CHAPTER – V BRAND CONSCIOUSNESS AND PERCEIVED EFFECT...
Transcript of CHAPTER – V BRAND CONSCIOUSNESS AND PERCEIVED EFFECT...
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CHAPTER – V
BRAND CONSCIOUSNESS AND PERCEIVED EFFECT OF ADVERTISEMENTS ON PURCHASE OF FMCG’S
5.1 Role Played in the Family While Making Buying Decisions
This question was asked to know about the role played by the respondents in
their families while making a purchase decision of a particular brand of Toiletry.
Interpretation of the Data
Table 5.1 reveals that 31 percent of the respondents played the role of an
influencer, which is followed by 24 percent acting as deciders, 20.5 percent as initiator,
16.5 as buyers and only 8 percent as users of the particular brand of a toiletry.
TABLE 5.1
Role Played in the Family While Making Buying Decisions
Sr. No.
Roles Played
No. of Respondents
Percent
1
Initiator 82 20.5
2
Influencer 124 31.0
3
Decider 96 24.0
4
Buyer 66 16.5
5
User 32 8.0
Total 400 100.0
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The diversity in the roles played by the family members can be attributed to the
sample of two members taken from each of the household, wherein one member was
the head of the family and the other was chosen on the basis of availability at the time
of the survey. Generally the respondents were found to play the role of an influencer,
i.e. one who pressurizes his decision on the members of the family. Decider was the
ultimate deciding authority of a household.
5.2 Perception of Rural Respondents towards Television Advertising – A
Factor Analytic Approach
In order to find out the factors influencing the perception of rural consumer for
television advertising, the factor analytic technique has been applied. A set of 12
statements shown in Table 5.2.1 measured on a five point Likert scale (where 1 is
strongly agree and 5 strongly disagree) regarding the opinion of respondents (derived
through a survey) regarding the insight of television advertisements of Toiletries have
been factor analyzed.
For conducting Factor Analysis, minimum sample size should be at least four or
five times of the variables taken under consideration. To carry on the present study a
total of 400 questionnaires were analysed. Thus, present study qualifies the sample size
requirement for applying Factor Analysis.
Before applying factor analysis, it is essential to test the reliability of the scale.
The reliability of scale can be tested by a widely used method called Cronbach’s Alpha.
It is the average of all possible split-half coefficients resulting from different ways of
splitting the scale items. This coefficient varies from 0 to 1 but satisfactory value of
Alpha should be more than 0.6. A value of 0.6 or less generally indicates unsatisfactory
results (Malhotra, 2007 and Hair, 2007). In the present study, we have also computed
Cronbach’s Alpha to test the reliability of scale. Its value has found to be 0.826
ensuring the reliability of used scale. After ensuring the reliability of scale, it is
obligatory to check the adequacy of collected data for the application of Factor
Analysis.
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Adequacy of the data for Factor Analysis:
For checking the adequacy of the data for Factory Analysis, the various
recommended techniques are:
a) Construction of Correlation Coefficient Matrix of Explanatory Variables
b) Construction of Anti-Image Correlation Matrix
c) Kaiser-Meyer-Oklin (KMO) Measure of Sampling Adequacy.
d) Bartlett’s Test of Sphericity
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TABLE 5.2.1
S. No. Statements Focusing on Perception of Television Advertising Among Rural Respondents
1 Television advertising is a necessary component of the market place, which on an average raises the standard of living.
2 Television advertising results in making the consumers more brand conscious regarding the toiletries.
3 Television advertising is a source of information about products, which in turn affects the social roles and lifestyle.
4 Advertisements on television encourage materialism and corruption of societal values.
5 Repeated advertisements on television make the attitude more favorable about the product.
6 Television advertisements induce impulsive buying in majority of the consumers.
7 Advertising on television creates an image about the product in our minds , which in turn influences the purchase of that brand.
8 Advertisements differ in effectiveness primarily due to variation in ads creative cues.
9 Campaigns using Television media significantly outperform other medias of advertising.
10 Television Advertising is a need creating process.
11 TV Advertisements based on village life are true representative of Indian culture and traditions.
12 Majority of people living in the villages can judge the factual societal, political and economic impacts of advertising.
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Construction of Correlation Coefficient Matrix of E xplanatory Variables:
It is a lower triangle Matrix showing simple correlations among all possible
pairs of variables included in the analysis. For the application of Factor Analysis, it is
obligatory that the data matrix should have enough correlations. If visual inspection
reveals no substantial number of correlations greater than 0.30, then the factor analysis
is probably inappropriate. (Hair, 2007). The Correlation Coefficient Matrix has also
been computed for the data to check the inter-correlation between various variables. For
the factor analysis to be appropriate, the variables must be correlated.
Anti-Image Correlation Matrix:
It is the matrix of partial correlations among variables. The diagonal contains the
measures of sampling adequacy for each variable and the off-diagonal elements are the
partial correlations among variables. If true factors existed in the data, the partial
correlations would be small (Hair, 2007). Present study has also computed Anti-Image
correlations and found that the partial correlations are very low indicating that true
factor existed in the data.
Kaiser-Meyer-Oklin (KMO) Measure of Sampling Adequacy:
It is an index used to examine the appropriateness of factor analysis. High values
(between 0.5 and 1.0) indicate adequacy of data for the use of Factor Analysis
(Malhotra, 2007). Here, the computed value of KMO statistic is 0.818 indicating the
adequacy of data for Factor Analysis.
Bartlett’s Test of Sphericity:
It is a test often used to examine the hypothesis that the variables are
uncorrelated in the population i.e. population correlation matrix is an identity matrix
(Malhotra 2007). This test finds the overall significance of correlation matrix and
provides the statistical probability that the correlation matrix has significant correlations
among at least some of the variables (Hair, 2007). Here, Bartlett’s Test’s Chi-square
value is 1.500E3 (approx), Df = 66, significant at 0.000. This significant value indicates
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that correlation coefficient Matrix is not an identity matrix. All this ensures the
adequacy of data for application of Factor Analysis.
From the above discussion, the following results have been extracted:
(i) Correlation Coefficient Matrix contains enough high correlations. (ii) Anti-Image Correlation Matrix contains low partial correlations.
(iii) Value of KMO statistic is large. (iv) Value of Bartlett’s Test of Sphericity is significant.
All this confirms the adequacy of data for application of Factor Analysis. Now,
after ensuring the reliability of scale and testing the adequacy of data, the set of 12
statements regarding the factors affecting the perception of respondents towards
television advertising were subjected to Factor Analysis. Principal Component Analysis
(PCA) was used for extraction of factors and the number of factors to be retained was
on the basis of Latent Root Criterion (Eigen Value Criterion). An Eigen value
represents the amount of variance associated with the factor. Thus, only the factors
having latent roots or Eigen values greater than 1 are considered significant; all the
factors with latent roots less than 1 are considered insignificant and are disregarded
(Hair, 2007). Therefore, factors with Eigen values more than one should be selected.
Three components were found to have Eigen values greater than unity and total
variance accounted for by these factors is 57.364 percent and remaining 42.636 percent
was explained by other factors.
Then, in the next step, we orthogonally rotated the principal factors using
Varimax Rotation. This method minimizes the number of variables that have high
loading on a factor and there by enhancing the interpretability of factors (Malhotra,
2007). Rotation does not affect the communalities and the percentage total variance
explained. However, the percentage of variance accounted for by each factor does
change. The variance explained by the rotated factors is redistributed by rotation.
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As per (Bhaduri, 2002), the factor loadings greater than 0.45 should be retained
(ignoring signs) because loadings below it are poor. The study has also followed the
same criterion for factor loadings. The Varimax Rotated Factor Loading Matrix has
been presented in Table 5.2.2 Scrutiny of Table 5.2.2 revealed that there are three
factors which together accounted for 57.364 percent variance. It shows that 57.364
percent of total variance is explained by the information contained in the factor matrix.
Thus, a model with these three factors explaining 57.364 percent variance.
Communality shows the amount of variance a variable shares with all the other
variables being considered. It can also be treated as the proportion of variance explained
by the common factors. The size of communality is the index for assessing how much
variance in a particular variable is accounted for by the factor solution. Large size of
communalities indicates that a large amount of variance in a variable has been extracted
by factor solution while small size of communalities shows that a significant amount of
variance in a variable has not been accounted for by the factor solution. Communalities
are considered high if they are all 0.8 or greater but this is unlikely to occur in real data.
Generally accepted communalities lie in the range of 0.40 to 0.80 (Costello and
Osborne, 2005). In our study all the communalities were above 0.40 and many of them
were above or very close to 0.7 also. We finally found that the variables X7, X8, X10,
X11, X12 loaded on factor 1, the variables X2, X4, X5, X6, and X9 were loaded on
factor 2 and variables X1 and X3 were loaded on factor 3.
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Table 5.2.2
Varimax Rotated Factor Loading Matrix
Components
Variables 1 2 3 Communality
X1 .048 .097 .837 .712
X2 .009 .442 .298 .285
X3 .121 .406 .560 .493
X4 .079 .671 .076 .463
X5 .224 .655 .263 .549
X6 .098 .695 .127 .509
X7 .631 .434 .099 .596
X8 .693 .408 -.111 .659
X9 .497 .592 -.239 .655
X10 .786 .320 -.027 .721
X11 .778 -.096 .080 .621
X12 .734 -.035 .284 .621
Eigen Values 4.236 1.580 1.067 6.883
Percent of Variation 35.300 13.169 8.895 ----
Cumulative Variation 35.300 48.469 57.364 ----
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Interpretation of Factors:
A factor loading represents the correlation between variable and its factor. Their
signs are just like any other correlation coefficient. Like signs mean the variables are
positively related and opposite signs mean the variables are negatively related. In fact
the variables carried out in this research study do not reveal any negative related factor
loading. Factors can be labeled symbolically as well as descriptively. Symbolic tags are
precise and help avoiding confusion (Rummel, 1970). Present study has also given
symbolic labels to the factors. The factors along with their codes and factor loadings are
given in Table 5.2.3
Rationale of TV Advertisement (F1):
Perusal of Table 5.2.3 reveals that it is the most significant factor with 35.300
percent of total variance explained. Total five variables have been loaded on this factor.
This factor reveals that in the changing world scenario respondents believe that
television plays a dominant position in selling of the products. The respondents in all
consider brand image, effectiveness, Indian culture etc. to be the dimensions of
advertisement which are important for creating awareness about new products, wherein
media plays a dominant role.
Attitudinal changes due to TV Advertisements (F2):
Analysis of Table 5.2.3 shows that it is the second important factor with 13.169
percent variance explained, talks about the trustworthiness placed on the advertisements
by the respondents as they are making the respondents more brand conscious, and
induce impulsive buying among them.
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Table 5.2.3
Interpretation of Factors
Factor Loadings Statements included in the Factor
Rationale of TV Ads (F1)
0.596
Advertising on television creates a brand’s image about the product in our minds, which in turn influences the purchase of that brand. (X7)
0..693
Advertisements differ in effectiveness primarily due to variation in ads creative cues. (X8)
0.786
Television Advertising is a need creating process (X10).
0.778
TV Advertisements based on village life are true representative of Indian culture and traditions. (X11)
0.734
Majority of people living in the villages can judge the factual societal, political and economic impacts of advertising. (X12)
Attitudinal changes due to TV
Advertisements (F2)
0.442
Television advertising results in making the consumers more brand conscious regarding the toiletries. (X2)
0.671
Advertisements on television encourage materialism and corruption of societal values. (X4)
0.655 Repeated advertisements on television make the attitude more favorable about the product (X5)
0.695 Television advertisements induce impulsive buying in majority of the consumers (X6)
0.592 Campaigns using Television media significantly outperform other medias of advertising. (X9)
Impact of TV Advertisements(F3)
0.837 Television advertising is necessary component of the market place, which on an average raises the standard of living. (X1)
0.560
Television advertising is a source of information about products, which in turn affects the social roles and lifestyle.(X3)
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Impact of Advertisements (F3):
Examination of Table 5.2.3 shows that it is the third important factor with 8.895
percent variance explained, talks about the television advertising being the important
component which affects the social roles and lifestyle.
5.3 Perception about People Who Get Influenced by the TV Ads of Toiletries
Today, in the world of advertisements, many of us just purchase a product
because of its inducing and repetitive advertisement on the television. This question was
asked to the rural respondents to know the perception about people who get influenced
by the TV ads of toiletries.
Interpretation of Data
The scrutiny of Table 5.3 presents that 43.5 percent of the respondents feel that
76 and above percentage of population gets influenced by TV ads, whereas 21.8 percent
feels that 26-49 percentage of population gets influenced by TV ads followed by 18.5
percent perceiving that 50-75 percent of the population are induced by TV ads and 16.3
percent feel that 0-25 percent population is attracted towards the television ads of
toiletries.
It can thus, be concluded that most of the respondents feel that a large
percentage of their fellow population gets influenced by TV advertisements and are
stimulated to buy the toiletry advertised on the television.
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TABLE 5.3
Perception about People Who Get Influenced by TV Ads
Sr. No.
Perception about people who gets influenced by TV Ads
No. of Respondents
Percentage
1
0-25 65 16.3
2
26-49 87 21.8
3
50-75 74 18.5
4
76 and Above 174 43.5
Total 400 100
5.4 The Brands of Various Toiletries Used by the Rural Respondents 5.4.1 Bathing Soap Interpretation of Data
Table 5.4.1 shows rural usage of Bathing soap brand. 24 percent are using
Lifebuoy and 17 percent use Fair Glow, followed by Breeze (16.3 percent), Godrej
No.1 (15 percent), Lux (12 percent), Cinthol (9.3 percent) and Hamam (6.5 percent).
Considering the high competition and saturation of products in the urban areas,
the big FMCG players have started concentrating in the rural markets where the
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potential is still untapped. The penetration levels of the FMCG’s are increasing year
after year because of the aggressive approach of corporate sector on one hand and rising
disposable income of the rural areas on the other. Since, the new consumers are entering
the markets at a quick pace, it is up to the corporate world and the acumen of the
marketer, as to how to develop innovative model for taking their goods to the rural
heartland in a cost effective manner.
TABLE 5.4.1
Brand Usage of Bathing Soap
Sr. No. Brand Name No. of Respondents Percent
1
Hamam
26 6.5 2
Lux
48 12 3
Lifebuoy
96 24 4
Breeze
65 16.3 5
Cinthol
37 9.3 6
Fair Glow
68 17 7
Godrej No.1
60 15
Total 400 100
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5.4.2 Washing Soap/Powder
Interpretation of Data
Table 5.4.2 shows rural usage the brand of washing soap/ powder. 25 percent of
the respondents make use of Nirma Washing Powder, followed by Surf excel (21
percent), Rin Shakti (16.3 percent), Wheel (13.3 percent), Super 501 (10.3 percent),
Henko (7.5 percent), and Ghari (6.5 percent).
The main feature which has made Nirma Brand popular in rural areas is that it is
the lowest priced detergent. Nirma has become a generic to the washing powder
category and has virtually ruled the rural markets with no competition worth the name
for a long time. Surf was the first ever detergent to be introduced in India by HLL in
1959. It had a virtual monopoly in the detergents category but the introduction of low
priced detergents overpowered it soon.
TABLE 5.4.2
Brand Usage of Washing Soap/ Powder
Sr. No.
Brand Name No. of Respondents Percent
1
Wheel 53 13.3
2
Rin Shakti 65 16.3
3
Super 501 41 10.3
4
Surf Excel 84 21
5
Nirma 100 25
6
Ghari 26 6.5
7
Henko 30 7.5
8
Others 1 0.3
Total 400 100
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5.4.3 Shampoo
Interpretation of Data
Velvette shampoo was found to be the most used brand among the rural
respondents with 39.5 percent using the brand. Vatika (30.5 percent) is the next most
utilized brand, followed by Clinic All Clear and Rejoice (7.8 percent) each, Pantene
(5.8 percent), Chik (5.3 percent) and Sunsilk (3.5 percent).
TABLE 5.4.3
Brand Usage of Shampoo
Sr. No.
Brand Name No. of Respondents Percent
1
Velvette 158 39.5
2
Pantene 23 5.8
3
Sunsilk 14 3.5
4
Chik 21 5.3
5
Vatika 122 30.5
6
Clinic All Clear 31 7.8
7
Rejoice 31 7.8
Total 400 100
5.4.4 Talcum Powder
Interpretation of Data
Spinz (31 percent) talcum powder was the most largely used brand. It is
followed by Ponds (20 percent), Emami (16 percent), Ayur (12.8 percent), Breeze (8.5
percent), Axe Denim (6.8 percent), and Lifebuoy Active (5 percent).
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It has been seen that though lifebuoy soap is the first preference of the rural
masses but as far as talcum powder is concerned, it is the least used brand. It shows the
rationality of the rural consumers who know what is best for them. It can also be
attributed to the repetitive advertisements on the television about a particular brand of a
product category.
TABLE 5.4.4
Brand Usage of Talcum Powder
Sr. No. Brand Name No. of Respondents Percent
1
Ponds 80 20
2
Spinz 124 31
3
Emami 64 16
4
Ayur 51 12.8
5
Breeze 34 8.5
6
Axe Denim 27 6.8
7
Lifebuoy Active 20 5
Total 400 100
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5.4.5 Toothpaste
Interpretation of Data
Analysis of table 5.4.5 illustrates that 37 percent of the respondents prefer
Promise toothpaste over the other brands. Colgate (15.5 percent) is the next favorite
brand of toothpaste, followed by Dabur Lal (15 percent), Close Up (13 percent), Babool
(10.5 percent), Cibaca (5.3 percent) and Pepsodent (3.8 percent).
The preferential treatment given to Promise has its foundation in the claim in the
TV ads that it contains Clove oil which is considered to be the best remedy for painful
teeth and gums.
TABLE 5.4.5
Brand Usage of Toothpaste
Sr. No. Brand Name No. of Respondents
Percent
1
Close up 52 13
2
Colgate 62 15.5
3
Dabur Lal 60 15
4
Promise 148 37
5
Babool 42 10.5
6
Pepsodent 15 3.8
7
Cibaca 21 5.3
Total 400 100
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5.4.6 Creams
Interpretation of Data
Table 5.4.6 shows that 28.3 percent respondents prefer Fairever cream over the
others. It is followed by Fair and Lovely (20 percent), Charmis (16 percent), Boroplus
(11.3 percent), Ponds (8.8 percent), Nivea (8.3 percent) and Ayur (7.5 percent).
Today, the TV advertisements allege that the use of creams can make an
individual fair and beautiful. The preference of such creams like Fairever, Fair and
Lovely by the rural individuals shows the direct effect of the television advertisements
on the purchase behaviour.
TABLE 5.4.6
Brand Usage of Creams
Sr. No.
Brand Name No. of Respondents Percent
1
Ponds 35 8.8
2
Fair and Lovely 80 20
3
Fairever 113 28.3
4
Charmis 64 16
5
Boroplus 45 11.3
6
Nivea 33 8.3
7
Ayur 30 7.5
Total 400 100
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5.4.7 Blue Interpretation of Data
Table 5.4.7 explains that 19.5 percent of the respondents use Nirma blue for
their clothes followed by Ranipal (17.5 percent), Aarti (16.5 percent), Robin Blue (14.3
percent), Neel (11.3 percent), Ujala (10.8 percent), and Henko 10 percent).
TABLE 5.4.7
Brand Usage of Blue
Sr. No.
Brand Name No. of Respondents Percent
1
Ujala 43 10.8
2
Robin 57 14.3
3
Aarti 66 16.5
4
Nirma 78 19.5
5
Ranipal 70 17.5
6
Neel 45 11.3
7
Henko 40 10
8
Others 1 0.3
Total 400 100
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5.4.8 Hair Oil Interpretation of Data
Table 5.4.8 demonstrates that Parachute and Keo Karpin hair oil are both
equally preferred by 26.3 percent of the respondents in rural areas. Navrattan oil (12.3
percent) is the next preferred brand, followed by Almond Oil (10.8 percent), Shanti
Amla (9.8 percent), Vatika (8 percent) and Medikar (6.8 percent).
TABLE 5.4.8
Brand Usage of Hair Oil
Sr. No.
Brand Name No. of Respondents Percent
1
Parachute 105 26.3
2
Shanti Amla 39 9.8
3
Medikar 27 6.8
4
Navrattan 49 12.3
5
Keo Karpin 105 26.3
6
Almond Oil 43 10.8
7
Vatika 32 8
Total 400 100
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The analysis of data above about the brand usage of various toiletries reveals
that the most preferred brand of bathing soap is Lifebuoy whereas that of washing soap
is Nirma. A large number of rural consumers are found to use Velvette shampoo, Spinz
talcum powder, Promise toothpaste, and parachute hair oil. The results show that the
brands of toiletries chosen by the rural consumer are those which are in medium to low
price category. The marketers need to design their strategies in such a manner that their
products in high price category are also promoted and purchased by the rural
consumers.
5.5 Factors Evolving Preference of a Particular Brand of Toiletry Interpretation of Data
Respondents were asked to rank the factors which affected their preference of
use of particular brand of toiletry. Rank 1 depicts the most preferred factor and rank 9
depicts least preferred factor. Table 5.5.1 gives the frequency of responses of consumers
giving different ranks to different factors. It shows that Economical and Promotional
Schemes are the most favored factors for use of a particular brand of toiletry, followed
by Quality, specific design, Packaging, availability, Discount offers, celebrity
advertisement and colour of the product.
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TABLE 5.5.1
Factors Responsible for Preference of a Particular Brand of Toiletry
Sr. No
FACTORS Rank 1
Rank 2
Rank 3
Rank 4
Rank 5
Rank 6
Rank 7
Rank 8
Rank 9
Mode
1
QUALITY 31
(7.8) 61
(15.2) 110
(27.5 77
(19.2) 31
(7.8) 30
(7.5) 32
(8.0) 0
(0.0) 28
(7.0) 3
2.
ECONOMICAL 90
(22.5) 62
(15.5) 34
(8.5) 18
(4.5) 77
(19.2) 30
(7.5) 1
(0.2) 30
(7.5) 58
(14.5) 1
3.
SPECIFIC DESIGN 79
(19.8) 64
(16.0) 86
(21.5) 31
(7.8) 3
(0.8) 3
(0.8) 73
(18.2) 2
(0.5) 59
(14.8) 3
4. PACKAGING 5
(1.2) 35
(8.8) 4
(1.0) 117
(29.2) 31
(7.8) 73
(18.2) 32
(8.0) 43
(10.8) 60
(15.0) 4
5. COLOUR 59
(14.8) 2
(0.5) 59
(14.8) 49
(12.2) 58
(14.5) 63
(15.8) 2
(0.5) 73
(18.2) 35
(8.8) 8
6. AVAILABILITY 5
(1.2) 86
(21.5) 5
(1.2) 3
(0.8) 89
(22.2) 88
(22.0) 59
(14.8) 33
(8.2) 32
(8.0) 5
7. CELEBRITY
ADVERTISEMENT 0
(0.0) 62
(15.5) 29
(7.2) 29
(7.2) 35
(8.8) 32
(8.0) 61
(15.2) 90
(22.5) 62
(15.5) 8
8. DISCOUNT
OFFERS 44
(11.0) 31
(7.8) 58
(14.5) 30
(7.5) 46
(11.5) 5
(1.2) 89
(22.2) 62
(15.5) 35
(8.8) 7
9. PROMOTIONAL
SCHEMES 86
(21.5) 2
(0.5) 62
(15.5) 60
(15.0) 1
(0.2) 60
(15.0) 34
(8.5) 64
(16.0) 31
(7.8) 1
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Spearman’s Rank Correlation
Further, in order to find the relationship between various factors preferred for
usage of a particular brand of toiletry, the Spearman’s Rank Order correlation was
applied to the responses of consumers. The values of the coefficient range form 1 to +1.
The sign of the co-efficient indicates the direction of the relationship, and its absolute
value indicates the strength. It means that larger absolute values indicate stronger
relationship. Table 5.5.2 shows the Spearman’s Rank Order correlation for various
factors considered for product choice.
The highest correlation was between “Celebrity advertisement” and “Discount
Offers” .476, followed by “Colour” and “Packaging” (.443), “Discount Offers” and
“Availability”.401.
Quality has correlation with Economical at 5 percent level of significance;
Economical has strong correlation with Celebrity Advertisement at 1 percent level of
significance, Specific Design with Colour at 1 percent level of significance and
Promotional Schemes with Packaging.
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TABLE 5.5.2
Spearman Rank Order Correlation
Factors Quality Economical Specific design Packaging Colour Availability Celebrity
advertisement Discount
offers
Promotional schemes
Quality 1.000 .113* .061 -.024 .044 -.441** -.036 -.113* -.366**
Economical .113* 1.000 -.046 -.278** -.475** -.510** .366** -.192** -.071
Specific design
.061 -.046 1.000 .241** .305** .073 -.332** -.546** -.420**
Packaging -.024 -.278** .241** 1.000 .443** -.273** -.562** -.594** .026
Colour .044 -.475** .305** .443** 1.000 .190** -.723** -.417** -.255**
Availability -.441** -.510** .073 -.273** .190** 1.000 -.072 .401** -.149**
Celebrity advertisement
-.036 .366** -.332** -.562** -.723** -.072 1.000 .476** -.050
Discount offers
-.113* -.192** -.546** -.594** -.417** .401** .476** 1.000 -.013
Promotional schemes
-.366** -.071 -.420** .026 -.255** -.149** -.050 -.013 1.000
* Correlation is significant at 5 percent level of significance. ** Correlation is significant at 1 percent level of significance.
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5.6 Perception about the Price of Products Advertised on Television Interpretation of Data
Table 5.6 illustrates that 55.3 percent respondents believe that products
advertised on television are priced higher than the products that are not advertised,
whereas 33.5 percent do not agree that products advertised are priced higher and 11.3
percent have no idea about the relation between prices of products and the
advertisements.
TABLE 5.6
Perception about the Price of Products Advertised on Television
Sr. No. Perception No. of Respondents Percent
1 Yes 221 55.3
2 No 134 33.5
3 Can’t say 45 11.2
Total 400 100
The analysis above proves the rationality of the rural consumers, who perceive
that it is actually the consumers who bear the advertising costs incurred by the
companies. They also recognize the fact that the price of the advertised products are
higher than the products that are not advertised yet, the purchase of the advertised
brands of toiletries by the consumers prove that the benefits of advertising surpass its
drawbacks.
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5.7 Belief about the Promotional Scheme Claims
Interpretation of Data
Table 5.7 shows that 35 percent respondents believe that 0-25 % of the prize and
gift voucher claims are trustworthy, followed by 26-49 % (33.7 percent), 50-75 % (19
percent) and 76 and above (12.3 percent)
TABLE 5.7
Belief about the Promotional Scheme Claims
Sr. No. Beliefs No. of Respondents Percent
1 0-25 % 140 35
2 26-49 % 135 33.7
3 50-75 % 76 19
4 76 % and above 49 12.3
Total 400 100
Due to the increasing competition among the FMCG players to tap the rural
potential to the maximum, the companies are providing the consumers with many
promotional schemes. The consumers residing in rural areas consider these promotional
schemes to be trustworthy to an extent but cannot be always relied upon.
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FINDINGS
The findings that have emerged from the chapter are:
• While making the buying decisions in the family, majority of the respondents
were found to play the role of an influencer, followed by role as a Decider,
initiator, buyers and users of the particular brand of a toiletry.
• In order to find out the factors influencing the perception of rural consumer for
television advertising, the factor analytic technique has been applied. Factor
analysis reveals that three factors had Eigen values exceeding 1 and they
accounted for as high as 57.364 percent variance. The strongest factor which
influenced the perception of rural consumer has been “Rationale of TV
advertisements” with Eigen value of 4.236 and contributes 35.300 percent of
total variance. The second important factor has come out to be “Attitudinal
change due to television advertisements”, and the third important factor is
“Impact of Advertising on lifestyle of rural consumers”. This shows that rural
consumers believe that television plays an important role in today’s world and
has brought about a drastic change in the outlook and approach of rural
consumers.
• A good number of the respondents feel that a large percentage of their fellow
population gets engrossed in TV advertisements and are stimulated to buy the
toiletry advertised on the television
• The analysis of brand usage of various toiletries among rural masses revealed
that the most preferred brand of bathing soap is Lifebuoy whereas that of
washing soap is Nirma. A large number of rural consumers were found to use
Velvette shampoo, Spinz talcum powder, Promise toothpaste, and parachute hair
oil as their favorite brands of toiletries. The reason for the choice of the brands
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of various toiletries is majorly based on the television advertisements or
hoardings of those brands in the villages and fairs.
• Respondents were asked to rank the factors which affected their preference of
use of particular brand of toiletry. The results disclosed that Economical and
Promotional Schemes were the most favored factors for use of a particular brand
of toiletry, followed by Quality, specific design, Packaging, availability,
Discount offers, celebrity advertisement and colour of the product. Spearman’s
Rank Order correlation was applied to find the relationship between various
factors preferred for usage of a particular brand of toiletry. The highest
correlation was between “Celebrity advertisement” and “Discount Offers”,
followed by “Colour” and “Packaging”, “Discount Offers” and “Availability”.
• Many of the respondents were found to believe that products advertised on
television are priced higher than the products that are not advertised. They also
considered the prize and gift voucher claims on various brands of toiletry as
trustworthy.
To check the brand consciousness of the rural consumers for the purchase of
toiletries, they were first asked about the role they played in making the purchase
decision. As two members were chosen from each of the household, one being the head
of the family and another being the younger member, majority of the respondents were
found to play a role of a decider and an influencer. The various brands that were
popular among the consumers were Lifebuoy bathing soap, Nirma washing powder,
Velvette shampoo, Spinz talcum powder, Promise toothpaste, Fairever facial cream,
Nirma blue and Parachute and Keokarpin hair oil. The main factors considered
responsible by the consumers for their preference of a particular brand of toiletry were
low price of the product and the various promotional schemes available. The least
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preferred factors that affected the purchase were celebrity advertisements and colour of
the toiletry.
To know about the perception of the consumers towards television advertising,
factor analytic approach was applied which, extracted three factors which were labeled
in accordance of their importance as Rationale of TV ads, attitudinal changes due to
television ads and Impact of television ads. The consumers though believed that a large
number of their fellow villagers got influenced by the televisions ads and also trusted
the promotional scheme claims, yet, they were aware of the fact that the products
advertised on television are priced higher than the products that are not being
advertised.