Research Methodology

Research Methodology Synopsis
On
Assessing the market potential for customized bra in India
Submitted by
Bittu Kumar
Komal Gajjar
Radhe Kumar
Shubham Singh
Under the supervision of
Prof. Jagriti Mishra
Submitted to
Department of Fashion Technology (DFT)
National Institute of Fashion Technology (NIFT)
(Ministry of Textiles, Govt. of India)
GH-0 Road, Behind Infocity
Gandhinagar 382007. Gujarat
http://www.nift.ac.in
5th
December, 2018
1

Contents
Contents...........................................................................................................................................................2
1.Background of the research..........................................................................................................................3
2.Problem Definition........................................................................................................................................3
3.Review of Literature......................................................................................................................................3
4.Research Gap:...............................................................................................................................................5
5.Objective:......................................................................................................................................................6
6.Methodology:...............................................................................................................................................6
7.Scope of the study:.......................................................................................................................................7
8.Chi-Square Test.............................................................................................................................................7
8.1.Chi-Square test 1....................................................................................................................................8
8.2 Chi Square test 2....................................................................................................................................9
9.Logistic Regression......................................................................................................................................11
10.Findings:-...................................................................................................................................................19
Annexure – I...................................................................................................................................................19
Bibliography...................................................................................................................................................23
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Assessing the market potential for customized bra in India
1. Background of the research
Under-garments are considered to be the second skin for human beings. Lingerie being the closest
thing to a woman’s skin is of utmost vitality regarding aspect of her personal comfort. Fitting and
the materials from which the lingerie is made are of high importance in its comfort factor. Usually,
lingerie is made of soft fabrics like cotton, hosiery, satin and silk. A well fitted lingerie gives
women self-confidence on the inside as well as the outside. But, do all of them get to wear a
lingerie that really fits them well? The answer is a big – “NO”! Ill-fitting lingerie is one of the
biggest problems being faced by other half of the population across the country. It’s a problem
which most of the women hesitate to discuss in open forums due the cultural taboo associated with
it. It’s high time that this menace be addressed for betterment of Indian women.
2. Problem Definition
Indian lingerie manufacturers & retailers have mostly copied lingerie sizes and measurements from
the western world adding little modifications to it. The fact being that Indian is an extremely
diverse country having people from several ethnic races with different body sizes supports the
argument that western sizes can’t be applicable to such a demographically diverse set of people.
Fitting for garments as privy as lingerie is of great importance for the overall well-being of women
in this country. This research is focused on study the market potential and acceptability of
customized lingerie products.
3. Review of Literature
India lingerie market is projected to grow at a CAGR of over 24% during 2018-2023 During
2006-09, the lingerie market has grown at a CAGR of 15.8 per cent. Main factors affecting the
demand are adoption of western culture and lifestyle. Expenditure on personal appearance is
increasing and fashion trends in these segments are changing. (India-lingerie-market, 2017). The
innerwear category has broadened from being a basic requirement to designer wear with
emphasis on styling and comfort. According to a Technopak report, the innerwear category will
grow at a CAGR of 14 per cent to reach Rs. 31,306 crores in 2021 and Rs.60,277 crores in 2026.
(Krishna, 2017)
India’s lingerie market is currently valued at $3 billion. In the next few years the market value is
projected to jump to $5 billion. The Indian lingerie market is making a remarkable growth and the
retailers are realizing that lingerie market have a higher profit margin as compared with other
regular apparels. The average selling price (ASP) of lingerie varies from INR 37 per piece to INR
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1,029 per piece. The Indian lingerie industry constitutes 5.1 per cent of the total Indian apparel
market and 15.8 % of the overall women apparel market. The unorganized sector is worth INR 20
billion. (recent-trends-in-indian-lingerie-market, 2018)
Indian market in these segments is mostly unorganized. So there is a huge potential for a scope
of customized lingerie market. Indians buy lingerie more as a necessity and purchase of the
product is not well thought. This can be changed by customized lingerie. Because of it they will
start thinking over the product which they are going to buy. Recent trend in lingerie (recent-
trends-in-indian-lingerie-market,2018)
With international brands domestic and national brands too are pulling up to tap this market by
offering stylish and trendy innerwear. Karan Behal, Founder & CEO, Pretty Secrets, maintains,
“The lingerie market in India can be classified in luxury, premium, mid - market and mass market
segment. The major share of lingerie market is held by the mid-market segment. The retail
environment getting more sophisticated and offering the best buying experience to the consumers,
the premium and super premium segments will get support for further growth.”
E-commerce has been a game changer or rather a boon for this category because of privacy being
offered online selling portals. Considering the awkwardness most women feel while going and
buying lingerie from physical stores, manned by salesmen, online shopping is a much better way to
buy lingerie. It allows you to shop from your comfort zone and also allows you to browse through
various styles and designs. (Neha Kant, Clovia), Clovia provides options like the ‘fit test’ that helps
one calculate the right size.
The lingerie market is witnessing trends in terms of fabric design, finish application, introduction of
wider colour choices and fitting. Karan Behal says, “As a fashion statement and ‘feel incredible’
factor, lingerie is gaining more and more significance among Indian audience. Innerwear today
makes a big difference to a woman’s wardrobe. Lingerie buying choices are now more about
feeling and being empowered. The younger generation today is more confident of them and are not
afraid to experiment with colours, cuts and designs. This means a greater emphasis on rich fabrics,
laces, embroideries and brighter, more daring colours can be offered to the customers. Pretty
Secrets, have pop prints, colours and new designs. Campaign #Redefine Basics designed for
targeting young customers with experimenting with colours instead of whites and the dull. The
Indian women are now letting go of their inhibitions and are keen on trying different styles other
than the regular whites. Consumers are constantly evolving in their tastes and preferences. While
the basics of nude and black are must haves in any lingerie wardrobe, the younger consumer is
more experimental and loves variety, ranging from colourful choices to experimenting with prints
and different textures,” clarifies Smita Murarka from Amanté.
Also, India has become more open to paying for quality and value- added products than ever
before. According to survey study by BCG which was conducted in 2016 suggests that 30 per cent
of consumers in India are willing to spend more on products that they perceive are “better”—a
much higher percentage than is found in more developed markets such as the US, Germany, and the
UK. In apparel and intimate wear segment, affluent consumers spend 5 times more than they use to
in the last 5 years. (Karan Behal, Pretty Secrets)
From a basic brassier to one specially designed for a t-shirt, blouse, etc., the sub-categories are
expanding. Also the colours and the fabrics too are changing very much, it ranges from velvet to
lace and many more options. In this kind of situation there are big opportunities of customization of
the lingerie items. These days lingerie is inspired by recent RTW trends, from bodysuits as tops to
night-gown slips as dresses, lingerie being worn in interesting ways these days.
In terms of elements/ embellishments being used in innerwear, Smita Murarka informed that lace,
crochet, jacquard fabrics are the quintessential favourite. Shimmer and shine fabrics are perfect for
the festive season. Additional detailing like charms, bows, contrast straps add a personalized
element of style to every item of lingerie. Elements like metal rings, chains, leather straps, etc. too
are in trend.
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There are so many health benefits associated with running. Every woman has different need for
sports bra – some people need it for compression, some need for more cupping, and some for both.
8 out of 10 women into running, wear the wrong sports bra.
(cazaro-lingerie, 2017)
80% of the women in India wear the wrong bra size. Not only will a major bra fail look bad, but it’s
far healthier and more comfortable to get the right fit. Whereas a lot of women think the tighter are
the better. Bra should be at the same height all around your chest. (The-struggle-to-find-the-right-
size-.html, 2017) Fit is the biggest problem in lingerie wear, Bra which is tugging at it, compressing
the wrong nerves, creating not so wise pressure spots. Wrong fit poses multiple threats to health.
Breast pain is the most common ill effects of wearing a wrong bra size. Wrong bra size can also
make you experience frequent back ache & discomfort. This usually occurs in women with large
breast size using a bra that does not exactly fit you. If your bra is too tight, it can also exert too
much pressure on your rib cage. So if you are wearing a smaller sized bra, then be prepared to
suffer from back pain. Shoulder and neck pain, Blockage of the lymph nodes, Ruining of natural
posture, Threat of breast cancer, skin abrasions
Indian leading lingerie brand Zivame has come up with fitting room concept in which customers
can walk in and enter their details on a tab for the professional fitters and experts. After this, they
are measured and fitted and can then pick and choose the kind of bra they want to try out. If
convinced, they can make an online purchase right there or can decide to later on. The fitting rooms
have over 16 different sizes and measurements shown with different categories and types.
(https://yourstory.com)
Researchers found that impulse buyers usually do not set out with the specific purpose of visiting a
certain store and purchasing a certain item; the behavior occurs after experiencing an urge to buy
(Beatty & Ferrell, 1998), and such behaviors are influenced by internal states and
environmental/external factors. Research findings suggest that impulse buying accounts for
substantial sales across a broad range of product categories (Bellenger, Robertson & Hirschman,
1978; Cobb & Hoyer, 1986; Han, Morgan, Kotsiopulos, & Kang-Park, 1991; Kollat & Willet,
1967; Rook & Fisher, 1995; Weinberg & Gottwald, 1982).
This is also the best time to innovate in product as the customer is far more demanding and aware
than they ever were. The modern woman is increasingly working and stepping out of homes in
diverse career options. These evolved women need more evolved wardrobe solutions and therefore
need for multiple types of lingerie has become inevitable. For the evolving Indian woman, social
media have been key change drivers to make informed choices. Social media has helped in
educating the consumer on benefits of good lingerie.
4. Research Gap:
There is a gap in the market that presents opportunity for an approach to capitalize on customized
lingerie products with all the specifications, colour variations and all possible fabric options
offering with proper buying guidance in accordance with their need and want. Parameters for
customized lingerie products will be set according to consumers’ willingness to buy the customized
product and how much profitable it will be.
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5. Objective:
• To study the need of customized lingerie and assessing the market potential for customized
lingerie in India with demographical preferences and provide a perfect product with
customization in size, fit, color, fabric, cut and trims.
6. Methodology:
• Research Design:
Research design is based on descriptive method.
There are two ways research can be done for this descriptive research project, and they are:
• In-depth Interviews - Defined as a brief interview or discussion with an individual
about the topic.
• Survey - A structured questionnaire would be designed in order to take the responses of
consumers with respect to customised lingerie.
• Data Sources:
 Primary:
Primary survey will be conducted to assess the market structure, size, and growth trends in
Ahmedabad & Gandhinagar. The primary survey will be carried out through interview based on
structured questionnaires with college students and local residents.
 Secondary:
The secondary research will be carried out to analyse top brands on the basis of their current
offerings & positioning in the market.
• Questionnaire Design:
Fixed alternative question: It provides multiple choice questions
Form of question response: Multichotomous questions having a range of responses as in
multiple choice
Number of questions asked will be between 10 to 15.
• Sampling Design: Sample size, frame, element, technique
Sample size will consist of 100 consumers under this study.
In this survey, non-probability sampling method will be used under which convenience
sampling techniques will be used to get the required sample size. This technique is used to draw
conclusions about the whole population by studying just a small group of individuals and
convenience sampling will help us gather responses from people as per our convenience saving
6

time but being the representative of the whole population will give us correct results for the
study.
7. Scope of the study:
According to the Census of India, 2011; India is home to 587 million females. This is a huge set of
population having a common need for clothing. Lingerie is an essential part of a woman’s
wardrobe. This research project aims to
• Find out if women are willing to try customized lingerie
• Identify the problems faced by women with their lingerie
• Shortlist problems & provide some solutions towards development of a model to provide
customized lingerie
• This research would be conducted for 3 months in Gandhinagar & Ahmedabad.
8. Chi-Square Test
Introduction
The Chi Square statistic is commonly used for testing relationships between categorical variables.
The null hypothesis of the Chi-Square test is that no relationship exists on the categorical variables
in the population; they are independent.
First, Chi-Square only tests whether two individual variables are independent in a binary, “yes” or
“no” format.
How does the Chi-Square statistic work?
The Chi-Square statistic is most commonly used to evaluate Tests of Independence when
using a cross tabulation. Cross tabulation presents the distributions of two categorical variables
simultaneously, with the intersections of the categories of the variables appearing in the cells of the
table. The Test of Independence assesses whether an association exists between the two variables
by comparing the observed pattern of responses in the cells to the pattern that would be expected if
the variables were truly independent of each other. Calculating the Chi-Square statistic and
comparing it against a critical value from the Chi-Square distribution allows the researcher to
assess whether the observed cell counts are significantly different from the expected cell counts.
The calculation of the Chi-Square statistic is quite straight-forward and intuitive:
Where, o = the observed frequency (the observed counts in the cells)
and e = the expected frequency if NO relationship existed between the variables.
As depicted in the formula, the Chi-Square statistic is based on the difference between what is
actually observed in the data and what would be expected if there was truly no relationship
between the variables.
7

8.1. Chi-Square test 1
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
6. What is the shape of
your breasts? * 18.
How much can you
spend for such a product?
100 100.0% 0 0.0% 100 100.0%
9. How do your breasts
rest in your bra? * 18.
How much can you
spend for such a product?
100 100.0% 0 0.0% 100 100.0%
6. What is the shape of your breasts? * 18. How much can you spend for such
a product?
HO: The willingness of women to buy customized bra does not depends on the shape
of breasts.
H1: The willingness of women to buy customized bra depends on the shape of
breasts.
Crosstab
Count
18. How much can you spend for such a
product?
Total3 1 2 0
6. What is the shape of
your breasts?
1 2 11 5 30 48
2 0 6 3 5 14
0 2 13 6 17 38
Total 4 30 14 52 100
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
8

Pearson Chi-Square 5.710a
6 .456
Likelihood Ratio 6.235 6 .397
N of Valid Cases 100
a. 5 cells (41.7%) have expected count less than 5. The minimum
expected count is .56.
Symmetric Measuresa
Value
a. Correlation statistics are
available for numeric data only.
Hence as given in the table above table relation is found significant. Here chi square (df=6 ,
N=100). Thus we accept null hypothesis as the p value is more than 0.05.
8.2 Chi Square test 2
9. How do your breasts rest in your bra? * 18. How much can you spend for
such a product?
HO: The willingness of women to buy customized bra does not depends on the way
breasts rest in a bra.
H1: The willingness of women to buy customized bra depends on the way breasts
rest in a bra.
Crosstab
Count
18. How much can you spend for such a
product?
Total3 1 2 0
9. How do your breasts
rest in your bra?
2 3 14 4 24 45
3 1 3 3 7 14
1 0 5 6 8 19
0 0 8 1 13 22
Total 4 30 14 52 100
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
9 .268
9

Cases
Valid Missing Total
N Percent N Percent N Percent
2. How well does your
bra fit? * 17. Are you
willing to pay a bit more for a
customized bra?
100 100.0% 0 0.0% 100 100.0%
HO: The willingness of women to buy customized bra for a bit more does not
depends on their current satisfaction level with their bra.
H1: The willingness of women to buy customized bra for a bit more depends on their
current satisfaction level with their bra.
2. How well does your bra fit? * 17. Are you willing to pay a bit more for a
customized bra? Crosstabulation
Count
17. Are you willing to pay a bit
more for a customized bra?
Total1 0
2. How well does your
bra fit?
1 0 2 2
2 1 7 8
1 16 64 80
0 1 9 10
Total 18 82 100
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
3 .740
10

Symmetric Measuresa
Value
a. Correlation statistics are
available for numeric data only.
9. Logistic Regression
Logistic regression is used to predict a categorical (usually dichotomous) variable from a set of
predictor variables. With a categorical dependent variable, discriminant function analysis is
usually employed if all of the predictors are continuous distributed.
Unweighted Casesa
N Percent
Selected Cases Included in Analysis 100 100.0
Missing Cases 0 .0
Total 100 100.0
Unselected Cases 0 .0
Total 100 100.0
a. If weight is in effect, see classification table for the total number of
cases.
Dependent Variable Encoding
Original Value Internal Value
1 0
0 1
Categorical Variables Codings
Frequency Parameter coding
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(1) (2) (3) (4) (5)
8. What is
your best fitting cup
size of bra?
1 13 1.000 .000 .000 .000 .000
0 2 .000 1.000 .000 .000 .000
2 41 .000 .000 1.000 .000 .000
3 22 .000 .000 .000 1.000 .000
4 12 .000 .000 .000 .000 1.000
5 7 .000 .000 .000 .000 .000
6 3 .000 .000 .000 .000 .000
13. Do your
caps runneth over?
Back 6 1.000 .000 .000 .000
Cleavage 15 .000 1.000 .000 .000
No spill 49 .000 .000 1.000 .000
Sides 13 .000 .000 .000 1.000
Underarm 17 .000 .000 .000 .000
15. Do you face
problems in fit
related to bra when
you go out to buy
one?
Always 12 1.000 .000 .000
Never 4 .000 1.000 .000
Often 29 .000 .000 1.000
Sometime
55 .000 .000 .000
5. How are
your shoulder
straps?
Digging 16 1.000 .000 .000
Slip sli 19 .000 1.000 .000
Slipping 14 .000 .000 1.000
They are 51 .000 .000 .000
2. How well
does your bra fit?
1 2 1.000 .000 .000
Excellen 8 .000 1.000 .000
Good 80 .000 .000 1.000
Poor 10 .000 .000 .000
10. How does
your band fit?
All band 13 1.000 .000 .000
Band fit 45 .000 1.000 .000
Band rid 11 .000 .000 1.000
Band tig 31 .000 .000 .000
12. Are you
right or left breasted
(is one bigger than
other)?
Both are 46 1.000 .000
Leftie 31 .000 1.000
Rightie
23 .000 .000
6. What is the
shape of your
breasts?
Archetyp 48 1.000 .000
Concave 14 .000 1.000
Full 38 .000 .000
11. Which hook
on your bra do you
prefer?
2 20 1.000 .000
1 49 .000 1.000
0 31 .000 .000
9. How do
your breasts rest in
your bra?
Full 45 1.000 .000
Full and 14 .000 1.000
Shallow 41 .000 .000
12

Block 0: Beginning Block
Classification Tablea,b
Observed
Predicted
more for a customized bra? Percentage
Correct1 0
Step 0 17. Are you willing to
pay a bit more for a
customized bra?
1 0 18 .0
0
0 82 100.0
Overall Percentage 82.0
a. Constant is included in the model.
b. The cut value is .500
Variables in the Equation
B S.E. Wald df Sig. Exp(B)
Step 0 Constant 1.516 .260 33.938 1 .000 4.556
Variables not in the Equation
Score df Sig.
Step 0 Variables @2.Howwelldoesyourbrafit 1.253 3 .740
@2.Howwelldoesyourbrafit(1
)
.448 1 .503
)
.178 1 .673
)
1.084 1 .298
@5.Howareyourshoulderstra
ps
3.835 3 .280
ps(1)
.007 1 .932
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ps(2)
2.930 1 .087
ps(3)
.130 1 .719
@6.Whatistheshapeofyourbr
easts
.154 2 .926
easts(1)
.035 1 .851
easts(2)
.152 1 .696
@8.Whatisyourbestfittingcup
sizeofbra
3.500 6 .744
sizeofbra(1)
.261 1 .609
sizeofbra(2)
.448 1 .503
sizeofbra(3)
.108 1 .743
sizeofbra(4)
1.517 1 .218
sizeofbra(5)
.453 1 .501
sizeofbra(6)
.570 1 .450
@9.Howdoyourbreastsrestin
yourbra
7.331 2 .026
yourbra(1)
2.631 1 .105
yourbra(2)
6.815 1 .009
@10.Howdoesyourbandfit 2.748 3 .432
@10.Howdoesyourbandfit(1) 1.076 1 .300
@10.Howdoesyourbandfit(2) 2.302 1 .129
@10.Howdoesyourbandfit(3) .000 1 .987
@11.Whichhookonyourbrad
oyouprefer
.186 2 .911
oyouprefer(1)
.068 1 .795
oyouprefer(2)
.182 1 .669
@12.Areyourightorleftbreast
edisonebiggerthanother
.892 2 .640
14

edisonebiggerthanother(1)
.807 1 .369
edisonebiggerthanother(2)
.107 1 .744
@13.Doyourcapsrunnethove
r
17.587 4 .001
r(1)
1.401 1 .237
r(2)
.898 1 .343
r(3)
.898 1 .343
r(4)
13.008 1 .000
@15.Doyoufaceproblemsinfit
relatedtobrawhenyougooutto
buyone
2.500 3 .475
buyone(1)
2.172 1 .141
buyone(2)
.138 1 .710
buyone(3)
.016 1 .900
Overall Statistics 31.447 30 .394
Block 1: Method = Enter
Omnibus Tests of Model Coefficients
Chi-square df Sig.
Step 1 Step 37.625 30 .160
Block 37.625 30 .160
Model 37.625 30 .160
Model Summary
15

Step -2 Log likelihood
Cox & Snell R
Square
Nagelkerke R
Square
1 56.654a
.314 .514
a. Estimation terminated at iteration number 20 because
maximum iterations has been reached. Final solution cannot be
found.
Classification Tablea
Observed
Predicted
more for a customized bra? Percentage
Correct1 0
Step 1 17. Are you willing to
pay a bit more for a
customized bra?
1 9 9 50.0
0
2 80 97.6
Overall Percentage 89.0
a. The cut value is .500
Variables in the Equation
B S.E. Wald Df Sig. Exp(B)
Step 1a
@2.Howwelldoesyourbrafit .788 3 .852
@2.Howwelldoesyourbrafit(1) 19.540 26913.534 .000 1 .999 306343185.380
@2.Howwelldoesyourbrafit(2) 2.357 3.236 .531 1 .466 10.558
@2.Howwelldoesyourbrafit(3) .079 2.212 .001 1 .971 1.083
ps
5.385 3 .146
16

ps(1)
-1.862 1.783 1.091 1 .296 .155
ps(2)
-2.894 1.270 5.190 1 .023 .055
ps(3)
-1.042 1.394 .559 1 .455 .353
easts
1.423 2 .491
easts(1)
-.487 1.012 .231 1 .631 .615
easts(2)
2.460 2.511 .960 1 .327 11.711
sizeofbra
1.934 6 .926
sizeofbra(1)
-18.845 19765.321 .000 1 .999 .000
sizeofbra(2)
-1.624 29549.603 .000 1 1.000 .197
sizeofbra(3)
-19.915 19765.321 .000 1 .999 .000
sizeofbra(4)
-19.264 19765.321 .000 1 .999 .000
sizeofbra(5)
-21.090 19765.321 .000 1 .999 .000
sizeofbra(6)
-18.938 19765.321 .000 1 .999 .000
@9.Howdoyourbreastsrestiny
ourbra
3.898 2 .142
ourbra(1)
1.048 1.231 .724 1 .395 2.852
ourbra(2)
-1.982 1.499 1.749 1 .186 .138
@10.Howdoesyourbandfit 3.101 3 .376
@10.Howdoesyourbandfit(1) -1.872 1.750 1.144 1 .285 .154
@11.Whichhookonyourbrado
youprefer
.078 2 .962
youprefer(1)
-.306 1.373 .050 1 .824 .737
youprefer(2)
-.304 1.167 .068 1 .794 .738
17

@12.Areyourightorleftbreaste
disonebiggerthanother
.547 2 .761
disonebiggerthanother(1)
.790 1.477 .286 1 .593 2.204
disonebiggerthanother(2)
.146 1.587 .008 1 .927 1.157
@13.Doyourcapsrunnethover 2.097 4 .718
@13.Doyourcapsrunnethover
(1)
-1.030 16105.115 .000 1 1.000 .357
(2)
-21.128 7795.193 .000 1 .998 .000
(3)
-22.209 7795.193 .000 1 .998 .000
(4)
-23.394 7795.193 .000 1 .998 .000
@15.Doyoufaceproblemsinfitr
elatedtobrawhenyougoouttob
uyone
.176 3 .981
uyone(1)
-.530 1.638 .105 1 .746 .589
uyone(2)
.084 2.069 .002 1 .968 1.088
uyone(3)
-.316 1.013 .097 1 .755 .729
Constant
45.102 21246.955 .000 1 .998
38701216331668
910000.000
a. Variable(s) entered on step 1: @2.Howwelldoesyourbrafit, @5.Howareyourshoulderstraps, @6.Whatistheshapeofyourbreasts,
@8.Whatisyourbestfittingcupsizeofbra, @9.Howdoyourbreastsrestinyourbra, @10.Howdoesyourbandfit,
@11.Whichhookonyourbradoyouprefer, @12.Areyourightorleftbreastedisonebiggerthanother, @13.Doyourcapsrunnethover,
@15.Doyoufaceproblemsinfitrelatedtobrawhenyougoouttobuyone.
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10. Findings:-
The tables include the Pseudo R², the -2 log likelihood is the minimization criteria used by
SPSS. We see that Nagelkerke’s R² is 0.514 which indicates that the model is good.
The classification table contains the classification results, with almost 89% correct
classification the model is good.
According to the table of significance, the problems which are most significant and affect the
buying decision of customized lingerie are:-
a. If the shoulder straps are slipping, sliding or digging in
b. If the breasts rest shallow or full in the bra
c. If the bands are riding up or tight
Therefore; fitting of straps, cup size and fitting of bands are key elements in which currently
customers are experiencing problems. So, by concentrating on these 3 key pain points, a good
product can be come up with.
Annexure – I
Questionnaire
Part A - Fit
1. Do you think, a well fitted bra affects your
 Personality
 Confidence
 Mood
 Aura
2. How well your bra fits?
 Poor
 Good
 Excellent
3. In which part of the bra, do you face maximum fit issues?
 Strap
 Band
19

 Cup
 Center front gore
 Wings
4. What general problems do you face while wearing a bra?
 Band is too tight
 Under wire digs into bottom
 Under wire digs in at side
 Center part digs in at chest
 No pain, all good
5. How are your shoulder straps?
 Slipping off
 Slip sliding
 Digging in
 They are fine
6. What is your shape?
 Well rounded
 Bottom happy
 Taking side
 Bottom & side
7. What is your best fitting band size of bra?
 28…….56
8. What is your best fitting cup size of bra?
 AA
 A
 B
 C
 D
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 DD
 E
 F
 FF
 G
 GG
 H
 HH
 J
 JJ
 K
9. How do your breasts rest in your bra?
 Shallow with gap
 Shallow
 Full
 Full and busting
10. How does your band fit?
 Band riding up
 Band fits fine
 Band tight
 All band are fine
11. Which hook on your bra gets?
 Tightest
 Middle
 Loosest
12. Are you right or left breasted (is one bigger than other)?
 Leftie
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 Rightie
 Both are the same
13. Do your caps runneth over?
 Cleavage
 Underarms
 Back
 Sides
 No spills, all good
Part B - Adverse Effects
14. What long term effects of ill-fitting bra are you aware of?
 Breast pain
 Sagging breasts
 Shoulder & neck pain
 Blockage of lymph nodes
 Spoilt posture
 Breast cancer
 Skin abrasions
Part C - Buying
15. Do you face problems in fit related to bra when you go out to buy one?
 Never
 Sometimes
 Often
 Always
16. Do you know about any platform where you can get your bra customized? (If, yes)
 Sites
 Tailor
17. Are you willing to pay a bit more for a customized bra?
 Yes
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 No
18. How much can you spend for such a product?
 500-1000
 1000-1500
 1500-2000
 >1500
Part D - Demographics:
19. City:
20. Age:
21. Occupation:
22. Income/family income:
Bibliography
• Zivame’s first fitting lounge. Retrieved 25 Sept, 2018.
https://yourstory.com/2015/12/pretty-laces-wine-cheese-opening-zivames-first-fitting-
lounge-bengaluru/
• Evolution & growth of lingerie market in India. Retrieved 25 Sept, 2018.
https://www.indianretailer.com/article/sector-watch/fashion/The-Evolution-Growth-of-
Lingerie-Market-in-India.a5851/
• Indian lingerie market. Retrieved 25 Sept, 2018.
https://www.techsciresearch.com/report/india-lingerie-market/1429.html
• Recent trends in Indian lingerie market. Retrieved 25 Sept, 2018.
https://www.fibre2fashion.com/industry-article/6066/recent-trends-in-indian-lingerie-
market
• The right fit marathon. Retrieved 25 Sept, 2018. https://cazaro-
lingerie.com/smartblog/7/The-Right-Fit-Marathon.html
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