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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=
d&output=search&sclient=psy-ab&q=chi+square+table&oq=chi+&gs_l=hp.1.1.0i20l2j0l8.2031.3453.1.5619.4.4.0.0.0.0.190.724.0j4.4.0.les%3B..0.0...1c.1.SzszzGz2XX4&psj=1&bav=on.2,or.r_gc.r_pw.r_cp.r_qf.&bvm=bv.1355534169,d.bmk&fp=abe7578b7545eafb&bpcl=40096503&biw=1366&bih=608
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