Introduction
The
retail landscape has seen a major shift in the recent years. The scenario in
the retail store (especially in metro cities) is altogether different as
compared to ten year ago. The way that consumers used to make purchase
decisions has changed dramatically: they stand in stores, using the smart
phones in their hands to compare the prices and product reviews on various
e-tailing websites and recommendations of family & friends through social
media. When they are ready to buy, the probability that any online retailer
would deliver them cheaply direct at their doorstep, sometime on the same day.
These kinds of unpredicted shifts have changed the viewpoint of the industry
experts and some of them predict to end the retail as we know it (Grewal et
al., 2003). It is predicted that retail will change more in next 10 years than
it has changed in the last 100 years. Though that is not to suggest that malls,
chain stores and big name brands will not continue in the foreseeable future
but it indicates that new players will rapidly emerge and will lead the market.
The trend of weekend shopping is also a major shift in retail industry.
Shopping has become much more than only buying and selling of goods (Machleit
et al., 2000). People visit the retail stores to have fun (eating out, watching
movies, enjoy good time with family etc.). Today’s consumers have more choice
and far more product information than ever before which makes the job of the
retailer quit tough in keeping the consumer in his fold.
Point-of-purchase Display
Today,
retail stores have everything from shoes, clothes, toys to electronics. It is
therefore important for store owners to have the necessary tools for
merchandising a wide variety of items in the most efficient manner within their
stores to help promote merchandise. As the retail stores develops visual
retailing and displaying of products is becoming a source of concern for
business owners. Retailers must be in tune with all the different types of
store displays and fixtures available for store displays that are available for
their stores’ merchandise.
Point-of-purchase
is the place where a customer is about to buy a product. Point-of-purchase display
refers to how a retailer should display various brands so that they are most
likely to be noticed and purchased by the customers. It is a well-recognized fact that many of
Indian customers make their final decision with respect to purchase of a product/brand
at the last minute. The point-of-purchase display derives its power out of this
phenomenon. The point-of-purchase display not only presents the last minute
reminder but also invites the customers to buy it. Effective display backed by
recommendation of the retailer can do wonders to a brand. The underlying
assumption is “jo dikhta hai vo bikta hai”.
Review of literature:
Point
of purchase displays are specially designed materials intended for placement in
retail stores. These allow products to be prominently presented, often in high
traffic areas, and thereby increase the probability the product will standout.
Point of purchase displays can leads to significant increase in sales as
compared to sales levels in a normal shelf position (www.knowthis.com, 2014)
A
salesperson’s behaviour and action can influence customer satisfaction up to a
large extent (Oliver and Swan, 1989).
Store environment had a much higher effect on impulse buying than the
personality variables and it was found that among all the display, store
environment elements and layout had the highest effect on impulsive buying.
Mower M. J. et al (2012)
provided useful information to small store retailers by investigating the
influence of external atmospheric variables, specifically window displays and
landscaping (i.e., accessory vegetation), on customers’ responses. Store
exteriors are what customers first encounter as they engage in shopping
behavior and thus are an important opportunity for stores to build positive
impressions. The study describes that store exterior includes display windows
storefront, entrances, physical characteristics of the building (height, size,
and color of buildings), parking, location (congestion and traffic),
surrounding area and nearby stores. The study resulted that when customers
liked the exterior retail environment, they experienced higher pleasure and
arousal which resulted in higher patronage intentions. The study concluded that
small retailers have an opportunity to differentiate themselves from corporate
retailers by focusing on the fact that they can give shoppers a unique shopping
experience that starts with the store exterior. Exterior display has an
important role in increasing the footfall for small retailers.
Efficient
shelf space allocation leads to a better display of the product and make the
store environment more pleasant. This is one of key determinants to gain an edge
in the highly competitive retail industry. Several models are developed for
allocation of shelf space to a large number of products to optimize retailer’s
objective under certain operating conditions within a store. Growing number of
products has posed a challenge to the retailers in allocating available shelf
space to them efficiently. If retailers can manage space allocation in an
efficient manner it can be helpful in increasing their bottom line (Gajjar H. K., Adil G. K., 2011).
Research
Methodology:
The present research is exploratory cum
descriptive in nature and depends largely upon the primary source of
information. Data has been collected from 100 respondents in NCR & Delhi with the help of a structured questionnaire.
Interview technique has been used when and where necessary, in order to gather
information about the present retail scenario. Data has been analyzed with the
help of SPSS using ‘t’ test and One way ANOVA. The objectives of the study are:
i.
To
study the impact of point of purchase display on consumer decision making.
ii.
To
study whether significant difference occurs among the opinions of people across
different demographic profile with respect to point of purchase display.
iii.
To study the scope of display as a
promotional tool.
Data
Analysis (Demographic)
Table
1 – distribution of respondents –gender wise
GENDER
|
Frequency
|
Percent
|
Cumulative Percent
|
Male
|
52
|
52
|
52
|
Female
|
48
|
48
|
100
|
Total
|
100
|
100
|
(Source – Primary data)
Male and female both are equally engaged
in shopping activities. The above table depicts that a mixture of both genders
has been taken in order to gain maximum insight.
Table
2 distribution of respondents – age wise
AGE
|
Frequency
|
Percent
|
Cumulative Percent
|
Less than 20
|
5
|
5
|
5
|
21 - 40
|
59
|
59
|
64
|
41-60
|
12
|
12
|
76
|
61 & above
|
24
|
24
|
100
|
Total
|
100
|
100
|
(Source – Primary data)
The data has been collected from the
various shoppers and the table indicates that maximum respondents belong to 21
– 40 age group. The reason observed behind this is that most of the shoppers
today are young customers and same is being reflected in this table too.
Table
3 – distribution of respondents – education wise
EDUCATION
|
Frequency
|
Percent
|
Cumulative Percent
|
upto 10th
|
4
|
4
|
4
|
upto graduation
|
47
|
47
|
51
|
pg & above
|
49
|
49
|
100
|
Total
|
100
|
100
|
(Source – Primary Data)
The above table indicates that most of
the respondents belong to either 2nd group or 3rd group.
Only 4% respondents belong to 1st group i.e. upto matric. This trend
show most of the customer visiting retail stores in NCR are highly educated.
Table
4 – distribution of respondents – occupation wise
OCCUPATION
|
Frequency
|
Percent
|
Cumulative Percent
|
Business
|
9
|
9
|
9
|
Service
|
45
|
45
|
54
|
Others
|
46
|
46
|
100
|
Total
|
100
|
100
|
(Source – Primary Data)
The above table indicates the occupation
of the respondents. For this three categories viz. business, service and others
had been taken. Other included students, house wives and retired persons (who
do not have a direct source of income). The data indicates that around 50%
respondents belong to first two categories and rest belongs to 3rd
category.
Table 5 – distribution of respondents –
income wise
INCOME
|
Frequency
|
Percent
|
Cumulative Percent
|
less than 10000
|
42
|
42
|
42
|
10000 - 20000
|
11
|
11
|
53
|
20000 - 30000
|
5
|
5
|
58
|
30000 - 40000
|
16
|
16
|
74
|
40000 & above
|
26
|
26
|
100
|
Total
|
100
|
100
|
(Source – Primary Data)
The table depicts that the respondents
are divided in 5 categories on the basis of income. Most of the respondents
belong to income less than 10,000/- per month. These are the respondents mainly
belonging to others category in occupation group which comprises of housewives,
students and retired persons. Around 1/4th of the respondents belong
to highest income group i.e. Rs. 40,000 & more per month.
These statements used in questionnaire
are:
S1
|
Display creates opportunity to compare
the prices & helps in calculating the
cost
|
S2
|
Display helps me in comparing various
brands
|
S3
|
Display helps me in making final
decisions
|
S4
|
I purchase the displayed products more
as compared to non displayed product
|
S5
|
I feel that display bound me to choose
from the available options only
|
S6
|
Display helps me in comparing the
packaging quality of various products
|
S7
|
Display helps me evaluating various
usages of a product
|
S8
|
Display made me aware about the usage
of a product, which I was not aware earlier
|
S9
|
Display helps me in changing my style
& fashion
|
The above statements have been analyzed
using anova. The analysis of each statement with various demographic factors
can be explained as:
(Analysis of data using Anova
across age)
N
|
Mean
|
Std. Deviation
|
F
|
Sig.
|
||
S1
|
<20
|
5
|
3.83
|
1.31
|
0.84
|
0.47
|
21-40
|
59
|
3.97
|
1.05
|
|||
41-60
|
12
|
3.88
|
1.18
|
|||
61 & Above
|
24
|
3.89
|
0.89
|
|||
TOTAL
|
100
|
3.74
|
1.16
|
|||
S2
|
<20
|
5
|
3.46
|
1.18
|
0.24
|
0.99
|
21-40
|
59
|
3.42
|
0.94
|
|||
41-60
|
12
|
3.44
|
1.08
|
|||
61 & Above
|
24
|
3.51
|
1.06
|
|||
TOTAL
|
100
|
3.49
|
1.01
|
|||
S3
|
<20
|
5
|
3.09
|
1.04
|
6.46
|
0.00
|
21-40
|
59
|
3.91
|
1.03
|
|||
41-60
|
12
|
3.20
|
1.18
|
|||
61 & Above
|
24
|
3.64
|
0.93
|
|||
TOTAL
|
100
|
3.79
|
1.01
|
|||
S4
|
<20
|
5
|
2.93
|
1.05
|
3.07
|
0.03
|
21-40
|
59
|
3.12
|
1.01
|
|||
41-60
|
12
|
3.27
|
1.18
|
|||
61 & Above
|
24
|
3.33
|
1.14
|
|||
TOTAL
|
100
|
3.29
|
1.13
|
|||
S5
|
<20
|
5
|
3.05
|
1.43
|
6.48
|
0.01
|
21-40
|
59
|
3.25
|
1.27
|
|||
41-60
|
12
|
2.73
|
1.29
|
|||
61 & Above
|
24
|
3.61
|
1.35
|
|||
TOTAL
|
100
|
3.29
|
1.28
|
|||
S6
|
<20
|
5
|
2.54
|
1.44
|
12.23
|
1.10
|
21-40
|
59
|
3.81
|
1.19
|
|||
41-60
|
12
|
2.29
|
1.53
|
|||
61 & Above
|
24
|
3.48
|
1.57
|
|||
TOTAL
|
100
|
3.93
|
1.43
|
|||
S7
|
<20
|
5
|
3.22
|
1.27
|
1.39
|
0.25
|
21-40
|
59
|
3.88
|
1.00
|
|||
41-60
|
12
|
3.14
|
1.11
|
|||
61 & Above
|
24
|
3.80
|
1.09
|
|||
TOTAL
|
100
|
3.08
|
1.08
|
|||
S8
|
<20
|
5
|
2.82
|
1.19
|
5.17
|
0.02
|
21-40
|
59
|
3.14
|
1.11
|
|||
41-60
|
12
|
3.25
|
1.07
|
|||
61 & Above
|
24
|
3.18
|
1.09
|
|||
TOTAL
|
100
|
3.07
|
1.13
|
|||
S9
|
<20
|
5
|
2.83
|
1.18
|
2.14
|
0.10
|
21-40
|
59
|
3.08
|
1.19
|
|||
41-60
|
12
|
2.85
|
1.12
|
|||
61 & Above
|
24
|
3.21
|
1.14
|
|||
TOTAL
|
100
|
3.23
|
1.16
|
|||
TOTAL
|
<20
|
5
|
3.09
|
0.72
|
10.58
|
0.04
|
21-40
|
59
|
3.37
|
0.58
|
|||
41-60
|
12
|
3.49
|
0.62
|
|||
61 & Above
|
24
|
3.68
|
0.60
|
|||
TOTAL
|
100
|
3.31
|
0.63
|
(Source – Primary Data)
Hypothesis:
H01: There
is no significant difference in the opinions of the respondents across the
different age groups regarding different dimension of impact of display on
buying behaviour.
The above table depicts the results of anova
that was intended to anayse whether there is any significant difference in the
opinions of the respondents across the different age groups viz. less than 20
years, 21 -40, 41- 60 and 60 years and above regarding different dimension of
impact of display on buying behavior. It can be interpreted that the opinion of
respondents for statements 3,4,5 & 8 were found significantly different
while for rest of the statement there is no significant difference in the
opinion of respondents belonging to different age group. For the overall
statements, the data shows a significant difference in the opinion of
respondents belonging to different age group, which on the whole rejects the
null hypothesis H01.
(Analysis of data using Anova
across education)
N
|
Mean
|
Std. Deviation
|
F
|
Sig.
|
||
S1
|
Upto Matric
|
4
|
3.79
|
1.33
|
1.86
|
0.16
|
Upto Graduation
|
47
|
3.89
|
1.32
|
|||
PG & Above
|
49
|
4.93
|
0.96
|
|||
Total
|
100
|
3.04
|
1.03
|
|||
S2
|
Upto Matric
|
4
|
3.60
|
0.93
|
1.65
|
0.01
|
Upto Graduation
|
47
|
3.98
|
1.02
|
|||
PG & Above
|
49
|
3.56
|
0.35
|
|||
Total
|
100
|
3.40
|
1.07
|
|||
S3
|
Upto Matric
|
4
|
3.20
|
1.03
|
8.90
|
0.02
|
Upto Graduation
|
47
|
3.34
|
1.22
|
|||
PG & Above
|
49
|
3.87
|
0.64
|
|||
Total
|
100
|
3.49
|
1.13
|
|||
S4
|
Upto Matric
|
4
|
3.15
|
1.02
|
4.98
|
0.04
|
Upto Graduation
|
47
|
3.27
|
1.12
|
|||
PG & Above
|
49
|
3.47
|
1.32
|
|||
Total
|
100
|
3.39
|
1.61
|
|||
S5
|
Upto Matric
|
4
|
2.27
|
1.47
|
11.21
|
0.03
|
Upto Graduation
|
47
|
3.31
|
1.25
|
|||
PG & Above
|
49
|
3.24
|
1.16
|
|||
Total
|
100
|
3.55
|
1.23
|
|||
S6
|
Upto Matric
|
4
|
2.21
|
1.40
|
23.22
|
0.04
|
Upto Graduation
|
47
|
3.50
|
1.26
|
|||
PG & Above
|
49
|
3.26
|
1.76
|
|||
Total
|
100
|
3.56
|
1.23
|
|||
S7
|
Upto Matric
|
4
|
3.64
|
1.16
|
6.25
|
0.09
|
Upto Graduation
|
47
|
3.53
|
1.65
|
|||
PG & Above
|
49
|
3.68
|
0.86
|
|||
Total
|
100
|
3.87
|
1.47
|
|||
S8
|
Upto Matric
|
4
|
2.35
|
1.28
|
14.54
|
0.02
|
Upto Graduation
|
47
|
3.12
|
1.47
|
|||
PG & Above
|
49
|
3.23
|
1.76
|
|||
Total
|
100
|
3.05
|
1.18
|
|||
S9
|
Upto Matric
|
4
|
2.97
|
1.83
|
0.98
|
0.38
|
Upto Graduation
|
47
|
2.63
|
1.80
|
|||
PG & Above
|
49
|
3.11
|
1.78
|
|||
Total
|
100
|
3.36
|
1.84
|
|||
TOTAL
|
Upto Matric
|
4
|
3.03
|
0.73
|
17.65
|
0.00
|
Upto Graduation
|
47
|
3.33
|
0.15
|
|||
PG & Above
|
49
|
3.56
|
0.87
|
|||
Total
|
100
|
3.36
|
0.78
|
(Source
– Primary Data)
H02: There
is no significant difference in the opinions of the respondents across the
different educational groups regarding different dimension of impact of display
on buying behaviour.
Analyzing the above table shows the
result of anova from the perspective of different education groups of the
respondents which further reveals that opinion of respondents over S2, S3, S4,
S5, S6 & S8 were found significantly different as the significant level of
these statements are less than 0.05. While for other statements the opinion was
not significantly different. . For the overall statements, the data shows a
significant difference in the opinion of respondents belonging to different age
group, which on the whole rejects the null hypothesis H02.
(Analysis of data using Anova across occupation)
N
|
Mean
|
Std. Deviation
|
F
|
Sig.
|
||
S1
|
Business
|
9
|
3.00
|
0.89
|
0.57
|
0.59
|
Service
|
45
|
4.92
|
0.96
|
|||
Others
|
46
|
3.88
|
1.16
|
|||
Total
|
100
|
3.52
|
1.36
|
|||
S2
|
Business
|
9
|
3.27
|
1.03
|
1.09
|
0.21
|
Service
|
45
|
3.84
|
0.96
|
|||
Others
|
46
|
3.44
|
1.02
|
|||
Total
|
100
|
3.49
|
1.00
|
|||
S3
|
Business
|
9
|
3.58
|
1.13
|
2.34
|
0.15
|
Service
|
45
|
3.78
|
1.04
|
|||
Others
|
46
|
3.59
|
1.13
|
|||
Total
|
100
|
3.49
|
1.10
|
|||
S4
|
Business
|
9
|
3.38
|
1.14
|
11.71
|
0.00
|
Service
|
45
|
3.54
|
1.05
|
|||
Others
|
46
|
3.14
|
1.10
|
|||
Total
|
100
|
3.57
|
1.11
|
|||
S5
|
Business
|
9
|
3.11
|
1.18
|
8.01
|
0.07
|
Service
|
45
|
3.42
|
1.13
|
|||
Others
|
46
|
3.88
|
1.36
|
|||
Total
|
100
|
3.65
|
1.26
|
|||
S6
|
Business
|
9
|
2.08
|
1.32
|
5.07
|
0.04
|
Service
|
45
|
3.56
|
1.14
|
|||
Others
|
46
|
3.17
|
1.31
|
|||
Total
|
100
|
3.13
|
1.26
|
|||
S7
|
Business
|
9
|
3.88
|
0.90
|
0.98
|
0.37
|
Service
|
45
|
3.84
|
1.07
|
|||
Others
|
46
|
3.74
|
1.13
|
|||
Total
|
100
|
3.58
|
1.08
|
|||
S8
|
Business
|
9
|
3.08
|
1.20
|
8.07
|
0.02
|
Service
|
45
|
3.13
|
0.98
|
|||
Others
|
46
|
2.88
|
1.19
|
|||
Total
|
100
|
3.08
|
1.13
|
|||
S9
|
Business
|
9
|
2.87
|
1.13
|
1.49
|
0.24
|
Service
|
45
|
3.17
|
1.15
|
|||
Others
|
46
|
3.01
|
1.17
|
|||
Total
|
100
|
3.01
|
1.16
|
|||
TOTAL
|
Business
|
9
|
3.02
|
0.59
|
10.18
|
0.06
|
Service
|
45
|
3.59
|
0.62
|
|||
Others
|
46
|
3.31
|
0.62
|
|||
Total
|
100
|
3.43
|
0.61
|
(Source – Primary Data)
H03:
There
is no significant difference in the opinions of the respondents across the
different occupational groups regarding different dimension of impact of
display on buying behaviour.
The table depicts the result of anova
that was intended to analyze whether there is any significant difference in the
opinion of the occupation groups – business, service and others over different
statements. It can be interpreted that for S4, S6 & S8 only the
significance level was found to be less than 0.05 thus opinion of respondents
was found significantly different for these statements. But for all other
statement, including overall analysis the significance level was found more
than 0.05. overall it can be concluded that there is no significant difference in
the opinions of the respondents across the different occupational groups regarding
different dimension of impact of display on buying behavior and null hypothesis
is accepted.
(Analysis of data using Anova across income)
N
|
Mean
|
Std. Deviation
|
F
|
Sig.
|
||
S1
|
Upto 10,000
|
42
|
3.85
|
1.08
|
2.16
|
0.07
|
10,001 - 20,000
|
11
|
3.79
|
1.28
|
|||
20,001 - 30,000
|
5
|
3.60
|
1.99
|
|||
30,001 - 40,000
|
16
|
3.69
|
0.68
|
|||
40,001 & above
|
26
|
4.84
|
0.96
|
|||
Total
|
100
|
3.87
|
1.08
|
|||
S2
|
Upto 10,000
|
42
|
3.48
|
1.04
|
3.19
|
0.01
|
10,001 - 20,000
|
11
|
3.72
|
0.69
|
|||
20,001 - 30,000
|
5
|
3.63
|
1.07
|
|||
30,001 - 40,000
|
16
|
3.12
|
0.97
|
|||
40,001 & above
|
26
|
3.33
|
0.94
|
|||
Total
|
100
|
3.45
|
1.00
|
|||
S3
|
Upto 10,000
|
42
|
3.54
|
1.12
|
4.28
|
0.00
|
10,001 - 20,000
|
11
|
3.38
|
1.24
|
|||
20,001 - 30,000
|
5
|
3.24
|
1.24
|
|||
30,001 - 40,000
|
16
|
3.88
|
0.87
|
|||
40,001 & above
|
26
|
3.82
|
0.94
|
|||
Total
|
100
|
3.59
|
1.10
|
|||
S4
|
Upto 10,000
|
42
|
3.13
|
1.10
|
5.98
|
0.01
|
10,001 - 20,000
|
11
|
3.02
|
1.12
|
|||
20,001 - 30,000
|
5
|
3.22
|
1.08
|
|||
30,001 - 40,000
|
16
|
3.84
|
0.84
|
|||
40,001 & above
|
26
|
3.49
|
1.15
|
|||
Total
|
100
|
3.29
|
1.11
|
|||
S5
|
Upto 10,000
|
42
|
3.09
|
1.38
|
5.30
|
0.02
|
10,001 - 20,000
|
11
|
3.25
|
0.92
|
|||
20,001 - 30,000
|
5
|
2.83
|
1.30
|
|||
30,001 - 40,000
|
16
|
3.80
|
1.03
|
|||
40,001 & above
|
26
|
3.49
|
1.16
|
|||
Total
|
100
|
3.25
|
1.26
|
|||
S6
|
Upto 10,000
|
42
|
3.17
|
1.32
|
8.33
|
0.00
|
10,001 - 20,000
|
11
|
2.87
|
1.16
|
|||
20,001 - 30,000
|
5
|
2.59
|
1.43
|
|||
30,001 - 40,000
|
16
|
3.60
|
0.86
|
|||
40,001 & above
|
26
|
3.66
|
1.07
|
|||
Total
|
100
|
3.23
|
1.26
|
|||
S7
|
Upto 10,000
|
42
|
3.79
|
1.10
|
2.40
|
0.04
|
10,001 - 20,000
|
11
|
3.60
|
1.21
|
|||
20,001 - 30,000
|
5
|
3.57
|
1.14
|
|||
30,001 - 40,000
|
16
|
4.08
|
0.80
|
|||
40,001 & above
|
26
|
3.98
|
1.01
|
|||
Total
|
100
|
3.82
|
1.08
|
|||
S8
|
Upto 10,000
|
42
|
2.88
|
1.21
|
3.19
|
0.01
|
10,001 - 20,000
|
11
|
3.17
|
0.89
|
|||
20,001 - 30,000
|
5
|
3.15
|
1.16
|
|||
30,001 - 40,000
|
16
|
3.08
|
1.07
|
|||
40,001 & above
|
26
|
3.37
|
1.05
|
|||
Total
|
100
|
3.09
|
1.13
|
|||
S9
|
Upto 10,000
|
42
|
3.07
|
1.20
|
1.69
|
0.15
|
10,001 - 20,000
|
11
|
2.81
|
1.06
|
|||
20,001 - 30,000
|
5
|
2.78
|
1.28
|
|||
30,001 - 40,000
|
16
|
3.24
|
1.15
|
|||
40,001 & above
|
26
|
3.10
|
1.07
|
|||
Total
|
100
|
3.03
|
1.16
|
|||
TOTAL
|
Upto 10,000
|
42
|
3.35
|
0.64
|
5.29
|
0.00
|
10,001 - 20,000
|
11
|
3.28
|
0.61
|
|||
20,001 - 30,000
|
5
|
3.19
|
0.62
|
|||
30,001 - 40,000
|
16
|
3.62
|
0.61
|
|||
40,001 & above
|
26
|
3.60
|
0.56
|
|||
Total
|
100
|
3.41
|
0.63
|
(Source – Primary Data)
H04: There
is no significant difference in the opinions of the respondents across the
different income groups regarding different dimension of impact of display on
buying behaviour.
Analyzing the above table shows the
result of anova from the perspective of different education groups of the
respondents which further reveals that opinion of respondents over S2, S3, S4,
S5, S6, S7 and S8 were found significantly different as the significant level
of these statements are less than 0.05. While only for S1 and S9 the opinion
was not significantly different. . For the overall statements, the data shows a
significant difference in the opinion of respondents belonging to different age
group, which on the whole rejects the null hypothesis H04.
Findings
& Recommendations
After analyzing the data it was found
that for most of the statements the opinion of various groups of respondents
significantly differs. For statements like display helps me in making final
decision, I purchase the displayed products more as compared to non displayed
product, I feel that display bound me to choose from the available options only
and Display made me aware about the usage of a product, which I was not aware
earlier, the opinion of the respondents over various demographic groups was
found significantly differ. It was found that point of purchase display have an
impact on the final decisions of the customers. It was also found that
customers purchase from the displayed product more and display is helpful to
the customers about the usage of the product.
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