MARKET RESEARCH ON HEALTH DRINKS IN INDIA

PRESENTED BY,GROUP NO-01ANIMESH AMAL (01)MADHURA JAGTAP (10)SHAFAATALI (18)BHAVIKA SACHDEV (23)BOSCO JAMES (15)

INTRODUCTION MAJOR PLAYERS IN INDIA RESEARCH METHODOLOGY PIMARY INVESTIGATION COLLECTION OF QUANTITATIVE DATA SAMPLING PROCESS FIELD WORK DATA ANALYSIS PLAN FINDINGS CHI-SQUARE ANALYSIS CONCLUSION REFERENCES

CONTENTS

People are turning more health conscious these

days. Because of this the non-carbonated beverage

segment has become one of the fastest growing and most exciting businesses at the moment.

Consumers today have better tasting and more healthy alternatives

Since the year 2007, the country has seen numerous product launches in the field of nutraceuticals/functional foods and beverages that cater to distinct consumer brackets and ages.

Introduction

To study the market potential of health drinks

To evaluate the consumer preference and consumer behaviour towards health drinks

Objectives

Powder Category

MAJOR PLAYERS IN INDIA

Liquid Category

Traditional Category

New Market Players

Research Design

This phase involved preliminary investigation

of the various factors which could possibly affect the consumer’s perception about the various brands and in turn influence the purchase decisions of the consumer. The secondary data gathered was analysed to understand the current scenario of the health drinks segment.

Conti…..

1) Age

DATA ANALYSIS PLAN

Less than 20 9 5%

20-23 80 49%

23-25 55 34%

More than 25 20 12%

Gender

Male 92 56%

Female 72 44%

Education

SSC/HSC

5 3%

Under Graduate 13 8%

Graduate 76 46%

Post graduate 70 43%

Occupation

Student

107 65%

Self employed/ Business 15 9%

Service 37 23%

House wife 5 3%

Solid form

Health drinks

Horlicks 24 15%

Bournvita 82 50%

Complan 14 8%

Other 45 27%

Stored/canned juices

Conti…

Tropicana 62 38%

Real Fruit Juices 66 40%

Other 36 22%

Dairy products

Conti…

Buttermilk 76 46%

Energee (Aarey) 33 20%

Yakult (probiotic) 15 9%

Other 40 24%

Frequency

Morning 108 66%

Evening 33 20%

Night 23 14%

Once 121 74%

Twice 37 23%

More than twice 6 4%

Market Place

Super Markets 64 39%

Local General Stores 76 46%

Medicals 17 10%

Other 7 4%

Sources Of The Information

TV advertisements 67 41%

From Doctors/ Medicals 16 10%

Hoardings/ Paper Ads 6 4%

Other 75 46%

Gender and Brand-

Findings

  Bournvita complan Boost Horliks Other

Male 44 10 2 12 25

Female 38 4 0 12 18

Bournvita

complan

Boost

Horliks

Other

0 10 20 30 40 50 60 70 80 90

MaleFemale

Age and Brand  Bournvita complan Boost Horliks Other

less than 20 6 2 0 1 0

20-23 45 5 1 9 20

23-25 25 6 1 11 13

more than 25 6 1 0 3 10

Bournvita

complan

Boost

Horliks

Other

0 10 20 30 40 50 60 70 80 90

less than 2020-2323-25more than 25

Education and Brand

  Bournvita complan Boost Horliks Other

SSC/HSC 4 1 0 0 0

Under Graduate 10 0 0 2 1

Graduate 27 9 1 13 26

Post Graduate 41 4 1 9 16

Bournvita

complan

Boost

Horliks

Other

0 10 20 30 40 50 60 70 80 90

SSC/HSCUnder GraduateGraduatePost Graduate

Income and Brand

  Bournvita complan Boost Horliks Other

Less than 1 lac 35 5 1 9 13

1-3 lac 22 5 0 5 17

3-5 lac 14 1 1 5 6

more than 5 lac 12 3 0 5 6

Bournvita

complan

Boost

Horliks

Other

0 10 20 30 40 50 60 70 80 90

Less than 1 lac1-3 lac3-5 lacmore than 5 lac

Brand Vs Gender

Chi-Square AnalysisGender * Brand Crosstabulation

  Brand Total

Bournvita Boost Complan Horlicks Other

Gender

Male

Count 43 2 10 12 25 92

Expected Count

45.4 1.1 7.9 13.5 24.1 92.0

Female

Count 38 0 4 12 18 72

Expected Count

35.6 .9 6.1 10.5 18.9 72.0

Total

Count 81 2 14 24 43 164

Expected Count

81.0 2.0 14.0 24.0 43.0 164.0

 Chi-Square Tests

  Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 3.635a 4 .458

Likelihood Ratio 4.438 4 .350

Linear-by-Linear Association .147 1 .701

N of Valid Cases 164    

a. 2 cells (20.0%) have expected count less than 5. The minimum expected count is .88.

Here Sig value is >0.05So Null hypothesis is accepted,There is no relationship between Brand and Gender

Age * Brand Crosstabulation

  Brand Total

Bournvita Boost Complan Horlicks Other

Age

Less than 20Count 6 0 2 1 0 9

Expected Count

4.4 .1 .8 1.3 2.4 9.0

20-23Count 45 1 5 9 20 80

Expected Count

39.5 1.0 6.8 11.7 21.0 80.0

23-25Count 24 1 6 11 13 55

Expected Count

27.2 .7 4.7 8.0 14.4 55.0

More than 25Count 6 0 1 3 10 20

Expected Count

9.9 .2 1.7 2.9 5.2 20.0

TotalCount 81 2 14 24 43 164

Expected Count

81.0 2.0 14.0 24.0 43.0 164.0

Brand Vs Age

Chi-Square Tests

  Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 15.479a 12 .216

Likelihood Ratio 16.851 12 .155

Linear-by-Linear Association 7.950 1 .005

N of Valid Cases 164    

a. 11 cells (55.0%) have expected count less than 5. The minimum expected count is .11.

Here Sig value is >0.05So Null hypothesis is accepted,There is no relationship between Brand and Age.

Education * Brand Crosstabulation

  Brand Total

Bournvita Boost Complan Horlicks Other

Education

SSC/HSCCount 4 0 1 0 0 5

Expected Count

2.5 .1 .4 .7 1.3 5.0

Under GraduateCount 10 0 0 2 2 14

Expected Count

6.9 .2 1.2 2.0 3.7 14.0

GraduateCount 27 1 9 13 26 76

Expected Count

37.5 .9 6.5 11.1 19.9 76.0

Post graduateCount 40 1 4 9 15 69

Expected Count

34.1 .8 5.9 10.1 18.1 69.0

TotalCount 81 2 14 24 43 164

Expected Count

81.0 2.0 14.0 24.0 43.0 164.0

Brand Vs Education

Chi-Square Tests

  Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 15.743a 12 .203

Likelihood Ratio 18.928 12 .090

Linear-by-Linear Association .028 1 .866

N of Valid Cases 164    

a. 11 cells (55.0%) have expected count less than 5. The minimum expected count is .06.

Here Sig value is >0.05So Null hypothesis is accepted,There is no relationship between Brand and Education.

Income * Brand Crosstabulation

  Brand Total

Bournvita

Boost Complan Horlicks Other

Income

Less than 1lacCount 43 1 5 10 14 73

Expected Count

36.1 .9 6.2 10.7 19.1 73.0

1-3lacCount 19 0 5 6 17 47

Expected Count

23.2 .6 4.0 6.9 12.3 47.0

3-5lacCount 10 1 1 4 6 22

Expected Count

10.9 .3 1.9 3.2 5.8 22.0

More than 5lacCount 9 0 3 4 6 22

Expected Count

10.9 .3 1.9 3.2 5.8 22.0

TotalCount 81 2 14 24 43 164

Expected Count

81.0 2.0 14.0 24.0 43.0 164.0

Brand Vs Income

Chi-Square Tests

  Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 10.618a 12 .562

Likelihood Ratio 10.539 12 .569

Linear-by-Linear Association 2.514 1 .113

N of Valid Cases 164    

a. 9 cells (45.0%) have expected count less than 5. The minimum expected count is .27.

Here Sig value is >0.05So Null hypothesis is accepted,There is no relationship between Brand and Income.

Using health drinks is a popular practice among people for a

variety of reasons. consumer consume one health drink with a frequency of

once in a day, twice in a day or more than twice in a day. Future research should identify if people of age group 20-25

will continue to consume health drinks. Their perception about health drinks regarding taste,

nutrition. Now a days the awareness about Biotech product are not

very well. There are 9% market of biotech products share , it means it

has good potential to increase its market share for biotech product such as Yakult.

Conclusion

www.scrib.com articles.timesofindia.com www.yakuly.co.in Asian Journal of Food & Agro Industry https://www.google.co.in/#hl=en&safe=off&tbo=

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http://www.nutritionj.com/about/access/#opendata http://www.studymode.com/essays/Market-Survey-Of

-Traditional-Health-Drinks-593080.html http://answers.yahoo.com/question/index?qid=2008

0922192313AAcoWyq

References