final ppt

PRESENTED TO:Saurabh Agarwal(09283)

Vijit Kumar(0294)Pawandeep (09275)Vineet Singh(09295)

Atul O Pathak(09261)Samit Sinha(09282)

Ankit Chaturvedi(09254)Rachit Singh(09277)

India is world’s second largest producer of food after China and has the potential of being the biggest with Food & Agricultural sector.

The total food production in India is likely to be double in next ten years & there is an opportunity for large investments in food industry especially in Packaged Foods, Beverages & Soft Drinks.

Indian Food Industry…

Health food & supplements is another rapidly rising segment of industry that is gaining vast popularity amongst health conscious people.

Growth in package food industry - 8% - 9%. Demand of Packaged Food in India – In India the

demand for packaging goods has been increased immensely, it is just because of: -

• Increase in per capita income. • Standard of living.• Purchasing power & Consumer Expenditure.• Source of Income of the family has been increased

mainly in urban areas.

The Packaged Food Industry in India

Size - The size of packaged food market in India is estimated at $10 billion & is expected to reach at $ 20 billion by 2014.

Product coverage - ready to eat products, Baby food, Bakery products,Snacks/confectionary food etc

Continued…

Some of the key players in this industry are HUL(tea, instant coffee,biscuits), ITC NESTLE(ready to eat product, instant coffee) PepsiCo & Haldiram (sweets, namkeens,

snacks).

To determine the consumer preference towards packaged food.

Various factor affecting consumer perception towards packaged food.

Research Design - Descriptive research.• Sample Unit - The sample unit of our study

is all those persons who are coming to retail stores, people who buy package foods in NCR region.

• Sample size - The sample size for the study is thirty.

• Sampling area - Delhi, Noida & Ghaziabad.

• Sampling Technique - Conveyance sampling.

Research Design

Data Collection - There are 2 sources for data collection : -

• Primary source.• Secondary source.The primary data was collected through

structured questionnaire. As per our research study we have collected primary data.

Continued..

Interpretations

The person for whom the respondants buy came out to be- Myself-44% ,Family-5%,children-25%,Institutional

purposes/Social occasions-26%.

The type of packaged food genrealy bought. Ready to cook food Bakery products-15%,Dairy products-

35%, Staples-36.5,Fruit drinks -13.5%etc.

Interpretations

The store they preferred was

Kirana store-42.5%,organized retails store-57.5%.

Crosstabulation age and categories to packaged foods..

Nutritional value.

Ready to cook Bakery products Dairy

products Stapels Fruit

drinks. Count 1 4 0 1 10 17-21 Expected Count

11.8 2.9 2.9 2 4.1

Count 2 0 0 7 3 21-24 Expected Count

3.9 1.0 1.0 2.7 1.4

Count 0 0 1 8

1 25-28

Expected Count

2.7 .7 .7 1.9 1.0

Count 18 4 4 9 4

age

>31 Expected Count

1.6 .4 .4 41.1 .5 Higher income groups buy most from staples and dairy category,and lower in ready to eat and drinks

Chi-Square Tests

Va lue df

Asymp. Sig. (2-s ided)

Pearson Ch i-Squ are 79.848 a 9 .010 Like lihood Rat io 66.842 9 .000 Linear -by-Linear Assoc iat ion

.860 1 .354

N of Va lid Cases 50 a. 12 ce lls (75.0% ) ha ve expec ted count less than 5. The minimum expected count is .04.

At 5% level of significance Ho rejected hence there isassociation between income group and frequency of buying

Chi square test Income group and Frequency of buying

Cross Tabulation monthly

income & frequency of buying

monthly income * frequency of buy food Crosstabulation frequency of buy food

1-3 4-6 >6 t imes rare ly Count 1 0 0 5 >10,000 Expected Cou nt 3.0 2.0 .2 .7 Count 18 2 2 1 10,000 -

50,000 Expected Count 11.5 7.8 .9 2.8 Count 1 0 0 0 50,000 -

100000 Expected Count .5 .3 .0 .1 Count 3 15 2 0

month ly inco me

10000 0-500000 Expected Count 10.0 6.8 .8 2.4

Count 25 17 2 6 Tota l Expected Count 25.0 17.0 2.0 6.0

Here we can see that higher income groups purchase Frequency is the highest.

Chi-Square Tests

Value df

Asymp. Sig. (2-sided)

Pearson Chi-Square 79.848a 9 .010 Likelihood Ratio 66.842 9 .000 Linear-by-Linear Association

.860 1 .354

N of Valid Cases 50 a. 12 cells (75.0%) have expected count less than 5. The minimum expected count is .04.

Monthly income and attitude for which we buying

At 5% level of significance Ho rejected hence there is association between monthly income and attitude reflection.

monthly income * attitude Crosstabulation attitude

strong ly agree agree neutra l disagree

storng ly dissagr e

e Count 0 0 3 2 0 >10,000 Expected Count

1.9 2.4 .3 .2 .1

Count 0 22 0 0 1 10,000 -50,000 Expecte

d Count 8.9 11.3 1.4 .9 .5

Count 0 1 0 0 0 50,000 -100000 Expecte

d Count .4 .5 .1 .0 .0

Count 17 1 0 2 0

month ly inco me

10000 0-500000 Expecte

d Count 7.8 9.8 1.2 .8 .4

Count 19 24 3 2 1 Tota l Expected Count

19.0 24.0 3.0 2.0 1.0

Crosstabulation-Monthly income & Attitude

Chi-Square Tests

Va lue df



31.804 1 .000

N of Va lid Cases 49 a. 16 ce lls (80.0%) ha ve expec ted count less than 5. The minimum expected count is . 02.

Chi square -Age & nutritional value

At 5% level of significance Ho rejected hence there is Association between age group and nutrients required.

Nutritional value.

strongly agree agree neutral dissagree strongly

dissagree Count 1 1 0 1 17-21 Expected Count

11.8 2.9 2.9 8.2 4.1


3.9 1.0 1.0 2.7 1.4


2.7 .7 .7 1.9 1.0

Count 18 4 4 3 2

age

>31 Expected Count

1.6 .4 .4 1.1 .5


20.0 5.0 5.0 14.0 7.0

Cross tabulation Age & Nutritional value requirement

Hence, we can see that higher income groups stress moreOn nutritional value.

Chi-Square Tests

Va lue df



15.998 1 .000

N of Va lid Cases 49 a. 16 ce lls (80.0%) ha ve expec ted count less than 5. The minimum expected count is .02.

Chi square-Monthly income & brand value

At 5% level of significance Ho rejected ,hence there is association between Brand value requirement and income group

monthly income * brand value Crosstabulation brand value

strong ly agree agree neutra l disagree

strong ly disagree

Count 0 1 3 2 0 >10,000 Expected Count

1.8 2.0 .9 .1 .1

Count 1 18 3 1 0 10,000 -50,000 Expected

Count 8.4 9.4 4.2 .5 .5

Count 0 1 0 0 0 50,000 -100000 Expected

Count .4 .4 .2 .0 .0

Count 17 1 1 0 1

month ly inco me

10000 0-500000 Expected

Count 7.3 8.2 3.7 .4 .4


18.0 20.0 9.0 1.0 1.0

Cross tabulation- Monthly income & Brand value.

Hence,we can see higher income group strongly agree they prefer packaged foods with high brand value or name.

Chi-Square Tests

Va lue df



11.468 1 .001

N of Va lid Cases 51 a. 18 ce lls (90.0%) ha ve expec ted count less than 5. The minimum expected count is .39.

Chi square age vs their buying behaviourDependent on visual appeal

visulappeal

strongly agree agree neutral dissagree strongly

dissagree Count 18 4 4 3 1 17-21 Expected Count

11.8 2.9 2.9 8.2 4.1


3.9 1.0 1.0 2.7 1.4


2.7 .7 .7 1.9 1.0

Count 0 1 0 1 2

age

>31 Expected Count

1.6 .4 .4 1.1 .5


20.0 5.0 5.0 14.0 7.0

Crosstabulation:Age & Visual appeal

Total Variance Explained

Initial Eigenvalues Extraction Sums of Squared Loadings

Rotation Sums of Squared Loadings

Component

Tota l % of

Variance Cumulat

ive % Tota l

% of Varianc

e Cumulat

ive % Tota l

% of Varianc

e Cumulative

% 1 4.879 40.661 40.661 4.879 40.661 40.661 4.669 38.911 38.911 2 2.053 17.110 57.771 2.053 17.110 57.771 2.151 17.923 56.833 3 1.182 9.851 67.622 1.182 9.851 67.622 1.295 10.789 67.622 4 .949 7.909 75.531 5 .868 7.230 82.761 6 .826 6.880 89.642 7 .671 5.591 95.233 8 .263 2.188 97.421 9 .140 1.166 98.587 10

.104 .868 99.455

11

.035 .295 99.750

dimensi on0

12

.030 .250 100.00 0

Extract ion Method: Pr inc ipa l Co mponent Ana lys is.

Factor analysis

Rotated Component Matrixa Component

1 2 3 taste .910 var iety .855 ava ilab ility .787 clean less -.456 .461 manufac turing date .8 67 .1 82 advert isment .927 brand ambass ador .965 nutr itiona l va lue . .624 brand va lue .932 sku un it .466 pro motiona l sch emes .860 visu a l appea l .953 Extract ion Method: Pr inc ipa l Co mponent Analys is. Rotat ion Method: Varimax with Kaiser Normalizat ion. a. Rotat ion conver ged in 4 iterat ions.

Rotated Component matrix

INTERPRETATION:-

67.622% of the total variance is explained by first three factors only.

Hence decomposing all the factors into further sub headings.

•Factor 1(Brand Awareness)

Advertisment, Brand ambassdor,brand value, promotional Schemes,visual appeal.

•Factor 2(Product characterstics)

Taste,Variety, cleanliness

Factor 3(product Quality)Product availability, manufacturing date, sku unit, nutritional value

Interpretations Similarly there was found to be association between Gender and

price .Ho was rejected and hence association was there between gender and pricing,Females were more price conscious. There was no association between gender,income groups ,age

groups and variety,availability,cleanliness that is all of our respondents considered variety,cleanliness and availability as an important factor for their buying of packaged foods.

There came out to be no association between promotional schemes and age.All respondents buying was dependent on promotional schemes adopted by companies.

The scope of research is confined only in ghaziabad.

Sample size to be small.The limitation of time of the project this is

minimum.The respondent always to hurry fill up the

questionnaire that can may be biased.

Limitations

Packaged food company should make attractive packaging of the product.

Packaged food company need to choose famous brand ambassador for advertisement of the product.

Extra nutritional value should be added for consumer attraction.

Mostly target lower age group consumer who are want to changed.

Recommendation

final ppt

Documents

count income expecte

packaged food industry

snacksconfectionary

baby food

demand of packaged food

type of packaged food

t e ig

xpec c e t i e