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MARKET RESEARCH PROJECT ON “WHAT FACTORS DRIVE SALES OF BISCUIT”

BY

Aanchal Luthra (FT161003)

Ankush Ballal (FT161019)

Devankshi Prakash (FT161033)

Manu Chugh (FT161049)

Poornima Venkatesan (FT161064)

Senoj Jones (FT161079)

Surbhi Vyas (FT161093)

- GROUP 3, Section 1

“You gotta risk it to take the biscuit”

Introduction:

Biscuits are one of the fastest moving packaged food categories in the retail channel. It is registered as an easily available and affordable type of food and forms an integral part of day-to-day life not only in India, but also in many parts of the world. In the early 19th century, people perceived biscuits as easy-to-carry and long lasting food and used it only during long journey. As time passed, people started consuming biscuits to get instant energy. It also served as a glucose supplement for the ill. In the recent decades, biscuit industry has grown leaps and bounds in the national bakery scene. Today, it not only serves as a snack along with tea or coffee, but it is also categorized according to needs and preference of people. From sweet to salt, simple to exotic, simple snack to healthy food, we get biscuits in lot more varieties and brands in today’s market than we did earlier. Biscuit market is growing at a rate of 9% annually and 20.5 Lakh metric tons of biscuits were produced in the year 2011-2012. It is therefore important for a biscuit company to understand the factors that affect the sales of their product. This market research is conducted to determine the factors that influence the purchase of biscuits and analyze these factors and their effects on the sales.

Literature Review:

A research conducted by Britannica to identify consumer preference [1] like taste, awareness about brand, frequency of purchase and satisfaction found that homemakers are always in a better position to buy the house requirements. They also found that advertisement and monthly income affects the buying behavior of consumers. At the end, they were able to find out the taste which most consumers prefer.

A research ‘Taking the Biscuit’[2] examines the popularity of biscuits and cakes categories for Irish customers to satisfy their snacking requirements.

Another study was conducted in Portugal, with children, to find the effect of packaging in consumer behavior. They found that packaging can be a differentiating factor at the point of purchase. Also it is important not to overuse information available on the packaging since it could lead to a negative impact on the product

(Dilution effect)[3]. However, when it comes to nutritional information that is displayed, a research conducted by Carnage et al[4] says access to nutrition information at the point of purchase may empower customer decisions regarding food selection, and lead to higher satisfaction and product ratings. Another research by FRTP Research shows how tea biscuits are cash cows for the FMCG industry [5].

Qualitative Research Method:

We chose to conduct focus group for this research. Since this is not a sensitive topic or a B2B survey, we did not choose an interview. A focus group with 9 participants were selected, with 5 boys and 4 girls. The insights we derived from the focus group led us to the following variables and the questionnaires to measure those variables. All the responses were measured in Likert scale.

Dependent Variable:-

Sales of biscuits

I eat biscuits very frequently The amount I spend on biscuits per week is approximately (In Rupees)

Independent Variables:-

1. Brand

I prefer branded biscuits over confectionery biscuits (Confectionery biscuits include local bakery biscuits like Jira biscuits, Atta biscuits, etc) I prefer biscuits of a single brand I eat biscuits of my preferred category irrelevant of the brand

2. Price

Biscuits are good Value for money If price of a biscuit increases, I switch to others I search for discounts while shopping for biscuits

3. Taste

Biscuits are tasty

4. Advertising

Biscuit advertisements are valuable source of information In general, information provided in biscuit advertisements are accurate I easily get to know about promotional offers of biscuits through advertisements

5. Variety

I love flavours in biscuits (Chocolate, Vanilla, Milk, etc.) I like eating biscuits having some variety (Cream biscuits, choco-chip biscuits, etc.)

6. Health factor

Biscuits have good nutritional value I consider biscuits to be junk food I reflect on the nutritional value of biscuit I eat

7. Packaging

Looks of the biscuit packet do not matter Quality of packaging of biscuits is important

Covariates:

Age Gender Occupation Annual income Tendency to snack

Hypothesis:

Based on the independent variables we have come up with the following set of hypothesis

H1: Brand of a biscuit influences its sales

H2: Price has an influence in the sales of biscuits (frequency of purchase and amount)

H3: Taste of the biscuit influences its sales

H4: Advertising affects sales

H5: The more variety the biscuit has, the more it is sold.

H6: The Health factor of a biscuit influences its sales.

H7: Packaging of the biscuits(neatness and attractiveness) influences sales

Reliability

Scale: HealthCase Processing Summary

N %

Cases

Valid 257 98.8

Excludeda 3 1.2

Total 260 100.0

a. Listwise deletion based on all variables in the procedure.

Reliability Statistics

Cronbach's Alpha N of Items

.569 3

We deleted item 3 to get a higher cronbach alpha

ReliabilityCase Processing Summary

N %

Cases

Valid 257 98.8

Excludeda 3 1.2

Total 260 100.0



Cronbach's Alpha N of Items

.764 2

Scale: Variety

Case Processing Summary

N %

Cases

Valid 257 98.8

Excludeda 3 1.2

Total 260 100.0



Cronbach's Alpha

N of Items

.614 2

Item-Total Statistics

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total Correlation

Cronbach's Alpha if Item Deleted

V1 I like eating biscuits having some variety

3.81 1.360 .444 .

V2 I love flavours in biscuits

3.84 1.197 .444 .

ReliabilityScale: PriceCase Processing Summary

N %

Cases

Valid 257 98.8

Excludeda 3 1.2

Total 260 100.0



Cronbach's Alpha

N of Items

.791 3






P1 Biscuits are good Value for money

5.84 3.486 .673 .674

P2 price of a biscuit increases, I switch to others

6.28 3.532 .657 .691

P3 I search for discounts while shopping for biscuits

6.28 3.562 .573 .783

ReliabilityScale: AdvertisementCase Processing Summary

N %

Cases

Valid 246 94.6

Excludeda 14 5.4

Total 260 100.0



Cronbach's Alpha

N of Items

.837 3






Ad2 In general, information provided in biscuit advertisements are accurate

5.28 3.558 .738 .737

Ad1Biscuit advertisements are valuable source of information

5.29 3.659 .651 .822

Ad3 I easily get to know about promotional offers of biscuits through advertisements

5.20 3.537 .712 .762

Reliability

Scale: PackagingCase Processing Summary

N %

Cases

Valid 257 98.8

Excludeda 3 1.2

Total 260 100.0



Cronbach's Alpha

N of Items

.631 2






Packaging 2 Reverse - look matter

3.87 1.175 .461 .

Package 3 done Quality of packaging of biscuits is important

3.02 1.210 .461 .

ReliabilityScale: BrandCase Processing Summary

N %

Cases

Valid 257 98.8

Excludeda 3 1.2

Total 260 100.0



Cronbach's Alpha

N of Items

.614 3






BR1 I prefer branded biscuits over confectionery biscuits

5.50 3.103 .570 .281

BR2 I prefer biscuits of a single brand

5.86 2.632 .694 .044

BR3 Reverse code -I eat biscuits of my preferred category ,irrelevant of the brand

4.96 5.252 .100 .888

Summary of Cronbach Alpha

Independent VariablesCronbach

AlphaHealth 0.764Variety 0.614Price 0.791

Advertisement 0.837Packaging 0.631Brand 0.614

After Reliability Analysis, we see that for every construct, we have obtained Chronbach Alpha greater than 0.6 therefore we conclude that all our constructs are valid to go ahead with further analysis.

Correlations

Taste 1Biscuits are tasty

IV 2 Health average

IV 3 Variety average

IV 4 Price Average

IV 5 Ad average

IV 6 - package average

Brand Average IV 7

Taste

Pearson Correlation

1 .237** .413** .338** .042 .166** .311**

Sig. (2-tailed) .000 .000 .000 .498 .008 .000

N 257 257 257 257 257 257 257

Health

Pearson Correlation

.237** 1 .142* .346** .076 .069 .307**

Sig. (2-tailed) .000 .023 .000 .225 .269 .000N 257 257 257 257 257 257 257

Variety

Pearson Correlation

.413** .142* 1 .334** .111 .164** .316**

Sig. (2-tailed) .000 .023 .000 .075 .008 .000N 257 257 257 257 257 257 257

Price

Pearson Correlation

.338** .346** .334** 1 .054 .121 .958**

Sig. (2-tailed) .000 .000 .000 .386 .054 .000N 257 257 257 257 257 257 257

Ad

Pearson Correlation

.042 .076 .111 .054 1 .015 .041

Sig. (2-tailed) .498 .225 .075 .386 .809 .508N 257 257 257 257 257 257 257

Package

Pearson Correlation

.166** .069 .164** .121 .015 1 .107

Sig. (2-tailed) .008 .269 .008 .054 .809 .086N 257 257 257 257 257 257 257

Brand

Pearson Correlation

.311** .307** .316** .958** .041 .107 1

Sig. (2-tailed) .000 .000 .000 .000 .508 .086

N 257 257 257 257 257 257 257

**. Correlation is significant at the 0.01 level (2-tailed).*. Correlation is significant at the 0.05 level (2-tailed).

As seen from the correlation matrix, since correlation is observed between independent variables, we have to undergo factor analysis so as to reduce correlated variables to uncorrelated factors.

Factor AnalysisCommunalities

Initial Extraction

Taste 1.000 .506

Health 1.000 .298

Variety 1.000 .511

Brand 1.000 .907

Ad 1.000 .954

Package 1.000 .565

Price 1.000 .923

Extraction Method: Principal Component Analysis.

Total Variance Explained

Component Initial Eigenvalues Extraction Sums of Squared Loadings

Total % of Variance Cumulative % Total % of Variance Cumulative %

1 2.575 36.791 36.791 2.575 36.791 36.7912 1.080 15.428 52.219 1.080 15.428 52.2193 1.009 14.412 66.630 1.009 14.412 66.6304 .863 12.322 78.9525 .835 11.927 90.8796 .597 8.533 99.4127 .041 .588 100.000


As observed, three factors have Eigen values greater than one and hence all the independent variables are reduced to three factors .

Component Matrixa

Component

1 2 3

Taste .553 .410 -.181

Health .523 -.087 .128

Variety .573 .424 .052

Brand .880 -.364 -.029

Ad .124 .236 .940

Package .268 .648 -.270

Price .898 -.342 -.017


a. 3 components extracted.

Component Score Coefficient Matrix

Component

1 2 3

Taste .215 .379 -.179

Health .203 -.081 .127

Variety .223 .392 .051

Brand .342 -.337 -.029

Ad .048 .218 .932

Package .104 .600 -.267

Price .349 -.316 -.017

Extraction Method: Principal Component Analysis. Component Scores.

Component Score Covariance Matrix

Component 1 2 3

1 1.000 .000 .0002 .000 1.000 .0003 .000 .000 1.000

Extraction Method: Principal Component Analysis. Component Scores.

Since we have multiple factor loadings for few of the variables, we perform factor rotation for better classification of our variables against the factors.

The table below depicts the component matrix after factor rotation

Rotated Component Matrixa

Component

1 2 3

Taste .285 .652 -.021

Health .508 .136 .147

Variety .307 .611 .209

Brand .945 .111 -.043

Ad .040 .006 .976

Package -.082 .744 -.070

Price .951 .135 -.025

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 4 iterations.

Component Transformation Matrix

Component 1 2 3

1 .880 .466 .0882 -.472 .844 .2553 .045 -.267 .963

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

Component Score Coefficient Matrix

Component

1 2 3

Taste .002 .468 -.057

Health .223 -.007 .119

Variety .013 .421 .169

Brand .459 -.118 -.083

Ad -.019 -.042 .957

Package -.204 .626 -.095

Price .456 -.100 -.067

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Component Scores.

Component Score Covariance Matrix

Component 1 2 3

1 1.000 .000 .0002 .000 1.000 .0003 .000 .000 1.000

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Component Scores.

From the rotated component matrix, we observe that three constructs independent variables brand and price are loaded the 1st component. Independent variables taste, variety, packaging are loaded on 2nd component. Independent variable advertising is loaded on 3rd component. We depict the loading of variables on the component if loading of a variable is >0.4.

The factor component 1 can be named Conscientiousness

The factor component 2 can be named Appeal on senses

The factor component 3 can be named Effect of advertising

Now the regression analysis is done with these three factors as independent variables and the dependent variables as sales of biscuits

Regression Analysis:

Model Variables Entered Variables Removed Method

1Effect_Of_Advertising, Appeal_To_Senses, Conscientousnessb

. Enter

a. Dependent Variable: The amount I spend on biscuits per week is approximately

b. All requested variables entered.

Model Summaryb

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .727a .529 .523 20.653

a. Predictors: (Constant), Effect_Of_Advertising, Appeal_To_Senses, Conscientousnessb. Dependent Variable: The amount I spend on biscuits per week is approximately

ANOVAa

Model Sum of Squares df Mean Square F Sig.

1

Regression 121213.076 3 40404.359 94.723 .000b

Residual 107917.874 253 426.553

Total 229130.949 256


b. Predictors: (Constant), Effect_Of_Advertising, Appeal_To_Senses, Conscientousness

Coefficientsa

Model Unstandardized Coefficients Standardized Coefficients

T Sig.

B Std. Error Beta

1

(Constant) 140.109 1.288 108.754 .000

Conscientiousness 12.589 1.291 .421 9.753 .000

Appeal_To_Senses 15.172 1.291 .507 11.754 .000

Effect_Of_Advertising 9.210 1.291 .308 7.135 .000


Residuals Statisticsa

Minimum Maximum Mean Std. Deviation N

Predicted Value 67.77 196.57 140.11 21.760 257

Residual -150.184 33.522 .000 20.532 257

Std. Predicted Value -3.324 2.595 .000 1.000 257

Std. Residual -7.272 1.623 .000 .994 257


Regression Analysis is done and we got adjusted R square of about 0.523. 52.3% variance in sales is explained by the independent variables considered.

Conclusion:

All three factors are significant , and the Beta value for all the factors is positive which depicts factors are positively correlated with the dependent variable i.e. Sales of biscuits .

Recommendations:

To increase the sales, manufacturers can concentrate more on the appeal of senses category. Hence improving package design, variety and taste, improves the overall sales of biscuit

The next factor that contributes to the sales is Conscientiousness. Showcasing the product as a VFM, improves the overall sales.

Advertisement affects the least in the sales of biscuit.

Hence, it can be seen that improving the qualities of product improves sales rather than focusing on advertisement. Hence more budget should be allotted for product improvement to attract more sales.

Reference:

[1] A STUDY ON CONSUMERS' PREFERENCE TOWARDS VARIOUS TYPES OF BRITANNIA BISCUITS IN KANCHIPURAM TOWNS Dr. M. Arutselvi, IJRIME Volume2, Issue5 (May-2012) ISSN: 2249-1619

[2]Taking the Biscuit. Checkout Jul 2014, Vol 40 issue 7, p36-40.

[3] Encouraging children to eat more healthily: The influence of packaging, CARLA PIRES* and LUÍSA AGANTE Journal of Consumer Behaviour, J. Consumer Behav. 10: 161–168 (2011))

[4] Effect of nutritional information in perceptions of food quality, consumption behavior and purchase intentions, Crange, david A. Conklin, Martha T. Lambert, Carolyn U, Journal of food service business research. 2004, Vol7 Issue 1, p43-61. 19p

[5] How the tea biscuit category remains the cash cow for the FMCG companies like Britannia, parle and ITC., FRPT-FMCG Snapshot. 4/27/2014, p28-30. 2p.

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