A STUDY ON CONSUMER BUYING BEHAVIOR OF DECORATIVE …

ELK’S ASIA PACIFIC JOURNALS OF MARKETING AND RETAIL MANAGEMENT

ISSN 2349-2317 (Online); EAPJMRM/ISSN 0976-7193(PRINT); Volume 10 Issue 1 (2019)

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www.elkjournals.com

A STUDY ON CONSUMER BUYING BEHAVIOR OF DECORATIVE PAINTS IN GUJARAT

Dr. Pranav Desai

Assistant Professor of Faculty of Management Studies, Charotar

University of Science and Technology (charusat) CHANGA - 388 421

Dist. ANAND

Email - [email protected]

ABSTRACT

Indian paint sector is Booming! According to Indian pain association it will touch Rs. 70,875 crores by 2019-20 at

CAGR of 12.7% still the per capital consumption was lower than the developed countries it was estimated 3.34 kg in year

2014-15 but actual is only 0.5 kg. Even though there are lots of varieties are available in the different market segment

such as interior and exterior. New paint development also includes Low VOD paint, Eco-Friendly and Dust Free paint

introduced by different companies such as Asian paints and Berger paints. Hence, it was very much essential to know

what is the consumer’s buying behaviour is and consumer’s buying intension towards the decorative paint sector. The

research problem was why such a situation has come across the Indian paint sector with the objective of to examine the

relationship between purchase intention and purchase behaviour of consumers in respect of paints. The research

approach working through the deductive method and mix of both qualitative and quantitative perspectives were

functional practically.

Key Word: Consumer Buying Behaviour, Decorative Paint Industry, Consumer Belief Pattern

INTRODUCTION

Indian consumer is emotionally involved with

Paint. Colours have attractive background all

through history; the relationship of people and

Colours is over 20,000 years of age!

Numerous cave paint artworks are observer of

it. Indian paint industry starts manufacturing

of paints in 1902 and Constant R&D,

standardizing process and taking care of

quality assurance of products by main players

of pain industry like Asian Paints, Nerolac

Paints, Berger Paint and Dulux India Paints

make more choice available to customer.

Upcoming technology is introducing us Smart

Paint now! Novel Paint (Kenya) is the first to

bring in this Smart Paint to people to make life

easier and safe. Increase in per capita income

of Indian paint consumers and endeavours

with respect to producers to present enhanced

variants like Eco-Friendly paint, Dust Free and

Water Proof paints, have moved the

development of the paint showcase in India.

Worthy efforts of Indian paint companies,

their initiatives, and emerging new technology

are making The Indian paint showcase

expected that would achieve Rs.70,875 crore

by year 2019-20 from Rs.40,300 crore in

2014-15, The decorative paint Segment is

expected to observe CAGR of 12.7% and the



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industrial paint Segment CAGR of 9.5%, as

indicated by Indian Paint Association.

LITERATURE REVIEW

The standard buying behaviour is a process of

identifying the need, information search,

evaluation, purchase and post purchase

behaviour, but the consumer buying behaviour

is little differs, it measures how consumers

select, buy, use and dispose the

product/service/experience. To predict

anything about consumer is like walking on

water, but as the revolutionary actions comes

across the paint industries, it is being little

easy to have the idea about the consumer

buying behaviour.

R. Maruthi Ram, (2011) says that The Indian

paint industry brought progressive changes in

Indian industry as market introduction,

customer concentrate, usage of technologies,

new product range, competition, faster market

reaction, item dependability and even the

budgetary help to consumers. He also points

out that paint companies should meet the end

user in order to know the root problems and

search new findings.

Soumik Gangopadhyay, Pradip

Bandyopadhay, (2013) point out in their

research that there is an important role in the

choice process of customer. Further,

companies must create their product by

focussed on the features of the paints. Hence,

interior designer, dealer can recommend the

domestic paints on the basis of brand features.

Dr Devendra Kumar Pandey, Dr. Ronald

V Mani, (2013) had discussed the important

influencing factors for the growth of the

Indian paint industry such as Industrial

Growth, Heavy Infrastructure Spending, Rise

in Commercial construction, Less Seasonality,

and Rise in Income. They also stated that now

people are accepting more Eco-Friendly paints

like lead free paint, low VOC paint, and

odourless paint.

Prashant Pareek, (2016) point out that

customer is highly motivated with the view

point of the painters and dealers while they are

deciding on the paint brand. He also state that

what are those major influencing factors

during purchase of a paint brand customer

show such as advertisement, sales promotion,

positive word of mouth from relatives and

neighbours. He also believes that marketing

initiative with aggressive advertising would go

a long way and creating a strong brand image.

Rowley, (1997) in his research work had

commented that consumer buying process

offers two useful perspectives: the decision-

making process associated with consumer

buying and the factors which affect the buying

process. The author further stated that the

consumers buying process can be divided into

personal, psychological and social and cultural

factors. Consumer’s small groups, family,

reference group, social roles and status can



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also be get affect consumer responses and

influence their buying behavior.

DECORATIVE PAINT INDUSTRY

The paint industry has controlled by Asian

paints (30%) followed by, Kansai Nerolac

(20%), Berger Paints (19%), Akzo Nobel (8%)

and Shalimar Paints (2.5%). To differentiate

one from the other the Indian Paint firms has

employed techniques like implementation of

colour mixing equipment at dealer’s shop,

computerization of the supply chain, ensuring

return on investment for the dealer. Nowadays

India has more than 20,000 outlets in process,

possibly the highest for any country.

Geographical Distribution of this firms are all

major cities of India including, Mumbai,

Ahmadabad, Coimbatore, New Delhi, Surat,

Vadodara. In India 30% accounts for the

industrial paint segment in paint Industry

while the decorative paint segment accounts

for 70 % of paints sold in India. The

decorative paint industry is growing and with

technical support it is rising like a star.

Recently some researchers of Carnegie Mellon

University and Disney Research, USA founds

that they could transform 'dumb' walls into

smart ones at quite low cost - nearly USD 20

per square metre - using simple tools and

techniques, like a paint roller and other simple

tools. So, with this kind of new technologies

the industry is being smart and growing day

by day!

RESEARCH OBJECTIVE

21st century is mother of new technologies and

innovation; it comes across the paint industry

and helps it to grow further. Results are also

positive many companies are successful to

launch new verities of products in paint such

as water proof, dust proof paint and eco-

friendly paint also but as product ranges are

increases the buying behaviour and customer

belief pattern changes and hence the key

objective of research is “To examine the

relationship between purchase intention and

purchase behavior of consumers in respect of

decorative paints”.

PROBLEM STATEMENT

The Indian paint industry has witnessed more

than 115 years in the market; over year passes

the Indian paint industry successfully grab the

attention of many new international players

but the main problem is that there is not many

achievements has been with Indian Decorative

Paint Industry because of changing consumer

buying behaviour, celebrity attraction, and

changing belief pattern of customers.

RESEARCH GAP

This problem of organizations in the Paint

Industry revels that the product performance

and product quality is high priorities in mind

of customers, Preeti Khicha (2008) mention

that the paint is now become a high

https://timesofindia.indiatimes.com/topic/Carnegie-Mellon-University

https://timesofindia.indiatimes.com/topic/Carnegie-Mellon-University

https://timesofindia.indiatimes.com/topic/Disney-Research



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involvement product, A sample observation of

the market revels that few factors are

influencing major during buying decision is

making by customer.

RESEARCH METHODOLOGY

In taking data, larger consideration was paid

on essential information because of the way

this is an exact examination in nature. In this

specific circumstance, questionnaire was made

as a noteworthy technique. In addition, when

and where essential interviews were held and

perceptions were additionally made.

Research will be completed with using mix of

both qualitative and quantitative perspectives,

the survey method will be adopted for this

study. This is because the survey method

would allow one to collect quantitative data

which can be analyzed quantitatively using

descriptive and inferential statistics (Saunders,

et al, 2007). It will also used because it

reduces cost and time connected by census.

Furthermore, auxiliary sources were likewise

related for more data. For choosing the

individual example, straightforward irregular

testing strategy was utilized. It was

advantageous to get the example on similar

premise. For introducing data descriptive

statistics was used.

HYPOTHESIS

With the support of the variables identified

through factor analysis made based on the

literature review the following hypotheses are

formulated.

H0: There is no relationship between brand

image and consumer buying behaviour

H1: There is a relationship between brand

image and consumer buying behaviour.

H2: Product quality makes impact on

consumer buying behaviour.

H3: Product price makes influences on


RESEARCH MODEL

From the literature and factor analysis

following variable structure, research model is

constructed.

Variable Structure

Independent Variables Dependent Variables

Objective (refer figure 1 below).

SAMPLING PLAN

Sample Frame:

The population for the study consisted of

customers of decorative paint industry in

Gujarat.

Sample Size: A total Sample size of 300

respondents will represent as the customer of

decorative paint industry in Gujarat.

Sampling Method: By the use of simple

random sampling and systematic sampling, the

questionnaires will be administered personally

by the researcher.



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DATA ANALYSIS, FINDINGS AND

INTERPRETATION (refer table no. 1)

This table show how many valid cases (N)

were processed and how many cases had

missing values for each of our variables. Here

we have 0 missing values; the number of valid

cases is the full 300 students for both

variablesAges (refer table 2.) Here the

frequency Colum specifies that how much

observation fell into the given category. The

percentage Colum specifies the percentage of

particular categories out of all observation

such as below 25: 57/300= 19, The valid


observation in that category out of the total

number of no missing responses. This

statistical table proves that out of 300

respondent highest respondent are age of 35 to

45.

GENDER (refer table no.3) Here the





such as Male: 168/300= 56, Female:

132/300=44, The valid percentage Colum

specifies the percentage of observation in that

category out of the total number of no missing

responses. This statistical table proves that the

highest respondent was male with 168

number.

INCOME (refer table no.4) Here the





such as, below 25000: 55/300= 18.3, The valid




statistical table proves that highest income

group was between 35000 to 45000 means

39.7% out of paint customer are having good

income.

QULIFICATION (Refer table no.5) Here

the frequency Colum specifies that how much




such as below graduate: 88/300= 29.3, the

valid percentage Colum specifies the

percentage of observation in that category out

of the total number of no missing responses.

This statistical table proves that most of the

respondent was graduate means 42.3% out of

all paint customer are graduate people.

NO. OF ROOM (Refer table no. 6) Here the





such as 1 room: 59/300= 19.7, the valid



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statistical table proves that the highest

respondent having 3 room houses means

41.7% out of paint customer will consume

more litres of paint than others because of

more surfaces.

Re paint the house-how frequently repaint

the house (refer table no.7) Here the





such as 1 room: 59/300= 19.7

the valid percentage Colum specifies the



This statistical table proves that highest

frequency of re-painting the house is 4 to 5

years which says that 42.3% people are not

painting their house annually. They will either

for any occasion or wait for 5 years. number of

no missing responses. This statistical table

proves that highest frequency of re-painting

the house is 4 to 5 years which says that

42.3% people are not painting their house

annually. They will either for any occasion or

wait for 5 years.

Which Company’s Paint You Have Used at

Your Home Most Recently?

(Refer table no.8) Here the frequency Colum

specifies that how much observation fell into

the given category. The percentage Colum

specifies the percentage of particular

categories out of all observation such as Asian

paints: 150/300= 50, the valid percentage

Colum specifies the percentage of observation

in that category out of the total number of no

missing responses. This statistical table proves

that half of the respondent is using Asian

paints as paint brand.

Whom You Consult First at the Time of

Paint? (refer table no.9)

Here the frequency Colum specifies that how

much observation fell into the given category.

The percentage Colum specifies the

percentage of particular categories out of all

observation such as Retailer: 174/300= 58, the




This statistical table proves that almost 58% of

people out of all paint customers are consult

retailer first when they are willing to paint

their house.

Do You Know what is Interior and Exterior

Paints? (refer table no.10)





observation such as Yes: 249/300= 83, the



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This statistical table proves that 83% of people

have the knowledge about interior and exterior

paints.

Which Type of Interior Paints Do You

Buy? (Refer table no.11)





observation such as Enamel paints: 111/300=

37, the valid percentage Colum specifies the



This statistical table proves that highest

selected interior paint is enamel paints with

37% of selection percentage.

Which Type of Exterior Paints Do You

Buy? (refer table no.12)





observation such as Cement paints: 137/300=

45.7, the valid percentage Colum specifies the



This statistical table proves that cement paint

is the highest selected and used exterior paint

with 45.7% selection percentage.

What Is Your Expected Life of Paint?

(Refer table no.13) Here the frequency

Colum specifies that how much observation

fell into the given category. The percentage

Colum specifies the percentage of particular

categories out of all observation such as Less

than 1-year paints: 174/300= 58, the valid




statistical table proves that 58% of people are

expecting that their paint’s durability is less

than one year.

Which Type of Guidance Do You Expect

from The Paint Company? (Refer table

no.14) Here the frequency Colum specifies

that how much observation fell into the given

category. The percentage Colum specifies the


observation such as Provide Details on the

New Product Development and Innovations:

192/300= 64, the valid percentage Colum

specifies the percentage of observation in that

category out of the total number of no missing

responses. This statistical table proves that

64% of people are expecting guidance that

company should provide detail on new

products.

Recalling paint brand advertisement and

identifying brand by brand ambassador

(Refer table no. 15) This is

the Statistics table. This table show how many



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valid cases (N) were processed and how many

cases had missing values for each of our

variables. Here we have 0 missing values; the

number of valid cases is the full 300 students

for both variables.

Recall the Paint Brand) ‘Clean Air

Beautiful Homes’, ‘Royal Atmos’, Deepika

Padukone (Refer table no. 16)





observation such as Yes: 208/300= 68.6, the




This statistical table proves that 69.3% of

people are able to recall the ad for Asian

paints when they use Deepika in their ad.

Recall the Paint Brand) ‘Ghar Bulake To

Dekho’, ‘HD Colour', Shah Rukh Khan

(Refer table no.17)





observation such as Yes: 206/300= 68, the





people are able to recall the ad for Nerolac

when they use Shah Rukh in their ad.

Recall the Paint Brand) ‘Toh Chamak

Rahe Ho Tum’, ‘Velvet Touch’, Farhan

Akhtar (Refer table no.18)










people are able to recall the ad for Dulux

paints when they use Farhan in their ad.

Recall the Paint Brand) ‘Duniya Dekhegi

Jab SILK Se Saje Duniya’, ‘Deewaron Se

Nazar Nahi Hat-Ti’, ‘SILK’ Katrina Kaif

(refer table no.19)










people are able to recall the ad for Berger

paints when they use Katrina in their ad.



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Recall the Paint Brand) ‘Barrish Ko Aane

Do’, ‘Barkha’, ‘Waterproofing Vala

Exterior Paint’ Ranbir Kapoor (Refer

table no.20)

Here the frequency Colum specifies that

how much observation fell into the given

category. The percentage Colum specifies the






This statistical table proves that 72% of

people are able to recall the ad for Asian

paints when they use Ranbir in their ad.

Which Paint Brand Will You Select Next

Time (Refer table no.21)





observation such as Asian Paints: 89/300=

29.4, the valid percentage Colum specifies the




people are interested into purchasing Asian

Paints and 30.3% people will go with Berger

Paints.

KMO and Bartlett’s Test (Refer table

no.22)

Kaiser-Meyer-Olkin (KMO) Test is a measure

of how suited your data is for Factor Analysis.

The test measures sampling adequacy for each

variable in the model and for the complete

model. The statistic is a measure of the

proportion of variance among variables that

might be common variance. The lower the

proportion, the more suited data is to Factor

Analysis.

• KMO returns values between 0 and 1.

A rule of thumb for interpreting the

statistic

• KMO values between 0.8 and 1

indicate the sampling is adequate.

• KMO values less than 0.5 indicate the

sampling is not adequate and that

remedial action should be taken.

• KMO Value of 0.706 suggests that

factor analysis can be use for further

analysis

Moreover, Bartlett’s test checks, whether there

is any correlation exists between variable or

not.Bartlett’s test with a significance value of

0.000 indicates that the alternate hypothesis is

accepted which states that there is co-relation

exists among various variables. Further, for

interpretation of new expected factors, 0.5 is

considered as a cut-off value.

This table shows you the actual factors that

were extracted. If we look at the section

labelled “Rotation sums of squared loading” it

shows you only those factors that met cut-off



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of criterion (extraction method) so, here in this

case there were nine factors with eigenvalue

greater than one.

The % of “variance” Colum tells you how

much of the total variability can be accounted

for by each of these summery scales or factors

Descriptive statistics are useful for describing

the basic features of data. The Expressive

insights suggest a basic quantitative outline of

an informational index that has been gathered.

It causes us comprehend the investigation or

informational index in detail and lets us know

all that we have to put the information in

context. Here the table shows the Mean,

Standard Deviational and Analysis Value.

Extraction Method: Principal Component

Analysis. Rotation Method: Varimax with

Kaiser Normalization. a Rotation converged in

11 iterations. (Refer table no.23)

Here we can see that the slop of the curve

level out after just One factors, rather than

nine. Decorative paint industry- Co-Relation

Analysis {refer table no.24) Regression

Correlation analysis is outcome of identifying

the relationship among dependent variable and

one or more independent variables. In this

analysis the dependent variable is what paint

brand will select the customer simple ‘paint

brand selection’ for next time.

One of nine variables, seven variable such as

past experience, dealer suggestions price,

quality, trust, advertisement and discount

offers are more related to the dependent

variable. Let’s know further analysis in detail.

1. Past Experience: This independent variable

is co-related with the dependent variable

purchase decision of last purchased paint

brand. And it affects much during the

customer is making the buying decision.

2. Suggested by Dealers/Painters: Customers

will always listen to the dealers as well as

painters, and their final decision. Hence, it is

correlated with the purchase decision of

consumer.

3. Price: Price is another important factor

while customers purchase the paint. It is

correlated with the purchase decision and the

consumer’s belief pattern.

4. Quality: Many big businessmen say that

never play with quality. Quality is another

most observed factor during the paint purchase

decision and it is correlated with the paint

purchase decision.

5. Trust on Brand Name: The trust on brand

is obviously correlated with the dependent

variable the paint purchase decision.

CONCLUSION/MANAGERIAL

APPLICATIONS

From the analysis of the gathered data it can

be say that the consumer buying behaviour in



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highly influenced with the price, brand name

and dealers & painters too. As per the test

analysis, It was proven that there is a

relationship between the price factors and

buying behavior & suggestions of dealers and

painters and consumers belief pattern during

the selection of decorative paints.

• It is understood that consumers worry

about the quality of the paints. And

also recalls the television

advertisements and celebrity

endorsement help to change their


• Though it is so, another evident thing

is that other than quality, a greater

place is given to brand image that there

is a positive relationship between the

dealer and the buying behavior.

• More specifically, as per the results the

house owners are concern about price

and quality of paint, mostly recalls the

celebrity they watch on advertisement,

and they almost accept the suggestions

given by dealers, painters and nearby

reference group.

• Accordingly, it can be concluded that

whatever the price and quality of the

paint will be but consumers mostly

consider brand name, celebrity

endorsement, and durability, quality of

paint brand. Hence, paints companies

should focus on this parameters and

factors to perform better in the

Decorative Paint Industry of Gujarat.

REFERENCES

[1.] Arnold, D. (2002). "Seven rules of

international distributors" . Harvard business

reviews .

[2.] Howard, J.A. sheth, J.N. (1969). "The

Theory of Buyer behavior" Loves, J.M.S.

Essentials in behaviour

[3.] Pandey, D. D., & DR. Ronald v Mani.

(2013). “Influencers and their impact on

decorative paint trade”. International journal of

marketing, financial services & management

research .

[4.] Pareek, P. (2016). A study on

perception of end-users towards various paint

brands in Ahmadabad and north Gujarat.

[5.] Pecotich, A. a. (2007 ). "Global

branding, country of origin of enterprise".

[6.] Perner, L. (2008). "Consumer behavior:

The psychology of Marketing.

[7.] Peter, J. a. (2004). "Consumer behavior

and marketing strategy Wells".

[8.] Ram, R. M. (2011). A study of

competitiveness in Indian paint industry.

[9.] Soumik Gangopadhyay, P. B. (2013).

Choice of decorative paints: recommendation

of interior designer and dealers, an opinion

survey of berger paints limited, kolkata. .

International Letters of Social and Humanistic

Sciences .

ELK’S ASIA PACIFIC JOURNALS OF MARKETING AND RETAIL

MANAGEMENT


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LIST OF FIGURES:-

Figure no.1 VARIABLE STRUCTURE.

W.D. And Preusky, D. (1996). "Consumer Behavior" New York, Brisbane.

Figure no.2 SCREE PLOT

Brand Image

Product Quality

Product Price

Influence of Dealers &

Painters

Consumer

Buying

Behavior

Consumer

Belief pattern

To examine the

relationship

between purchase

intention and

purchase

behaviour of

consumers in

context of

decorative paints


MANAGEMENT


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LIST OF TABLES: -

TABLE NO.1 - FREQUENCIES ANALYSIS ON DEMOGRAPHIC VARIABLE

Gender Age Income Qualification Occupation

No of

rooms

Re-paint

house (How

Frequently)

(Which

Company’s

Paint

Recently)

N Valid 300 300 300 300 300 300 300 300

Missing 0 0 0 0 0 0 0 0

Mean 1.4400 2.3300 2.2667 2.0233 1.9733 2.4400 2.3067 1.9533

Median 1.0000 2.5000 2.0000 2.0000 2.0000 3.0000 2.0000 1.5000

Std.

Deviation .49722 .80203 .79013 .82769 1.04383 .92877 1.14761 1.16433

Variance .247 .643 .624 .685 1.090 .863 1.317 1.356

TABLE NO.2 -AGE

Frequency Percent Valid Percent Cumulative Percent

Valid below 25 57 19.0 19.0 19.0

25-35 93 31.0 31.0 50.0

35-45 144 48.0 48.0 98.0

more than 45 6 2.0 2.0 100.0

Total 300 100.0 100.0

TABLE NO.3-GENDER


Valid male 168 56.0 56.0 56.0

female 132 44.0 44.0 100.0

Total 300 100.0 100.0

TABLE NO.4- INCOME


Valid below 25000 55 18.3 18.3 18.3


MANAGEMENT


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25000-35000 119 39.7 39.7 58.0 35000-45000 117 39.0 39.0 97.0 more than 45000 9 3.0 3.0 100.0 Total 300 100.0 100.0

TABLE NO.5 -QUALIFICATION


Valid Below Graduate 88 29.3 29.3 29.3

Graduate 128 42.7 42.7 72.0

Post Graduate 73 24.3 24.3 96.3

Doctorate 11 3.7 3.7 100.0

Total 300 100.0 100.0

TABLE NO. 6 -NO. OF ROOMS


Valid 1 Room 59 19.7 19.7 19.7

2 Rooms 83 27.7 27.7 47.3

3 Rooms 125 41.7 41.7 89.0

4 Rooms 33 11.0 11.0 100.0

Total 300 100.0 100.0

TABLE NO. 7 (RE-PAINT HOUSE) HOW FREQUENLY YOU RE-PAINT THE

HOUSE?

Frequency Percent Valid Percent

Cumulative

Percent

Valid 2-3 Years 82 27.3 27.3 27.3

4-5 Years 127 42.3 42.3 69.7

6-7 Years 8 2.7 2.7 72.3

If Occasionally (Diwali) 83 27.7 27.7 100.0

Total 300 100.0 100.0


MANAGEMENT


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TABLE NO.8 -WHICH COMPANY’S PAINT YOU HAVE USED AT

YOUR HOME MOST RECENTLY?


Valid Asian Paints 150 50.0 50.0 50.0

Berger Paints 72 24.0 24.0 74.0

Nerolac 22 7.3 7.3 81.3

Dulux Paints 54 18.0 18.0 99.3

If Any Other 2 .7 .7 100.0

Total 300 100.0 100.0

TABLE NO.9-WHOM YOU CONSULT FIRST AT THE TIME OF PAINT?


Valid Retailer 174 58.0 58.0 58.0

Company Outlet 93 31.0 31.0 89.0

Interior Designer 23 7.7 7.7 96.7

Wholesaler 7 2.3 2.3 99.0

Contractor 3 1.0 1.0 100.0

Total 300 100.0 100.0

TABLE NO.10- DO YOU KNOW WHAT IS INTERIOR AND EXTERIOR PAINTS?


Valid Yes 249 83.0 83.0 83.0

No 51 17.0 17.0 100.0

Total 300 100.0 100.0

TABLE NO.11 - WHICH TYPE OF INTERIOR PAINTS DO YOU BUY?


Valid Enamel Paints 111 37.0 37.0 37.0

Distemper Paints 110 36.7 36.7 73.7

Emulsion Paints 79 26.3 26.3 100.0

Total 300 100.0 100.0


MANAGEMENT


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TABLE NO.12 -WHICH TYPE OF EXTERIOR PAINTS DO YOU BUY?


Valid Cement paints 137 45.7 45.7 45.7

Emulsion 69 23.0 23.0 68.7

Textured 93 31.0 31.0 99.7

5.00 1 .3 .3 100.0

Total 300 100.0 100.0

TABLE NO.13-WHAT IS YOUR ECPECTED LIFE OF PAINT?


Valid Less than 1 year 174 58.0 58.0 58.0

2 -3 years 72 24.0 24.0 82.0

3-5 years 54 18.0 18.0 100.0

Total 300 100.0 100.0

TABLE NO.14-WHICH TYPE OF GUIDANCE DO YOU EXPECT FROM THE

PAINT COMPANY?

Frequency Percent

Valid

Percent

Cumulative

Percent

Valid Provide Details on the New Product

Development and Innovations 192 64.0 64.0 64.0

Educate About the Product Features 44 14.7 14.7 78.7

Knowledge of Sales Discount 53 17.7 17.7 96.3

Budgeting While Painting 2 .7 .7 97.0

Suggestions for Increasing the

Effectiveness / Efficiency 9 3.0 3.0 100.0

Total 300 100.0 100.0


MANAGEMENT


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TABLE NO. 15-RECALLING PAINT BRAND ADVERTISEMENT AND

IDENTIFYING BRAND BY BRAND EMBASADOR

Statistics

Recall the

Paint Brand

‘Clean Air

Beautiful

Homes’,

‘Royal

Atmos’ ,

Deepika

Padukone

‘Ghar

Bulake To

Dekho’,

‘HD

Colour',

Shah Rukh

Khan

‘Toh Chamak

Rahe Ho Tum’,

‘Velvet Touch’,

Farhan Akhtar

‘Duniya Dekhegi

Jab SILK Se Saje

Duniya’, ‘Deewaron

Se Nazar Nahi Hat-

Ti’, ‘SILK’ Katrina

Kaif

‘Barrish Ko

Aane Do’,

‘Barkha’,

‘Waterproofin

g Vala

Exterior

Paint’ Ranbir

Kapoor

N Valid 300 300 300 300 300

Missing 3 3 3 3 3

Mean 1.3067 1.3133 1.5367 1.3300 1.2800

Median 1.0000 1.0000 2.0000 1.0000 1.0000

Std.

Deviation .46188 .46462 .49949 .47100 .44975

Variance .213 .216 .249 .222 .202

TABLE NO.16 (RECALL THE PAINT BRAND) ‘CLEAN AIR BEAUTIFULL HOMES’,

‘ROYAL ATMOS’, DEEPIKA PADUKONE

Frequency

Percen

t

Valid

Percent

Cumulative

Percent

Valid Yes 208 68.6 69.3 69.3

No 92 30.4 30.7 100.0

Total 300 99.0 100.0

Missing System 3 1.0

Total 303 100.0


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TABLE NO.17 (RECALL THE PAINT BEAND) ‘GHAR BULAKE TO DEKHO’,

‘HD COLOUR', SHAH RUKH KHAN

Frequenc

y Percent

Valid

Percent

Cumulative

Percent

Valid Yes 206 68.0 68.7 68.7

No 94 31.0 31.3 100.0

Total 300 99.0 100.0

Missing Syste

m 3 1.0

Total 303 100.0

TABLE NO.18 (RECALL THE PAINT BRAND) ‘TOH CHAMAK RAHE HO TUM’,

‘VELVET TOUCH’, FARHAN AKHTAR

Frequ

ency Percent Valid Percent

Cumulative

Percent

Valid Yes 139 45.9 46.3 46.3

No 161 53.1 53.7 100.0

Total 300 99.0 100.0


Total 303 100.0

TABLE NO.19 - (RECALL THE PAINT BRAND) ‘DUNIYADEKHEGI JAB SILK SE SAJE

DUNIYA’, ‘DEEWARO SE NAZAR NAHI HAT TI’, ‘SILK’ KATRINA KAIF

Frequ

ency Percent Valid Percent

Cumulativ

e Percent

Valid Yes 201 66.3 67.0 67.0

No 99 32.7 33.0 100.0


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TABLE NO. 23

Compo

nents

Variables Value Factors

(Name)

1 (Past experience) Why? Which Reason Pulls You to This

Brand? .809

Brand

Selection

(Suggested by Dealers/Painters) Why? Which Reason Pulls You

to This Brand? .508

Total 300 99.0 100.0


Total 303 100.0

TABLE NO.20 (RCALL THE PAINT BRAND) ‘BARRISH KOAANE DO ‘BARKHA’’

WATERPROOF VALA EXTERIOR PAINT ‘RANBIR LAPOOR


Valid

Missing

Total

Yes 216 71.3 72.0 72.0

No 84 27.7 28.0 100.0

Total 300 99.0 100.0

System 3 1.0

303 100.0


Total 303 100.0

TABLE NO.22 KMO AND BARLETT’S TEST

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .706

Bartlett's Test of Sphericity Approx. Chi-Square 8105.791

Df 666

Sig. .000


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(Price) Why? Which Reason Pulls You to This Brand? .583

(Quality) Why? Which Reason Pulls You to This Brand? .725

(Trust On Brand Name) Why? Which Reason Pulls You to This

Brand? .733

(Advertisement Attraction) Why? Which Reason Pulls You to

This Brand? .670

(Discount Offers) Why? Which Reason Pulls You to This

Brand? -.615

2 (Finishing) Rate Your Preference That You Are Taken In

Consideration At The Time of Paint Your

House/Office/Building.

.761

Customer

Preferenc

e

(Long Durability) Rate Your Preference That You Are Taken

In Consideration At The Time of Paint Your


.717

(Price) Rate Your Preference That You Are Taken In



-.590

(Advertisement) Rate Your Preference That You Are Taken In



-.728

(Celebrity Endorsement) Rate Your Preference That You Are

Taken In Consideration At The Time of Paint Your


.774

3

(Exact Shade) Rate Your Preference That You Are Taken In



-.701

Customer

Awarenes

s

(Smoothness) Rate Your Preference That You Are Taken In



.637

(Square Feet Coverage) Rate The Following Awareness

Parameters As Per Your Preference/Experience. 727


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(Paint Durability) Rate The Following Awareness Parameters

As Per Your Preference/Experience. .849

(Surface Coverage with Paint) Rate The Following Awareness

Parameters As Per Your Preference/Experience. .753

(Paint Quality) Rate The Following Awareness Parameters As

Per Your Preference/Experience. .787

(Past Experience) At The Time of Selection of The Paint

Brand; What Parameters You Would Like to Consider? .651

(Advertisement) At The Time of Selection of The Paint Brand;

What Parameters You Would Like to Consider? .500

4 (Suggestion by Dealers or Painters) At The Time of Selection

of The Paint Brand; What Parameters You Would Like to

Consider?

.625

Selection

Process

(Word of Mouth Publicity) At The Time of Selection of The

Paint Brand; What Parameters You Would Like to Consider? .535

(Warranty) At The Time of Selection of The Paint Brand;

What Parameters You Would Like to Consider? .699

(Technical Support of The Brand at Paint Shop) At The Time

of Selection of The Paint Brand; What Parameters You Would

Like to Consider?

.890

(Eco Friendliness) At The Time of Selection of The Paint

Brand; What Parameters You Would Like to Consider? .658

5 (Interior designer) At the Time of Paint Purchase Decision;

who’s Suggestions Will Helpful to you the Most? .639

Paint

Purchase

Decision (Painter) At the Time of Paint Purchase Decision; who’s

Suggestions Will Helpful to you the Most? .764

(Contractor) At the Time of Paint Purchase Decision; who’s


(Paint Hardware Shop) At the Time of Paint Purchase

Decision; who’s Suggestions Will Helpful to you the Most? .773

(Friends) At the Time of Paint Purchase Decision; who’s .653


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Suggestions Will Helpful to you the Most?

(Family) At the Time of Paint Purchase Decision; who’s


(Advertisement) At the Time of Paint Purchase Decision;

who’s Suggestions Will Helpful to you the Most? .652

6

(Putty) According to Your Preference What Makes the

Finishing of Paint More Aesthetic/Effective? .781

Finishing

(Use of Proper Painting Tools) According to Your Preference

What Makes the Finishing of Paint More Aesthetic/Effective? .792

(Experienced Painter) According to Your Preference What

Makes the Finishing of Paint More Aesthetic/Effective? .804

(Branded Paint) According to Your Preference What Makes

the Finishing of Paint More Aesthetic/Effective? -.658

(Use of Proper Paint Process) According to Your Preference

What Makes the Finishing of Paint More Aesthetic/Effective? .522

Table- factors identified.

TABLE NO.24.-Correlation Analysis

Paint

Brand

Selection

Past

exper

ience

Suggested

by

Dealers/Pai

nters Price Quality

Advertis

ement

Attractio

n

Discount

Offers

Which Paint

Brand Will

You Select

Next Time

Pearson

Correlati

on

1 .094 .107 .034 .088 .005 .133*

Sig. (2-

tailed) .106 .064 .554 .129 .927 .021

N 300 300 300 300 300 300 300

(Past

experience)

Why? Which

Pearson

Correlati

on

.094 1 .071 .463** .283** .105 .098


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Reason Pulls

You to This

Brand?

Sig. (2-

tailed) .106 .219 .000 .000 .070 .089

N 300 300 300 300 300 300 300

(Suggested by

Dealers/Painte

rs) Why?

Which Reason

Pulls You to

This Brand?

Pearson

Correlati

on

.107 .071 1 .000 .279** -.097 .185**

Sig. (2-

tailed) .064 .219 .994 .000 .095 .001

N 300 300 300 300 300 300 300

(Price) Why?

Which Reason

Pulls You to

This Brand?

Pearson

Correlati

on

.034 .463*

* .000 1 .190** .135* .160**

Sig. (2-

tailed) .554 .000 .994 .001 .019 .006

N 300 300 300 300 300 300 300

(Quality)

Why? Which

Reason Pulls

You to This

Brand?

Pearson

Correlati

on

.088 .283*

* .279** .190** 1 .062 .305**

Sig. (2-

tailed) .129 .000 .000 .001 .286 .000

N 300 300 300 300 300 300 300

(Advertiseme

nt Attraction)

Why? Which

Reason Pulls

You to This

Brand?

Pearson

Correlati

on

.005 .105 -.097 .135* .062 1 .063

Sig. (2-

tailed) .927 .070 .095 .019 .286 .274

N 300 300 300 300 300 300 300

(Discount

Offers) Why?

Which Reason

Pearson

Correlati

on

.133* .098 .185** .160** .305** .063 1


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Pulls You to

This Brand?

Sig. (2-

tailed) .021 .089 .001 .006 .000 .274

N 300 300 300 300 300 300 300

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

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

Table-Correlation Analysis

A STUDY ON CONSUMER BUYING BEHAVIOR OF DECORATIVE …

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