Effect of Brand Equity Umbrella Branding

EFFECT OF BRAND EQUITY UMBRELLA BRANDING

A project by:Adil Mirza

ACKNOWLEDGEMENT

I express my sincere thanks to Mr. Vishal Mishra for providing me ample amount of

support and opportunity for the successful completion of research on:

“ Effect of Brand Equity in Umbrella Branding”.

I am thankful to my respondents for their responses, colleagues for their support

and suggestions, which have proved to be very valuable for this research , without which

it would have not been possible to successfully complete the research.

LETTER OF TRANSMITTAL

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The project has been a great learning experience for young future managers like us, as we

got to be in direct touch with the customer and practically got to apply the marketing

concepts learned in the classrooms. We came to know about their taste and preferences.

The market research, preparing the report and analysis of the data taught us how a

business research happens and also the practicality of the subject: Business research.

Apart from all this, we had an overall development in the form of team spirit, team skills,

initiating skills and communication skills. The adaptation of using modern software for

analysis was totally a new experience.

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TABLE OF CONTENTS:

Content page number

1. Background 51.1. What is brand equity 51.2. Major factors that lead to brand choice 61.3. Process of brand equity 71.4. Selected major factors that affect brand equity 81.5. Umbrella branding 8

2. Executive summary 93. Research design

3.1 Type of research designs 10 3.2 Scaling techniques 11 3.3 Questionnaire development and pre-testing 11 3.4 Sampling techniques 16 3.5 Field work 16 4. Data Analysis 4.1 Procedure 16 4.2 Plan 19 5. Factor analysis using SPSS 5.1 KMO and Bartlett’s Test 23 5.2 Communalities 24 5.3 Total Variance explained 25 5.4 Scree Plot 26 5.5 Rotated Component Matrix 26 5.6 Component Score Coefficient Matrix 27 5.7 Component Transformation Matrix 28 6. Limitations 29 7. Conclusion 30 8. References 31

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BACKGROUND (LITERATURE REVIEW)

What is Brand equity?

Brand equity is one of the most valuable assets that a firm can have, and brand equity measurement and management continue to be important areas of research in both academics and industry. Most of the research on brand equity has looked at the issue from the perspective of either the consumer or the firm. Brand equity research from a consumer’s perspective usually involves collecting data on consumer mindset measures of brand equity from the consumer through surveys or experiments, and using the data to assess the consumer’s perceptions, feelings, and attitudes towards the brand. It may also involve collecting data on the consumer’s revealed preference behavior, using self-reported or actual purchase data, and using it to assess the incremental value that the brand name has on the consumer’s utility and her resulting choice behavior. On the other hand, brand equity research from a firm’s perspective generally involves the use of observed market data to assess the brand’s financial value to the firm. The market in question could be a geographic or physical product market, where performance measures such as market share or profit can be used, or it could be a financial market, where performance measures such as the firm’s stock price or other financial variables may be used to assess the brand’s value. But in this paper we are concentrating on the consumer aspect.

Factors contributing to the choosing of the brand

The usual core measures relate to:

Awareness Familiarity Favorability Usage Loyalty Individual brand/category attributes

These measures can be researched cheaply and effectively using only four sets of questions:

1. Brand/category usage 2. Brand stature 3. Brand intimacy 4. Brand attributes

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MAJOR FACTORS THAT LEAD TO A BRAND CHOICE

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PROCESS OF BRAND EQUITY

THE PYRAMID OF BRAND EQUITY

SELCETED MAJOR FACTORS THAT AFFECT BRAND EQUITY :

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Among all the major factors affecting brand equity the ones selected were based on the On the basis of priority given to these factors in the major marketing books like the PHILIP KOTLER etc. They majorly effect a consumer’s choice when a new product is launched by a renowned company through umbrella branding. The majors factors selected are:

1. Association with the parent brand: The consumers association with parent brand motivates the consumer to buy new products of that company if the company is a consistent performer. If it has been providing quality over the period of time the consumer will feel proud in associating itself with the brand. This will create brand equity through the word of mouth. For example UB group was successful in launching Kingfisher airlines because the consumers of its alcohol feel proud in drinking it.

2. Familiarity of the parent brand – means the proper use of communication strategy by the company to make the maximum public familiar with its brand and products. If the people are familiar with the brand they tend to use its new version all the more.

3. Awareness of the parent brand – shows how well the brand has climbed the BRAND LADDER. Brand awareness is the first step.

4. Longitivity of the parent brand - How long the brand has been in the market serving the people affects the consumers’ choice of new brands launched by the company.

5. Reliability of the parent brand- affects the consumers on the basis of how comfortable, secured, trustable the consumer feels using the brand.

UMBRELLA BRANDING: When a company extends the brand name to a new product line or revamps the product and again launches a product or diversifies the product portfolio it is known as umbrella branding.

EXECUTIVE SUMMARY

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The topic of our project is “Effect of Brand Equity in Umbrella Branding”. We basically wanted to see whether the brand equity of the parent brand helps a new product within the same umbrella in any way. We decided to collect primary data through survey by using questionnaires. Our first task after deciding this was to prepare a questionnaire .To do this ,we first analyzed the various parameters that contributes to the brand equity of a product .We went through a lot of options and finally narrowed down to five major parameters-

Association Familiarity Awareness Reliability Longitivity.

Then we started preparing the questions .To attain our objective ,we decided to mention some quite well-known instances of umbrella branding where a new product has been introduced under the umbrella of a famous mother brand .We asked in our questionnaire what the respondent thinks will be the reason of success of a new product introduced under the mother brand . The instances cited by us include :

introduction of clothing line by the famous sports gear manufacturers Nike and Reebok

launch of Kingfisher Airlines by the liquor producer Kingfisher introduction of soups under the umbrella of Maggie Noodles

and eleven other such instances.

This questionnaire was given to and filled up by 50 respondents which included students from IBS ,Hyderabad as well as people we met in front of Hyderabad Central and City Centre.

Then came the job of compiling and tabulating the data .The data was manually fed by us into the Excel sheets and the total data points were calculated .We used the cross tabulation method while compiling the data in the Excel sheet.

In the analysis part ,we took the help of SPSS .We did Factor Analysis and found out the Communalities ,Total Variance ,Scree Plot ,Rotated Component Matrix and Component Score Efficient Matrix .

Next came the preparation of the report where we explained in detail all our findings and the conclusion that we reached through this research.

RESEARCH DESIGN:

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Business research is an important tool for decision making for 100’s of organizations across the world as it help them take crucial decisions to gain an upper hand over competitors. Basically research is a systematic enquiry aimed at providing information that will solve managerial problems. A good design means that good research results can be obtained with minimum utilization of time, money and effort. Thus research design has to be developed very carefully as it forms the foundation for the entire research process that follows. An ideal research design should consider the following factors:

Identifying the exact research problems to be studied. The objective of the research The process of obtaining information Availability of adequate and skilled manpower Availability of adequate financial resources for carrying out research.

Business research can be defined as systematic enquiry that gives information to guide businesses in decision making.

RESEARCH DESIGN:

A. TYPES OF RESEARCH DESIGN:

It is very important to select an appropriate research design before starting the research. There are several research design approaches which can be classified as:

1. EXPLORATORY STUDIES:They are carried out to make problems suited to more precise investigation or to frame a working hypothesis from an operational perspective. They help in understanding and assessing critical issues of problems. They can not be used in cases where a definite result is desired. It included techniques like secondary data analysis, experience surveys, focus groups and two stage design.

2. DESCRIPTIVE STUDIES:Unlike exploratory studies, these come under formal research where the objectives are clearly established. In these, a researcher gathers details about all aspects of a problem situation. They form the basis for analytical, experimental and quasi-experimental studies which help in developing hypothesis.

3. CAUSAL STUDIES:The basic aim of causal studies is to identify the cause and effect relationship between variables. The basic premise of the causal relationship is that when we do

A particular thing (cause),it gives rise to another thing(effect).There are three types of relationship that can arise-

(a) symmetrical

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(b) asymmetrical (c) reciprocal

B. DATA COLLECTION A. Primary Sources

At times, secondary data might prove to be inadequate or of no use to the researcher for making further marketing decisions. In such cases, the researcher has to go in for primary data research employing survey research methods. Surveys are normally carried out to obtain primary data. Primary data is the data which is gathered first hand to answer the research question being investigated. In our project the survey was conducted using questionnaire and meeting the respondents in person to get them filled.

B. Secondary SourcesA secondary data study is concerned with the analysis of already existing data that is related to the research topic in question. In secondary studies, secondary data is studied in order to analyze the future of a product. It helps in projecting future trends using some mathematical models. Secondary data is based on source, category, medium and database. In our report we have used secondary data classified by medium that includes reference to hard copy and internet. We also have taken reference from the concept paper given by ZYMAN INSTITUTE OF BRAND SCIENCE and BEST GLOBAL BRANDS 2006-a ranking by brand value (inter-brand BUSINESS WEEK).Secondary data is used by managers as it is cheaper and takes less time to gather, thus saving them a lot of money and time that they would have otherwise spend in gathering primary data. It may provide alternative data methods that can be used for primary research. Also it generates requisite information for better creativity.

C. SCALING TECHNIQUES

Rating

We have asked the respondents to rate various parameters according to their preference on the scale of ten with 10 representing the ‘most preferred’ and 1 the ‘least preferred’. The respondents had a choice of giving the same rating to more than one parameter.

D. QUESTIONNAIRE DEVELOPMENT AND PRE-TESTING

A properly designed questionnaire can tap the necessary information from the respondents. In framing a questionnaire the researcher must ensure that the questions are designed to draw information that will fulfill research objective. Also the researcher must make sure of the target population for the same. A questionnaire contains all the close ended questions. These questions give respondents a finite set of specified responses to choose from.

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Our questionnaire contains structured questions i.e. which have a specified number of responses. All the questions were multiple choice questions. Choices were kept same for all the questions and the respondents have to rate the options that best describes their feelings. The questions wording were kept simple and easy to understand. The questions cover a wide range of industry.

The Role of Brand Equity in Umbrella Branding:

Questionnaire:

Kindly tick the most appropriate answers for the questions provided and also rank the various options from a scale of 1 to 10 where 1 stands for the least appropriate option and 10 stands for the most appropriate

Q1.UB Groups liquor has traveled to a lot of places, it is now ready to carry people to places. Why would you travel in Kingfisher Airlines?

Familiarity Awareness Reliability Longitivity of parent brand. Association with parent brand in terms of Price positioning, brand loyalty, product’s

usage, Brand popularity and marketing gimmicks.

Q2.After the break up of the Reliance Empire, the Ambani brothers are ready to expand individual bases: Mukesh Ambani’s venture into retail sector. Why would you visit his stores?



Q3. Titan’s Fast track has been protecting people from unpunctuality, now it’s ready to protect them from Ultra Violet Rays by manufacturing eyewear accessories. Why would you buy its goggles?



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Q4. Enough of licking Maggi ketchup, now they serve your taste buds also with ready to make soups. Why would you drink them?



Q5. Larsen & Toubro has constructed and developed India’s infrastructural base for a long time, now it also strengthening it by its cement. Why would you use it?



Q6.They says you never gift a man/woman their shoes. Levis Strauss & co. has given the world the unforgettable gift of denims, now it is ready to give the gift of shoes. Why would you wear/buy them?



Q7.Dressing men for years now have become monotonous for Allen solly, so now they dress women as well. Why will it be a success?



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Q8.Amul serves our taste buds through its milk products like chocolates, butter, ice cream etc. Why do you buy products under its Umbrella Branded products?



Q9.From airlines to News channel Sahara India gives ‘Sahara’ to a lot people of India. Reasons according to you for its popularity?



Q10.After holding 56% share in the white goods segment, LG is now ready to accelerate its levers by entering the FMCG segment. Why would you buy its product?



Q11.After giving you hardware systems that got your company ticking IBM now gives an entire company system through enterprise services. Reasons for popularity/



Q12.Pepsi India is now in agricultural products, chips – Lays. Reasons for popularity?

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Q13. “World leader in shoes” – Nike/ Adidas/Reebok are now in the retail sector. Will they again be world leader? Yes NoReasons:



Q14. ITC brand ’Wills’ is famous for its cigarettes, is it as famous for its clothing wills lifestyle too? Yes No Reasons:



Pre-testingPre-testing refers to testing the questionnaire on a small sample of respondents selected on a convenient basis that is not to divergent from the actual respondent. It includes testing all aspects of questionnaire starting from the question content to question sequence. Pre- testing enables the researcher to revise the questionnaire by identifying the flaws and eliminating any ambiguous questions. We have done pre-testing on 12 respondents and on getting positive response from their side we extended the sample size to 50.

E. SAMPLING TECHNIQUE

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Sampling is done to select a target audience for the purpose of determining the characteristic of the whole population. There are two basic approaches to sampling probability and non-probability. In the research we have used non-probability sampling which involves the selection of units based on factors other than random chance. Convenience sampling, quota sampling, judgment sampling and snowball sampling are few examples of non-probability sampling. In our research we have used quota sampling in which the entire population is segmented into mutually exclusive groups and categories. Quota sampling finds extensive use in commercial research where the main objective is to ensure that the sample represents in relative proportion, the people in the various categories in the population, such as gender, social class etc.

F. FIELD WORKWe have conducted research in vicinity of the Hyderabad city. We have distributed questionnaire in the places like HYDERABAD CENTRAL and CITY CENTRE to get the response from the respondents.

DATA ANALYSIS:

PROCEDUREWe have followed the general procedure of data analysis which included the following stages:

VALIDATION

EDITING

CODING

DATA ENTRY

DATA CLEANING

TABULATION AND ANALYSIS

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VALIDATIONValidation is the preliminary step in data preparation. It refers to the process of ascertaining whether the interviews conducted complied with specified norms. The essence of the process lies in detecting any fraud or failure by the interviewer to follow specified instructions. Validation helps to confirm if the interview was really conducted. In our research, the respondents included students of IBS and people whom we met at Hyderabad Central as well as City Center. They were asked to give their names, age and gender. In this way, we tried to validate our research.

EDITINGEditing is the process of checking for mistakes by the interviewer or respondent in filling the questionnaire. Editing is a manual process and is usually done twice before the data is submitted for data entry.

In our case, we checked for any mistakes as soon as the respondents filled the questionnaires so that in case of any problems, we could clarify and correct them. This is especially true for the respondents whom we interviewed outside the IBS campus because it would be difficult for us to contact them in case of problems.

CODINGThe process of assigning numbers or other symbols to answers in order to group the responses into limited categories is known as coding. This type of categorization and coding sacrifices some detail but is necessary for efficient data analysis. There are certain rules which are followed by a researcher while categorizing replies obtained from a questionnaire. These are:

1. Appropriate – Categorization should help validate the hypotheses of the research study. Categorization provides for better screening of data for Testing and establishing links among key variables. In our study, we tried to

analyze the relationship of the various variables (like familiarity, availability) with brand equity. To do this, we took the help of various brands from diverse industries.

2. Exhaustive – When multiple-choice questions are used, an adequate list of alternatives should be provided to tap the full range of information from the respondents. The absence of any response from the set of response options given will prove detrimental as that specific response will be under-represented in the analysis.

In case of our project, we went through numerous parameters that might affect brand equity n finally settled down to five. These were the options in our questions.

3. Mutually exclusive – Complying with this rule requires that a specific alternative is placed in one and only one cell of a category set.

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4. Single dimension – This means every class in the category set is defined in terms of one concept. In our case, the parameters that we have considered are in

terms of individual concepts.

There are open-ended and close-ended questions. We had all close-ended questions. It is somewhat easier to assign codes for responses that are generated by close-ended questions because the number of answer is fixed in that case. Coding makes it easier for data to be accessed directly from the questionnaire.

DATA ENTRYData entry helps convert information gathered by secondary or primary methods to a medium that facilitates viewing and manipulation. There are various means available for data entry like Optical scanning, Barcode reader and Voice recognition. In case of our project, due to unavailability of such advanced technology, we entered the data manually.

DATA CLEANINGData cleaning includes consistency checks and treatment of missing responses. Compared to the preliminary consistency checks during editing, checking at this stage is more thorough and expensive, as it uses computers. This is done in two ways – error checking routines and marginal reports.

TABULATION OF SURVEY RESULTSOnce data is cleansed off all errors and is stored in a database, it should be tabulated to facilitate further analysis. A researcher can tabulate in two ways:

One way is Frequency Tabulation – It is the most commonly used tabulation technique which shows the number of respondents who gave each possible answer to each possible question.

Cross Tabulation – In this, the idea is to look at responses to one question in relation to responses to other questions. Here, the data is organized into groups, categories, or classes to facilitate comparisons.

In our case, we used the cross tabulation method as it helps during the later stage of analysis. In fact, it is a simple yet powerful tool for analysis of gathered data.

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PLAN FOR ANALYSIS OF DATA:

THE BIG HURDLE: The information incited by our questionnaire through the factors that affect brand equity in umbrella branding is difficult to quantify. But it was only the close ended rating method that made our research possible by making these factors able to be analyzed by analytical and statistical tools. So our plan of action had to incorporate this factor mostly.

THE STEPS:A true research is the one which is unbiased and gives relevant information about its objective using the best statistical and analytical tools.

1. The data collected through the questionnaires (using face to face survey method of research) provide information about ratings of each parameter from 1-10 that effect brand equity in umbrella branding.

2. Our sample respondents covered a number of 50. We conducted the survey in places where we could expect to find educated people who are aware of all the brands covered in our questionnaire.

3. Our plan’s next step was to feed the raw data collected in the excel sheet. Here the best part to learn was: that in spite of having advanced tools to analyze data human still has to laboriously enter data to use these tools.

4. Then we planned to use Statistical Package for Social Sciences to analyze the data feeded in the excel sheet. Then we run the factor analysis on SPSS software.

5. After running factor analysis using the SPSS program we obtained the results , that were incorporated with the graphs made using the excel sheet to further analyze and represent information obtained by us.

The data collected from the questionnaire is clubbed in the form of graphs as under:

The under-mentioned table gives the cumulative rating for each variable.

FAMILIARI AWARENE RELIABILI LONGITIVI ASSOSIATI

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TY SS TY TY ON4511 4579 4711 4503 4464

4511

4579

4711

4503

4464

Series1

From the above we can infer that reliability followed by awareness and familiarities have the highest cumulative ranking. Hence we can say that Reliability gets the maximum score, out of all the variables as per the empirical data collected from the questionnaire

factor weightage in brand equity

430044004500460047004800

FAMILIARITY

AWARENESS

RELIABILITYLONGITIVITY

ASSOSIATION

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FAMILIARITY

0

2

4

6

8

10

12

1 34 67 100 133 166 199 232 265 298 331 364 397 430 463 496 529 562 595 628 661 694

data points

max

imu

m v

alu

e

AWARENESS

0

2

4

6

8

10

12

1 33 65 97 129 161 193 225 257 289 321 353 385 417 449 481 513 545 577 609 641 673

data points

max

imum

val

ue

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LONGITIVITY

0

2

4

6

8

10

12

1 43 85 127 169 211 253 295 337 379 421 463 505 547 589 631 673

data points

maxim

um

valu

e

RELIABILITY

0

2

4

6

8

10

12

1 33 65 97 129 161 193 225 257 289 321 353 385 417 449 481 513 545 577 609 641 673

data points

max

imu

m v

alu

e

ASSOSIATION

0

2

4

6

8

10

12

1 37 73 109 145 181 217 253 289 325 361 397 433 469 505 541 577 613 649 685

data points

max

imu

m v

alu

e

ASSOSIATION

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The above graphs shows the various data points for each question from 50 respondents.Therefore we have 700 datapoints for each factor (50*14).

Factor Analysis Using Statistical Package For The Social Sciences (SPSS):

KMO and Bartllets Test:

The output below shows the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett’s test of sphericity , the KMO statistics varies between 0 and 1 , a value of 0 indicates that the sum of partial correlations is large relative to the sum of correlations in dictating diffusion in the pattern of correlation, hence factor analysis is likely to be in-appropriate, a value closed to 1 indicates that the pattern of correlations are relatively compact and so factor analysis should yield distinct and reliable factor.

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.

.653

Bartlett's Test of Sphericity

Approx. Chi-Square558.865

Df 10

Sig. .000

As per our analysis the KMO measure of sampling gives a value of .653 i.e. > 0, hence we can conclude that the adequacy of the sample is satisfactory.

Bartlett’s Measure Test:This tests the null hypothesis that the original correlation matrix is an identity matrix, it tells us that there are some relationships between the variables we hope to include in the analysis. One wants this test to be significant (i.e. significance value > .05), in our analysis since the significance level has come out to be .000 , hence we can conclude that the test is highly significant, and hence the factor analysis is appoporiate.

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Communalities:

Initial ExtractionFAMILIARITY 1.000 .726

AWARENESS 1.000 .689

RELIABILITY 1.000 .551

LONGITIVITY 1.000 .720

ASSOSIATION 1.000 .616

Extraction Method: Principal Component Analysis.

Communality

00.10.20.30.40.50.60.70.8

Variables

Co

mm

un

ali

ty

Series1

The above graph depicts the table values in the form of a graph.

The table consists of communalities before and after extraction, the principal component analysis works on the initial assumption that all variance is common therefore before extraction all communalities are1 whereas the communalities labeled in the column labeled extraction reflects the common variance in the data structure.From our analysis 72.6% of the variance associated with the variable named ‘Familiarity’, 68.9% of the variance associated with the variable named ‘Awareness’ and 72% of the variance associated with variable ‘Longitivity’ has been taken into consideration for analysis.

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Total Variance Explained:

Component

Initial EigenvaluesExtraction Sums of Squared Loadings

Rotation Sums of Squared Loadings

Total% of Variance

Cumulative % Total

% of Variance

Cumulative % Total

% of Variance

Cumulative %

1 2.095 41.906 41.906 2.095 41.906 41.906 1.652 33.039 33.039

2 1.207 24.143 66.050 1.207 24.143 66.050 1.651 33.010 66.050

3 .670 13.408 79.457

4 .516 10.329 89.786

5 .511 10.214 100.000

Total Variance Explained


The first column (Initial Eigen value), lists the Eigen values associated with each linear factor before extraction.Before extraction, SPSS had identified 5 (five) components within the data set, the Eigen values associated with each factor represents the variance explained by that particular component and SPSS also displays the Eigen value in terms of percentage of variance explained.From the table it is evident that the variable 1 i.e. familiarity explains 41.9% of the total variance and the next factor i.e. component 2 (longitivity) shows 24.14% of the total variance and henceforth.

The next column (extraction sum of squared loadings) lists the same values as in the previous column i.e. component 1, except the values for the discarded factors are ignored.

The final column i.e. (rotation sum of squared loadings), the eigen value of the factors 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 two factors is equalized.Before rotation Familiarity accounted for 41.9% however after rotation it accounts for only 33.03% of variance .

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Scree Plot:

The screen plot shows the number of factors that should be retained.

54321

Component Number

2.0

1.5

1.0

0.5

Eig

en

va

lue

Scree Plot

The scree plot generated by the SPSS shows that a point of inflexion occurs at the component number 3 , therefore we retain only two components i.e. there are two factors that can explain the whole behaviour.

Rotated Component matrix:

This matrix shows the loading of the variables on the two extracted factors.

Rotated Component Matrix(a)

Component

1 2FAMILIARITY

.850 -.063

AWARENESS.811 .178

RELIABILITY.516 .533

LONGITIVITY.026 .848

ASSOSIATION.071 .782

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

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Rotated component Matrix

-0.5

0

0.5

1

1.5

2

2.5

1 2

Component

V ar

ia bl

e

AssociationLongitivityReliabilityAwarenessFamiliarity

Rotation converged in 3 iterations.

The loading tells the extent to which the factor contributes to the variables. From our analysis of the table generated by SPSS, we can infer that familiarity, awareness and reliability have a high loading of 0.85 and 0.81 respectively, on factor number 1, and this shows that the factor 1 is a combination of these two variables. A suitable phrase to explain that is: POPULARITY (say F1)

Longitivity , reliability and association have a high loading of 0.848, 0.782 and 0.533 respectively on factor number 2 .this shows that factor 2 is a combination of the above mention three variables. A suitable phrase to explain this is: CONSISTENT PERFORMANCE (say F2)

Component Score Coefficient Matrix:

Component

1 2FAMILIARITY .566 -.190

AWARENESS .498 -.026

RELIABILITY .243 .258

LONGITIVITY -.132 .549

ASSOSIATION -.091 .498


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Rotation Method: Varimax with Kaiser Normalization.

This table gives the factor weight matrix and is used to compute the factor scores The two factors (Popularity and Consistent Performance) calculated above, can be put into empirical form by the help of component score coefficient matrix, the values under the column marked as 1 depict the factor scores for factor 1 i.e. Popularity (F1) and column marked as 2 depict the factor scores for factor 2 i.e. Consistent Performance (F2).

Based on the matrix we can formulate two equation, one for Popularity and the other Consistent Performance as under :

F1 (Popularity) = 0.566 X11 (Familiarity) + 0.498 X21 (Awareness)

F2(Coust. Pref.) = 0.258 X12 (Reliability) + 0.549 X22 (Longitivity) + 0.498 X32 (Association)

Component Transformation Matrix:

This output shows the correlation of the factors before and after the rotation.

Component Transformation Matrix

Component 1 21 .708 .707

2-.707 .708

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

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THE LIMITATIONS:

TWO BIG HURDLES: 1. The information incited by our questionnaire through the factors that affect brand

equity in umbrella branding are difficult to quantify. But it was only the close ended rating method that made our research possible by making these factors able to be analyzed by analytical and statistical tools. So our plan of action had to incorporate this factor mostly.

2. The respondents used by us had to be aware of different brands of different sectors covered by us. So we needed educated people to provide us with information that could help us obtain proper results and make our research a success to analyze factors that affect brand equity in umbrella branding.

OTHER HURDLES:

1. Situated 40 kilometers away from the city was a hurdle to get the quality of respondents we wanted. But we overcame this by traveling in and out and covering places like City Centre, Hyderabad Central etc.

2. Other limitation was that our 14 questions covered different industries which disabled us to compare contribution of each factor towards brand equity in umbrella branding

industry wise.

3. We have covered only five parameters affecting brand equity in our study but there can be more. The five factors covered are the major ones as they were chosen on the basis of priority to given to these factors in various marketing books like The Philip Kotler , ICMR marketing.

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CONCLUSION:

Primary data was collected through questionnaires by asking respondents to rate the alternatives between 1 to 10 to find the effect of brand equity on umbrella branding. The variables taken into consideration are awareness, reliability, familiarity, longitivity and association. As per the ratings received by the respondents on a scale from 1 to 10, the same was run into SPSS to draw a conclusion using factor analysis.Through factor analysis the 5 variables taken into consideration were reduced to two components. From the loadings we could infer the extent to which the factors contributed to the variables. We could infer that component 1 is a combination of familiarity and awareness which can be summarized as popularity. Longitivity, reliability and association forms part of component 2 which can be summarized as consistent performance and the relationship between them can be given by the following two equations.

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REFERENCES:

Research design, Icfai Center for Management and Research, chapter 3, p 26-29

Data Collection, Icfai Center for Management and Research, chapter 7 & 8, p 81-115

Questionnaire development and pre-testing, Malhotra N, chapter 10, p 278-306

Sampling techniques, Malhotra N, chapter 11, p 312-335

Data analysis, Malhotra N, chapter 14, p 400-420

Factor analysis, Malhotra N, chapter 20, p 584-604

Secondary data, internet, ZYMAN INSTITUTE OF BRAND SCIENCE, www.zibs.com, Dec.06, 2006.

BEST GLOBAL BRANDS 2006-a ranking by brand value (inter-brand BUSINESS WEEK), internet, www.interbrand.com, Dec 06,2006.

Brand equity, internet, www.marketingline.com, Dec.06,2006

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http://www.marketingline.com/

http://www.zibs.com/

THANK YOU, HOPE YOU ENJOYED THETREAT

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Effect of Brand Equity Umbrella Branding