54113814 Mentoring Live Project

8/6/2019 54113814 Mentoring Live Project

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RESEARCH ON THE CUSTOMER SATISFACTION AND

STRATEGIC POSITIONING OF ALLEN SOLLY

Submitted By:

Ajay

Nupur

Anupam


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INTRODUCTION OF THE RESEARCH PROJECT

Today, formal shirts are in demand not only for business and work purposes but also for

parties and other occasions. Our group decided to conduct a survey on a particular

brand of formal shirts and analyze and interpret the output of survey as part of our

research project.

Allen Solly was founded in 1744 by a company called William Hollin and Co Ltd. The brand was purchased some tim e in the 90's by a new company called Madura

Garments which was a part of Madura Coats.

Allen Solly brings together people from different walks of life and unites them in the

matters of style and attitude. The innovative garments of Allen Solly give people anidentity in the work place and also while chilling out.

OBJECTIVE:-

The main purpose of this research is to find out the levels of customer satisfaction with

Allen Solly and its position in the market with respect to competitors like Peter England,

John Players, Louis Philippe etc.

SCOPE OF THE STUDY:

By understanding the various factors that contribute to the satisfaction level of the users

of Allen Solly we could find out which factor contributed the most and the least to the

satisfaction of the users of Allen Solly formal shirts.

This study helps us better determine the positioning of Allen Solly as compared to the

other competitors of it, based on various parameters. It helps us understand the areas

Allen Solly should improve on and the areas it can capitalize on (Strengths and

weakness).

PROBLEM STATEMENT

Looking at Allen Solly, the brand is not faring very well in the m arket and the research is

basically em phasizing on the formal shirts of Allen Solly. The reasons for it not faring

well could be

Competition

Customer Loyalty


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Price

Positioning of the brand

RESEARCH DESIGN:

Both qualitative and quantitative research methods were used to collect the data.

Qualitative method included focus group and in-depth interviews. Focus Groupinterviews was to find out the positioning of Allen Solly compared to other brands. In-

Depth interviews was carried on to see the satisfaction level of the users of Allen Solly.

Quantitative method included satisfaction and positioning survey.

SAMPLING PLAN:

Survey was conducted with the help of a questionnaire with two parts- one relating to

satisfaction of the users and the other part to see the positioning of the brand.

Sample size was 40 which mainly included students and young working professionals.

The survey was only conducted for men as they are the major users of formal shirts.

LIMITATIONS OF THE STUDY:

The sampling size was comparatively small(40).

The focus was on only one segment of the market- one gender(men).

Respondent bias

Willingness of the participants in the focus groups and in-depth interviews.

QUALITATIVE RESEARCH:

Focus Group and In-Depth interviews gave us an overview regarding the preference of

people to Allen Solly over other brands.

Focus group study conducted in Sjcba to assess the brand positioning for men on the

kind of formal shirts they use.

Size of the focus group was 8.

The moderator introduced the session to the participants by highlighting the purpose o

the study and its importance.

For the focus group interview we asked the following questions like

-What attributes influences their purchase of formal shirts?

-What other things determines the purchase of a formal shirt?

-Rank the top five attributes mentioned by them?

-How often they bought formal shirts?


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-What was the purpose of the buy?

-Which big brand names were familiar to them among formal shirts?

-What was the market share of the Allen Solly in India?

-Who all were the competitors for Allen Solly?

The participants had a discussion about various attributes which are important for themwhile they go for purchasing formal shirts. They felt that comfort, fabric,price, slim -fit,

colour, design, brand, availability and quality were important attributes. They were

asked to rank the top five attributes. Thus the top five attributes according to the group

were quality, comfort level, fabrics, price and design.

Some of the participants also considered discount offers and brand ambassadors as

important attributes. The purpose of their buy was for college as most of them were

management students and even for functions and occasions. The com petitors for Allen

Solly listed were Louis Phillipe, Van Heusen, Peter England, Arrow, Zodiac and John

Players. Most of them said that the look of the shirts of Louis Phillipe are outstanding.

They considered Allen Solly as a very expensive brand fit for working professionals and

students, therefore participants who had Allen Solly shirts did not buy it rather it was

gifted. They also stated that the brand was expensive for students but if given a chance

they would always want to try the brand.

IN-DEPTH INTERVIEW:

Two users of Allen Solly shirts were interviewed to know their satisfaction level with the

brand Allen Solly.

The following questions were asked:

Who influenced them to buy Allen Solly shirts?

Did they face any problem with the quality or the service of Allen Solly?

Would they recommend to others to buy a Allen Solly shirt?

Attributes which are there in Allen Solly which is not their in other brands?

Attributes which are there in other brands but not in Allen Solly?

Happy or emotional moments experienced with the brand?

Suggestions if any.

The respondents were not restricted with these questions. They were given the liberty to

share whatever they wanted associated with the brand.

Respondent 1: Advertisements and friends influenced his purchase of Allen Solly Shirt

which gives him comfort and the right fitting. According to him Allen Solly shirts gave

him the perfect formal look that is r equired for a official or responsible work. The comfort


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factor and fitting is better compared to other brands. He said price is surely on the

higher side but its worth paying and is also easily available. He would surely

recommend the brands to others. He said that the other brands do have an edge over

Allen Solly because thay have more variety. He suggested that Allen Solly should work

on their pricing as it is not affordable by everyone. Also more variety and shades could

be introduced.

Respondent 2: Nobody influenced the decision for purchase of Allen Solly shirt. His

first purchase was just shopping in a mall and when he liked the fitting he became a

regular user of the brand. The quality and durability of Allen Solly shirts are liked by him.

He also believes that Allen Solly shirts potray what you are. The interaction of the

salesperson in the outlets are also impressive. According to him he would not suggest

the brands to everyone as the price is on the higher side and people who are not

working cannot afford. He felt that promotions are very rare in Allen Solly compared to

brands like Peter England and Van Heusen. He suggested that Allen Solly can make its

shirts more available to a larger section by working on its price and availability and alsocome up with discount offers to motivate people to buy the shirt.

QUANTITATIVE RESEARCH:

Analysis and interpretation of satisfaction survey

Correlation Analysis

Descriptive Statistics

Mean Std. Deviation N

Comfort Level 5.3750 1.05460 40

Easeof Availability 4.8750 1.30458 40

Variety 5.2500 1.23517 40

Quality 6.1000 1.08131 40

Design 5.5500 1.08486 40

Fabrics 5.8000 1.06699 40

Overall Satisfaction 5.1750 1.10680 40

Above shows the means of all the satisfaction factors that are taken into account. From

the above data we see that mean of quality is the highest. i.e. people are most satisfied

with the quality of the shirt which is followed by the fabrics and design respectively.

(Nothing to do with overall satisfaction)


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Correlations

Ease o OverallComfort

Level Availability Variety Quality Design Fabrics Satisfaction

Comfort Level Pearson 1 .464 .477 .326 .375 .228 .777* * * * * * * *

Correlation

Sig. (2-tailed) .003 .002 .040 .017 .157 .000

N 40 40 40 40 40 40 40

Ease of Pearson .464 1 .561 .155 .104 .184 .495* * * * * *

Availability Correlation

Sig. (2-tailed) .003 .000 .341 .522 .255 .001

N 40 40 40 40 40 40 40

Variety Pearson .477 .561 1 .538 .488 .389 .680* * * * * * * * * * *

Correlation

Sig. (2-tailed) .002 .000 .000 .001 .013 .000

N 40 40 40 40 40 40 40

Quality Pearson .326 .155 .538 1 .630 .729 .585* * * * * * * * *

Correlation

Sig. (2-tailed) .040 .341 .000 .000 .000 .000

N 40 40 40 40 40 40 40

Design Pearson .375 .104 .488 .630 1 .518 .494* * * * * * * * *

Correlation

Sig. (2-tailed) .017 .522 .001 .000 .001 .001

N 40 40 40 40 40 40 40

Fabrics Pearson .228 .184 .389 .729 .518 1 .291* * * * *

Correlation

Sig. (2-tailed) .157 .255 .013 .000 .001 .069

N 40 40 40 40 40 40 40

Overall Pearson .777 .495 .680 .585 .494 .291 1* * * * * * * * * *

Satisfaction Correlation

Sig. (2-tailed) .000 .001 .000 .000 .001 .069

N 40 40 40 40 40 40 40

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

Here we are trying to find out, using correlation if the attributes are correlated with one

another and using partial correlation, we are trying to find out the extent of correlation

between the attributes, keeping one attribute suppressed.


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-0.3 to +0.3 little or no association.

+0.3 to +0.7 positive association.

+0.7 to +1.0 strong positive association.

On the basis of the output 1 we have interpreted the following

The Null Hypothesis (Ho): There is no correlation between overall satisfaction and

comfort level

Alternate Hypothesis (H1): There is a correlation between overall satisfaction and the

comfort level.

On the basis of comfort level, the significant level shown is less than o.o5 and hence P

value is less than 0.05. So we reject the null hypothesis. This indicates that there is

association or strong positive correlation between overall satisfaction and comfort level.

The Null Hypothesis (Ho): There is no correlation between overall satisfaction and ease

of availability.


ease of availability.

On the basis of ease of availability, the significant level shown is less than o.o5 and

hence P value is less than 0.05. So we reject the null hypothesis. This indicates that

there is positive association or correlation between overall satisfaction and ease ofavailability.


variety.


variety.

On the basis of variety, the significant level shown is less than o.o5 and hence P valueis less than 0.05. So we reject the null hypothesis. This indicates that there is positive

association or correlation between overall satisfaction and variety.


quality.


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quality.

On the basis of quality, the significant level shown is less than o.o5 and hence P value

is less than 0.05. So we reject the null hypothesis. This indicates that there is positive

association or correlation between overall satisfaction and quality.


design.


design.

On the basis of ease of design, the significant level shown is less than o.o5 and hence

P value is less than 0.05. So we reject the null hypothesis. This indicates that there is

positive association or correlation between overall satisfaction and design.


fabrics.


fabrics.

On the basis of fabrics, the significant level shown is greater than o.o5 and hence P

value is greater than 0.05. So we accept the null hypothesis. This indicates that there isno association or correlation between overall satisfaction and fabrics.


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Partial Correlation Analysis

-0.3 to +0.3 little or no association.

+0.3 to +0.7 positive association.

+0.7 to +1.0 strong positive association.


Mean Std. Deviation N

Overall Satisfaction 5.1750 1.10680 40

Quality 6.1000 1.08131 40

Ease of Availability 4.8750 1.30458 40

Design 5.5500 1.08486 40

Comfort Level 5.3750 1.05460 40

Fabrics 5.8000 1.06699 40

Variety 5.2500 1.23517 40

Correlations

Control Variables Overall Ease of

Satisfaction Quality Availability Design Comfort Level Fabrics

Variety Overall Satisfaction Correlation 1.000 .355 .187 .254 .702 .039

Significance (2-tailed) . .027 .254 .119 .000 .813

df 0 37 37 37 37 37

Quality Correlation .355 1.000 -.211 .499 .094 .669

Significance (2-tailed) .027 . .198 .001 .570 .000

df 37 0 37 37 37 37

Ease of Availability Correlation .187 -.211 1.000 -.235 .269 -.045

Significance (2-tailed) .254 .198 . .151 .097 .787

df 37 37 0 37 37 37

Design Correlation .254 .499 -.235 1.000 .186 .409

Significance (2-tailed) .119 .001 .151 . .258 .010

df 37 37 37 0 37 37

Comfort Level Correlation .702 .094 .269 .186 1.000 .052

Significance (2-tailed) .000 .570 .097 .258 . .753

df 37 37 37 37 0 37

Fabrics Correlation .039 .669 -.045 .409 .052 1.000

Significance (2-tailed) .813 .000 .787 .010 .753 .

df 37 37 37 37 37 0


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Controlling the effect of variety

Null Hypothesis: There is no correlation between quality and overall satisfaction, controlling the effect of

variety.

Alternate Hypothesis: There is a correlation between quality and overall satisfaction, controlling the effect

of variety.

Controlling the effect of variety, we find that the significance level is less than 0.05 for quality, so we reject

the null hypothesis. This indicates that there is a positive correlation between quality and overall

satisfaction.

Null Hypothesis: There is no correlation between comfort level and overall satisfaction, controlling the

effect of variety.

Alternate Hypothesis: There is a correlation between comfort level and overall satisfaction, controlling the

effect of variety.

Controlling the effect of variety, we find that the significance level is less than 0.05 for comfort level, so we

reject the null hypothesis. This indicates that there is a positive correlation between comfort level and

overall satisfaction.

Null Hypothesis: There is no correlation between ease of availability and overall satisfaction, controlling the

effect of variety.

Alternate Hypothesis: There is a correlation between ease of availability and overall satisfaction, controlling

the effect of variety.

Controlling the effect of variety, we find that the significance level is greater than 0.05 for ease of

availability, so we accept the null hypothesis. This indicates that there is no correlation between ease of

availability and overall satisfaction.

Null Hypothesis: There is no correlation between fabrics and overall satisfaction, controlling the effect of

variety.

Alternate Hypothesis: There is a correlation between fabrics and overall satisfaction, controlling the effect

of variety.

Controlling the effect of variety, we find that the significance level is greater than 0.05 for fabrics, so we

accept the null hypothesis. This indicates that there is a no correlation between fabrics and overall

satisfaction.

Null Hypothesis: There is no correlation between design and overall satisfaction, controlling the

effect of variety.

Alternate Hypothesis: There is a correlation between design and overall satisfaction, controllin gthe effect of variety.


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Satisfaction Availability Design Comfort Level Fabrics Variety

Q Overall Satisfaction Correlation 1.000 .505 .200 .765 -.244 .534

u Significance (2-tailed) . .001 .222 .000 .135 .000

al

df 0 37 37 37 37 37it

Ease of Availability Correlation .505 1.000 .009 .442 .106 .574y


df 37 0 37 37 37 37

Design Correlation .200 .009 1.000 .232 .112 .228


df 37 37 0 37 37 37

Comfort Level Correlation .765 .442 .232 1.000 -.015 .379


df 37 37 37 0 37 37

Fabrics Correlation -.244 .106 .112 -.015 1.000 -.005


df 37 37 37 37 0 37

Variety Correlation .534 .574 .228 .379 -.005 1.000


df 37 37 37 37 37 0

Controlling the effect of quality

Null Hypothesis: There is no correlation between ease of availability and overall

satisfaction, controlling the effect of quality.

Alternate Hypothesis: There is a correlation between ease of availability and overall

satisfaction, controlling the effect of quality.

Controlling the effect of quality, we find that the significance level is less than 0.05 for

ease of availability, so we reject the null hypothesis. This indicates there is a positive

correlation between ease of availability and overall satisfaction.

Null Hypothesis: There is no correlation between comfort level and overall satisfaction

controlling the effect of quality.

Alternate Hypothesis: There is a correlation between comfort level and overall

satisfaction controlling the effect of quality.


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comfort level, so we reject the null hypothesis. This indicates there is a positive

correlation between comfort level and overall satisfaction.

Null Hypothesis: There is no correlation between variety and overall satisfaction


Alternate Hypothesis: There is a correlation between variety and overall satisfaction



variety, so we reject the null hypothesis. This indicates there is a positive correlation

between variety and overall satisfaction.

Null Hypothesis: There is no correlation between design and overall satisfaction


Alternate Hypothesis: There is a correlation between design and overall satisfaction


Controlling the effect of quality, we find that the significance level is greater than 0.05 for

design, so we accept the null hypothesis. This indicates there is no correlation between

design and overall satisfaction.

Null Hypothesis: There is no correlation between fabrics and overall satisfaction


Alternate Hypothesis: There is a correlation between fabrics and overall satisfaction


Controlling the effect of quality, we find that the significance level is greater than 0.05 for

fabrics, so we accept the null hypothesis. This indicates there is no correlation between

fabrics and overall satisfaction.


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Correlations


Satisfaction Availability Comfort Level Fabrics Variety Quality

Design Overall Satisfaction Correlation 1.000 .513 .734 .047 .578 .405


df 0 37 37 37 37 37

Ease of Availability Correlation .513 1.000 .460 .153 .588 .115


df 37 0 37 37 37 37

Comfort Level Correlation .734 .460 1.000 .042 .364 .125


df 37 37 0 37 37 37

Fabrics Correlation .047 .153 .042 1.000 .182 .606


df 37 37 37 0 37 37

Variety Correlation .578 .588 .364 .182 1.000 .340


df 37 37 37 37 0 37

Quality Correlation .405 .115 .125 .606 .340 1.000


df 37 37 37 37 37 0

Controlling the effect of design


satisfaction controlling the effect of design.



Controlling the effect of design, we find that the significance level is less than 0.05 for

ease of availability, so we reject the null hypothesis. This indicates there is positive



controlling the effect of design.




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comfort level, so we reject the null hypothesis. This indicates there is positive correlation

between comfort level and overall satisfaction.

Null Hypothesis: There is no correlation between quality and overall satisfaction


Alternate Hypothesis: There is a correlation between quality and overall satisfaction



quality, so we reject the null hypothesis. This indicates there is positive correlation

between quality and overall satisfaction.






variety, so we reject the null hypothesis. This indicates there is positive correlation






Controlling the effect of design, we find that the significance level is greater than 0.05

for fabrics, so we accept the null hypothesis. This indicates there is no correlation

between fabrics and overall satisfaction.


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Correlation

Control Variables Overall Ease o

Satisfaction Availability Fabrics Variety Quality Design

Comfort Level Overall Satisfaction Correlation 1.000 .242 .186 .559 .557 .347


df 0 37 37 37 37 37

Ease of Availability Correlation .242 1.000 .091 .436 .004 -.085


df 37 0 37 37 37 37

Fabrics Correlation .186 .091 1.000 .328 .711 .480


df 37 37 0 37 37 37

Variety Correlation .559 .436 .328 1.000 .460 .379


df 37 37 37 0 37 37

Quality Correlation .557 .004 .711 .460 1.000 .579


df 37 37 37 37 0 37

Design Correlation .347 -.085 .480 .379 .579 1.000


df 37 37 37 37 37 0

Controlling the effect of comfort level


controlling the effect of comfort level.



Controlling the effect of comfort level, we find that the significance level is less than 0.05

for design, so we reject the null hypothesis. This indicates there is positive correlationbetween design and overall satisfaction.




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for quality, so we reject the null hypothesis. This indicates there is positive correlation







for variety, so we reject the null hypothesis. This indicates there is positive correlation



satisfaction controlling the effect of comfort level.


satisfaction controlling the effect of comfort level.

Controlling the effect of comfort level, we find that the significance level is greater than

0.05 for ease of availability, so we accept the null hypothesis. This indicates there is no






Controlling the effect of comfort level, we find that the significance level is greater than0.05 for fabrics, so we accept the null hypothesis. This indicates there is no correlation

between fabrics and overall satisfaction.


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Correlations


Satisfaction Availability Variety Quality Design Comfort Level

Fabrics Overall Satisfaction Correlation 1.000 .469 .643 .569 .420 .763


df 0 37 37 37 37 37

Ease of Availability Correlation .469 1.000 .540 .030 .010 .441


df 37 0 37 37 37 37

Variety Correlation .643 .540 1.000 .403 .363 .433


df 37 37 0 37 37 37

Quality Correlation .569 .030 .403 1.000 .430 .240


df 37 37 37 0 37 37

Design Correlation .420 .010 .363 .430 1.000 .309


df 37 37 37 37 0 37

Comfort Level Correlation .763 .441 .433 .240 .309 1.000


df 37 37 37 37 37 0

Controlling the effect of fabrics


satisfaction controlling the effect of fabrics.



Controlling the effect of fabrics, we find that the significance level is less than 0.05 for

ease of availability, so we reject the null hypothesis. This indicates there is a positive



controlling the effect of fabrics.


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comfort level, so we reject the null hypothesis. This indicates there is positive correlation

between comfort level and overall satisfaction.






variety, so we reject the null hypothesis. This indicates there is positive correlation







quality, so we reject the null hypothesis. This indicates there is positive correlation






Controlling the effect of fabrics, we find that the significance level is less than 0.05 fordesign, so we reject the null hypothesis. This indicates there is positive correlation

between design and overall satisfaction.


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Correlation

Control Variables Overall

Satisfaction Variety Quality Design Comfort Level Fabrics

Ease of Availability Overall Satisfaction Correlation 1.000 .559 .592 .512 .711 .234


df 0 37 37 37 37 37

Variety Correlation .559 1.000 .551 .522 .296 .351


df 37 0 37 37 37 37

Quality Correlation .592 .551 1.000 .624 .291 .721


df 37 37 0 37 37 37

Design Correlation .512 .522 .624 1.000 .371 .511


df 37 37 37 0 37 37

Comfort Level Correlation .711 .296 .291 .371 1.000 .164


df 37 37 37 37 0 37

Fabrics Correlation .234 .351 .721 .511 .164 1.000


df 37 37 37 37 37 0

Controlling the effect of ease of availability


controlling the effect of ease of availability.



Controlling the effect of ease of availability, we find that the significance level is less

than 0.05 for design, so we reject the null hypothesis. This indicates there is positive

correlation between design and overall satisfaction.




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controlling the effect of ease of availability


than 0.05 for variety, so we reject the null hypothesis. This indicates there is positive

correlation between variety and overall satisfaction.



Alternate Hypothesis: There is a correlation quality and overall satisfaction control ling

the effect of ease of availability


than 0.05 for quality, so we reject the null hypothesis. This indicates there is positive

correlation between quality and overall satisfaction.




satisfaction controlling the effect of ease of availability


than 0.05 for comfort level, so we reject the null hypothesis. This indicates there ispositive correlation between comfort level and overall satisfaction.




controlling the effect of ease of availability

Controlling the effect of ease of availability, we find that the significance level is greaterthan 0.05 for fabrics, so we accept the null hypothesis. This indicates there is no

correlation between fabrics and overall satisfaction.


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REGRESSION ANALYSIS

H : There is no variation in the overall satisfaction on account of the variation in theO

attributes.

H : There is variation in the overall satisfaction on account of the variation in the1

attributes

ANOVAs

Model Sum of Squares df Mean Square F Sig.

1 Regression 38.968 6 6.495 24.337 .000 a

Residual 8.807 33 .267

Total 47.775 39

a. Predictors: (Constant), Fabrics, Ease of Availability, Comfort Level,

Design, Variety, Quality

b. Dependent Variable: Overall Satisfaction

Model Summary

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

d1 .903 .816 .782 .51659a

i

m

e

n

s

i

o

n

0

a. Predictors: (Constant), Fabrics, Ease of Availability, Comfort Level, Design,

Variety, Quality


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Coefficients a

Model Standardized

Unstandardized Coefficients Coefficients

B Std. Error Beta t Sig.

1 (Constant) -.631 .599 -1.053 .300

Comfort Level .549 .097 .523 5.684 .000

Ease of Availability .097 .085 .114 1.133 .265

Variety .185 .102 .206 1.810 .079

Quality .491 .132 .480 3.718 .001

Design .039 .106 .039 .373 .712

Fabrics -.310 .116 -.299 -2.678 .011

a. Dependent Variable: Overall Satisfaction

On the basis of the output

From the annova table, since the significance level is less than 0.05, so we reject

the null hypothesis. From the model summary table the R square value is .816

therefore 81.6% variation in the overall satisfaction is due to the variation in

quality fabrics and comfort level since their significance level is less than 0.05

From the coefficient Table we find:

Un-standardised Equation

Overall Satisfaction= .549 Comfort level + .491 Quality + (310) fabrics

Standardized Equation

Overall Satisfaction= .523 Comfort level + .480 Quality + (.299) fabrics

Therefore the variation in the overall satisfaction is maximum due to comfort level and

least due to fabrics.


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RELIABILITY ANALYSIS: OVERALL SATISFACTION

Reliability Statistics

Cronbach's

Alpha Based onCronbach's Standardi zed

Alpha Items N of Items

.803 .807 6

On the basis of the output:

The Cronbachs Alpha for all the attributes combined together is 0.803 which is greater

than .6 therefore we can say that the scale used to measure satisfaction is reliable and

all the attributes can be combined together to find the overall satisfaction and therefore

its reliable scale.

POSITIONING STUDY:

Null Hypothesis(H0): There is no difference in the importance of the attributes that

influence the purchase of formal shirts by men.

Alternative Hypothesis(H1): There is a difference in the importance of the attributes that

influence the purchase of formal shirts by men.

Importance of the Attributes:

ANOVA

ATTRIBUTES

Sum of Squares df Mean Square F Sig.

Between Groups 25.493 6 4.249 3.886 .001

Within Groups 298.475 273 1.093

Total 323.968 279


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Interpretation:

The sig value is less than 0.05, thus we reject the null hypothesis. This implies that

there is a difference in the importance of attributes which influences the purchase of

formal shirts by men.

Means of the attributes:

Descriptives

ATTRIBUTES

95% Confidence Interval for

Mean

N Mean Std. Deviation Std. Error Lower Bound Upper Bound Minimum Maximum

FABRIC 40 5.85 .893 .141 5.56 6.14 4 7

COLOUR 40 5.88 .939 .148 5.57 6.18 3 7

BRAND NAME 40 5.18 1.500 .237 4.70 5.65 1 7

VARIETY 40 5.75 .954 .151 5.44 6.06 3 7

AVAILABILITY 40 5.28 1.132 .179 4.91 5.64 3 7

QUALITY 40 5.98 .800 .127 5.72 6.23 4 7

PRICE 40 5.93 .944 .149 5.62 6.23 4 7

Total 280 5.69 1.078 .064 5.56 5.82 1 7

The most important attribute is quality followed by price, colour, fabric, variety,

availability and brand name. There is very minute difference in the means of quality and

price which shows that the value for money which consumers pay are also an important

factor. Even the fabric and colour is very important. The least important attribute is the

brand name which influences the purchase of formal shirts.


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Performance of the attributes:

ONE WAY ANOVA

FABRIC:

Null hypothesis(H0): There is no variance of preference between the brands Alle n Solly,

Peter England, Provogue, Van Heusen, Louis Phillipe, John Players when the factor

fabric is taken into consideration.

Alternative Hypothesis(H1): ): There is variance of preference between the brands Allen

Solly, Peter England, Provogue, Van Heusen, Louis Phillipe, John Players when the

factor fabric is taken into consideration.

ANOVA

BRANDS


Between Groups 49.471 5 9.894 6.933 .000

Within Groups 333.925 234 1.427

Total 383.396 239


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Interpretation:

The sig value is less than 0.05 thus we reject the null hypothesis, which implies that

there is a difference in the preferences between the brands when the fabric is

considered.

Means of the Brands:


N Minimum Maximum Mean Std. Deviation

ALLENSOLLY 40 3 7 5.80 1.067

PETERENGLAND 40 3 7 5.05 1.197

PROVOGUE 40 2 7 4.82 1.318

VANHUESEN 40 3 7 5.77 1.121LOUISPHILLIPE 40 2 7 5.95 1.197

JOHNPLAYERS 40 2 7 4.97 1.250

Valid N (listwise) 40

The most preferred brand is Louis Phillipe followed by Allen Solly when the attribute

fabric is considered The mean of Louis Phillipe is 5.95 and of Allen Solly is 5.80. Thus

by looking at the means we see that the least preferred brand in terms of fabric is John

Players while others have very little variance.

Colour:

Null hypothesis(H0): There is no variance of preference of brands i.e. Allen Solly, Peter

England, Provogue, Van Heusen, Louis Phillipe, John Players when the attribute colour

is taken into consideration.

Alternative Hypothesis(H1): There is variance of preference of brands i.e. Allen Solly,

Peter England, Provogue, Van Heusen, Louis Phillipe, John Players when the attribute

colour is taken into consideration.


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ANOVA

BRANDS


Between Groups 15.688 5 3.138 2.313 .045

Within Groups 317.375 234 1.356

Total 333.063 239

Interpretation:


there is a difference in the preference of the brands when the attribute colour is

considered.

Means of the brands:



Allensolly 40 3 7 5.63 1.005

Peterengland 40 2 7 5.28 1.301

Provogue 40 3 7 5.43 .958

Vanhuesen 40 3 7 5.75 1.032

Louisphilli pe 40 2 7 5.58 1.217

Johnplayers 40 1 7 4.98 1.405


The most preferred brand is Van Heusen followed by Allen Solly when the attribute

color is considered. The mean of Van Heusen is 5.75 and mean of Allen Solly is 5.63.

This means that there is more variety of colours to choose from the brand Van Heusen

and then Allen Solly while others have few range of colours.

Brand Name:

Null hypothesis (H0): There is no variance of preference of brands i.e. Allen Solly, Peter

England, Provogue, Van Heusen, Louis Phillipe, John Players when the attribute colour



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colour is taken into consideration.

ANOVA

BRANDS


Between Groups 25.521 5 5.104 3.255 .007

Within Groups 366.975 234 1.568

Total 392.496 239

Interpretation:


there is a difference in the preference of the brands when the attribute brand name is

considered.




AllenSolly 40 3 7 5.63 1.192

Peterengland 40 2 7 5.32 1.403

Provogue 40 3 7 5.47 1.281

VanHeusen 40 2 7 6.15 1.001

LouisPhil lipe 40 2 7 5.93 1.289

JohnPlayers 40 2 7 5.23 1.310


The most preferred brand is Van Heusen followed by Louis Phillipe when the attribute

Brand Nam e is considered.. The mean of Van Heusen is 6.15 and mean of Louis

Phillipe is 5.93. When we look at the mean of Allen Solly i.e.5.63 we see that there is a

significant amount of difference between Allen Solly and the other top two brands

mentioned. Thus the brand name Van Heusen and Louis Phillipe is more popular

than Allen Solly or we can say that when brand name is considered people prefer Van

Heusen and Louis Phillipe over Allen Solly.


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Variety:


England, Provogue, Van Heusen, Louis Phillipe, John Players when the attribute variety


Alternative Hypothesis(H1): There is no variance of preference of brands i.e. Allen Solly,Peter England, Provogue, Van Heusen, Louis Phillipe, John Players when the attribute

variety is taken into consideration.

ANOVA

BRANDS


Between Groups 12.933 5 2.587 1.926 .091

Within Groups 314.250 234 1.343

Total 327.183 239

Interpretation:

The sig value is more than 0.05 thus we retain the null hypothesis, which implies that

there is no difference in the preference of the brands when the attribute variety is

considered.

Availability:


England, Provogue, Van Heusen, Louis Phillipe, John Players when the attribute

availability is taken into consideration.



availability is taken into consideration.


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ANOVA

BRANDS


Between Groups 8.071 5 1.614 1.171 .324

Within Groups 322.425 234 1.378

Total 330.496 239

Interpretation:


there is no difference in the preference of the brands when the attribute availability is

considered.

Quality:


England, Provogue, Van Heusen, Louis Phillipe, John Players when the attribute quality




quality is taken into consideration.

ANOVA

BRANDS


Between Groups 27.521 5 5.504 5.367 .000

Within Groups 239.975 234 1.026

Total 267.496 239

Interpretation:


there is a difference in the preference of the brands when the attribute quality is

considered.


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Descriptives

BRANDS

95% Confidence Interval for

MeanStd. Std.

N Mean Deviation Error Lower Bound Upper Bound Minimum Maximum

ALLEN SOLLY 40 5.93 .944 .149 5.62 6.23 3 7

PETER 40 5.43 1.279 .202 5.02 5.83 3 7

ENGLAND

PROVOGUE 40 5.45 1.131 .179 5.09 5.81 3 7

VAN HEUSEN 40 6.13 .853 .135 5.85 6.40 4 7

LOUIS PHILLIPE 40 6.18 .747 .118 5.94 6.41 4 7

JOHN PLAYERS 40 5.38 1.030 .163 5.05 5.70 3 7

Total 240 5.75 1.058 .068 5.61 5.88 3 7

The most preferred brand is Louis Phillipe followed by Van Huesen and then Allen Solly.

There is very minute difference between the means of Louis Phillipe and Van Heusen.

The mean of Louis Phillipe is 6.18 and mean of Van Heusen is 6.13.

We know that quality is a very important attribute when we go for purchasing clothes.

Thus among the brands Allen Sollys quality of shirts are good but it has to work on

more to reach the marks of Van Heusen and Louis Phillipe.

Price:


England, Provogue, Van Heusen, Louis Phillipe, John Players when the attribute price




price is taken into consideration.


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ANOVA

BRANDS


Between Groups 5.683 5 1.137 .718 .610

Within Groups 370.300 234 1.582

Total 375.983 239

Interpretation:


there is no difference in the preference of the brands when the attribute price is

considered.

Thus there is no difference in the range of prices of shirts offered by these brands. To

be more specific the value for money which the customers for these brands are justified.

SUMMARY OF FINDINGS:

In Correlation analysis (descriptive statistics) we found that that people are most

satisfied and give more importance to the quality of the shirt since the mean is the

highest we are not considering the overall satisfaction here.

In the correlation analysis between overall satisfaction and other attributes we found

that there is high correlation between overall satisfaction with comfort level, variety and

quality. On the other hand there is a positive but low correlation between overall

satisfaction ease of availability and design. There is no correlation or association

between overall satisfaction and fabric.

In the Cronbachs alpha test, we found that the scale is reliable and all the factors can

be clubbed together to find the effect of those attributes on the overall satisfaction.

In Regression analysis we found that 81.6% variation in the overall satisfaction is due to

the variation in quality fabrics and comfort level since their significance level is less than

0.05. Therefore the variation in the overall satisfaction is maximum due to comfort level

and least due to fabrics.


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ANNEXURES

ALLEN SOLLY SURVEY

Valued Customer,

Please take a few minutes to fill this Customer Satisfaction and Positioning Survey being conducted by

us. Your comments will help us gauge how well our products are performing and help us ascertain

how to improve our products and serve you better.

SECTION A

Please rate your satisfaction with each of the following service factors provided by Allen Solly:

Extremely

Dissatisfied Satisfied

1. Overall Satisfaction 1 2 3 47

2. Comfort Level 1 2 3 4

73. Ease of availability 1 2 3 4

74. Variety 1 2 3 4

75. Quality of shirts 1 2 3 4

76. Design/patterns of shirts 1 2 3 4 5

7. Fabrics 1 2 3 47

8. Have you found any defects while making a purchase? Yes No

Extremely

Dissatisfied Satisfied

9. If you have, how satisfied are you

with the way it was resolved? 1 2 3 4 5 6

10. What areas could be worked on to improv e your satisfaction with Allen Solly?

_____________________________________________________________________________________

_____________________________________________________________________________________


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SECTION B

11. How important are the following factors/attributes How do you perceive the following

to you when you go to purchase a formal shirt? companies perform on this attribute?

Least Most

ExcellentImportant Important

1. Fabric 1 2 3 4 5 6 7 Allen Solly 1 2 3

6 7Peter England 1 2 3 4 5 6 7

Provogue 1 2 3 4 5 6 7

Van Heusen 1 2 3 4 5 6 7

Louis Phillipe 1 2 3 4 5 6 7

John Players 1 2 3 4 5 6 7

2. Colour 1 2 3 4 5 6 7 Allen Solly 1 2 3

6 7Peter England 1 2 3 4 5 6 7Provogue 1 2 3 4 5 6 7

Van Heusen 1 2 3 4 5 6 7



3. Brand 1 2 3 4 5 6 7 Allen Solly 1 2 3

6 7 Name Peter England 1 6 7Provogue 1 2 3 4 5 6 7

Van Heusen 1 2 3 4 5 6 7



4. Variety 1 2 3 4 5 6 7 Allen Solly 1 2 3

6 7Peter England 1 2 3 4 5 6 7

Provogue 1 2 3 4 5 6 7

Van Heusen 1 2 3 4 5 6 7



5. Availability 1 2 3 4 5 6 7 Allen Solly 1 2 3 47Peter England 1 2 3 4 5 6 7

Provogue 1 2 3 4 5 6 7

Van Heusen 1 2 3 4 5 6 7




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6. Quality 1 2 3 4 5 6 7 Allen Solly 1 2 3 4

7Peter England 1 2 3 4 5 6 7

Provogue 1 2 3 4 5 6 7

Van Heusen 1 2 3 4 5 6 7



7. Price 1 2 3 4 5 6 7 Allen Solly 1 2 3 47Peter England 1 2 3 4 5 6 7

Provogue 1 2 3 4 5 6 7

Van Heusen 1 2 3 4 5 6 7



SECTION C

12. Since when have you been using Allen Solly?

1. Less than 1 year

2. 1-3 years

3. 3-5 years

4. More than 5 years

13. How did you get to know about it?

1. TV Ads

2. Print Ads

3. Friends and Family

4. Radio5. Bill Boards

14. Apart from Allen Solly, which is the next best brand? _____________________________

15. Would you switch to that brand? A. Yes B. No

16. If yes, for what reasons?

______________________________________________________________________________

______________________________________________________________________________

17. Age: ___________

18. Occupation: _____________

Documents

54113814 Mentoring Live Project