Analysis of Survey CHAPTER -...
Transcript of Analysis of Survey CHAPTER -...
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CHAPTER 6
Analysis of Survey
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6.1 - Introduction 6.2 - Analysis of Data 6.3 - Reliability Analysis 6.4 - Factor Analysis 6.5 - Testing of Hypothesis 6.6 - Descriptive Statistical Analysis
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6.1 - INTRODUCTION
The present research work is study on the “Review of Customer Relationship
Management in Banking Sector”. The collected data has been tabulated in both the
forms like Simple Tabulation with one variable and Cross Tabulation having two
variables. The tabulated data has been analysed by using SPSS 17.0 consisting of the
following statistical techniques.
� Univariate Analysis: It has involved only one variable for analysis and the
methods related to this analysis include Simple Percentage method & Chi-
Square Test.
� Bivariate Analysis: It has involved only two variables and the methods related
to this analysis include Pearson Correlation and Chi-Square Test of two
variables.
� Multivariate Analysis: It has involved more than two variable at a time. It has
explained the associations among more than two variables simultaneously.
The methods include Factor Analysis.
� Hypothetical Analysis: The hypothesis which is formulated has been tested by
using Chi-Square Test & Kolmogorov Smirnov Test.
6.2 - ANALYSIS OF DATA
Facts, information, systematically collected and formally presented for the
purpose of drawing inferences. Statistical information collected Compiled and
presented for the purpose of establishing appropriate relationships between variables.
Both the primary and secondary data has been used for the purpose of analysis.
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The following table is presented to understand the distribution of the Customers
according to their age.
Age Frequency Percentage (%)
16-26 202 20.2
27-37 401 40.1
38-48 237 23.7
49 & above 160 16.0
Total 1000 100.0
Table 6.1: Age Category of Customers (Source: Compiled from the questionnaire)
Graph 6.1: Age Category of Customers
Inference : Table 6.1 and Graph 6.1 shows that, out of 1000 Banking customers
surveyed, 40.1% of customers are in the age group 27-37, 23.7% of the customers are
in the age group 27-48, 20.2% of the customers are 16-26 and 16.0% of customers are
in 49 & above. It is apparent that majority of the customers belong to the age group
27-37 and 38-48.
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The following table is presented to understand the distribution of the respondents
according to their Age category of selected four Banks.
Age State
Bank of India
Bank of Maha.
ICICI Bank
HDFC Bank Total
16-26 15 57 60 70 202
27-37 126 87 97 91 401
38-48 57 35 77 68 237
49 & above 52 71 16 21 160
Total 250 250 250 250 1000
Mean 2.584 2.480 2.1960 2.1600 2.3550
Std. Deviation 0.88435 1.13080 0.87673 0.93052 0.97669
Table 6.2: Age Category of Customers of Selected Banks
(Source: Compiled from the questionnaire)
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Graph 6.2: Age Category of Customers of Selected Banks
Inference : Table 6.2 and Graph 6.2 shows that, 250 customers of each bank selected
for study, 401 customers are in the age group 27-37 out of which maximum 126
customers of State Bank of India and minimum 87 customers from Bank of
Maharashtra, 237 customers are in the age group 27-48 out of which 77 customers
from ICICI Bank, 202 customers are 16-26 age group out of which maximum 70
customers from HDFC Bank and 160 customers are in 49 & above out of which
maximum 71 customers from Bank of Maharashtra. It is apparent that majority of the
customers belong to the age group 27-37 and 38-48.
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The following table is presented to understand the distribution of the respondents
according to their level of education.
Education Frequency Percentage (%)
PG 286 28.6
GRADUATE 491 49.1
H.S.C. 161 16.1
S.S.C. 62 6.2
Total 1000 100.0
Table 6.3: Customers Education Level (Source: Compiled from the questionnaire)
Graph 6.3: Customers Education Level
Inference : Table 6.3 and Graph 6.3 shows that, out of 1000 Customers, 28.6% of
customers are having their level of education as Post Graduate. 49.1% of customers
having Graduate Level education, 16.1% of customers are educated upto H.S.C. and
6.2% of customers having S.S.C. level education. It is clear that Graduate and Post
Graduate is the level of education for most of the customers.
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The following table is presented to understand the distribution of the respondents
according to their Education Level category of selected four Banks.
Education State
Bank of India
Bank of Maha.
ICICI Bank
HDFC Bank Total
PG 54 75 69 88 286
GRADUATE 112 73 161 145 491
H.S.C. 62 81 12 6 161
S.S.C. 22 21 8 11 62
Total 250 250 250 250 1000
Mean 2.2080 2.1920 1.8360 1.7600 1.9990
Std. Deviation 0.88082 0.96273 0.65331 0.70455 0.83408
Table 6.4: Customers Education Level of Selected Banks
(Source: Compiled from the questionnaire)
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Graph 6.4: Customers Education Level of Selected Banks
Inference : Table 6.4 and Graph 6.4 shows that, 250 customers of each bank selected
for study, 286 customers are having their level of education as Post Graduate out of
which 88 customers from HDFC Bank. 491 customers having Graduate Level
education out of which maximum 161 customers from ICICI Bank and minimum 73
customers from Bank of Maharashtra, 161 customers are educated upto H.S.C. out
which maximum 81 from Bank of Maharashtra and 62 customers having S.S.C. level
education out of which maximum 22 customers from State Bank of India. It is clear
that Graduate and Post Graduate is the level of education for most of the customers.
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The following table is presented to understand the distribution of the respondents
according to their income category.
Income Frequency Percentage (%)
High 275 27.5
Medium 588 58.8
Low 137 13.7
Total 1000 100.0
Table 6.5: Income Category of Customers (Source: Compiled from the questionnaire)
Graph 6.5: Income Category of Customers
Inference : Table 6.5 and Graph 6.5 shows that, out of 1000 customers surveyed,
58.8% of customers are having medium income, 13.7% of the customers are having
low income and 27.5% of the customers are having high income, it shows that most of
the customers are belonging to the middle class and it can be a measure for
determining their socio-economic status.
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The following table is presented to understand the distribution of the respondents
according to their Income Level customers of selected four Banks.
Income State
Bank of India
Bank of Maha.
ICICI Bank
HDFC Bank
Total
High 45 48 88 94 275
Medium 157 146 144 141 588
Low 48 56 18 15 137
Total 250 250 250 250 1000
Mean 2.0120 2.0320 1.7200 1.6840 1.8620
Std. Deviation 0.61102 0.64548 0.58906 0.58906 0.62718
Table 6.6: Income Category of Customers of Selected Banks
(Source: Compiled from the questionnaire)
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Graph 6.6: Income Category of Customers of Selected Banks
Inference : Table 6.6 and Graph 6.6 shows that, 588 customers are having medium
income out of which maximum 157 customers from State Bank of India and
minimum 141 customers from HDFC Bank, 137 customers are having low income
out of which maximum 56 customers from Bank of Maharashtra and 275 customers
are having high income out of which maximum 94 customers from HDFC Bank, it
shows that most of the customers are belonging to the middle class and it can be a
measure for determining their socio-economic status.
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The following table is presented to understand the distribution of the respondents
according to their Experience of doing Banking Transaction.
Experiences Frequency Percentage (%)
Below 5 Years 248 24.8
5 – 15 Years 449 44.9
Above 15 Years 303 30.3
Total 1000 100.0
Table 6.7: Banking Experiences of Customers (Source: Compiled from the questionnaire)
Graph 6.7: Banking Experiences of Customers
Inference : Table 6.7 and Graph 6.7 shows that, out of 1000 customers revealed that,
44.9% of customers are having 5 to 15 years experiences of doing Banking
transaction, 30.3% of the customers are having above 15 years experiences and 24.8%
of the customers are having below 5 years experiences of doing Banking
Transactions.
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The following table is presented to understand the distribution of the respondents
according to their Experience of doing Banking Transaction of Different Banks.
Experiences State
Bank of India
Bank of Maha.
ICICI Bank
HDFC Bank
Total
Below 5 Years 35 52 79 82 248
5 – 15 Years 101 77 135 136 449
Above 15 Years 114 121 36 32 303
Total 250 250 250 250 1000
Mean 2.3160 2.2760 1.8280 1.8000 2.0550
Std. Deviation 0.70579 0.78632 0.65738 0.64627 0.74062
Table 6.8: Banking Experiences of Customers of Selected Banks
(Source: Compiled from the questionnaire)
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Graph 6.8: Banking Experiences of Customers of Selected Banks
Inference : Table 6.8 and Graph 6.8 shows that, 250 customers of each bank selected
for study, 449 customers are having 5 to 15 years experiences of doing Banking
transaction out of which maximum customers from HDFC Bank, 303 customers are
having above 15 years experiences out of which 136 customers are from HDFC Bank
and 248 customers are having below 5 years experiences of doing Banking
Transactions out of which maximum 121 customers from Bank of Maharashtra.
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The following table is presented to understand the distribution of the respondents
according to their preference giving while cash withdrawal.
Preferences Frequency Percentage (%)
ATM 522 522
Bank Withdrawal 221 22.1
Both 257 25.7
Total 1000 100.0
Table 6.9: Cash Withdrawal Preferences of Customers (Source: Compiled from the questionnaire)
Graph 6.9: Cash Withdrawal Preferences of Customers
Inference : Table 6.9 and Graph 6.9 shows that, out of 1000 customers revealed that,
52.2% of customers are having cash withdrawal preferences towards A.T.M. cash
withdrawal, while 22.1% of the customers are preferences to Bank Cash Withdrawal
and 25.7% of the customers are having both the side in cash withdrawal situation.
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The following table is presented to understand the distribution of the customers
according to their attitude about Requirement of CRM practices in Banking Sector.
Attitude Frequency Percentage (%)
Highly Favorable 255 25.5
Favorable 479 47.9
Neutral 152 15.2
Unfavorable 75 7.5
Highly Unfavorable 39 3.9
Total 1000 100.0
Mean 2.1640
Std. Deviation 1.01594
Table 6.10: Attitude of Customers towards CRM
(Source: Compiled from the questionnaire)
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Graph 6.10: Attitude of Customers towards CRM
Inference : Table 6.10 and Graph 6.10 shows that, out of 1000 customers surveyed,
479 customers are having highly favorable attitude towards Customer Relationship
Management, 255 customers favorable, 152 Neutral, 75 are unfavorable and 39 are
Highly Unfavorable. The study reflects the positive attitude of the customers towards
requirement of CRM in Banking Sector.
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The following table is presented to understand the level of awareness of the customers
towards Customer Relationship Management.
Attitude Frequency Percentage (%)
Very Low 38 3.8
Low 106 10.6
Neutral 168 16.8
High 461 46.1
Very High 227 22.7
Total 1000 100.0
Mean 3.7330
Std. Deviation 1.04441
Table 6.11: Awareness Level of Customers towards
Customer Relationship Management
(Source: Compiled from the questionnaire)
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Graph 6.11: Awareness Level of Customers towards
Customer Relationship Management
Inference : Table 6.11 and Graph 6.11 shows that, out of 1000 customers surveyed,
46.1% of customers are having high awareness level towards CRM, 22.7% of
customers are having very high awareness level, 16.8% of customers are Neutral,
10.6% of customers are having low awareness level and 3.8% of customers are very
low awareness level. The study clearly indicates that customers are having high
awareness level towards CRM and they understand CRM means alternate marketing
approaches of bank.
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The following table is presented to understand the distribution of the respondents on
the opinion about Bank should enhance customer loyalty.
Experiences Frequency Percentage (%)
Yes 787 78.7
No 213 21.3
Total 1000 100.0
Table 6.12: Opinion about Bank should enhance customer loyalty (Source: Compiled from the questionnaire)
Graph 6.12: Opinion about Bank should enhance customer loyalty
Inference : Table 6.12 and Graph 6.12 shows that, out of 1000 customers surveyed,
78.7% of customers are considering bank should enhance customer loyalty and 21.3%
of the customers are not agree that there is no need of enhance customer loyalty by
bank. It is clearly indicates that there is need of enhance customer loyalty which
permit them to start CRM practices, that can easily enhance customer loyalty.
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The following table is presented to understand the distribution of the customers
according to their agreement about satisfy with service quality offered by bank.
Level of Agreement Frequency Percentage (%)
Strongly Disagree 13 1.2
Disagree 35 3.5
Undecided 81 8.1
Agree 719 71.9
Strongly Agree 152 15.2
Total 1000 100.0
Mean 3.9620
Std. Deviation 0.69932
Table 6.13: Opinion of Customers towards satisfy with
service quality offered by bank
(Source: Compiled from the questionnaire)
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Graph 6.13: Opinion of Customers towards satisfy with
service quality offered by bank
Inference : Table 6.13 and Graph 6.13 shows that, out of 1000 customers surveyed,
15.2% of customers are strongly agree that service quality offered by bank. 71.9% of
customers agree, 8.1% of customers neither agree nor disagree, 3.5% of customers
disagree and 1.3% of customers strongly disagree. It is clear from the study that the
majority of the customers agree that good service quality offered by bank and they are
satisfied with that.
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The following table is presented to understand the distribution of the customers
according to their agreement about Service influences the Customers to continue with
their Existing Bank.
Extent to Influences Frequency Percentage (%)
Very Large Extent 188 18.8
Large Extent 502 50.2
Medium Extent 142 14.2
Some Extent 102 10.2
Not at All 66 6.6
Total 1000 100.0
Mean 2.3560
Std. Deviation 1.09839
Table 6.14: Opinion of Customers towards Service influences
the Customers to continue with their Existing Bank
(Source: Compiled from the questionnaire)
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Graph 6.14: Opinion of Customers towards Service influences
the Customers to continue with their Existing Bank
Inference : Table 6.14 and Graph 6.14 reveals that, out of 1000 customers surveyed,
18.8% of customers the opinion that service influences to continue with their Existing
Bank to a very large extent while 50.2% of consumes opinioned that it influences to a
large extent. 14.2% of the customers felt that service influences to a medium extent.
10.2% of customers are said that some extent and 6.6% of customers are opinioned
that it does not influence at all. The study shows that Service Quality influences to a
large extent towards Continuity with existing bank.
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The following table is presented to understand the distribution of the respondents on
the opinion about improving services by trained staff.
Opinion Frequency Percentage (%)
Yes 721 72.1
No 279 27.9
Total 1000 100.0
Table 6.15: Opinion about improving services by trained staff (Source: Compiled from the questionnaire)
Graph 6.15: Opinion about improving services by trained staff
Inference : Table 6.15 and Graph 6.15 shows that, out of 1000 customers surveyed,
72.1% of customers are agree that service should be improved by trained staff and
27.9% of the customers are not agree about improving service by trained staff. It is
clearly indicates that there is bank should appoint trained staff and improve service
the benefit of the customers and society.
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The following table is presented to understand the distribution of the respondents on
the opinion about improving services by trained staff for their bank.
Opinion State
Bank of India
Bank of Maha.
ICICI Bank
HDFC Bank
Total
Yes 151 147 208 215 721
No 99 103 42 35 279
Total 250 250 250 250 1000
Mean 1.3960 1.4120 1.1680 1.1400 1.2790
Std. Deviation 0.49005 0.49318 0.37462 0.34768 0.44873
Table 6.16: Opinion about improving services by
trained staff of selected banks
(Source: Compiled from the questionnaire)
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Graph 6.16: Opinion about improving services by
trained staff of selected banks
Inference : Table 6.16 and Graph 6.16 shows that, out of 1000 customers surveyed,
721 customers are agree that service should be improved by trained staff out of which
151 customers of State Bank of India suggested that service should be improved and
279 customers are not agree about improving service by trained staff out of which
minimum 35 customers from HDFC Bank. It is clearly indicates that there is State
Bank of India and Bank of Maharashtra should appoint trained staff and improve
service the benefit of the customers and society.
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The following table is presented to understand the distribution of the customers
according to their opinion towards benefits of CRM in Banking Sector.
Productive Frequency Percentage (%)
Highly Productive 242 24.2
Productive 502 50.2
Difficult to say 101 10.1
Unproductive 68 6.8
Highly Unproductive 87 8.7
Total 1000 100.0
Mean 2.2560
Std. Deviation 1.15490
Table 6.17: Opinion of Customers towards productive benefits
of CRM in Banking Sector
(Source: Compiled from the questionnaire)
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Graph 6.17: Opinion of Customers towards productive benefits
of CRM in Banking Sector
Inference : Table 6.17 and Graph 6.17 shows that, out of 1000 customers surveyed,
50.2% of customers the opinion that CRM provides productive benefits while 24.2%
of consumes opinioned that it is high productive. 10.1% of the customers are
undecided, 6.8% of the customers termed as unproductive. 8.7% of customers termed
as highly unproductive. The study clearly indicates that the most of the customers are
considering that productive benefit of CRM in Banking Sector even of different
selected four banks customers also agree the same.
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The following table is presented to understand the distribution of the customers
according to their satisfaction level regarding the performance and services of the
banks.
Satisfaction Level Frequency Percentage (%)
Very Poor 48 4.8
Poor 88 8.8
Difficult to say 138 13.8
Good 588 58.8
Excellent 138 13.8
Total 1000 100.0
Mean 3.6800
Std. Deviation 0.97906
Table 6.18: Satisfaction level customers regarding the
performance and services of the banks
(Source: Compiled from the questionnaire)
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Graph 6.18: Satisfaction level customers regarding the
performance and services of the bank
Inference : Table 6.18 and Graph 6.18 reveals that, out of 1000 customers surveyed,
58.8% of customers the opinion that satisfaction level of regarding performance and
services of banks is Good while 13.8% of consumes opinioned as Excellent. 13.8% of
the customers are undecided, 8.8% of the customers termed as poor. 4.8% of
customers termed as Very poor. Majority of customers are of the opinion that they
are satisfied with the existing level of performance and services of their banks.
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The following table is presented to understand the distribution of the respondents on
the opinion about CRM attract new customers.
Opinion Frequency Percentage (%)
Yes 801 80.1
No 199 19.9
Total 1000 100.0
Table 6.19: Opinion about CRM attract new customers (Source: Compiled from the questionnaire)
Graph 6.19: Opinion about CRM attract new customers
Inference : Table 6.19 and Graph 6.19 shows that, out of 1000 customers surveyed,
80.1% of customers are agree for CRM attract new customers and 19.9% of the
customers are not agree about CRM attract new customers. It is clearly indicates that
there is need of CRM in Banking Sector for attracting new customers and to the
benefit of customers and society.
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The following table is presented to understand the distribution of the respondents on
the opinion about CRM ensure basic and key facilities and services.
Opinion Frequency Percentage (%)
Yes 775 77.5
No 225 22.5
Total 1000 100.0
Table 6.20: Opinion about CRM ensure basic and key facilities and services (Source: Compiled from the questionnaire)
Graph 6.20: Opinion about CRM ensure basic and key facilities and services
Inference : Table 6.20 and Graph 6.20 shows that, out of 1000 customers surveyed,
77.5% of customers are agree for CRM ensure basic and key facilities and services,
22.5% of the customers are not agree. It is clearly indicates that there is CRM ensure
basic and key facilities and services and provides guidance to customers.
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The following table is presented to understand the distribution of the
respondents regarding factors that important to Retail Marketing
Important Factors Frequency Rank
CRM helps to build customer loyalty 392 VI
CRM attract new customers 410 V
CRM benefits banks performance & productivity 381 VII
CRM promotes customers awareness 472 I
CRM should be implemented in Banking Sector 466 II
CRM create all round friendly environment 420 IV
CRM help to Customers 459 III
Table 6.21: Factors that important to CRM in Banking Sector
(Source: Compiled from the questionnaire)
Note: Total is more than sample size due to multiple choices
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Graph 6.21: Factors that important to CRM in Banking Sector
Inference : Table 6.21 and Graph 6.21 reveals that CRM promotes customers
awareness, CRM should be implemented in Banking Sector and CRM help to
Customers have been emerged first three important factors that are necessary required
to CRM in Banking Sector. Customers also responded positive towards it can used for
CRM create all round friendly environment, CRM attract new customers and CRM
helps to build customer loyalty. The study reflects the positive attitude of the
customers towards CRM in Banking Sector.
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The following table is presented to understand the distribution of the customers
according to their agreement for Conveyance in about CRM practices of your Bank.
Conveyance Frequency Percentage (%)
Irritatingly bad 57 5.7
Not Satisfactory 98 9.8
Neutral 101 10.1
Fairly good 602 60.2
Very good 142 14.2
Total 1000 100.0
Mean 3.6740
Std. Deviation 1.02116
Table 6.22: Opinion of Customers towards
Conveyance in about CRM practices of your Bank
(Source: Compiled from the questionnaire)
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Graph 6.22: Opinion of Customers towards
Conveyance in about CRM practices of your Bank
Inference : Table 6.22 and Graph 6.22 reveals that, out of 1000 customers surveyed,
14.2% of customers feels Very Good conveyance about CRM practices of your bank
while 60.2% of consumes opinioned as Fairly good. 10.1% of the customers are
Neutral at their opinion, 9.8% of the customers termed as not satisfactory. 5.7% of
customers termed as Irritatingly Bad conveyance about CRM practices of your Bank.
It is clear from the study that majority of customers are of the opinion that they feel
fairly good and very good conveyance about CRM practices of your bank.
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The following table is presented to understand the distribution of the customers
according to their opinion about main Purpose of CRM in Banking Sector.
Factor Affecting Frequency Percentage (%)
Retention of existing customers 302 30.2
Enhances customers loyalty 332 33.2
Prevalent customers at levels 138 13.8
Attract new customers 228 22.8
Total 1000 100.0
Mean 2.2920
Std. Deviation 1.12606
Table 6.23: Opinion of Customers towards main
purpose of CRM in Banking Sector
(Source: Compiled from the questionnaire)
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.
Graph 6.23: Opinion of Customers towards main
purpose of CRM in Banking Sector
Inference : Table 6.23 and Graph 6.23 reveals that, out of 1000 customers surveyed,
30.2% of customers said that Retention of existing customers while 33.2% of
consumes told that Enhances customers loyalty. 13.8% of the customers are feels that
Prevalent customers at levels, 22.8% of the customers think that Attract new
customers. It is clear from the study that majority of customers are of the opinion that
they main purpose of CRM are Enhances customers loyalty and Retention of existing
customers.
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The following table is presented to understand the distribution of the
respondents regarding Problems of Banking Sector.
Problems of Retail Marketing Frequency Rank
Technology 417 III
Customer service 462 I
Implementation of new accounting standards 381 VII
Competition 432 II
Transparency and Disclosures 387 VI
Corporate Governance 402 IV
Know Your Customer Guideline 398 V
Table 6.24: Problems of Banking Sector
(Source: Compiled from the questionnaire)
Note: Total is more than sample size due to multiple choices
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Graph 6.24: Problems of Banking Sector
Inference : Table 6.24 and Graph 6.24 shows that, out of 1000 customers surveyed,
reveals that Customer service, Competition and Technology have been emerged first
three important problems that are faced by banking sector. Customers also responded
towards Corporate Governance, Know Your Customer Guideline and Transparency
and Disclosures. The study clearly indicates that the problems of banking sector
majorly related with CRM and customers are ready to take overcome from these
problems and require proper CRM practices in Bank.
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The following table is presented to understand the distribution of the respondents on
the opinion about big challenge for the bank is customer retention.
Opinion Frequency Percentage (%)
Yes 784 78.4
No 216 21.6
Total 1000 100.0
Table 6.25: Opinion about Big challenge for bank to retention of customer (Source: Compiled from the questionnaire)
Graph 6.25: Opinion about Big challenge for bank to retention of customer
Inference : Table 6.25 and Graph 6.25 shows that, out of 1000 customers surveyed,
78.4% of customers are agree for big challenge for bank to retention of customer,
21.6% of the customers are not agree. It is clearly indicates that there is customer
retention in bank are big challenge facing by banks though it is clear from the study
that CRM is necessary to overcome with this.
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The following table is presented to understand the distribution of the respondents on
the opinion about CRM creates customer awareness about different services offered
by bank.
Opinion Frequency Percentage (%)
Yes 798 79.8
No 202 20.2
Total 1000 100.0
Table 6.26: Opinion about CRM creates awareness about different services (Source: Compiled from the questionnaire)
Graph 6.26: Opinion about CRM creates awareness about different services
Inference : Table 6.26 and Graph 6.26 shows that, out of 1000 customers surveyed,
79.8% of customers are agree for CRM creates customer awareness about different
services offered by bank, 20.2% of the customers are not agree about that. It is clearly
indicates that there is CRM create awareness about different services offered by bank.
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The following table is presented to understand the distribution of the customers
according to their satisfaction level regarding prompt services in mean time of your
Banks.
Satisfaction Level Frequency Percentage (%)
Very Poor 52 5.2
Poor 81 8.1
Difficult to say 133 13.3
Good 592 59.2
Excellent 142 14.2
Total 1000 100.0
Mean 3.6910
Std. Deviation 0.98615
Table 6.27: Satisfaction level customers regarding the
prompt services in mean time of your Banks
Source: Compiled from the questionnaire)
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Graph 6.27: Satisfaction level customers regarding the
prompt services in mean time of your Banks
Inference : Table 6.27 and Graph 6.27 reveals that, out of 1000 customers surveyed,
59.2% of customers the opinion that satisfaction level of regarding prompt services in
mean time of their bank is Good while 14.2% of consumes opinioned as Excellent.
13.3% of the customers are undecided, 8.1% of the customers termed as poor. 5.2% of
customers termed as Very poor. Majority of customers are of the opinion that they
are satisfied with the existing level of service in mean time of their banks.
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6.3 - RELIABILITY ANALYSIS
Before conducting Factor analysis, the scale of reliability is used to find out
the internal consistency of the variables to be used in Factor Analysis. Reliability is
synonymous with repeatability. It is a measurement that yields consistent results over
time is said to be reliable. When a measurement is prone to random error, it lacks
reliability. The reliability of an instrument places an upper limit on its validity. A
measurement that lacks reliability will also lack validity. If the scale of reliability is
close to 1, then it can be concluded that variables are suitable for conducting factor
analysis. Reliability analysis is a popular and frequently used SPSS methods of
measuring the internal consistency of the variables.
Cronbach Alpha(α) is designed as a measure of internal consistency. Alpha is
measured on the same scale as a Pearson correlation coefficient which varies between
0 and 1. The closer the alpha to 1, the greater the internal consistency of items in the
instrument being assessed.
Cronbach’s Alpha N of Items
0.385 6
Table 6.28: Reliability Analysis
(Source: Compiled from the questionnaire)
Inference : Table 6.28 revealed that, the value of alpha is 0.385. It can conclude that
the variables are having high internal consistency and hence these variables are
considered to be suitable for conducting factor analysis.
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6.4 - FACTOR ANALYSIS
For the purpose of Factor Analysis, Hypothesis has to tested using Barlett’s
test of sphericity, from which the internal consistency and reliability among the
variables can be determine.
The following hypothesis is tested by using Barlett’s test of sphericity to determine
the internal consistency and reliability among the variables in the study.
Hypothesis 1
H0: There is no internal consistency and reliability among the variables selected in the
study for conducting factor analysis.
H1: There is an internal consistency and reliability among the variables selected in the
study for conducting factor analysis.
Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.511
Bartlett’s Test of Sphercity
Approx.Chi.Square Degree of freedom Significance Level
14.103 3
.003
Table 6.29: KMO and Bartlett’s Test of Hypothesis
(Source: Compiled from the questionnaire)
Inference : It can be seen from the Table 6.29 that, the significance level 0.003 is less
than the assumed value 0.05. So we reject H0. This means that factor analysis is valid.
The value of KMO coefficient should be always more than 0.05. The table value
shows that it is 0.511. So this implies that factor analysis for data reduction is very
effective.
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6.5 - TESTING OF HYPOTHESIS
The specific relationship between variables, which is skeptically formulated,
should be empirically demonstrated by the hypothesis are tested. This is necessitates a
systematic research and empirical investigation, which result in proving the
hypothesis and facilitate theorizing of the observation.
The following hypothesis is tested to know the strong association among the various
demographic factors like Age, Education and Income.
Hypothesis 2
H0: There is no strong association among various demographic factors like Education,
Age and Income with the Awareness Level of the customers towards CRM in
Banking Sector.
H1: There is a strong association among various demographic factors like Education,
Age, and Income with the Awareness Level of the customers towards CRM in
Banking Sector.
The above hypothesis consists of three variables Education, Age and Income. These
variables are tested individually and they are formulated as hypothesis 2a, hypothesis
2b and hypothesis 2c as follows.
Hypothesis 2a
H0: There is no significant association between Education and the Awareness Level
of the customers towards CRM.
H1: There is a strong association between Education and the Awareness Level of the
customers towards CRM.
- 116 -
The following table 6.30 consists of the cross tabulated values between the Education
of the customers and their Awareness Level.
Education
Awareness Level
Total Very Low
Low Neutral High Very High
PG 4 25 30 182 45 286 GRADUATE 6 26 75 227 157 491 H.S.C. 16 37 41 46 21 161 S.S.C. 12 18 22 6 4 62 Total 38 106 168 461 227 1000
Table 6.30: Education * Awareness Level (Cross Table)
(Source: Compiled from the questionnaire)
The following table 6.31 consists of the Chi-Square Test for the Education of the
customers and their Awareness Level values.
Description Value df Asymp.Sig. Person Chi-Square 239.227 12 .000 Likelihood Ratio 217.655 12 .000 Linear by Linear Association 99.949 1 .000 Number of Valid Cases 1000
Table 6.31: Chi-Square Analysis for Education * Awareness Level
(Source: Compiled from the questionnaire)
Inference : It can be seen from the Table 6.31 that, the significance level 0.000 is less
than the assumed value 0.05. So we reject H0. This means that Education influences
the awareness level of the customers towards CRM. Hence it is confirm that,
Education can become a significant demographic factor in influencing the awareness
level of the customers towards the CRM in Banking Sector.
- 117 -
The following graph 6.28 consists of the cross tabulated values between the Education
of the customers and their Awareness Level.
Graph 6.28: Education * Awareness Level (Cross Tabulation)
- 118 -
Hypothesis 2b
H0: There is no significant association between Age and the Awareness Level of the
customers towards CRM.
H1: There is a strong association between Age and the Awareness Level of the
customers towards CRM.
The following table 6.32 consists of the cross tabulated values between the Age of the
customers and their Awareness Level.
Age
Awareness Level
Total Very Low
Low Neutral High Very High
16-26 8 13 25 69 87 202 27-37 9 52 61 201 78 401 38-48 11 37 50 103 36 237 49 & above 10 4 32 88 26 160 Total 42 102 171 451 234 1000
Table 6.32: Age * Awareness Level (Cross Table)
(Source: Compiled from the questionnaire)
The following table 6.33 consists of the Chi-Square Test for the Age of the customers
and their Awareness Level values.
Description Value df Asymp.Sig. Person Chi-Square 91.388 12 .000 Likelihood Ratio 89.392 12 .000 Linear by Linear Association 15.325 1 .000 Number of Valid Cases 1000
Table 6.33: Chi-Square Analysis for Age * Awareness Level
(Source: Compiled from the questionnaire)
Inference : It can be seen from the Table 6.33 that, the significance level 0.000 is less
than the assumed value 0.05. So we reject H0. This means that Age influences the
awareness level of the customers towards CRM. Hence it is confirm that, Age can
become a significant demographic factor in influencing the awareness level of the
customers towards the CRM in Banking Sector.
- 119 -
The following graph 6.29 consists of the cross tabulated values between the Education
of the customers and their Awareness Level.
Graph 6.29: Age * Awareness Level (Cross Tabulation)
- 120 -
Hypothesis 2c
H0: There is no significant association between Income and the Awareness Level of
the customers towards CRM.
H1: There is a strong association between Income and the Awareness Level of the
customers towards CRM.
The following table 6.34 consists of the cross tabulated values between the Income of
the customers and their Awareness Level.
Income
Awareness Level
Total Very Low
Low Neutral High Very High
HIGH 4 31 68 112 60 275 MEDIUM 14 42 72 312 148 588 LOW 20 33 28 37 19 137 Total 38 106 168 461 227 1000
Table 6.34: Income * Awareness Level (Cross Table)
(Source: Compiled from the questionnaire)
The following table 6.35 consists of the Chi-Square Test for the Income of the
customers and their Awareness Level values.
Description Value df Asymp.Sig. Person Chi-Square 123.142 8 .000 Likelihood Ratio 103.424 8 .000 Linear by Linear Association 18.832 1 .000 Number of Valid Cases 1000
Table 6.35: Chi-Square Analysis for Income * Awareness Level
(Source: Compiled from the questionnaire)
Inference : It can be seen from the Table 6.35 that, the significance level 0.000 is less
than the assumed value 0.05. So we reject H0. This means that Income influences the
awareness level of the customers towards CRM in Banking Sector. Hence it is
confirm that, Income can become a significant demographic factor in influencing the
awareness level of the customers towards the necessity of CRM in Banking Sector.
- 121 -
The following graph 6.30 consists of the cross tabulated values between the Income
values of the customers and their Awareness Level.
Graph 6.30: Income * Awareness Level (Cross Tabulation)
The following hypothesis is tested to know how Quality service effects the customers
to continue with existing bank. The hypothesis is tested by using Chi-Square test
(non-parametric)
- 122 -
Hypothesis 3
H0: Quality Service doesn’t effects the customers to continue with existing bank and
do not motivate for Good Relationship.
H1: Quality Service does effects the customers to continue with existing bank and
motivate for Good Relationship.
Dimension Observed Expected Residual
Very Large Extent 188 200 -12.0
Large Extent 502 200 302
Medium Extent 142 200 -58.0
Some Extent 102 200 -98.0
Not at All 66 200 -134.0
Total 1000
Table 6.36: Observed and Expected values about Quality Service
(Source: Compiled from the questionnaire)
The following graph 6.31 consists of the values of agreement towards Quality Service
which can surely effects the customers to continue with existing bank and motivate
for good relationship.
- 123 -
Graph 6.31: Quality Service effects customers to continue with existing bank
Description Values
Chi-Square 611.360
Df 4
Asymp.Sig. .000
Table 6.37: Chi-Square Test for Agreement about Quality Service
Inference : It can be seen from the Table 6.37 that, the significance level 0.000 is less
than the assumed value 0.05. So we reject H0. This means that Quality Service effects
the customers to continue with existing bank and do motivate good relationship.
- 124 -
The following hypothesis is tested to know how Quality Service is significant in the
development of CRM in Banking Sector. The hypothesis is tested by using
Kolmogorov Smirnov test which is non-parametric.
Hypothesis 4
H0: Quality Service is not significant in the development of CRM in Banking Sector.
H1: Quality Service is highly significant in the development of CRM in Banking
Sector.
Dimension O.V. O.P. O.C.P. N.P. N.C.P. A.D.
(1) (2) (3) (4) (5) (6) (7)
Very Large Extent 188 0.188 0.188 0.2 0.2 -0.012
Large Extent 502 0.502 0.69 0.2 0.4 0.29
Medium Extent 142 0.142 0.832 0.2 0.6 0.232
Some Extent 102 0.102 0.934 0.2 0.8 0.134
Not at All 66 0.066 1 0.2 1 0
Total 1000
Table 6.38: Kolmogorov-Smirnov Test for testing
the importance of Quality Service
(Source: Compiled from the questionnaire)
O.V. : Observed Value
O.P. : Observed Proportion
O.C.P. : Observed Cumulative Proportion
N.P. : Null Proportion
N.C.P. : Null Cumulative Proportion
A.D. : Absolute Difference
Inference : It can be seen from the Table 6.38 that, the largest absolute difference is
0.29 which is known as the Kolmogorov-Smirnov D value. The Absolute difference
value is exceeds the critical value, therefore the null hypothesis is rejected. It means
that Quality Service is highly significant in the development of CRM in Banking
Sector.
- 125 -
6.6 - DESCRIPTIVE STATISTICAL ANALYSIS
The following table 6.39 represents the descriptive statistics values of the variables
V1, V2, V3, V4, V5, V6, V7, V8, V9, V10 & V11.
Variables A1 A2 A3 A4 A5 Total
Customer Retention (V1) 14 32 84 729 141 1000
Basic and key facilities (V2) 25 47 98 682 148 1000
Enhance Customer loyalty (V3) 10 17 53 792 128 1000
Practices throughout levels (V4) 14 36 91 697 162 1000
Employee approach (V5) 33 71 53 757 86 1000
Increase Relationship (V6) 10 26 52 802 10 1000
Frame customer data base (V7) 104 146 121 586 43 1000
Attract new customers (V8) 36 80 90 687 107 1000
Build customer loyalty (V9) 46 74 99 646 135 1000
Boosts customer confidence (V10) 100 113 66 600 121 1000
Performance & Productivity (V11) 83 99 89 651 78 1000
Table 6.39: Descriptive Statistical Values of Variables
(Source: Compiled from the questionnaire)
A1 : Strongly Disagree
A2 : Disagree
A3 : Undecided
A4 : Agree
A5 : Strongly Agree
- 126 -
The following table 6.40 represents the descriptive statistics analysis of the variables
V1, V2, V3, V4, V5, V6, V7, V8, V9, V10 & V11.
Variables Mean Std.
Deviation Total
Customer Retention (V1) 3.951 0.69071 1000
Basic and key facilities (V2) 3.881 0.80342 1000
Enhance Customer loyalty (V3) 4.011 0.58242 1000
Practices throughout levels (V4) 3.957 0.72227 1000
Employee approach (V5) 3.792 0.82305 1000
Increase Relationship (V6) 3.976 0.59647 1000
Frame customer data base (V7) 3.318 1.10458 1000
Attract new customers (V8) 3.749 0.88248 1000
Build customer loyalty (V9) 3.750 0.93925 1000
Boosts customer confidence (V10) 3.529 1.14825 1000
Performance & Productivity (V11) 3.542 1.04945 1000
Table 6.40: Descriptive Statistical Analysis of Variables
(Source: Compiled from the questionnaire)
Inference : From the table 6.39 & 6.40, the variables from V1 to V11 are measured
on a Likert-Rating scale ranging from 1 to 5, with 1 being Strongly Disagree and 5
being Strongly Agree. The lowest mean being 3.318 and highest mean being 4.011. It
shows that the mean is consistent and it is good measure for analysis and conclusion.