Guidelines For Good Brand Management

Published Date: 02 Nov 2017

1. INTRODUCTION

1.1 Purpose Of The Study

The purpose of the study was to study how should online shopping sites and social networking sites should create brand identity for themselves online. This study also includes the kinds of branding elements they are using to maintain a competitive edge. This study also included why companies operating online have not been able to continue having a competitive edge. This study also examines the preference a consumer has while making his or her own account on social networking sites and online shopping sites

1.2 What is a Brand?

The Oxford American Dictionary contains the following definition: Brand (noun): a trade mark, goods of a particular make: a mark of identification made with a hot iron, the iron used for this: a piece of burning or charred wood, (verb): to mark with a hot iron, or to label with a trade mark. Similarly, The Pocket Oxford Dictionary of Current English says: Brand. 1. n. Piece of burning or smouldering wood, torch, (literary); sword (poet.); iron stamp used red-hot to leave an indelible mark, mark left by it, stigma, trade-mark, particular kind of goods (all of the best bb.). 2. v.t. Stamp (mark, object, skin), with b., impress indelibly (is branded on my memory)

1.3 Guidelines for good brand management

Some of the guidelines given below are eternal truths that apply equally to product, services and corporate brands, and some apply particularly to one category of brand or another.

Protect your brand.

Trademark law offers provision for the protection of your brand and corporate names, your logo and colors, the shape of your packaging, smells, and the advertising jingle you use.

Honor your stakeholders.

Your customers expect attractive, well-differentiated products and services that will live up to their expectations and are well priced.

Treat your brand as an investment, not a cost.

Brands are among the most important assets that a business can own, and strong brands can ensure business continuity in times of difficulty.

Exploit the financial potential of your brand.

As well as seeking ways to extend the brand through new product development, companies should look at opportunities to exploit the equity in their brands through co-branding, licensing and franchising.

1.4. Necessities for a new Brand

Short & Simple

Easy to Spell & Read

Easy to Recognize & Remember

Easy to Pronounce

1.5. Brand identity

The outward expression of a brand – including its name, trademark, communications, and visual appearance – is brand identity. Because the identity is assembled by the brand owner, it reflects how the owner wants the consumer to perceive the brand – and by extension the branded company, organization, product or service.

identity_ENG_popravki.gif

(Figure no. 1 - Brand Identity Model by Kapferer)

(Source-http://www.inboundmarketingagents.com/Portals/160334/images/Brand%20Identity.gif)

As per Kapferer, Brand identity can be defined by six parameters:

1.Personality

2.Physique

3.Culture

4.Relationship

5.Self Image

6.Reflection

1.6. Online Shopping

When you buy a product or a service over the internet, instead of going to a traditional brick-and-mortar store, it is called online shopping. Globally, an increasing number of people are buying over the Internet because it is more convenient. This year, holiday shopping for Christmas and New Year is estimated to be over $20 billion.

1.7 Online Shopping Sites Chosen for the project

Flipkart is an Indian e-commerce company headquartered in Bangalore, Karnataka. It was founded by Sachin Bansal and Binny Bansal in 2007. In its initial years, Flipkart focused on online sales of books. but it later expanded to electronic goods and a variety of other products.

Snapdeal.com is an Online marketplace and deals website, headquartered in New Delhi, India. Snapdeal features products across categories like Mobiles, Electronics, Fashion accessories, Apparel, Footwear, Kids, Home and Kitchen, Sports, Books; and services like Restaurants, Spas & Entertainment amongst others.

eBay Inc. (rendered as ebay) is an American multinational internet consumer-to-consumer corporation that manages eBay.com, an online auction and shopping website in which people and businesses buy and sell a broad variety of goods and services worldwide.

Deals and You is a group buying portal that features a daily deal on the best stuff to do, see, eat, and buy in some of India's leading cities. Headquartered in Gurgaon, they are a part of the Group Buying Global AG which runs leading collaborative buying websites across four continents. Fashion&You, their sister concern, is now the leading fashion, luxury & style site in India as well as among the top 10 online multi-brand retailers in the country.

Tradus.com is India's fastest growing marketplace, where buyers and sellers come together to conduct transactions. With over a thousand pre-qualified merchants and an industry-leading buyer protection policy, Tradus offers a worry-free shopping experience where you can buy a wide variety of products across 50 different categories ranging from the latest gadgets to exquisite hand-crafted jewelry - all in one shopping cart.

1.8. Social Media

Social media refers to the means of interactions among people in which they create, share, exchange and comment contents among themselves in virtual communities and networks. According to Jan H. Kietzmann, social media employ mobile and web-based technologies to create highly interactive platforms via which individuals and communities share, cocreate, discuss, and modify user-generated content.

1.8.1. History of Social Network Sites

According to the definition above, the first recognizable social network site launched in 1997. SixDegrees.com allowed users to create profiles, list their Friends and, beginning in 1998, surf the Friends lists. Each of these features existed in some form before SixDegrees, of course. Profiles existed on most major dating sites and many community sites.

1.10. Social Networking Sites chosen

Facebook is a social networking service launched in February 2004, owned and operated by Facebook, Inc. As of September 2012, Facebook has over one billion active users, more than half of them using Facebook on a mobile device.

Twitter is an online social networking service and microblogging service that enables its users to send and read text-based messages of up to 140 characters, known as "tweets".It was created in March 2006 by Jack Dorsey and launched that July. The service rapidly gained worldwide popularity, with over 500 million active users as of 2012, generating over 340 million tweets daily and handling over 1.6 billion search queries per day.

Orkut is a social networking website that is owned and operated by Google Inc.The service is designed to help users meet new and old friends and maintain existing relationships. The website is named after its creator, Google employee Orkut Büyükkökten. Although Orkut is less popular in the United States than competitors Facebook and MySpace, it is one of the most visited websites in India and Brazil

LinkedIn (NYSE: LNKD) is a social networking website for people in professional occupations. Founded in December 2002 and launched on May 5, 2003,it is mainly used for professional networking. As of June 2012, LinkedIn reports more than 175 million registered users in more than 200 countries and territories.

Google+ (pronounced and sometimes written as Google Plus, sometimes abbreviated as G+) is a multilingual social networking and identity service owned and operated by Google Inc. It was launched on June 28, 2011. As of December 2012, it has a total of 500 million registered users of whom 235 million are active on a monthly basis.

1.11. Rationale of proposed investigation

This study revolves around Brand identity. Brand identity can be defined as "Brand identity is different than brand image, which is what consumers actually think. It is constructed by the business itself. A negative gap between brand identity and brand image means a company is out of touch with market sentiment, which will make selling its products more difficult. The brand image held by consumers can reach a point at which a business or product has to rebrand itself or risk not bringing in sales." This study is being done for online shopping sites and social networking sites. In this study, the comparative parameters will be preference, security, appealing factors, price, waiting time, etc. This study will help to gain better understanding of consumer’s preference/choices/attitudes towards these sites. This study is important as what all strategies should these sites use to deliver an effective identity of themselves so as to gain competitive advantage.

1.12. Theoretical Framework

The Project was regarding Brand identity of the online shopping sites and social networking sites. In this, data was collected through the means of online questionnaires. First, various research were analyzed and studied. After this, questionnaire was formed on the basis of effectiveness of the branding elements used by the sites, their preference, the parameters seen by them while choosing an online shipping sites and social networking sites, and the reasons why online shopping sites and social networking sites have not been able to sustain their proper brand identity.

CHAPTER:2

2. REVIEW OF THE LITERATURE

Carmen María, Amo Alarcón, Carlota Lorenzo-Romero and Ángel Miguel, Borja Gómez(2012) studied the purpose of this article is to carry out a conceptual study of social networking sites (SNS), to analyze the users’ use and behaviour in SNS. This study develops a technology acceptance model (TAM) in order to analyze the factors influencing the level of acceptance and use of SNS, applying a structural equation modelling (SEM) techniques. For that, an online survey focused to panel of SNS users has been carried out. The findings indicated that there is significant positive effect of perceived ease of use of SNS on perceived usefulness and attitude.

Jothi P. Sri, Neelamalar M., Prasad R. (2011) stated that Internet is the emerging information technology with the credibility of immediacy and fastness, thus, it brings globalization in every aspects of communication. Communication through internet is more specified, with effective interactive strategy among its users.

They not only create impact over the audience but also make them interact with the marketing statistics created. People get attached to brand communication in social networking sites than usual banner and pop up ads.

Jong-Kuk Shin, Min-Sook Park And Yong Ju(2011) said With the rapid growth of online social network, it was widely used by different purposes. This study aims to find out whether the connecting with social network sites by online retailer can influence their consumers’ shopping behavioural or not. And find out the characteristics of the social networking integration service as convenience, personalization, and social surveillance, They think it can be the motivation for online shoppers to use the service.

Since they use the internet as a commercial instrument, most offline retailers have set up online retail stores directly or by third-parties to increase revenues.

Peslak Alan, Ceccucci Theyndy, Sendall Patricia (2011) said that One of the most important means of communication for young people today is social networking. Facebook has become the most visited Site. This study is an attempt to understand SN by exploring social networking (SN) behavioural using the Ajzen and Fishbein model of human behavioural known as Theory of Reasoned Action (TRA). Specifically, findings reveal that both attitude toward social networking and "subjective norm" are positively associated with intention to use SN.

The TRA model provides a strong fit with the overall data and can be used to predict and understand the usage of social networking in the target population. Definitions of the TRA model’s factors are as follows: Attitude is how

Hsiu-Lan Wu, Jau-Theyn Wang(2011) studied how Social network sites (SNS) have simplified and amplified social interaction between online users. The unique hedonic-oriented features provide experiential motives for SNS users. In the study, SNS is growing popularity, a number of questions remain to be addressed concerning the usage of SNS: What are experiential motives for SNS users? What is the relationship between flow experiences and behaviouralal intentions within the SNS context.

The present study proposes their flow experiences of SNS users such as perceived enjoyment, concentration, escape and social interaction to represent the multidimensional aspect of flow instead of a single dimension. To investigate the research model, this study applied structural equation model(SEM) analysis with 342 valid replies.

Thumsamisorn Apiwan and Nattharika Rittippant(2011) studied how Social networks have changed the way people access and interact with internet-based information. In commerce activities and economic development, social networks play a crucial role to increase the popularity of products and services by augmenting transaction business and communities via social networking sites. One of the most popularity social networking sites is Facebook.

Facebook usage as social media for business has the magnificent impact toward company in order to encourage users to adopt and continue to use the particular system. Hence, there has been a little or no research on Facebook upon D&M IS success model.

Ebermann, Jana, Wozniak, Thomas, Stanoevska-Slabeva(2011) studied that the paper analyzes influential factors of recommendation behavioural in social network sites (SNSs). Extant research on both SNSs and electronic word of mouth (eWOM) has given insufficient attention to SNSs as a potential eWOM channel. Considering the specificities of SNSs, this paper distinguishes implicit and explicit recommendation behavioural.

A recommendation, that is word-of-mouth (WOM) communication among existing or potential customers of a company, is considered as one of the most powerful and influential marketing communication. The value of WOM information lies in its influence on decision making and attitude formation WOM communications taking place in an online environment can be referred to as eWOM . Research on eWOM is increasing.

Ebermann, Jana, Wozniak, Thomas, Stanoevska-Slabeva(2011) studied that the paper analyzes influential factors of recommendation behavioural in social network sites (SNSs). Extant research on both SNSs and electronic word of mouth (eWOM) has given insufficient attention to SNSs as a potential eWOM channel. Considering the specificities of SNSs, this paper distinguishes implicit and explicit recommendation behavioural.

A recommendation, that is word-of-mouth (WOM) communication among existing or potential customers of a company, is considered as one of the most powerful and influential marketing communication. The value of WOM information lies in its influence on decision making and attitude formation WOM communications taking place in an online environment can be referred to as eWOM . Research on eWOM is increasing.

Lee Pugh Jessica(2010) studied that Social networking sites (SNWs) have opened the doors of communication, allowing people from around the world to engage in identity creations and relationship development. This study extends prior theory developed on the topics of identity creation through personal pages on CMEs.

Recent statistics provided by Facebook revealed that 50 percent of their active user’s log-in everyday, and 35 million use the status feature to update their profiles daily. The fundamental differences between CMEs and SNWs create a new platform for identity construction online. Facebook and personal Sites differ in three key areas, interactivity, standardization, and usability..

International Telecommunications Union (2010) said that historically, it used to be enough to have an online presence on the Internet for the one-way broadcasting and dissemination of information. Today, social networks such as Facebook and Twitter are driving new forms of social interaction, dialogue, exchange and collaboration. Social networking sites (referred to more broadly as social media) enable users to swap ideas, to post updates and comments, or to participate in activities and events, while sharing their wider interests.

Vesey Ken (2010) studied that Two of the key drivers to building brand strength are creating a distinct brand identity and developing a unique brand personality. Unfortunately, semantics often gets in the way of understanding how these two factors can influence brand. Brand identity, for example, is often used in a limited, graphic-centric manner or used interchangeably with brand image.

Ishak Megat(2010) studied that the first useful Internet service for the masses was email. Today, this vast network has grown into a truly worldwide that is accessible to ordinary users, turning the Internet into a mainstream phenomenon. Access to the Internet can be found at home, cybercafes, offices, Internet kiosks, cafes and anywhere else where there is a meeting of people for social or business purpose. What assists Internet usage growth even more is the expansion of devices such as desktop computers, notebooks and Smartphone’s, thus not only has it grown in popularity but it has grown into a necessity in their everyday lives. The social networking revolution was born.

McAfee (2010) stated that If you’re like most people who use the Internet, you will probably purchase something online within the next month or two. And why not? You have so many choices, with a world of products at their fingertips, and you don’t have to waste gas or deal with parking hassles, mall crowds, and long lines. Perhaps the best thing about shopping online is that you can do it barefoot in the comfort of Their home.

Purchase with Care. Unfortunately, there are some drawbacks to shopping online.

Owyang Jeremiah (2009) stated social experience is disjointed because consumers have separate identities in each social network they visit. A simple set of technologies that enable a portable identity will soon enable consumers to bring their identities with them — transforming marketing, ecommerce, CRM, and advertising. IDs are just the beginning of this transformation, in which the they will evolve step by step from separate social sites into a shared social experience. Privacy will continue to scare users as they connect with brands.

Fabrício Benevenuto, Tiago Rodrigues, Meeyoung Cha, Virgílio Almeida(2009) studied how users behave when they connect to social networking sites creates opportunities for better interface design, richer studies of social interactions, and improved design of content distribution systems. In this paper, They present a kind analysis of user workloads in on-line social networks.

Coleman Darren Andrew (2009) studied how a valid, reliable and parsimonious service brand identity scale was developed and applied to assess the construct’s influence on brand performance. The aim of this chapter is to lay the foundations and provide the context for subsequent chapters. It is structured as follows.

CHAPTER:3

3. RESEARCH METHODS AND PROCEDURES

3.1 Research Methodology

Research methodology is a way to systematically solve the research problem. It may be understood as a science of studying how research is done scientifically. In it we study the various steps that are generally adopted by a researcher in studying his research problem along with the logic behind them. It is necessary for the researcher to know not only the research methods/techniques but also the methodology. Researchers not only need to know how to develop certain indices or tests, how to calculate the mean, the mode, the median or the standard deviation or chi-square, how to apply particular research techniques, but they also need to know which of these methods or techniques, are relevant and which are not, and what would they mean and indicate and why. Researchers also need to understand the assumptions underlying various techniques and they need to know the criteria by which they can decide that certain techniques and procedures will be applicable to certain problems and others will not. All this means that it is necessary for the researcher to design his methodology for his problem as the same may differ from problem to problem. For example, an architect, who designs a building, has to consciously evaluate the basis of his decisions, i.e., he has to evaluate why and on what basis he selects particular size, number and location of doors, windows and ventilators, uses particular materials and not others and the like. Similarly, in research the scientist has to expose the research decisions to evaluation before they are implemented. He has to specify very clearly and precisely what decisions he selects and why he selects them so that they can be evaluated by others also. From what has been stated above, we can say that research methodology has many dimensions and research methods do constitute a part of the research methodology. The scope of research methodology is wider than that of research methods. Thus, when we talk of research methodology we not only talk of the research methods but also consider the logic behind the methods we use in the context of our research study and explain why we are using a particular method or technique and why we are not using others so that research results are capable of being evaluated either by the researcher himself or by others. Why a research study has been undertaken, how the research problem has been defined, in what way and why the hypothesis has been formulated, what data have been collected and what particular method has been adopted, why particular technique of analysing data has been used and a host of similar other questions are usually answered when we talk of research methodology concerning a research problem or study.

3.2 Research Design

The research design for this paper is Descriptive Research.

A research design encompasses the methodology and procedure employed to conduct scientific research. The design of a study defines the study type (descriptive, correlation, semi-experimental, experimental, review, meta-analytic) and sub-type (e.g.: descriptive-longitudinal case study), research question and hypotheses, independent and dependent variables, experimental design if applicable, data collection methods and a statistical analysis plan.

Descriptive research:

Descriptive research, also known as statistical research, describes data and characteristics about the population or phenomenon being studied. However, it does not answer questions about e.g.: how/when/why the characteristics occurred, which is done under analytic research.

Although the data description is factual, accurate and systematic, the research cannot describe what caused a situation. Thus, Descriptive research cannot be used to create a causal relationship, where one variable affects another. In other words, descriptive research can be said to have a low requirement for internal validity.

The description is used for frequencies, averages and other statistical calculations. Often the best approach, prior to writing descriptive research, is to conduct a survey investigation. Qualitative research often has the aim of description and researchers may follow-up with examinations of why the observations exist and what the implications of the findings are.

3.3.Factor analysis

Factor Analysis has been Used while analyzing the data.

Factor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors. In other words, it is possible, for example, that variations in three or four observed variables mainly reflect the variations in fewer unobserved variables. Factor analysis searches for such joint variations in response to unobserved latent variables. The observed variables are modelled as linear combinations of the potential factors, plus "error" terms. The information gained about the interdependencies between observed variables can be used later to reduce the set of variables in a dataset. Computationally this technique is equivalent to low rank approximation of the matrix of observed variables. Factor analysis originated in psychometrics, and is used in behavioral sciences, social sciences, marketing, product management, operations research, and other applied sciences that deal with large quantities of data.

Factor analysis is related to principal component analysis (PCA), but the two are not identical. Latent variable models, including factor analysis, use regression modelling techniques to test hypotheses producing error terms, while PCA is a descriptive statistical technique. There has been significant controversy in the field over the equivalence or otherwise of the two techniques (see exploratory factor analysis versus principal components analysis).

3.4. Research Objectives

1. To study the strategies being used by both networking sites and online shopping sites to create a brand identity.

2. To study the reasons for failure online shopping and networking sites have been unsuccessful in creating brand identity.

3. To study the parameters these sites are judged upon by the consumers, which describes their preference.

4. To study the branding elements being used by online shopping sites and networking sites.

5. To study how companies are evolving their capabilities, self image to gain competitive edge over the other competitors to ensure increase in customer traffic.

3.5. Data Collection

Data collection is any process of preparing and collecting data, for example, as part of a process improvement or similar project. The purpose of data collection is to obtain information to keep on record, to make decisions about important issues, or to pass information on to others. Data are primarily collected to provide information regarding a specific topic

Data Collection has been done using Survey’s.

3.5.1. Survey

With the application of probability sampling in the 1930s, surveys became a standard tool for empirical research in social sciences, marketing and official statistics. The methods involved in survey data collection are any of a number of ways in which data can be collected for a statistical survey. These are methods that are used to collect information from a sample of individuals in a systematic way. For my research, I have used Online Surveys.

Online surveys:

Online (Internet) surveys are becoming an essential research tool for a variety of research fields, including marketing, social and official statistics research. According to ESOMAR online survey research accounted for 20% of global data-collection expenditure in 2006. They offer capabilities beyond those available for any other type of self-administered questionnaire. Online consumer panels are also used extensively for carrying out surveys but the quality is considered inferior because the panelists are regular contributors and tend to be fatigued.

Advantages of online surveys:

1. Web surveys are faster, simpler and cheaper. However, lower costs are not so straightforward in practice, as they are strongly interconnected to errors. Because response rate comparisons to other survey modes are usually not favourable for online surveys, efforts to achieve a higher response rate (e.g. with traditional solicitation methods) may substantially increase costs.

2. The entire data collection period is significantly shortened, as all data can be collected and processed in little more than a month.

3. Interaction between the respondent and the questionnaire is more dynamic compared to e-mail or paper surveys. Online surveys are also less intrusive, and they suffer less from social desirability effects.

4. Complex skip patterns can be implemented in ways that are mostly invisible to the respondent.

5. Pop-up instructions can be provided for individual questions to provide help with questions exactly where assistance is required.

Key methodological issues of online surveys:

Sampling

The difference between probability samples (where the inclusion probabilities for all units of the target population is known in advance) and non-probability samples (which often require less time and effort but generally do not support statistical inference) is crucial.

Invitations to online surveys.

Due to the lack of sampling frames many online survey invitations are published in the form of an URL link on web sites or in other media, which leads to sample selection bias that is out of research control and to non-probability samples.

Non-response

Online survey response rates are generally low and also vary extremely – from less than 1% in enterprise surveys with e-mail invitations to almost 100% in specific membership surveys.

3.6. Sample size

In this study, the sample is 250 people.

Sample size determination is the act of choosing the number of observations or replicates to include in a statistical sample. The sample size is an important feature of any empirical study in which the goal is to make inferences about a population from a sample. In practice, the sample size used in a study is determined based on the expense of data collection, and the need to have sufficient statistical power. In complicated studies there may be several different sample sizes involved in the study: for example, in a survey sampling involving stratified sampling there would be different sample sizes for each population. In a census, data are collected on the entire population, hence the sample size is equal to the population size. In experimental design, where a study may be divided into different treatment groups, there may be different sample sizes for each group.

3.7. Sampling techniques

In this study, random sampling technique will be followed

In statistics and survey methodology, sampling is concerned with the selection of a subset of individuals from within a statistical population to estimate characteristics of the whole population. Two advantages of sampling are that the cost is lower and data collection is faster.

Random Sampling Technique

A grid is drawn over a map of the study area Random number tables are used to obtain coordinates/grid references for the points Sampling takes place as feasibly close to these points as possible. It includes-

3.7.1A Random line sampling

Pairs of coordinates or grid references are obtained using random number tables, and marked on a map of the study area. These are joined to form lines to be sampled

3.7.1B. Random area sampling

Random number tables generate coordinates or grid references which are used to mark the bottom left (south west) corner of quadrats or grid squares to be sampled

3.8. SPSS

SPSS has been used for analyzing the results of the data.

SPSS Statistics is a software package used for statistical analysis. It is now officially named "IBM SPSS Statistics". Companion products in the same family are used for survey authoring and deployment (IBM SPSS Data Collection), data mining (IBM SPSS Modeler),text analytics, and collaboration and deployment (batch and automated scoring services).

PSS (originally, Statistical Package for the Social Sciences, later modified to read Statistical Product and Service Solutions) was released in its first version in 1968 after being developed by Norman H. Nie, Dale H. Bent and C. Hadlai Hull. SPSS is among the most widely used programs for statistical analysis in social science. It is used by market researchers, health researchers, survey companies, government, education researchers, marketing organizations and others. The original SPSS manual (Nie, Bent & Hull, 1970) has been described as one of "sociology's most influential books". In addition to statistical analysis, data management (case selection, file reshaping, creating derived data) and data documentation (a metadata dictionary is stored in the datafile) are features of the base software. SPSS was released in its second version in 1972 and its company name is INDUS Nomi.

Statistics included in the base software:

Descriptive statistics: Cross tabulation, Frequencies, Descriptives, Explore, Descriptive Ratio Statistics.

Bivariate statistics: Means, t-test, ANOVA, Correlation (bivariate, partial, distances), Nonparametric tests Prediction for numerical outcomes: Linear regression Prediction for identifying groups: Factor analysis, cluster analysis (two-step, K-means, hierarchical), Discriminate

The many features of SPSS are accessible via pull-down menus or can be programmed with a proprietary 4GL command syntax language. Command syntax programming has the benefits of reproducibility, simplifying repetitive tasks, and handling complex data manipulations and analyses. Additionally, some complex applications can only be programmed in syntax and are not accessible through the menu structure. The pull-down menu interface also generates command syntax; this can be displayed in the output, although the default settings have to be changed to make the syntax visible to the user. They can also be pasted into a syntax file using the "paste" button present in each menu. Programs can be run interactively or unattended, using the supplied Production Job Facility.

3.9. Likert Scale

Surveys are consistently used to measure quality. For example, surveys might be used to gauge customer perception of product quality or quality performance in service delivery. Likert scales are a common ratings format for surveys. Respondents rank quality from high to low or best to worst using five or seven levels. Statisticians have generally grouped data collected from these surveys into a hierarchy of four levels of measurement:

Nominal data: The weakest level of measurement representing categories without numerical representation.

Ordinal data: Data in which an ordering or ranking of responses is possible but no measure of distance is possible.

Interval data: Generally integer data in which ordering and distance measurement are possible.

Ratio data: Data in which meaningful ordering, distance, decimals and fractions between variables are possible.

Likert scales were developed in 1932 as the familiar five-point bipolar response that most people are familiar with today.3 These scales range from a group of categories—least to most—asking people to indicate how much they agree or disagree, approve or disapprove, or believe to be true or false. There’s really no wrong way to build a Likert scale. The most important consideration is to include at least five response categories. Some examples of category groups appear in Table 1.

http://www.asq.org/img/qp/075685_table1.gif

(Figure no. 3- Likert Scale Response Categories)

(Source-http://asq.org/img/qp/075685_table1.gif)

3.10. Hypothesis

Ho : There is not a significant preference towards Facebook social networking site by the people

H1: There is a significant preference towards Facebook social networking site by the people Facebook is preferred by people.

Ho : Twitter is not preferred by people

H1: There is a significant preference towards Twitter social networking site by the people Facebook is preferred by people.

Ho : There is not a significant preference towards Linked.in social networking site by the people

H1: There is a significant preference towards Facebook social networking site by the people Facebook is preferred by people

Ho : There is not a significant preference towards Flipkart social networking site by the people

H1: There is a significant preference towards Flipkart social networking site by the people Facebook is preferred by people

Ho : There is not a significant preference towards Ebay.in social networking site by the people

H1: There is a significant preference towards Ebay.in social networking site by the people Facebook is preferred by people

Ho : There is not a significant preference towards Tradus.com social networking site by the people

H1: There is a significant preference towards tradus.com social networking site by the people Facebook is preferred by people

CHAPTER: 4

4. DATA ANALYSIS

4.1 What is the effectiveness of the Branding elements used by Social Networking Sites ? (Branding elements include - Brand Name, logos, symbols, Characters, Taglines)

 Social networking sites

strongly disagree

disagree

neither agree nor disagree

agree

strongly agree

facebook

27

6

12

46

159

Twitter

15

15

17

60

142

google plus

16

14

33

120

65

Orkut

14

86

82

43

25

linked.in

17

16

24

128

64

(Table Number 4.1- Responses for the effectiveness of the branding elements of social networking sites)

( Graph Number 4.1- Responses for the effectiveness of the branding elements of social networking sites)

Analysis-

1. 159 respondents strongly agree that facebook’s branding elements are effective

2. 142 respondents strongly agree that Twitter branding elements are effective

3. 120 respondents agree that google plus branding elements are effective

4. 86 respondents disagree that Orkut’s branding elements are effective

5. 128 respondents strongly agree that Linked.in branding elements are effective

4.2 What is the effectiveness of the Branding elements used by Online Shopping Sites? (Branding elements include - Brand Name, logos, symbols, Characters, Taglines)

 Online shopping sites

strongly disagree

disagree

neither agree nor disagree

agree

strongly agree

flipkart

13

11

20

42

164

snap deal

9

14

24

67

135

deals and you

11

100

80

41

17

tradus

10

26

31

141

41

ebay.in

10

15

20

134

70

(Table Number 4.2- Responses for the effectiveness of the branding elements of online shopping sites sites)

( Graph Number 4.2- Responses for the effectiveness of the branding elements of online shopping sites sites)

Analysis-

1. 164 respondents strongly agree that flipkart’s branding elements are effective

2. 135 respondents strongly agree that snapdeal’s branding elements are effective

3. 100 respondents disagree that dealsandyou’s branding elements are effective

4. 141 respondents agree that tradus’s branding elements are effective

5. 134 respondents agree that ebay.in branding elements are effective

4.3 Why do you think a social networking site should continue evolving ?

S.NO

REASONS FOR SOCIAL NETWORKING

NUMBER OF RESPONDENTS

1

Competitive Edge

63

2

Make The Site More Interesting

92

3

Get New Registers

89

4

Innovation In Technology

81

5

More Customers Internet Usage

69

6

Retain Customers

89

7

Create Awareness

89

8

Ease Of Use

93

9

Protection Against Cyber Crime

51

10

Customized Social Space

43

(Table Number 4.3- Responses for the reasons of a social networking site to continue evolve)

( Graph Number 4.3- Responses for the reasons of a social networking site to continue evolve)

Analysis-

Thus, the main reasons for a social networking site to continue evolving are:

1. 92 respondents felt that the web site should be continuously made more interesting

2. 89 respondents felt that the web site should Retain Customers thus, evolving itself.

3. 93 respondents felt that the web site should be of Ease Of Use.

4.4 Why do you think an online shopping site should continue evolving ?

S.NO

REASONS FOR ONLINE SHOPPING

NUMBER OF RESPONDENTS

1

Competitive Edge

66

2

Make The Site More Interesting

102

3

Get New Registers

117

4

Innovation In Technology

70

5

More Customers Internet Usage

78

6

Retain Customers

98

7

Create Awareness

72

8

Ease Of Use

73

9

Protection Against Cyber Crime

60

10

Customized Social Space

40

(Table Number 4.4- Responses for the reasons of an online shopping site to continue evolve)

(Graph Number 4.4- Responses for the reasons of an online shopping site to continue evolve)

Analysis-

Thus, the main reasons for a social networking site to continue evolving are:

1. 98 respondents felt that the web site should Retain Customers thus, evolving itself.

2. 102 respondents felt that the web site should be continuously made more interesting

3. 117 respondents felt that the web site should continue getting new registers.

Factor analysis

I) For Online Shopping Sites

KMO Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.

.877

Rotated Component Matrixa

Component

1

2

3

f1

.907

.173

.170

f2

.802

.455

.024

f3

.733

.223

.083

f4

.783

.492

.034

f5

.286

.057

.838

f6

.803

.172

.235

f7

.208

.827

-.004

f8

.094

.025

.843

f9

.740

.189

.179

f10

.153

.885

-.027

f11

.722

.500

.071

f12

.151

.818

-.107

f13

.751

.143

.301

f14

.141

.833

-.031

f15

.085

-.074

.793

f16

.768

.034

.277

f17

.208

-.158

.783

f18

.796

-.026

.030

f19

.767

.355

.037

f20

.808

-.084

.164

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.

The Discerning Shopper

A shopper who exhibits the following characteristics:

Quality at affordable prices

Tech savvy image

Reliability and trust

Security

Range of products

Ease and fun in shopping

Product Value

User Friendly

Easy search of Products

Product Comparisons

Awareness of any delay in delivery

Seasonal Deals

The Artificial Shopper

A shopper who exhibits the following characteristics:

Design of web site

Visual appeal

Product Customization

Product Variety

The Safe Shopper

A shopper who exhibits the following characteristics:

Delivery

Privacy

Post Purchase Discomfort

Tracking ID system

II) For Social Networking Sites

KMO Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.

.751

Rotated Component Matrixa

Component

1

2

3

g1

.673

.436

.237

g2

.826

.271

.185

g3

.734

.236

.327

g4

.671

-.073

-.367

g5

.686

.449

.182

g6

.261

.408

.317

g7

.583

-.236

-.303

g8

.737

.333

.184

g9

.165

.570

.332

g10

.628

.541

.371

g11

.517

-.166

.111

g12

.037

.689

.138

g13

.207

.783

-.187

g14

.348

.114

.119

g15

.218

.121

.646

g16

.142

.664

-.039

g17

.051

.162

.645

g18

-.066

.628

.281

g19

.164

-.262

.788

g20

.062

.355

.723

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.

The Social Friend

A person who exhibits the following characteristics:

Information leakage

Level of cyber stalking

Privacy setting

Applications for fun and games

Chat options

Free Time Utilization

Peer pressure

Measure of meeting new friends

Impersonal

Picture Uploading

The Seeker Friend

A person who exhibits the following characteristics:

Virtual Friendship

Cross Geographic Friends

Social Relations

Mobile Phone Applications

Continuous Updates

Security Level

The Professional Friend

A person who exhibits the following characteristics:

Professional work

Job Employment

Give Opinion’s and review’s

Continuous Updates about personal and professional friends

4.5 What do you think are the reasons for ORKUT.COM failure ?  

S.NO

REASONS

NUMBER OF RESPONDENTS

1

Not cool anymore

75

2

Unattractive Logo

93

3

Losing the universal selling point of the site

99

4

Wrong identity communicated

65

5

No scope for innovation

89

6

Privacy settings

113

7

Emergence of new competitors

81

8

Peer pressure to join different site

59

9

Not enough advertising

34

(Table Number 4.5- Responses for the reasons of Orkut.com’s failure)

( Graph Number 4.5- Responses for the reasons of Orkut.com’s failure)

Analysis-

Thus, the main reasons for the failure were:

1. 91 respondents felt that it had an unattractive logo

2. 89 respondents felt that it had no scope for innovation

3. 99 respondents felt that it was losing the universal selling point of the site

4. 113 respondents felt that the site did not have proper privacy settings

4.6 What do you think are the reasons for HI5.COM failure ?

S.NO

REASONS

NUMBER OF RESPONDENTS

1

Not cool anymore

72

2

Unattractive Logo

88

3

Losing the universal selling point of the site

110

4

Wrong identity communicated

68

5

No scope for innovation

104

6

Privacy settings

105

7

Emergence of new competitors

75

8

Peer pressure to join different site

67

9

Not enough advertising

35

(Table Number 4.6- Responses for the reasons of hi5.com’s failure)

( Graph Number 4.6- Responses for the reasons of hi5.com’s failure)

Analysis-

Thus, the main reasons for the failure were:

1. 104 respondents felt that it had no scope for innovation

2. 110 respondents felt that it was losing the universal selling point of the site

3. 105 respondents felt that the site did not have proper privacy settings

4.7 What do you think are the reasons for MY SPACE.COM failure ?

S.NO

REASONS

NUMBER OF RESPONDENTS

1

Not cool anymore

54

2

Unattractive Logo

79

3

Losing the universal selling point of the site

108

4

Wrong identity communicated

76

5

No scope for innovation

95

6

Privacy settings

111

7

Emergence of new competitors

90

8

Peer pressure to join different site

58

9

Not enough advertising

44

(Table Number 4.7- Responses for the reasons of myspace.com’s failure)

( Graph Number 4.7- Responses for the reasons why myspace.com’s failure)

Analysis-

Thus, the main reasons for the failure were:

1. 90 respondents felt that it was due to the emergence of the new competitors

2. 95 respondents felt that it had no scope for innovation

3. 108 respondents felt that it was losing the universal selling point of the site

4. 111 respondents felt that the site did not have proper privacy settings

4.8 What do you think are the reasons for DEALS AND YOU.COM failure ?

S.NO

REASONS

NUMBER OF RESPONDENTS

1

Limited products

66

2

Bad customer relationship management

73

3

Bad user interface

89

4

Unawareness

78

5

High prices as compared to competitors

73

6

No good deals

91

7

Old Products

97

8

Emergence of new competitors

80

9

Payment options

60

10

Delivery time

47

11

Transit damages

18

12

Failed online transactions

20

(Table Number 4.8- Responses for the reasons of dealsandyou.com’s failure)

(Graph Number 4.8- Responses for the reasons of dealsandyou.com’s failure)

Analysis-

Thus, the main reasons for the failure were:

1. 91 respondents felt that it had no good deals

2. 89 respondents felt that it had a bad user interface

3. 97 respondents felt that it just had old products

4.9 What do you think are the reasons for COMPARE INDIA.COM failure ?

S.NO

REASONS

NUMBER OF RESPONDENTS

1

Limited products

45

2

Bad customer relationship management

65

3

Bad user interface

91

4

Unawareness

98

5

High prices as compared to competitors

66

6

No good deals

74

7

Old Products

94

8

Emergence of new competitors

79

9

Payment options

68

10

Delivery time

57

11

Transit damages

30

12

Failed online transactions

16

(Table Number 4.9- Responses for the reasons of compareindia.com’s failure)

(Graph Number 4.9- Responses for the reasons of compareindia.com’s failure)

Analysis-

Thus, the main reasons for the failure were:

1. 98 respondents felt that they had unawareness of the site

2. 91 respondents felt that it had a bad user interface

3. 94 respondents felt that it just had old products

4.10. What do you think are the reasons for FASHION ARA.COM failure ?

S.NO

REASONS

NUMBER OF RESPONDENTS

1

Limited products

51

2

Bad customer relationship management

59

3

Bad user interface

87

4

Unawareness

88

5

High prices as compared to competitors

49

6

No good deals

86

7

Old Products

97

8

Emergence of new competitors

73

9

Payment options

63

10

Delivery time

53

11

Transit damages

36

12

Failed online transactions

27

(Table Number 4.10- Responses for the reasons of fashionara.com’s failure)

(Graph Number 4.10- Responses for the reasons of fashionara.com’s failure)

Analysis-

Thus, the main reasons for the failure were:

1. 86 respondents felt that it had no good deals

2. 87 respondents felt that it had a bad user interface

3. 97 respondents felt that it just had old products

4. 88 respondents felt that they had unawareness of the site

4.11 Which parameters are judged by you while choosing an online shopping site ?

Factor

Online Shopping

Quality At Affordable Prices

67

Tech Savvy Image

74

Reliability And Trust

87

Security

66

Delivery

75

Range Of Products

69

Design Of Web Site

68

Privacy

63

Ease And Fun In Shopping

62

Visual Appeal

64

Product Value

73

Product Customization

59

User Friendly

61

Product Variety

55

Post Purchase Discomfort

44

Easy Search Of Products

61

Tracking ID System

58

Tracking ID System

50

Awareness Of Any Delay In Delivery

32

Seasonal Deals

30

(Table Number 4.11- Responses for the Paramereters judged while choosing an online shopping site)

(Graph Number 4.11- Responses for the Paramereters judged while choosing an online shopping site)

Analysis:

87 respondents feel that reliability and trust that it is an important factor while selecting an online shopping site

73 respondents feel that Delivery that it is an important factor while selecting an online shopping site

74 respondents feel that a Tech Savy Image of the website that is an important factor while selecting an online shopping site

69 respondents feel that Range of Products and Product Value it is an important factor while selecting an online shopping site

68 respondents feel that Design of the Web Site is an important factor while selecting an online shopping site

4.12 Which parameters are judged by you while choosing a Social networking site ?

Factor

Social Networking

Information Leakage

62

Level Of Cyber Stalking

75

Privacy Setting

104

Applications For Fun And Games

56

Chat Options

79

Virtual Friendship

74

Free Time Utilization

73

Peer Pressure

78

Cross Geographic Friends

47

Measure Of Meeting New Friends

67

Impersonal

55

Social Relations

72

Mobile Phone Applications

52

Picture Uploading

68

Professional Work

57

Continuous Updates

50

Job Employment

55

Security Level

49

Give Opinion’s And Review’s

30

Continuous Updates About Personal And Professional Friends

22

(Table Number 4.12. Responses for the Paramereters judged while choosing aSocial networking site)

(Graph Number 4.12- Responses for the Paramereters judged while choosing a Social networking site)

Analysis:

103 respondents feel that Privacy Setting it is an important factor while selecting a Social Networking Site.

79 respondents feel that Chat Options is an important factor while selecting a Social Networking Site.

76 respondents feel that Peer Pressure is an important factor while selecting a Social Networking Site.

75 respondents feel that the level of cyber stalking is an important factor while selecting a Social Networking Site.

74 respondents feel that Virtual Friendship is an important factor while selecting a Social Networking Site.

Crosstabs Analysis

Age with preference of social networking sites

Facebook

preference for social networking sites

Total

Facebook

Twitter

Orkut

q15

below 18

15

0

0

15

18-23

92

2

0

94

24-29

83

9

1

93

30-35

29

3

0

32

36-41

8

0

0

8

above 41

8

0

0

8

Total

235

14

1

250

(Table Number 4.13. Responses for Age with Facebook)

Analysis:

92 people in 18-23 years of age prefer facebook

83 people in 24-29 years of age prefer facebook

T test:

N

Mean

Std. Deviation

Std. Error Mean

q5.1

250

1.0680

.29619

.01873

Thus, we accept alternative hypothesis, There is a significant preference towards Facebook social networking site by the people Facebook is preferred by people.

Twitter

preference for social networking sites

Total

Facebook

Twitter

Google plus

Orkut

Linked.in

q15

below 18

0

12

2

1

0

15

18-23

2

76

3

0

1

82

24-29

3

89

13

0

0

105

30-35

1

26

5

0

0

32

36-41

0

8

0

0

0

8

above 41

0

8

0

0

0

8

Total

6

219

23

1

1

250

(Table Number 4.14. Responses for Age with Twitter)

Analysis:

89 people in 24-29 years of age prefer twitter

76 people in 18-23 years of age prefer twitter

T test:

N

Mean

Std. Deviation

Std. Error Mean

q5.1

250

3.1080

.41111

.02600

Thus, Alternative hypothesis is accepted. There is a significant preference towards Twitter social networking site by the people Facebook is preferred by people.

Linked.in

preference for social networking sites

Total

Facebook

Twitter

Google plus

Orkut

Linked.in

q15

below 18

0

2

0

2

5

9

18-23

0

2

7

7

11

27

24-29

7

5

0

2

8

22

30-35

1

1

2

2

48

54

36-41

0

0

0

0

58

58

above 41

0

0

1

0

79

80

Total

8

10

10

13

209

250

(Table Number 4.15. Responses for Age with Linked.in)

Analysis:

79 people in above 41 years of age prefer linked.in

58 people in 36-41 years of age prefer linked.in

T test:

N

Mean

Std. Deviation

Std. Error Mean

q5.1

250

4.6200

.97127

.06143

Thus, Null hypothesis is accepted, There is not a significant preference towards Linked.in social networking site by the people

Age with preference of online shopping sites

flipkart

preference for online shopping sites

Total

below 18

18-23

24-29

30-35

36-41

above 41

Q6.1

Flipkart

12

90

85

30

8

8

233

Deals and you

2

3

8

2

0

0

15

Ebay.in

1

1

0

0

0

0

2

Total

15

94

93

32

8

8

250

(Table Number 4.16. Responses for Age with Flipkart)

Analysis:

90 people in 18-23 years of age prefer flipkart

85 people in 24-29 years of age prefer flipkart

T test:

One-Sample Statistics

N

Mean

Std. Deviation

Std. Error Mean

Q6.1

250

1.0760

.29423

.01861

Thus, Alternative hypothesis is accepted, There is a significant preference towards Flipkart social networking site by the people Facebook is preferred by people

ebay.in

preference for online shopping sites

Total

below 18

18-23

24-29

30-35

36-41

above 41

Q6.3

Flipkart

2

2

1

2

0

0

7

Deals and you

2

8

2

0

0

1

13

Ebay.in

10

73

80

27

8

7

205

Tradus

1

10

10

3

0

0

24

Snapdeal

0

1

0

0

0

0

1

Total

15

94

93

32

8

8

250

(Table Number 4.17. Responses for Age with Ebay.in)

Analysis:

80 people in 24-29 years of age prefer ebay.in

73 people in 18-23 years of age prefer ebay.in

T test:

One-Sample Statistics

N

Mean

Std. Deviation

Std. Error Mean

Q6.3

250

2.9960

.52640

.03329

Thus, Alternative Hypothesis is accepted, There is a significant preference towards Ebay.in social networking site by the people Facebook is preferred by people

Tradus.com

preference for online shopping sites

Total

below 18

18-23

24-29

30-35

36-41

above 41

Q6.4

Flipkart

1

0

1

0

0

0

2

Deals and you

0

1

0

0

0

0

1

Ebay.in

1

4

2

0

0

0

7

Tradus

12

74

79

28

8

7

208

Snapdeal

1

15

11

4

0

1

32

Total

15

94

93

32

8

8

250

(Table Number 4.18. Responses for Age with tradus)

Analysis:

79 people in 24-29 years of age prefer tradus

74 people in 18-23 years of age prefer tradus

One-Sample Statistics

N

Mean

Std. Deviation

Std. Error Mean

Q6.4

250

4.0680

.49024

.03101

Thus, Alternative Hypothesis is accepted , There is a significant preference towards tradus.com social networking site by the people Facebook is preferred by people

Demographics:

(Graph Number:13 . Responses for the Demographics)

Analysis:

95 respondents belong from the age group of 18-23 years of age.

93 respondents belong from the age group of 24-29 years of age.

32 respondents belong from the age group of 30-35 years of age.

105 respondents belong from Gurgaon

88 respondents belong from Delhi

57 respondents belong from Noida

83 respondents are Students

79 respondents are Employed

56 respondents are from the Business background

32 respondents are Self Employed

CHAPTER: 5

5. CONCLUSION AND RECOMMENDATIONS

5.1 SUMMARY OF THE FINDINGS

Effectiveness of the Branding elements used by Social Networking Sites

1. 159 respondents strongly agree that facebook’s branding elements are effective

2. 142 respondents strongly agree that Twitter branding elements are effective

3. 120 respondents agree that google plus branding elements are effective

Effectiveness of the Branding elements used by Online Shopping Sites

1. 164 respondents strongly agree that flipkart’s branding elements are effective

2. 135 respondents strongly agree that snapdeal’s branding elements are effective

3. 100 respondents disagree that dealsandyou’s branding elements are effective

Main Reasons why a social networking site should continue evolving