Cnb Final Report

8/14/2019 Cnb Final Report

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INTRODUCTION

RESEARCH OBJECTIVE

EXPLORATORY STUDY

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INTRODUCTION

India, the worlds largest malt-based drinks market, accounts for 22% of theworlds retail volume sales. These drinks are traditionally consumed as milk

substitutes and marketed as a nutritious drink, mainly consumed by the old,

the young and the sick. HFDs are mainly targeted at children aged 5-18 years.

The kids are active and play during this age and the pressure is on the home

maker to keep the energy level of the kids high using some drinks. The HFD

category comprises of two sub-categories Brown Powder and White

Powder. While the white drink finds a bigger market in South and East, thebrown one makes its presence felt in North and West. White drinks account

for almost two-thirds of the market. Currently, brown drinks (cocoa-based)

continue to grow at the expense of white drinks like Horlicks and Complan.

The share of brown drinks has increased from about 32% to 35% over the last five years. Cadburys

Bournvita is the leader in the brown drink segment with a market share of around 18%. India has a

thriving Rs.2,000-crore health food drinks market, with many global players, like the market leader,

GlaxoSmithKline (Horlicks, Boost, Viva and Maltova), Cadbury (Bournvita), Nestle (Milo),

Heinz (Complan). Glaxo rules the Indian HFD market with a share of around 64%.

RESEARCH OBJECTIVE

This project is undertaken with an objective to understand the buyers behaviour in the Health

Food Drinks (HFD) category. Through this study, we intend to find the answers to these questions:

What are the prominent factors that drive a customer to purchase a HFD?

What are the various customer segments that buy a HFD?

What are the sources of information for these customer segments?

We also look at the current positioning strategy of two leading brands of the HFD Category in India

i.e. Cadburys Bournvita and GlaxoSmithKlines Horlicks; and would suggest the possible

recommendation strategies for marketing this product category.

EXPLORATORY STUDY

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biggest consumers of milk are in the age group of 6-16 years. The study also shows that 60 per cent

of the high income households are regular consumers of the beverage. These families on an average

consume about 30-40 gm of the product a day. Mothers are the key influencers in brand choice.Children also have a strong say in the brand selection. These beverages are usually added to warm

or cold milk. In addition to its use as a tasty and nutritious milk drink, some of the brands

(especially brown beverages) are also used as an additive in milk to make it a tasty snack drink in

institutional segments like restaurants, canteens, juice parlors.

A higher percentage of consumers prefer white beverages over brown beverages. White beverages

are used for their therapeutic benefits while brown beverages are used more for their taste.

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Since health food drinks are consumed mostly with milk, therefore

consumption behavior of milk can be extended to the consumption of

HFDs as well.

Both flavouring and packaging were found to be important factors in

consumption, especially amongst kids. A US based research has shown

that when it comes to milk, 85% of US children prefer any kind of

flavoured milk to the plain white milk. Chocolate was found to be a

leading flavour for milk in the flavoured milk category. While other

varieties such as strawberry, banana and vanilla were also available.1This consumption behaviour can be extended to Indian consumers

because of the widened impact of urbanization and globalization.

Milk intakes and habits with respect to milk consumption are found to vary with the sex of theperson according to a study published in Journal of American Dietetic Association. In a cross

sectional study amongst American adolescents it was found that milk intake was proportional to

the taste preference of the teenagers. Also attitude of personal health / nutrition was found to be an

important parameter. It was also found that consumption of milk was found to be significantly and

inversely related to fast food consumption.2Thus factors such as social income status, personal

attitude towards health and taste preferences are important influencers in milk consumption.

Considering these facts, promoting the health benefits and catering to the taste preferences of the

consumers becomes imperative for the health food drink manufacturers.

Beverages constitute a significant amount in the dietary intake of the children. Milk leads the

category of beverages consumed by children. With chocolate flavour being favoured by most of the

children, most of the health food drink manufacturers have launched the chocolate version of their

products Chocolate flavoured milk variants are the most popular variant in the flavoured milk


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category.3 This fact is also reflected in the strategy adopted by Horlicks with the launch of its ready-

to-drink version of Doodh in India.

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Factors which might influence the purchase and consumption of HFDs as identified from the

literature survey are as follows:

Colour of the health food drink

Age of the consumer

Income of the family

Key Influencers in the purchase decision

Flavour

Packaging

Attitude towards personal health

3ULPDU\5HVHDUFKFocused Group Discussion technique was used to conduct a primary exploratory study to

determine the attributes people seek as a decision criteria for choosing a health drink. For this

purpose, two groups of five parents each were formulated.

Location:

AgriCo Colony, Jamshedpur

Adityapur, Jamshedpur

A freewheeling discussion on the attribute influencing the choice of Health Food Drinks was

encouraged. Based on the discussions, the following product attributes were identified as

influencing the purchase decisions of the customers:

Nourishment: The unhealthy food habits and modern lifestyle of todays youth is somewhat

affecting their proper growth and development. So people are looking for supplements

which can give them proper nutritional value and are beneficial for a healthy lifestyle.

Moreover increasing health awareness among parents and household incomes has

aggravated this trend. People are looking for health drinks which can provide sufficient

iron, calcium, vitamins A and D and vitamin C intake in daily dietary consumption.


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colour is generally considered a utilitarian attribute which is seen as symbol of quality in

Indian markets.

Palatability: The HFDs basically target children and early youth as a potential consumer.

They are largely impulsive, fun loving and choosy towards products. So taste of a product

does play a significant role in this segment.

Economy: As HFD is a daily consumption product, people expect value for the money spent.

Moreover the middle class, a large potential buyer of health drinks is price sensitive and

hence prefers a value for money product.

Shelf-presence: Presence in the market or shelf-presence influences the purchase of the

HFD. People generally purchase the most visible product and in case of unavailability of a

brand the consumers do not delay their purchase decision. Moreover a larger shelf space

attracts innovators (youths) to buy them.

Packaging: The attractive packaging entices children, who are sometimes the key decision

makers behind a HFD purchase. The advertisement formulates the attitude of consumer. A

packaging design in sync with the advertisements will attract consumers by affecting theircognitive component. Moreover packaging can consider the after use of containers jars for

Indian markets. Historically attractive designs and packaging has boosted the sales of the

HFDs.

Brand Image: The brand is the trust between company and the consumer. A high utilitarian

value product category like HFD needs to have a trust among its customer base to sell its

value proposition. So a brand attached to high nutritional and health values will play an

immense role in the sale of HFD.

Promotions: The Indian market is price sensitive market wherein promotions increase the

sale of a product. Children also get attracted to promotional schemes like freebies of soft

toys etc. So Health drinks companies are frequently coming up with offers such as free

shakers, toys etc.

Granular/Powder: The granular and powdered form of HFDs is considered as a decisive

variable for their purchase in some cases.

Easy to Mix: The HFDs should easily mix up with the liquid. A HFD with low solubility

challenges the functionality of the core product.

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Demographics

Income

Age

Education

Family

Role of influencer in family

Family size

Reference Groups

Of child

Of mother (decision maker)

Marketing Activities

Advertising

Promotion

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Limited Decision Making


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Limited decision making involves recognizing a problem for which there are several possible

solutions. It then involves internal and limited external search, few alternatives, simple decision

rules on a few attributes and little post purchase evaluation unless there is a product problem. It

covers the middle ground between nominal and extended decision making.

In case of HFDs, there are many brands available in the market. While purchasing a HFD, we look

for few attributes based on our past experience and little external search like POS, any TV

advertisement or a word of mouth from some known person. The decision might just involve

evaluating the newness of the available alternative HFD; or might involve evaluating the actual or

anticipated behaviour of others.

DATA COLLECTION

,QVWUXPHQW8VHGA detailed questionnaire was made which measured the cognitive, affective and behavioral

components of the attitude of customers towards the purchase of HFD on a 5 point Likert scale.

Please refer Appendix 1 for the full questionnaire used for the process. A sample question is shown

below.

ProblemRecognition

Selective

Information Search

Limited Internal

Alternative Evaluation

Few Attributes

Simple Decision RulesFew Alternatives

Purchase

Postpurchase

No dissonance

Limited Evaluation


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0HWKRGRORJ\Data was collected using the following techniques:

Personal Interviews: With the mothers who are the

purchasers of HFD

Web based survey: Web link sent to our relatives and

colleagues.

Telephone based survey: Telephonic interviews were

conducted of our relatives and colleagues.

Via the above methods, we were able to collect 70 responses. The sampling method employed was

convenience based sampling. Next, we move to analyze the data collected above by using various

quantitative techniques in SPSS software.

DATA ANALYSIS

)DFWRU$QDO\VLVThis was undertaken to group the similar factors that drive a customer to purchase a HFD into

distinct heads. Factor analysis is a statistical method used to describe variability among observed

variables in terms of fewer unobserved variables called factors. The observed variables are

modeled as linear combinations of the factors, plus "error" terms. The information gained about the

interdependencies can be used later to reduce the set of variables in a dataset.

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Sample Size: Correlation coefficients fluctuate from sample to sample, much more so in

small samples than in large. Therefore, the reliability of factor analysis is also dependent on

sample size. A sample size 5 times the number of variables is considered good. In our survey

there were 13 variables and we had a sample size of 70 parents.

Data Screening: The first thing to do when conducting a factor analysis is to look at the

inter-correlation between variables. If the test questions measure the same underlying

dimension (or dimensions) then we would expect them to correlate with each other

(because they are measuring the same thing). If there are variables that do not correlate


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KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .860

Bartlett's Test of Sphericity Approx. Chi-Square 1.254E3

Df 276

Sig. .000

The KMO statistic varies between 0 and 1. A value of 0 indicates that the sum of partial correlationsis large relative to the sum of correlations, indicating diffusion in the pattern of correlations. A value

close to 1 indicates that the patterns of correlations are relatively compact and so factor analysis

should yield distinct and reliable factors. A value greater than .5 is recommended. Furthermore,

values between .5 and .7 are mediocre; values between .7 and .8 are good and above .9 are

considered superb. Since the test value is .860 which is very close to 1, we are confident that Factor

analysis will give good results.

Bartletts measure tests the null hypothesis that the original correlation matrix is an identity

matrix. For factor analysis to work there should be some relation between variables because if the

matrix were an identity matrix all correlation coefficients would be zero. If the test is significant, it

can be inferred that there are some relationships between the variables. For this, Bartletts test is

highly significant (p


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11 .291 2.235 98.291

12 .222 1.709 100.000

13 -

3.898E

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Extraction Method: Principal

Component Analysis.

The above output lists the Eigen values associated with each linear factor before extraction, afterextraction and after rotation. Before extraction there were 13 linear components, the Eigen values

associated with each factor represent the variables explained by that particular linear component.

The first few factors explain relatively large variance whereas subsequent factors explain small

amount of variance. All the factors with Eigen values greater than 1 are extracted and we are left

with 4 factors. The Eigen values associated with them is again displayed in the columns labeled

Extraction Sums of Squared loading. The values are same as the values before extraction just that

the values for the discarded factors are ignored. In the final part of the table, the Eigen values of thefactors after rotation are displayed. Rotation has the effect of optimizing the factor structure and

one consequence for these data is that the relative importance of the four factors is equalized.

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The above table shows the table of communality before and after extraction. Principal component

analysis works on the assumption that all variance is common; therefore before extraction the

communalities are all one. After extraction some of the factors are discarded and so some

information is lost. The amount of variance in each variable that can be explained by the retained

factors is represented by the communalities after extraction.

The component matrix contains the loadings of each variable onto each factor. The loadings lessthan .4 have been suppressed in the matrix and so there are blank spaces for many of the loadings.

This table is not relevant from the point of view of interpretation.

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The rotated component matrix is a matrix of the factor loadings for each variable onto each factor.

This matrix contains the same information as the component matrix above except that it is

calculated after rotation. There are several things to consider about the format of this matrix. First,

factor loadings less than 0.4 have not been displayed because we asked for these loadings to be

suppressed.


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From the Factor analysis we could come with four main factors, as can be seen from the table

above. We have named these factors on the basis of commonalities among the sub factors. In the

factor 1 we can see that all other sub factors are closer to product likeability except the attractive

packaging which is coming as an outlier in this group. All the four factors as identified are shown in

the table below:


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&OXVWHU$QDO\VLVCluster Analysis is a technique used to assign a set of observations into subset as per similarity in

their behaviour. In the given consumer behaviour research each of the respondents had given

certain set of preference parameters while making their purchase decision. We use the cluster

analysis technique to group the customers into subsets who use similar type of factors into

consideration before buying the health food drink.

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The 13 factors rated by the consumers had been clubbed as 4 dominant factors using factor analysis

as presented earlier. The factor scores of each respondent were then used to do cluster analysis on

available data.

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We started with the hierarchical cluster analysis on the given data and used the Between-Groups

Linkage method to obtain the dendogram of sub-groups amongst the given set of respondents. The

measure used was Squared Euclidean Distance for interval. The 13 factors of the products were

Color of HFD

Chocolate flavor

Flavored milk preference

GranularityLikeability

SKU

Free Offer

Bottled packaging

Promotionsand packaging

Preferred Brand

Attitude towards healthy lifestyle

Top of the mind recall

Brandperception

PriceVisibility in shopPurchaseFeasibility


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After this we obtained the dendogram diagram for the given set of data which is reproduced from

the SPSS output below:

Dendograms start with individual cases and group the

most similar ones as one group. This process is continued

till an optimum centroid distance is obtained and clear

clusters emerge.

The image on the left is a screen shot of the dendogram

that we obtained as an output of the hierarchical cluster

analysis. The detailed dendogram is provided in the

Appendix 2 for reference.

In this dendogram it is evident that at the 4th level of

differentiation, there are 4 dominant clusters which could

b l d f h i d W hi


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.0HDQV&OXVWHU$QDO\VLVThe hierarchical cluster analysis was followed by the K- means cluster analysis to get quick cluster

results. Care was taken to group each case by membership for further data mining. To start with we

entered Number of clusters as 6 to obtain the set of clusters. The same is being represented below:

However with no of clusters as 6 we obtained clusters where there was just 1 case in a cluster.

Hence we iterated the process with number of clusters equal to 5. This also did not yield the correct

results. Finally with number of clusters given as 4 we obtained a fair segmentation of the available

data. The same is shown below in the table which is the output from SPSS file:

Number of Cases in each Cluster

Cluster 1 26.000


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The final cluster centers table that was obtained is as below. This table was further used for theinterpretation of clusters and identifying their membership traits.

Final Cluster Centers

Cluster

1 2 3 4

Health_attitude 4.19 3.67 4.42 4.58

Colour_of_HFD 3.77 3.28 3.17 2.00

Chocolate_flavour 3.88 3.00 4.33 2.92

Preference_for_flavoured_mi

lk4.19 3.11 4.33 2.92

Price 2.46 3.44 2.50 1.50

Visibility_in_shop 3.35 2.89 2.33 1.58Bottled 4.08 2.67 2.67 3.75

SKU_Size 4.27 3.61 1.83 2.42

Attractive_packaging 3.54 3.11 4.33 1.67

Preferred_brand 4.04 3.89 4.00 3.75

Free_offer 4.27 3.61 1.83 2.42

Top_of_mind_recall 3.58 3.11 2.58 3.25

Granularity 4.08 2.94 3.25 1.58

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The above table is obtained on a scale of 5. We multiplied all the scores by 2, to take the scores on a

scale of 10, in order to get a better understanding of the scores, and a better comparison across the

various clusters and various attributes.


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*in the above table, the RED coloured scores denote the important attributes which influence the

purchase behaviour of the customer in each cluster.

The above table is then subjected for interpretation, to find out the most pertinent attributes in

each of the clusters. These attributes will define the clusters purchase behaviour for the HFDs.

In the interpretation, we consider the factor-loading scores of each attribute, and compare that

score with the corresponding scores in the other clusters, and also with the scores of the other

attributes in the same cluster. This comparison is required to understand the weight of the

attribute in the overall purchase decision of the HFDs by a particular cluster.

Considering some example based on the above table:

The scores for the Health Attitudeare high across all 4 clusters, and also the difference of

the scores is not much.

This gives us the interpretation that Health Attitude is considered to be an

important attribute in the purchase decision of a consumer for a HFD

In the Preference for flavoured milk, the scores of Cluster 1 and 3 are very near to each

other, and are much higher than the scores of cluster 2 and 4. Also the scores are very high

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This shows that Top of mind recall is not considered to be an important attribute in

the purchase decision of HFDs by any of the clusters.

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Continuing on the same lines, and comparing the scores of the attributes across all the clusters and

all the attributes, we can see that the following attributes are important in the purchase decision of

the HFDs by each cluster:

Cluster 1

Health attitude

Colour of HFD

Chocolate flavour

Preference for f lavoured milk

Bottled

SKU Size

Preferred brand

Free offer

Granularity

Cluster 2

Health attitude

Price

SKU Size

Preferred brand

Free offer

Cluster 3

Health attitude

Chocolate flavour


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Preferred brand

Based on the above found attributes, we can name the 4 clusters as:

Cluster1 Value Seeker

These customer look out for complete value from a brand of HFD which they purchase, and

consider almost all of the attributes which we identified in our studies, for their purchase

decision

Cluster2 Price Conscious

These customers considers price to be a very important attribute in their purchasebehaviour, and want to have the best buy for the HFD, and also give preference for any free

offer available with any brand of HFD

Cluster3 PalatabilitySeeker

This cluster of customers considers the taste of the HFD and the packaging of the HFD to be

an important factor in their purchase decision.

Cluster4 Nutrition Seeker

These customers only buy HFD because of the nutrition which the HFDs provide in the

growth of their child. They have their preferred brand of HFD and are aware of what all

nutrition is being provided by the HFDs.

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The sources of information influencing the purchase decision are:

TV Advertisement

Children

Referral group

Internet

Print Advertisement

The respondents were asked to rank the factors in order of importance. A t-test was conducted on

the results of the survey in order to compare the means of the ranks for the factors. This was done

on all the 4 clusters identified above in the cluster analysis.


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Reference

groups26 2.5385 1.02882 .20177

TV

Advertisement26 2.0000 1.20000 .23534

Internet 26 3.9231 1.35420 .26558

Print

Advertisement26 3.5385 1.24035 .24325

Child 26 2.9231 1.38342 .27131

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One-Sample Statistics

N Mean Std. Deviation Std. Error Mean

Reference

groups18 3.0556 1.34917 .31800

TV

Advertisement18 2.4444 1.50381 .35445

Internet 18 3.4444 1.61690 .38111

Print

Advertisement18 3.3333 1.23669 .29149

Child 18 2.7778 1.30859 .30844

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TV

Advertisement12 1.9167 1.16450 .33616

Internet 12 3.7500 1.42223 .41056

Print

Advertisement12 3.9167 1.08362 .31282

Child 12 2.8333 1.40346 .40514

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N Mean Std. Deviation Std. Error Mean

Reference

groups 12 2.6667 1.72328 .49747

TV

Advertisement12 1.8333 .83485 .24100

Internet 12 3.0833 1.56428 .45157

Print

Advertisement12 3.2500 .86603 .25000

Child 12 4.1667 .93744 .27061

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We can say from the results that there is a significant difference between the ranks of the factors

with a 95% confidence.

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The two most important factors that emerge out of the tests are:


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This finding is an important implication for product placement as the marketer can target the

relevant source information for communicating with the customers in the respective clusters.

POSITIONING STRATEGIES

&XUUHQW3RVLWLRQLQJ%RXUQYLWDCadburys Bournvita is the market leader in the Brown HFD market with a share

of 18%. It has changed its positioning many a times from the time it was launched

way back in 1948. Its journey in terms of positioning is shown below:

Appendix 3 shows the print advertisements of Bournvita in current scenario.

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1948 Combination ofHealth & Taste

1970s

Helps in good upbringing

Tagline: Goodness that grows with you

1980s

Move from Upbringing to Intelligence

Tagline: Brought up right, Bournvita Bright

1990s

Focus onMind and Body

Tan ki Shakthi, Man ki Shakthi

1998

Focus on Health & Taste

RDA Formula: 2 cups of Bournvita, No Bournvita, Nomilk

Post2000

Focus onConfidence

Do you have the Bournvita Confidence?

2009

Science, Nature and Bournvita

Bournvita ++


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has now focused on children and started its famous Apang Opang Japangcampaign which has

become quite a hit amongst the children. It further strengthened its position in the minds of the

consumer by coming up with campaigns like N

ow proven-T

aller,S

tronger,S

harper.

Appendix 4 shows the print advertisements of Horlicks in current scenario.

3HUFHSWXDO0DSA perceptual map is a visual representation of how target consumers view the competing

alternatives in a Euclidean space which represents the market.

In order to develop the perceptual map, the questionnaire survey captured the brand of health fooddrink being usually used by the consumers. Question asked in the questionnaire: Which health

food drinkdo you usually use in the family? Thus against every respondent who had given his

choices for the various purchase factors we have his mostly used brand. This data along with the

ratings of the underlying purchase factors were fed as input to SPSS and Factor Analysis through

Principal Component Extraction was carried out. Based on the factor scores for the identified

factors viz, Likeability, Packaging & Promotions, Purchase Feasibility and Brand Perception,

perception for the brands was formulated by assigning relative weights based on the average

scores.

The average factor scores are calculated for the respondents of same brand. The same is

represented below in the tables:

Used Brand Likeability Packaging &

Promotion

Purchase

Feasibility

Brand Perception

Boost 0.442181 0.777112 0.056683 -0.36352

Bournvita 0.636334 -0.10239 0.149687 0.149345

Complan -0.4891 -0.771 -0.24864 -0.12282

Horlicks -0.75397 0.232525 -0.11274 -0.05191

The ideal self that should be represented for the market was calculated by taking an overall average

of the factor scores as given by all the respondents. This data was further filtered to keep average

factor scores for ideal market self and the two leading brands Bournvita and Horlicks. The same is

tabulated below:


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Horlicks -0.75397 0.232525 -0.11274 -0.05191

The average scores were then plotted on the graph to arrive at the perceptual map:

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The market ideal was calculated from the average response of all respondents. The perception mapfor the market ideal comes across as symmetric on all four factors with slight positive skewness for

packaging and promotion.

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Bournvita clearly comes across as the winner on all fronts as per the market ideal parameters. It is

evident that the consumers using Bournvita consider likeability, brand perception and purchase

feasibility as the drivers behind their purchase.

Bournvita lacks the market ideal on the packaging and the promotion front but scores very high on

the likeability factors such as chocolate flavour, granularity, and preference for flavoured milk.

Similarly for consumers who indicated brand image as the main purchase driver found Bournvita to

be high on factors such as nutritional value providing overall better health quality and higher brand

-0.8-0.6-0.4-0.20

0.20.40.60.8Likeability

Packaging &Promotion

PurchaseFeasibility

Brand Perception

Total (Ideal)

Bournvita

Horlicks


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market ideal on the packaging and promotion fronts i.e. launching attractive schemes, convenient

SKUs and colourful jars. However Horlicks needs to improve its perceived image on the palatability

front.

5HFRPPHQGHG)RFXV$UHDV

%RXUQYLWD

Focus on Product packaging and Promotion

Launch smaller sized SKUs

Provide freebies, gifts etc. with your product

+RUOLFNV

Possible changes in the colour of the product

Launch new flavours so as to increase customer likeability

CONCLUSION

It is highly imperative that marketers understand the purchase behaviour of the consumers so as to

focus on the prominent factors that consumers keep in mind while purchasing their product. The

project has clearly identified the answers of the questions it intended to find. To summarize the

same:

What are the prominent factors that drive a customer to purchase a HFD?

Likeability

Packaging & Promotion

Purchase feasibility

Brand perception

What are the various customer segments that buy a HFD?

Value Seeker

Price Conscious

Palatability seeker


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Children

APPENDIX 1


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Reference Group ____________________

TV Ads ____________________

Internet ____________________

Print Ad ____________________

Child ____________________

e) Which health food drink do you use in your family? ________________________

Please Tick on the option that best reflects your choice:

1. My general attitude towards health affects my buying behaviour of HFD

Strongly Agree

Agree

Neutral

Disagree

Strongly disagree2. I tend to buy Brown HFD over White HFD

Strongly Agree

Agree

Neutral

Disagree

Strongly disagree

3. My child prefers drinking chocolate flavoured HFD over non-chocolate flavoured HFD

Strongly Agree

Agree

Neutral

Disagree

Strongly disagree

4. My child prefers flavoured milk over plain milk

Strongly Agree

Agree

Neutral

Disagree

Strongly disagree

5. I consider price as a consideration while buying a HFD


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6. I prefer buying my brand of HFD even if it is not so visibly present in the shelf of the shop

Strongly Agree

Agree

Neutral

Disagree

Strongly disagree

7. I prefer buying a bottled HFD over a non-bottled pack HFD

Strongly Agree

Agree

Neutral

Disagree

Strongly disagree

8. I buy smaller packs of HFD over the larger packs HFD

Strongly Agree

Agree

Neutral

Disagree

Strongly disagree9. My child influences me to buy an attractive looking HFD (colour, shape)

Strongly Agree

Agree

Neutral

Disagree

Strongly disagree

10.I always buy my preferred brand of HFDStrongly Agree

Agree

Neutral

Disagree

Strongly disagree

11.I usually buy a HFD which come with freebies

Strongly Agree

Agree

Neutral

Disagree

Strongly disagree

12 I buy a HFD whose advertisement I remember at the time of purchase


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Strongly Agree

Agree

Neutral

Disagree

Strongly disagree


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Dendrogram using Average Linkage (Between Groups)

Rescaled Distance Cluster Combine

C A S E 0 5 10 15 20 25Label Num +---------+---------+---------+---------+---------+

55 65 43 32 39 46 42

37 56 66 54 22 36 41 45 50 60 34

33 44 47 38 48 21 13 15 9 12

40 31 3 14 10 24 7 1 27 29 8

11 4 26 16 17 18 51


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53 63 19 52

62 58 68 57 67 49 59

20


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678'


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Cnb Final Report

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Transcript of Cnb Final Report