (i) to comprehend the demographic characteristics of customers utilizing
SBI services, (ii) to examine customer awareness concerning SBI's customer relationship management policies, (iii) to evaluate
perceptions of customer relationship management practices across various SBI branches in Darjeeling, and (iv) to investigate the
impact of e-CRM strategies on achieving customer satisfaction.

III. Research Methodology:

This study is both analytical and empirical, utilizing a combination of primary and secondary data. Primary data were exclusively
gathered through a structured questionnaire administered during field surveys. This questionnaire employed a three-point rating
scale, as informed by prior relevant studies. Additionally, the research incorporates secondary data sourced from related research
journals, articles, papers, academic publications, and online sources. The study's sample comprised customers of SBI Bank in
Darjeeling, selected using convenience sampling from different SBI branches in the area. A total of 75 SBI customers provided
complete and positive responses to the questionnaires. The survey was conducted from July to August of 2025. The study
investigates several key variables and attributes related to customer relationship management, specifically: (i) customer awareness
of CRM policies at SBI (including customer recognition, quick response, retention strategy, technology-based service, personnel
assistance, cost transparency, grievance redressal, "May I help you" service, information on new services, ATM service, and online
banking service); (ii) customers’ perceptions of SBI's CRM practices (such as employee courtesy, bank ambiance, bank
environment, bank facilities, customer-friendly products, service promptness, ability to assist customers, knowledge of customer
redressal, customer familiarity, ATM locations, working hours, and service execution); (iii) e-CRM strategies at SBI (including
Internet banking, ATMs, mobile banking, emails, smart cards, fund transfers, and e-cheques); and (iv) customer service (covering
physical service, service reliability, service openness, service delivery, understanding of needs, and personal welfare). The reliability
and consistency of the questionnaire were assessed using Cronbach's alpha test, which yielded a satisfactory score of 0.974. Primary
data analysis involved frequency tables, simple percentages, and statistical tools such as ANOVA, correlation analysis, multiple
regression analysis, and one-sample t-tests. The statistical software SPSS-26 was used to analyse the primary data and derive
relevant conclusions from this research.

Hypothesis:

Five sets of hypotheses have been framed to achieve the research objectives. They are as follows:

H1: There is no difference between the demographic profile of customers and customer awareness of CRM policies in SBI.

H2: There is no correlation between awareness of CRM policies in SBI and satisfaction with CRM practices in SBI.

H3: There is no correlation between perception about the CRM practices in SBI and satisfaction with CRM Practices in SBI.

H4: There is no influence of customer service on customers' perception of CRM practices in SBI.

H5: There is no significant impact of the E-CRM strategies of SBI on customer satisfaction.

Analysis and Discussion:

The primary data collected from the field survey have been analyzed and are discussed in the subsequent section. This portion of
the study is organized into two subsections: the demographic profiles of the respondents and the examination of various hypotheses
using statistical methods such as ANOVA, correlation analysis, multiple regression analysis, and one-sample t-test. The analyses
are presented below.

Demographic Profile of the Respondents:

Table-1

Demographic Characteristics Attribute Frequency Percent

Gender Male 54 72

Female 21 28

Age 18-25Yrs 16 21.3

26-40Yrs 24 32

41-55Yrs 28 37.3

Above 55 Yrs 7 9.3

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Education Secondary 8 10.7

HS 16 21.3

UG 16 21.3

PG 28 37.3

Professional 7 9.3

Occupation Private Job 24 32

Govt. Job 23 30.7

Self-Employed 21 28

Student 7 9.3

(Source: Primary Data)

Observation: Gender Distribution: The sample demonstrated a significant male predominance, with males constituting 72% of the
cohort and females representing 28%. This resulted in a sex ratio of approximately 2.6:1 (male: female) within the sample. Age
Distribution: The sample was predominantly composed of middle-aged adults. The largest age cohort was 41-55 years, accounting
for 37.3%, followed closely by the 26-40 years group (32%). Collectively, these two groups comprised nearly 70% of the total
sample. Younger adults, aged 18-25 years, constitute 21.3%, whereas seniors aged above 55 years represent the smallest segment
at 9.3%. Education Level: The group is characterized by a high level of educational attainment. The largest proportion holds a
postgraduate (PG) degree, accounting for 37.3%. Individuals with an Undergraduate (UG) degree and those with a Higher
Secondary (HS) qualification each constitute 21.3%. Those possessing a professional degree and individuals with only secondary
education represent the smallest groups, at 9.3% and 10.7%, respectively. Occupation: Employment is fairly evenly distributed
across the private sector, government, and self-employment sectors. Private sector employees form the largest group at 32%,
followed closely by government employees at 30.7%. Self-employed individuals constituted 28% of the sample. Students represent
the smallest occupational group at 9.3%, which corresponds with the age data, indicating that the 18-25 years cohort comprises
21.3%, suggesting that not all young adults in the sample are students.

Hypothesis Testing:

10.2.1 ANOVA: Analysis of Variance (ANOVA) is a statistical method used to evaluate the means of two or more independent
groups to determine whether significant differences exist among them. This technique examines the variability within each group
and compares it with the variability between groups. When the variation between groups substantially exceeds the variation within
groups, it suggests that at least one group's mean is significantly different from the others. In this study, ANOVA was applied to
assess whether there was any difference between the demographic profile of customers and their awareness of Customer
Relationship Management (CRM) policies at the State Bank of India (SBI).

Hypothesis-1

H0: There is no difference between the demographic profile of customers and customer awareness of CRM policies in SBI.

H1: There is a difference between the demographic profile of customers and customer awareness of CRM policies in SBI.

Table-2

ANOVA

Sum of
Squares

df Mean
Square

F Sig.

Age Between Groups 36.27 2 18.135 48.874 0.000

Within Groups 26.716 72 0.371

Total 62.987 74

Educational Qualification Between Groups 57.899 2 28.95 46.56 0.000

Within Groups 44.767 72 0.622

Total 102.667 74

Occupation Between Groups 40.556 2 20.278 47.355 0.000

Within Groups 30.831 72 0.428

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Total 71.387 74

Gender Between Groups 7.879 2 3.939 39.168 0.000

Within Groups 7.241 72 0.101

Total 15.12 74

(Source: Compiled by author)

Interpretation: From the above table, it is seen that the P value of the test at the 5% level of significance is 0.000, which is less
than 0.05 for all the demographic variables, like gender, age, education, and occupation, in relation to customer awareness of CRM
policies in SBI by the respondents in the study area. So, the null hypothesis is rejected and the alternative hypothesis is accepted.
Therefore, it can be concluded that there is a significant difference between the demographic profile of customers and their
awareness of SBI’s CRM policies.

Correlation Test: Correlation denotes the degree to which two variables are related. When variations in the magnitude of one
variable are typically accompanied by variations in the magnitude of another variable, the variables are considered correlated. If an
increase in one variable is generally associated with an increase in another, they are positively correlated. Conversely, if an increase
in one variable is typically linked to a decrease in another variable, they are negatively correlated. When the value of one variable
remains unaffected by changes in another variable, the variables are deemed uncorrelated. In this study, two correlations were
examined: (i) the correlation between Awareness of CRM Policies in SBI and Satisfaction with CRM Practices in SBI, and (ii) the
correlation between Perception of CRM Practices in SBI and Satisfaction with CRM Practices in SBI.

Hypothesis-2

H0: There is no correlation between awareness of CRM policies in SBI and satisfaction with CRM practices in SBI.

H1: There is a correlation between awareness of CRM policies in SBI and satisfaction with CRM practices in SBI.

Table-3

Correlations

Customer Awareness in
CRM Policies in SBI

Customer Satisfaction

Customer Awareness in
CRM Policies in SBI

Pearson Correlation 1 0.675

Sig. (2-tailed) 0.000

N 75 75

Customer Satisfaction Pearson Correlation 0.675 1

Sig. (2-tailed) 0.000

N 75 75

(Source: Compiled by author)

Interpretation: In the above table, the bivariate correlation test has been applied to test the correlation between Awareness of CRM
Policies in SBI and Satisfaction with CRM Practices in SBI. In the above correlation matrix, Pearson’s correlation coefficient is
0.675, and the p-value for a two-tailed test is 0.000, which is less than 0.05 at the 5% level of significance. Hence, it can be
concluded that there is a positive correlation between Awareness of CRM Policies in SBI and Satisfaction with CRM Practices in
SBI.

Hypothesis-3

H0: There is no correlation between perception about the CRM practices in SBI and satisfaction with CRM practices in SBI.

H1: There is a correlation between perception about the CRM practices in SBI and satisfaction with CRM practices in SBI.

Table-4

Correlations

Customers' Perception of
CRM Practices in SBI

Customer Satisfaction

Pearson Correlation 1 0.89

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Customers' Perception of
CRM Practices in SBI

Sig. (2-tailed) 0.000

N 75 75

Customer Satisfaction Pearson Correlation 0.89 1

Sig. (2-tailed) 0.000

N 75 75

(Source: Compiled by author)

Interpretation: In the above table, the bivariate correlation test has been applied to test the correlation between Perception about
the CRM Practices in SBI and Satisfaction with CRM Practices in SBI. In the above correlation matrix, Pearson’s correlation
coefficient is 0.89, and the p-value for a two-tailed test is 0.000, which is less than 0.05 at the 5% level of significance. Hence, it
can be concluded that there is a positive correlation between the Perception of the CRM Practices in SBI and Satisfaction with
CRM Practices in SBI.

Multiple Regression Analysis: A multiple regression analysis was conducted to assess the relationship between a single dependent
variable and multiple independent variables. This analysis typically reveals the average relationship between two variables, enabling
the estimation or prediction of the unknown values of one variable based on the known values of the other. A multiple regression
model has been developed, as illustrated below;

Regression model-1: Y = a+ bx1 + cx2 + dx3 +ex4+fx5+E --------------------(1)

Where,

Y is the dependent variable, i.e., Customers' Perception of CRM Practices in SBI

‘a’ is a Constant

x1 is the independent variable, i.e., Need Understanding

x2 is the independent variable, i.e., Openness in Service

x3 is the independent variable, i.e., Reliability in Service

x4 is the independent variable, i.e., Physical Service

x5 is the independent variable, i.e., Service Delivery

b, c, d, e, f are the regression coefficients and

E is the Residual (error)

Hypothesis-4

H0: There is no influence of customer service on customers' perception of CRM practices in SBI.

H1: There is an influence of customer service on customers' perception of CRM practices in SBI.

Table-5

Model Summary

Model R R Square Adjusted R Square Std. Error of the
Estimate

1 0.953 0.908 0.902 0.20744

Predictors: (Constant), Need Understanding, Openness in Service, Reliability in Service, Physical Service, Service Delivery

Dependent Variable: Customers' Perception of CRM Practices in SBI

(Source: Compiled by author)

Table-6

ANOVA

Model Sum of
Squares

df Mean Square F Sig.

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1 Regression 29.378 5 5.876 136.543 0.000

Residual 2.969 69 0.043

Total 32.347 74

(Source: Compiled by author)

Interpretation: In this model, the p-value of the beta coefficient is 0.000, which is significant at 5% level of significance. So, the
null hypothesis is rejected and the alternative hypothesis is accepted. Hence, it can be concluded that customer service influences
customers' perception of CRM practices in SBI. Here, the value of F is 136.543, which is also significant at the 5% level of
significance. The R-squared value is 0.908, which indicates that the model is a good fit and that there is a high correlation between
customer service and customers' perception of CRM practices in SBI. A positive sign of the regression coefficient indicates a direct
or positive relationship between CRM practice in SBI and customer service. The adjusted R-squared value is 0.902, which implies
that customer service can explain approximately 90% of the customers' perception of CRM practices in SBI. Finally, it can be
concluded that various customer services positively impact customers' perception of CRM practices in SBI.

One-Sample t-test: The one-sample t-test is a statistical method employed to ascertain whether the mean of a sample significantly
deviates from a known or hypothesized population mean. Unlike tests that compare two distinct groups, this technique evaluates
the mean of a single sample against a specified value. In this context, a one-sample t-test was used to determine whether E-CRM
strategies significantly impact customer satisfaction.

Hypothesis-5

H0: There is no significant impact of the E-CRM strategies of SBI on customer satisfaction.

H1: There is a significant impact of the E-CRM strategies of SBI on customer satisfaction.

Table-7

One-Sample Test

Test Value = 0

t df Sig. (2-
tailed)

Mean
Difference

95% Confidence Interval of
the Difference

Lower Upper

Internet Banking 19.117 74 0.000 1.46667 1.3138 1.6195

ATMs 19.441 74 0.000 1.49333 1.3403 1.6464

Mobile Banking 19.117 74 0.000 1.46667 1.3138 1.6195

Emails 19.117 74 0.000 1.46667 1.3138 1.6195

Smart Card 18.216 74 0.000 1.37333 1.2231 1.5236

Fund Transfer 20.595 74 0.000 1.77333 1.6018 1.9449

E Cheques 22.574 74 0.000 1.98667 1.8113 2.162

(Source: Compiled by author)

Interpretation: From the above table, it is found that the P value of the test at the 5% level of significance is 0.000, which is less
than 0.05 for all the E-CRM strategies of SBI, as assumed by the respondents in the study area. So, the null hypothesis is rejected
and the alternative hypothesis is accepted. Therefore, it can be concluded that the E-CRM strategies of SBI have a significant impact
on customer satisfaction.

IV. Findings of the Study:

Based on the analysis and discussion presented, the key findings of the study on Customer Relationship Management (CRM)
practices at the State Bank of India (SBI) branch in Darjeeling, West Bengal, are as follows:

There is a significant difference between customers' demographic profiles and their awareness of CRM policies at SBI. Factors
such as gender, age, education, and occupation influence awareness levels.

There is a positive correlation (0.675) between customers' awareness of CRM policies and their satisfaction with SBI’s CRM
practices.

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There is a strong positive correlation (0.89) between customers' perceptions of CRM practices and their satisfaction with those
practices at SBI.

Customer service significantly influences customers' perceptions of CRM practices at SBI. The regression model showed that
customer service could explain approximately 90% of the variation in perceptions of CRM practices.

The E-CRM strategies of SBI have a significant impact on customer satisfaction, as evidenced by the one-sample t-test results.

The demographic profile of respondents showed a predominance of male customers (72%), with the largest age group being 41-55
years (37.3%). Most respondents had postgraduate degrees (37.3%) and were employed in the private sector (32%).

The study found high levels of customer awareness and positive perceptions of SBI's CRM policies and practices in Darjeeling.

Both traditional customer service aspects and e-CRM strategies were found to be important factors in shaping customer satisfaction
and perceptions of CRM at SBI.

These findings highlight the importance of tailored CRM strategies that account for demographic factors, as well as the need for
banks to focus on both in-person service quality and electronic banking services to enhance customer relationships and satisfaction.

V. Conclusion:

This study provides significant insights into the effectiveness of Customer Relationship Management (CRM) practices at the State
Bank of India (SBI) in Darjeeling. The findings indicate that CRM strategies substantially impact customer satisfaction and
perception. Demographic factors are crucial in shaping customer awareness of CRM policies, underscoring the need for customized
approaches tailored to distinct customer segments. The strong positive correlations between CRM awareness, perceptions, and
satisfaction highlight the importance of effective communication and the implementation of CRM practices. The notable influence
of customer service on CRM perceptions emphasizes the necessity of a sustained focus on service quality and delivery. E-CRM
strategies have emerged as critical components in enhancing customer satisfaction, reflecting the growing importance of digital
banking services. This trend aligns with the broader movement towards technological adoption within the banking sector. The
findings of this study have important implications for SBI and potentially for other banks operating in similar contexts. To enhance
customer relationships and satisfaction, banks should develop targeted CRM strategies that account for demographic variations,
improve customer awareness of CRM policies through effective communication, continuously enhance customer service quality,
and invest in and promote e-CRM services. Future research could investigate the long-term impact of CRM practices on customer
loyalty and bank performance and explore the specific needs of different customer segments in Darjeeling. In conclusion, this study
contributes to the understanding of CRM practices in the banking sector, particularly within the context of Darjeeling, and provides
actionable insights for improving customer relationships and satisfaction in the banking industry.

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