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A STUDY ON CUSTOMER SATISFACTION & BRAND PERFORMANCE OF JEANS TROUSER
PRESENTED BY:-
Vivek Kumar
(enigmaticvision@gmail.com) (+91‐9163902878)
IBS, KOLKATA 15 JANUARY 2009
AUTHORISATION
The report is submitted as a partial fulfillment of the requirement of
internal evaluation for MBA program conducted by IBS Kolkata.
ACKNOWLEDGEMENT
I would like to thank Prof. Ashim Ghosh,Director,IBS , Kolkata for giving us permission to carry
out our project.
With immense pleasure and deep sense of gratitude, we wish to express our sincere thanks to our
class lecturer and project guide Mr. Kalyan Sen Gupta, Lecturer, Business Research Method
IBS, Kolkata for his constant interest, encouragement and expert guidance throughout the course
of this project, which provide the necessary driven force that enabled me to pursue our work with
vigor and keen interest.
At last, we express our sincere gratitude to our peers for their moral support and the love
rendered during the course of our dissertation work.
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Table of Contents
1. Introduction: ......................................................................................................................................... 1
2. Methodology: ........................................................................................................................................ 1
3. Findings and Managerial Implication .................................................................................................... 3
4. Limitation .............................................................................................................................................. 5
5. Conclusion ............................................................................................................................................. 5
Appendix 1: Demographic profiling of respondent ...................................................................................... 6
Appendix 2: Analysis Result .......................................................................................................................... 7
Appendix 3: Questionnaire used for Survey ............................................................................................... 14
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Jeans trouser has been innovated during 1950s for a coal mines worker by Denim. By
looking over the popularity of jeans trouser and changing trend in fashion made it
essential to understand the factor which is desirable to make customer satisfied.
The objective of the study was to know the characteristic and significance of Fashion &
offer, generic requirement, efficient quality, Value for money, services and maturity of
person which may generate satisfaction in the customer’s mind.
We have conducted survey and used the data collected trough respondents. Our
sample size was 108 and our all respondent were from city of Kolkata, India. We used
suitable multivariate technique to conclude the result of survey.
1. Introduction:
After globalization in India several MNCs came here and they changed the overview of
culture of organization. Now a days, most of the organization does not force their
employee to come in strictly formal wear rather they feel comfortability of employee is
more essential. This is an important reason why in last one and half decade demand for
jeans trouser has been increased significantly in India.
Now it is interesting to know the test and preferences of consumer of jeans trouser in
term of finding out the reason, how market leader is capturing the market with respect to
other competitors.
2. Methodology:
We tried to measure customer satisfaction of five major players of Jeans trouser. We
collected information from different shop (15 shops) and try to find out which is most
salable brand in Kolkata, India. For this part of survey we never include the exclusive
outlets of any of the brand. We Found Pepe, Levi’s , Wrangler, Splyker and Lee are the
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brand which is most salable and hence we included this five brand for our survey. Our
survey can be divided in to two steps. We surveyed by the questionnaire. Firstly, we did
pilot survey to validate the question so that there should not be any ambiguity in the
question. For this pilot survey, randomly we selected 20 people from “City Center Mall”,
Kolkata, India. The purpose of this pilot survey was to remove or modify the ambiguous
question from the questionnaire. We modified or removed some of the question and for
final questionnaire we came out with 16 variables which may influence the customer
satisfaction. After this we surveyed for the variable which influence the customer
satisfaction and brand performance. In this survey we conducted interview for 107
consumers who uses jeans trouser in city of Kolkata, India.
This questionnaire was divided in to two section first was personal detail and second
was brand performance (Refer : Appendix 3). In this survey for brand performance we
had taken sixteen variables which were measured on five point likert scales from scale
range “very important” to “not at all important”. From the study we found detail of
demographic profile of respondent (Refer Appendix 1).
We had taken sixteen variables for the questionnaire and used factor analysis to see
the interdependent relationship among variables. For the factor analysis, we selected
“Principal component method”, “Varimax” rotation and Eigen value were used. We have
used scree test (Appendix 2: Figure 1) in which where Eigen value begin to smooth out
after six variable. This helps us to reduce sixteen variables into six factors. We can see
KMO and Bartlett’s test (Appendix 2: Table 1) for the adequacy and appropriation of
factor analysis. Here KMO measure of sampling adequacy is 0.782 which is significantly
high value and show factor analysis is appropriate. We can see rotated component
matrix (Appendix 2: Table 6) and we can see underline for every variables which is most
correlated with particular factor. Detail explanation of variable and factor is given below
in the table.
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Factor No. Name Variables
1 Fashion & Offers Style, Verity, color, sale (offer)
2 Generic Requirements Fitting ,Availability of size, Gender
3 Efficient quality Fabric quality, Comfort
4 Value for money Income, Price
5 Services Alteration Facility, Services (e.g. replacement )
6 Maturity of person Age , Education
Based on above factor it is desirable to do a cluster analysis to segment the customer.
We did K-Mean cluster analysis followed by Hierarchical method by Ward’s clustering
method and “Squared Euclidean distance” .By hierarchical method we analyses that six
cluster is needed . We refer Appendix 2: Table 1 for the final centre of all six variables in
six clusters.
3. Findings and Managerial Implication
While explain the all six Cluster Refer Appendix 2: Table 12, 14,16,18,20 for the
percentage of respondent in different clusters and for Chi-square test for dependency
Refer: Appendix 2: Table 13,15,17,19 and 21
Cluster 1: Twenty two is the size of this cluster (Refer Appendix 2: Table 10).All consumer less
than 20 year belongs from this cluster where as 20.6 % of total sample belongs from
this cluster (Refer: Appendix 2: Table 12). Also around 39 % of population who are in
age of 20-40 belongs from this Cluster. In this cluster around 31.7 % of the customer
preferred Levi’s over other brand. Also it is found that this group is dominated by
Female.
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Cluster 2: Twelve is the size of this cluster (Refer Appendix 2: Table 10).This cluster is dominated
by age group of 40-50 year with average monthly income less then Rs 5000. These
consumer prefer Spyker brand compare to others
Since Spyker is available in comparatively low price hence this market segment that is
having less then Rs. 5000 average monthly income is going for this brand of jeans
trousers. it can be suggested for other brand to reduce price to target this segment of
customer.
Cluster 3: Twenty four is the size of this cluster (Refer Appendix 2: Table 10).This cluster is
dominated by age group of 30-40 year with average monthly income Rs. 15000-20000 .
Most of respondent under this cluster is Male and they prefer Pepe jeans trouser
compare to others.
Cluster 4: Twenty one is the size of this cluster (Refer Appendix 2: Table 10).All customer under
this cluster are male and they prefer wrangler compare to other brand. This group is
dominated by age group of 30-50 year.
Cluster 5: Seventeenth is the size of this cluster (Refer Appendix 2: Table 10).Educational level of
most of the customer are Post graduate. Most of consumers under this segmet are
earning more than Rs. 2000. And they prefer Levi’s. These clusters represent 15.9% of
whole sample.
Cluster 6: Eleven is the size of this cluster (Refer Appendix 2: Table 10).In this cluster most of the
consumer are age group of 40-50 year. They are in income group of Rs. 15000 -20000
and they prefer Spyker and Wrangler equally.
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4. Limitation
This survey is conducted in city of Kolkata, India. There is possibility that perception of
whole Indian market will be not as similar as perception of Kolkata’s people. Also
perception in semirural area may be different.
5. Conclusion
It is found that most of the consumer are not brand royal and shift from one brand to
another. Also from study it is found all six factors Fashion & offer, generic requirement,
efficient quality, Value for money, services and maturity of person determining the
satisfaction of customer.
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Appendix 1: Demographic profiling of respondent
Age
2 1.9 1.9 1.952 48.1 48.1 50.026 24.1 24.1 74.119 17.6 17.6 91.7
9 8.3 8.3 100.0108 100.0 100.0
<2020-3030-4040-50>50Total
ValidFrequency Percent Valid Percent
CumulativePercent
Educational qualification
4 3.7 3.7 3.7
20 18.5 18.5 22.2
17 15.7 15.7 38.018 16.7 16.7 54.649 45.4 45.4 100.0
108 100.0 100.0
Primary school(till V)Senior School(class VI to X)Higher SecandryGradutePost GraduteTotal
ValidFrequency Percent Valid Percent
CumulativePercent
Gender
69 63.9 63.9 63.939 36.1 36.1 100.0
108 100.0 100.0
MaleFemaleTotal
ValidFrequency Percent Valid Percent
CumulativePercent
Income(Avg. Monthly)
78 72.2 72.2 72.212 11.1 11.1 83.3
9 8.3 8.3 91.79 8.3 8.3 100.0
108 100.0 100.0
< 50005000-1000015000-20000>20000Total
ValidFrequency Percent Valid Percent
CumulativePercent
Table 1: Frequency on age Category
Table 4: Frequency on Income
Table 3: Frequency on Gender
Table 2: Frequency on Educational qualification
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Appendix 2: Analysis Result
1. Factor analysis
Table 6: Rotated Component Matrixa
-3.71E-03 2.012E-02 .108 -5.79E-02 -8.69E-02 -.6111.001E-02 2.033E-02 .123 1.452E-02 -.164 .790
-.106 -.599 -.190 .113 .251 .413-.203 -4.18E-02 -5.54E-02 .706 -.139 7.177E-02
-1.59E-02 -8.61E-02 8.790E-03 .840 .104 5.952E-02-.104 -1.41E-02 .904 -6.50E-02 -3.67E-02 -.115
3.088E-02 .690 3.396E-02 -5.09E-02 -8.52E-02 4.426E-02.585 .316 .163 -.233 -.102 2.401E-02.190 8.940E-02 .736 4.417E-02 .404 .101.859 .117 .260 -.150 9.357E-02 4.101E-02
3.777E-02 .633 .140 -.113 .410 .168.698 .388 -.183 -.253 -1.98E-02 9.530E-02.760 -.179 -.277 .186 .129 -.147
6.012E-02 -.144 -7.60E-03 -.427 .663 .145
.256 .743 -.151 7.689E-02 .157 -9.86E-02
2.247E-02 .130 .160 .166 .803 -.166
AgeEducational qualification Gender Income(Avg. Monthly)PriceFabric Quality Fitting Style Comfort VerietyAvailabilty of Sizes Avaibility of ColorSale (Offers) Alteration FacilityAvailability of Changing Rooms Services(e.g:-replaceme nt)
1 2 3 4 5 6 Component
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.
Rotation converged in 6 iterations.a.
Scree Plot
Component Number
16151413121110987654321
Eig
enva
lue
3.5
3.0
2.5
2.0
1.5
1.0
.5
0.0
Table 5
Figure 1: Scree Plot
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Table 7:
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2. Cluster analysis
Initial Cluster Centers
1.20766 -.25740 -1.55942 .58804 -.62177 1.73489.37095 -.52835 .64075 2.39414 -.53685 .35984
-1.39342 1.47148 1.10447 -.59107 -.97570 1.35629-1.18410 -1.81761 -.26748 -.43832 2.25108 1.67507
.71197 -1.79750 1.62515 -.86739 .34792 .39440-1.07953 -.00563 -1.10817 1.27510 1.19227 -1.60952
Fashion & OffersGeneric RequirmentEfficient QualityValue For MoneyServicesMaturity of Person
1 2 3 4 5 6Cluster
Number of Cases in each Cluster
22.00012.00024.00021.00017.00011.000
107.0001.000
123456
Cluster
ValidMissing
Iteration Historya
1.587 1.505 1.277 1.328 1.534 1.534.392 .000 .130 .387 .161 .536.258 .125 .148 8.455E-02 .244 .257.216 .228 .236 .179 .166 .521.106 .135 9.330E-02 .000 .166 .356.217 .000 8.704E-02 .000 .000 .376.131 .000 .225 .119 .000 .000
8.796E-02 .257 .175 .000 .000 .000.000 .000 .000 .000 .000 .000
Iteration123456789
1 2 3 4 5 6Change in Cluster Centers
Convergence achieved due to no or small distance change. The maximumdistance by which any center has changed is .000. The current iteration is 9.The minimum distance between initial centers is 3.703.
a.
Final Cluster Centers
.07650 -.19529 -.63647 .14316 -.59567 2.09596-.48217 -.29431 -.19793 1.55253 -.48384 -.49889-.49184 1.45637 .37415 -.44615 -.42666 .08971-.96339 -.84674 .02467 -.03516 1.40064 .69918.44561 -1.11816 .58566 -.05756 -.39823 -.22388.62173 .38447 -.97885 .09212 .44672 -.39348
Fashion & OffersGeneric RequirmentEfficient QualityValue For MoneyServicesMaturity of Person
1 2 3 4 5 6Cluster
Table 11
Table 10Table 9
Table 8
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3. Crosstabs a. Customer age
Table 14: Educational qualification Crosstab
3 1 4
75.0% 25.0% 100.0%
1 10 4 2 2 19
5.3% 52.6% 21.1% 10.5% 10.5% 100.0%
4 2 4 3 2 2 17
23.5% 11.8% 23.5% 17.6% 11.8% 11.8% 100.0%
6 2 3 3 2 2 18
33.3% 11.1% 16.7% 16.7% 11.1% 11.1% 100.0%
11 8 4 11 11 4 49
22.4% 16.3% 8.2% 22.4% 22.4% 8.2% 100.0%
22 12 24 21 17 11 107
20.6% 11.2% 22.4% 19.6% 15.9% 10.3% 100.0%
Count % within Educationalqualification Count % within Educationalqualification Count % within Educationalqualification Count % within Educationalqualification Count % within Educationalqualification Count % within Educationalqualification
Primary school(till V)
Senior School (class VI to X)
Higher Secandry
Gradute
Post Gradute
Educational qualification
Total
1 2 3 4 5 6Cluster Number of Case
Total
Table 12 : Customer Age* Cluster Number Crosstab
2 2100.0% 100.0%
14 6 4 11 12 5 5226.9% 11.5% 7.7% 21.2% 23.1% 9.6% 100.0%
3 2 11 5 1 3 2512.0% 8.0% 44.0% 20.0% 4.0% 12.0% 100.0%
1 4 5 3 3 3 195.3% 21.1% 26.3% 15.8% 15.8% 15.8% 100.0%
2 4 2 1 922.2% 44.4% 22.2% 11.1% 100.0%
22 12 24 21 17 11 10720.6% 11.2% 22.4% 19.6% 15.9% 10.3% 100.0%
Count% within AgeCount% within AgeCount% within AgeCount% within AgeCount% within AgeCount% within Age
<20
20-30
30-40
40-50
>50
Age
Total
1 2 3 4 5 6Cluster Number of Case
Total
Chi-Square Tests
32.857a 20 .03534.901 20 .021
.320 1 .572
107
Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases
Value dfAsymp. Sig.
(2-sided)
22 cells (73.3%) have expected count less than 5. Theminimum expected count is .21.
a.
Table 13 :
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Table 17:Chi-Square Tests
33.257 a 5 .00039.604 5 .000
.902 1 .342
107
Pearson Chi-SquareLikelihood Ratio Linear-by-Linear Association N of Valid Cases
Value dfAsymp. Sig.
(2-sided)
2 cells (16.7%) have expected count less than 5. Theminimum expected count is 4.01.
a.
Table 15:Chi-Square Tests
30.646 a 20 .00033.166 20 .000
.531 1 .006
107
Pearson Chi-SquareLikelihood Ratio Linear-by-Linear Association N of Valid Cases
Value dfAsymp. Sig.
(2-sided)
24 cells (80.0%) have expected count less than 5. Theminimum expected count is .41.
a.
Crosstab
8 9 18 21 4 8 6811.8% 13.2% 26.5% 30.9% 5.9% 11.8% 100.0%
14 3 6 13 3 3935.9% 7.7% 15.4% 33.3% 7.7% 100.0%
22 12 24 21 17 11 10720.6% 11.2% 22.4% 19.6% 15.9% 10.3% 100.0%
Count% within GenderCount% within GenderCount% within Gender
Male
Female
Gender
Total
1 2 3 4 5 6Cluster Number of Case
Total
Table 16 :
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Table 18 : Income(Avg Monthly)* Crosstab
22 11 15 15 6 8 77
28.6% 14.3% 19.5% 19.5% 7.8% 10.4% 100.0%
1 5 6 12
8.3% 41.7% 50.0% 100.0%
4 2 3 9
44.4% 22.2% 33.3% 100.0%
9 9
100.0% 100.0%
22 12 24 21 17 11 107
20.6% 11.2% 22.4% 19.6% 15.9% 10.3% 100.0%
Count% within Income(Avg.Monthly)Count% within Income(Avg.Monthly)Count% within Income(Avg.Monthly)Count% within Income(Avg.Monthly)Count% within Income(Avg.Monthly)
< 5000
5000-10000
15000-20000
>20000
Income(Avg.Monthly)
Total
1 2 3 4 5 6Cluster Number of Case
Total
Chi-Square Tests
78.942a 15 .00070.773 15 .000
18.073 1 .000
107
Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases
Value dfAsymp. Sig.
(2-sided)
18 cells (75.0%) have expected count less than 5. Theminimum expected count is .93.
a.
Table 19
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Table 21 : Chi-Square Tests
58.400a 20 .00066.080 20 .000
5.880 1 .015
107
Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases
Value dfAsymp. Sig.
(2-sided)
24 cells (80.0%) have expected count less than 5. Theminimum expected count is .93.
a.
Table 20: Brand Choice * Cluster Number of Case Crosstabulation
19 6 16 6 10 3 6031.7% 10.0% 26.7% 10.0% 16.7% 5.0% 100.0%
5 4 2 1145.5% 36.4% 18.2% 100.0%
3 3 3 933.3% 33.3% 33.3% 100.0%
1 5 3 911.1% 55.6% 33.3% 100.0%
3 3 2 3 7 1816.7% 16.7% 11.1% 16.7% 38.9% 100.0%
22 12 24 21 17 11 10720.6% 11.2% 22.4% 19.6% 15.9% 10.3% 100.0%
Count % within Brand ChoiceCount % within Brand ChoiceCount % within Brand ChoiceCount % within Brand ChoiceCount % within Brand ChoiceCount % within Brand Choice
Levi's
Pepe
Spyker
Wrangler
Lee
Brand Choice
Total
1 2 3 4 5 6 Cluster Number of Case
Total
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Appendix 3: Questionnaire used for Survey
Questionnaire for end user Survey
PERSONAL DETAILS 1. Name : ………………………………………………………………… 2. Email : ……………………………………………............................... 3. Mobile Number : 4. What is your age (in years)?
< 20 20 – 30 30 – 40 40 – 50 50 – 60 > 60
5. What is your level of education?
Primary School (till class V) Senior School (class VI – X) Higher Secondary Graduate Post Graduate
6. What is the average monthly income of your family (in Rs.)?
< 5000 5000 – 10000 10000 – 15000 15000 – 20000
>20000
7. Gender : Male Female
Respondent ID:
BRAND PREFERENCE 8. How frequent do you purchase jeans trouser in a year.
a) Once b)Twice c)Thrice d)Four times e)More than 4 times
9. How important do you think the following parameters are in choosing your preferred brand?
10. Rank the brands you like most for buying jeans.(1 for most likeness and 5 for least
likeness):
Sl Brand Rank 1 Pepe 2 Levi’s 3 Spykar 4 Wrangler 5 Lee
Factors Very Important
Somewhat Important
Moderately Important
Not so Important
Not at all Important
Convenient Location Price Fabric Quality Fitting Style Fitting Comfort No of Variant (Varity) Availability of sizes Color Availability Alteration facility sales (Discount / Offer) Availability of changing room
Service (e.g. Replacement )