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


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


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.


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


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


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


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.


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.


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.


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


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.

chapter – v brand consciousness and perceived effect...

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