Brand Extension of Google Inc

Consumer Evaluation of Brand Extensions of Google Inc. (Online Brands Extended to Offline Market) – An Analytical Study

Submitted in partial fulfillment of the requirements for the award of the degree of

Master of Business Administration (MBA) To Guru Gobind Singh Indraprastha University, Delhi

Guide:

Submitted By:

Dr. Anu Nagpal

Sanjeev Kumar

Associate professor

13919103911

GITARATTAN INTERNATIONAL BUSINESS SCHOOL Delhi – 110085 Batch (2011-2013)

CERTIFICATE I, Sanjeev Kumar, Enrollment No. 13919103911 certify that the Project Report (MS-202) entitled “Consumer Evaluation of Brand Extensions of Google Inc.” is done by me and it is an authentic work carried out by me at Gitarattan International Business School. The matter embodied in this project work has not been submitted earlier for the award of any degree or diploma to the best of my knowledge and belief.

Signature of the Student Date: Certify that the Project Report (MS-202) entitled “Consumer Evaluation of Brand Extensions of Google Inc.” done by Mr. Sanjeev Kumar, Enrollment No. 13919103911, is completed under my guidance.

Signature of the Guide Date: Dr. Anu Nagpal Associate Professor Gitarattan International Business School, Delhi- 110085

Countersigned

Director/Project Coordinator

ACKNOWLEDGEMENT

Research Project Report is a venture that requires co-operation of many people. I wish to place on record my gratitude to Dr. S. Chaturvedi, Director and Mr. Rajesh S. Pyngavil, Program Coordinator, Gitarattan International Business School, New Delhi for their continuous encouragement and advice which were of immense help to me. I feel pleasure in taking this opportunity to express my sincere regards to my supervisor Dr. Anu Nagpal, Associate Professor, Gitarattan International Business School, New Delhi. Without her guidance, valuable suggestions, constructive criticisms and encouragement throughout the course of the project would not have been possible. I am also thankful to all teachers, non-teaching staff and all my friends of the institute for their kind help.

Sanjeev Kumar Enrollment No- 13919103911

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EXECUTIVE SUMMARY Increasing competence within the marketplace has provoked that firms seek to go beyond the boundaries of their actual businesses by offering products in totally new markets. Companies attempt to reduce the risk associated with launching these new products by using an existing brand name, which allows the companies to leverage brand equity in the new product categories. Brand extension has become a popular strategy not only within the limits of offline markets but, also in an online context to the extent that numerous offline companies have extended their brands to online markets. Nevertheless, a recent trend shows that the reverse is also possible, and Internet brands can also benefit from entering in new offline product categories. Online advertising is a form of promotion that uses the Internet and World Wide Web to deliver marketing messages to larger audience. Online advertising is a form of promotion that uses the Internet and World Wide Web to deliver marketing messages to attract targeted customers. Google Inc. is an American multinational corporation that provides Internet-related products and services, including internet search, Telecoms equipment and its application, cloud computing, software and advertising technologies. The project titled “Consumer Evaluation of Brand Extensions of Google Inc.” focused on the factors affecting brand extension. The study examines whether online brands can be successfully extended to offline product categories from a consumer perspective. Specifically, this study develops an descriptive model of consumer evaluation of brand extensions which combines variables previously studied in the literature with other extracted from online branding and applies them to the research context. Empirical survey data is analyzed through a regression analysis applied to iii

online brand and their offline extensions to identify the most important factors influencing consumer’s attitude toward the brand extensions. Before starting with the actual conduct of the study, various research papers were reviewed so as to provide a base for the study. For the purpose a sample of 100 respondents were taken. The data was collected using a questionnaire as a primary data from Rohini, Delhi. The secondary data for the study was taken from sources like journals, books, magazines and websites. For the purpose of testing hypothesis the analysis was conducted with the help of tools like Ms Excel and SPSS. During the research and while collecting information there were certain hurdles like the sample size was small, customers were uninterested, due to time constraint, etc. Future research can be done by accessing a wider area of network for getting improved results. As for the further possibilities for research in this area, rural area can be covered due to lack of awareness in that geographical area. From the analysis various findings were drawn, limitations were traced and suggestions laid down. The main results indicate that the attitude towards the offline extensions launched by online companies is determined by the degree of product similarity, the transference of emotional associations with the parent brand to the new product, the perceived similarity received by the extension and the extent to which the consumers are involved with the new product category. As consequence of these findings, the success of online brands going offline will depend on the capability of managers to build a strong and positive brand personality and product quality with consumers as well as implementing marketing activities which reinforce product similarity perceptions and foster consumer involvement with the brand extension.

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CONTENTS

S No

Topic

Page No

1

Certificate

i

2

Acknowledgement

ii

3

Executive Summary

iii

4

Contents

v

5

List of Tables

vi

6

List of Figures

vii

7

List of Symbols

viii

8

List of Abbreviations

ix

9

Chapter-1:

Introduction

1

10

Chapter-2:

Literature Review

32

11

Chapter-3:

Data Presentation & Analysis

55

12

Chapter-4: Summary and Conclusions

70

13

Chapter-5: Recommendations

76

14

Bibliography

79

15

Appendix

83

16

Annexure

89

v

LIST OF TABLES

Table No 1

Title

Page No

Top Ad sever vendors in 2008 9

2

World’s 10 largest mobile phone handset vendors 11

3

Reliability Statistics 26

4

Hypothesis and Factors 31

5

Main Factors of Brand Extension Evaluation 47

6

Percentage of Gender in Respondents 57

7

Percentage Age Group 58

8

Qualification of Respondents 59

9

Percentage of Profession Respondents 60

10

Correlations 61

11

Variables 63

12

Model Summary 64

13

ANOVAa 65

14

Cofficientsa 66

15

Review of Hypotheses 67

vi

LIST OF FIGURES

Figure No

Title

Page No

1

Timeline of Google Inc.

17

2

Brand Extension Attitude Model

46

3

Pie Chart of Percentage of Gender

57

4

Pie Chart of Percentage Age Group

58

5

Pie Chart of Qualified Respondents

59

6

Pie Chart of Profession Respondents

60

vii

LIST OF SYMBOLS

S No

Symbol

Nomenclature & Meaning

1

α

Alpha

2

β

Beta

3

@

At the rate

4

ε

Standard error

5

ρ

Significance Level

6

×

Multiplication

viii

LIST OF ABBREVIATIONS

S No

Abbreviated Name

Full Name

1

Inc.

Incorporation

2

SEM

Search Engine Marketing

3

SEO

Search Engine Optimization

4

SERP

Search Engine Result Pages

5

PDA

Personal Digital Assistant

6

OS

Operating System

7

GPL

General Public License

8

Q3

Quarter 3rd

9

FMCG

Fast Moving Consumer Goods

10

BE

Brand Extension

11

BT

Brand Trust

12

CPM

Cost Per Mille

13

CPV

Cost Per Visitor

14

CPC

Cost Per Click

15

PPC

Pay per click

16

CPA

Cost Per Acquisition

17

PPP

Pay Per Performance

18

CPL

Cost Per Lead

19

BA

Brand Affect

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CHAPTER 1 INTRODUCTION

1.1 Introduction Increasingly competitive forces in the global markets are forcing companies to differentiate themselves from competitors in order to survive and take advantage of the current opportunities of growth. One way to differentiate from competitors is the establishment of strong brands that allow companies to increase the efficiency of their marketing expenses achieving thus benefits to the company such as a more favorable perception of the products by the customers, greater loyalty, less vulnerability to competitors marketing actions, high profits margins, less negative reactions by consumers to price increases, higher support of middlemen, higher marketing promotion effectiveness, increasing licensing and brand extensions opportunities. In other words, while competitors can emulate financial and physical assets, intangible assets, as brands, represent a more sustainable competitive advantage. The importance of brands is not only measured in terms of the competitive advantages that they provide in their present markets but also the future opportunities that they provide in untapped markets. This way, firms can enter new markets by using an existing, well-known brand name in order to reduce both the cost of launching new products and the risk of product failure. The strategy behind the leverage of the company brand equity to new markets, products or sectors is known as brand extension. The acceptance of brand extension is principally due to the benefits that both brand and extension provide. On the one hand, the product commercialized under a well-known brand is more attractive to the consumers and suppliers, thus reducing the marketing costs and increasing the chance of success. On the other hand, brand extensions reinforce brand image and notoriety, which make consumers purchase other products offered by the brand. All this allows an increase of the market share and efficiency of market efforts. In other words, extensions benefit the companies

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because they transfer intangible components of the brand such as brand awareness, trust or other specific brand associations stored in the consumer’s minds to the new products. For example, National Geographic has been able to extend successfully its brand by transferring associations of nature, adventure and multiculturalism from photography and documentaries to travel products, furniture or outdoors clothing. Despite the positive effects of brand extensions, their inappropriate use may harm the company's brand image if the new products do not fit with the consumers brand associations. This does not mean that a high degree of similarity between the parent brand product category and the new product has to be present; in fact, some companies have stretched their brands to very dissimilar product classes. For instance, Louis Vuitton successfully extended to luxury resorts although it is a different business from fashion and ITC also successfully extended to the hotel, restaurants and luxury cloths industry although these are very different business from tobacco. The use of brand extensions as a strategy to achieve growth has drastically increased in recent years. In fact, between 80 and 90% of new products are launched under the name of an existing brand. Extensions also gone through the borders of the offline markets to markets from the online domain. Consequently, companies have stretched their brands within and towards the online markets. Traditionally based offline companies, in addition to use the internet as an alternative distribution channel or mean of running communication campaigns, have considered the online domain as a valuable market to commercialize both their current products or services and their extensions. For instance, Apple sells mobile applications and music on the internet through its iTunes shop and Google sell their mobile application and games on the internet through its Google Play apps. For offline brands, the expansion into the online market increases the brand value for consumers by providing additional

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availability and exposure through the internet. On the other hand, some online businesses, such as Google, Amazon, Yahoo, Microsoft and eBay, have extended their brands within the Internet limits, becoming some of the top 100 global brands. Amazon, for instance, started to sell electronic goods and music online in addition to books. It is also possible to extend online brands to offline markets. Following this trend, Google has launched a new mobile phone which uses Google's mobile operation system, Android. Besides, Amazon has extended its name to a new device, Amazon Kindle, which enables consumers to read eBooks, newspapers and magazines through an Internet connection. Microsoft Inc. also introduced Microsoft Surface Tablet & windows phone and extended to offline market from online or services. Therefore, offline markets enable Internet brands to enhance brand awareness by making them more tangible for consumers, which may create stronger trust and consequently higher brand loyalty. Furthermore, the adaptation of online brands competences to the commercialization of offline products and the absence of some of the costs originally attributed to brick and mortar companies such as, costs linked to the establishment of stores, turn offline product into attractive markets where online brands can be extended.

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1.2 Industry Profile  Online advertising Online advertising, also known as online advertisement, internet marketing, online marketing or e-marketing, is the marketing and promotion of products or services over the Internet. Online advertising is a form of promotion that uses the Internet and World Wide Web to deliver marketing messages to larger audience. Examples of online advertising include contextual ads on search engine results pages, banner ads, blogs, rich media ads, social network advertising, interstitial ads, online classified advertising, advertising networks, dynamic banner ads, cross-platform ads and e-mail marketing, including e-mail spam. Many of these types of ads are delivered by an ad server. Online advertising is a form of promotion that uses the Internet and World Wide Web to deliver marketing messages to attract targeted customers. One major benefit of online advertising is the immediate publishing of information and content that is not limited by geography or time. To that end, the emerging area of interactive advertising presents fresh challenges for advertisers who have hitherto adopted an interruptive strategy. Another benefit is the efficiency of the advertiser's investment. Online advertising allows for the customization of advertisements, including content and posted websites. For example, AdWords, Yahoo! Search Marketing and Google AdSense enable ads to be shown on relevant web pages or alongside search results. Although the overall return is not quantifiable as many Internet users either use ad blocking software or simply do not respond to online adverts as they regard them as an invasive platform. The internet has become an ongoing emerging source that tends to expand more and more. The growth of this particular medium attracts the attention of advertisers as a 5

more productive source to bring in consumers. A clear advantage consumers have with online advertisement is the control they have over the product, choosing whether to check it out or not. Online advertisements may also offer various forms of animation. In its most common use, the term "online advertising" comprises all sorts of banner, e-mail, in-game, and keyword advertising, including on platforms such as Facebook, Twitter, and MySpace. Web-related advertising has a variety of ways to publicize and reach a niche audience to focus its attention to a specific group. Research has proven that online advertising has given results and is growing business revenue. For the year 2012, Jupiter Research predicted $34.5 billion in US online advertising spending. Online advertisement can also be classified as Digital Promotions. Digital promotion in connection to the television industry is when networks use authentic digital resources to promote their new shows in a growing vast range of venues. Television networks development of digital off air promotional strategies allowed digital promotion to remain significant to the advertisement advancement in the television. Examples of television online digital promotions: The Sci-Fi network for loaded a special recap episode of Battlestar Galactica onto Microsoft’s Xbox online gaming service; this gave the audience additional opportunities to sample content if they may or may not be familiar with the show. Another example of digital promotion in television is when network CBS incorporated new digital technologies of Bluetooth-enabled mobile devices that were able to download a thirty-second clip of a new show on their devices; consumers standing in range of a billboard don’t need an internet link to download the show’s content. These non-linear viewing opportunities provided as a valuable tool for gaining audiences; and to encourage them to intersect with the linear audience.

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1.2.1 Types of Internet marketing/ online advertising Internet marketing is broadly divided in to the following types: Display advertising: the use of web banners or banner ads placed on a third-party website or blog to drive traffic to a company's own website and increase product awareness. Search engine marketing (SEM): a form of marketing that seeks to promote websites by increasing their visibility in search engine result pages (SERPs) through the use of paid placement, contextual advertising, and paid inclusion, or through the use of free search engine optimization techniques also known as organic result. Search engine optimization (SEO): the process of improving the visibility of a website or a web page in search engines via the "natural" or un-paid ("organic" or "algorithmic") search results. Social media marketing: the process of gaining traffic or attention through social media websites such as Facebook, Twitter and LinkedIn. Email marketing: directly marketing a commercial message to a group of people using electronic mail. Referral marketing: a method of promoting products or services to new customers through referrals, usually word of mouth. Affiliate marketing: a marketing practice in which a business rewards one or more affiliates for each visitor or customer brought about by the affiliate's own marketing efforts. Content marketing: the process of creating specialized content such as info graphics, blog articles and eBooks to attract more customers. Inbound marketing: involves creating and freely sharing informative content as a means of converting prospects into customers and customers into repeat buyers. 7

1.2.2 Business and Revenue Models Internet marketing is associated with several business models: E-commerce: a model whereby goods and services are sold directly to a consumer or business. Lead-based websites: a strategy whereby an organization generates value by acquiring sales leads from its website, similar to walk-in customers in retail world. These prospects are often referred to as organic leads. Affiliate marketing: a process wherein a product or service developed by one entity is sold by other active sellers for a share of profits. The entity that owns the product may provide some marketing material (e.g., sales letters, affiliate links, tracking facilities, etc.); however, the vast majority of affiliate marketing relationships come from e-commerce businesses that offer affiliate programs. It has following Revenue models: The three most common ways in which online advertising is purchased are CPM, CPC, and CPA. CPM (Cost Per Mille) or CPT (Cost Per Thousand Impressions) is when advertisers pay for exposure of their message to a specific audience. "Per mille" means per thousand impressions, or loads of an advertisement. However, some impressions may not be counted, such as a reload or internal user action. CPV (Cost Per Visitor) is when advertisers pay for the delivery of a Targeted Visitor to the advertisers website. CPV (Cost Per View) is when advertisers pay for each unique user view of an advertisement or website (usually used with pop-ups, pop-under and interstitial ads). CPC (Cost Per Click) or PPC (Pay per click) is when advertisers pay each time a user clicks on their listing and is redirected to their website. They do not actually pay 8

for the listing, but only when the listing is clicked on. This system allows advertising specialists to refine searches and gain information about their market. CPA (Cost Per Action or Cost Per Acquisition) or PPF (Pay Per Performance) advertising is performance based and is common in the affiliate marketing sector of the business. In this payment scheme, the publisher takes all the risk of running the ad, and the advertiser pays only for the number of users who complete a transaction, such as a purchase or sign-up. This model ignores any inefficiency in the seller's web site conversion funnel. CPL (Cost Per Lead) advertising is identical to CPA advertising and is based on the user completing a form, registering for a newsletter or some other action that the merchant feels will lead to a sale. Given below (Table 1) is a list of top Ad server vendors in 2008 with figures in millions of viewers published in an Attributor survey. Since 2008 Google has controlled an estimated 69% of the online advertising market. Vendor

Ad viewers (millions)

Google

1,118

DoubleClick (Google)

1,079

Yahoo!

362

MSN (Microsoft)

309

AOL

156

Adbrite

73

Total

3,097

Table No-1: Top Ad sever vendors in 2008 9

 Telecommunications equipment and its software Telecommunications equipment (also telecoms equipment or communications equipment) is hardware used for the purposes of telecommunications. Since the 1990s the boundary between telecoms equipment and IT hardware has become blurred as a result of the growth of the internet and its increasing role in the transfer of telecoms data. Companies in this industry make equipment used in telephone, data, radio and TV broadcast, and wireless communications networks. Major companies include Apple, Cisco Systems, Motorola Solutions, and QUALCOMM (all based in the US), as well as Alcatel-Lucent (France), Ericsson (Sweden), Huawei (China), Nokia (Finland), and Samsung (South Korea). The industry depends on purchases from businesses, telephone companies, cable companies, data communications providers, and TV and radio broadcasters. Profitability for individual companies is linked to technical innovation and the ability to secure high-volume contracts from large customers. Small companies can be successful if they make highly specialized products. There are large economies of scale in manufacturing standard products, but many products are specialized and produced in small manufacturing plants. The industry is highly concentrated: the 50 largest companies generate about 80 percent of revenue. About 80 percent of industry revenue comes from equipment for wireless communications (including radio and TV); about 20 percent comes from equipment for line-based communications. The industry produces transmitters and receivers (including satellites); signal boosters; signal processors; connecting devices; power supplies; switches; and phones.

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The world's 10 largest mobile phone handset vendors measured by unit sales in the third quarter of 2012 are (global market share shown in Table 2)

Company

Market Share (in %age)

Samsung

22.9

Nokia

19.2

Apple

5.5

ZTE

3.9

LG Electronics

3.3

Huawei

2.8

TCL

2.2

Research In Motion

2.1

Motorola

2.0

Mobility(now become Google Mobile) HTC

2.0

Table No-2: world’s 10 largest mobile phone handset vendors

As of 2012 many of the largest telecoms networking equipment vendors are struggling financially due to oversupply, rising market share of China-based vendors, and declining revenues for 2G and 3G networks not being fully offset by the growing market for 4G equipment.

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A mobile operating system, also referred to as mobile OS, is the operating system that operates a Smartphone, tablet, PDA, or other digital mobile devices. Modern mobile operating systems combine the features of a personal computer operating system with touch screen, cellular, Bluetooth, Wi-Fi, GPS mobile navigation, camera, video camera, speech recognition, voice recorder, music player, Near field communication, personal digital assistant (PDA) and other features. The most common mobile operating systems are: Android from Google Inc. Android was developed by a small startup company (Android Inc.) that was purchased by Google Inc. in 2005, which Google has continued to update the software. Android is a Linux-derived OS backed by Google, along with major hardware and software developers (such as Intel, HTC, ARM, Samsung, Motorola and eBay, to name a few), that forms the Open Handset Alliance. Released on November 5th 2007, the OS was well received from a number of developers upon its introduction. From Q2 of 2009 to the second quarter of 2010, Android's worldwide market share rose 850% from 1.8% to 17.2%. On November 15, 2011, Android reached 52.5% of the global Smartphone market share. BlackBerry 10 from BlackBerry BlackBerry 10 (previously BlackBerry BBX) the next generation platform for BlackBerry smartphones and tablets. In other words, there will be only one OS for both Blackberry smartphones and tablets going forward. iOS from Apple Inc.(closed source, on top of open source Darwin core OS) The Apple iPhone, iPod Touch, iPad and second-generation Apple TV all use an operating system called iOS, which is derived from Mac OS X. Native third party

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applications were not officially supported until the release of iOS 2.0 on July 11th 2008. Before this, "jailbreaking" allowed third party applications to be installed, and this method is still available. Currently all iOS devices are developed by Apple and manufactured by Foxconn or another of Apple's partners. Windows Phone from Microsoft (closed source, proprietary) On February 15th, 2010, Microsoft unveiled its next-generation mobile OS, Windows Phone. The new mobile OS includes a completely new over-hauled UI inspired by Microsoft's "Metro Design Language". It includes full integration of Microsoft services such as Microsoft SkyDrive and Office, Xbox Music, Xbox Video, Xbox Live games and Bing, but also integrates with many other non-Microsoft services such as Facebook and Google accounts. The new software platform has received some positive reception from the technology press. Linux based operating system (open source, GPL) Linux is strongest in China where it is used by Motorola (now Google), and in Japan, used by DoCoMo. Rather than being an OS in its own right, Linux is used as a basis for a number of different operating systems developed by several vendors, including Android, GridOS, Boot to Gecko, LiMo, Maemo, MeeGo, Openmoko and Qt Extended, which are mostly incompatible. PalmSource (now Access) is moving towards an interface running on Linux. Another software platform based on Linux is being developed by Motorola, NEC, NTT DoCoMo, Panasonic, Samsung and Vodafone. In 2006, Android, iOS, Windows Phone and Bada did not yet exist and just 64 million smartphones were sold. Today, nearly 10 times as many smartphones are sold and the top mobile operating systems marketed as "smartphones" by market share are Android, Symbian, Apple iOS, BlackBerry, MeeGo, Windows Phone and Bada.

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1.3 Company Profile Google Inc. is an American multinational corporation that provides Internet-related products and services, including internet search, Telecoms equipment and its application, cloud computing, software and advertising technologies. Advertising revenues from AdWords generate almost all of the company's profits. The company was founded by Larry Page and Sergey Brin while both attended Stanford University. Together, Brin and Page own about 16 percent of the company's stake. Google was first incorporated as a privately held company on September 4, 1998, and its initial public offering followed on August 19, 2004. In 2006, the company moved to its headquarters in Mountain View, California. The company offers online productivity software including email, an office suite, and social networking. Google's products extend to the desktop as well, with applications for web browsing, organizing and editing photos, and instant messaging. Google leads the development of the Android mobile operating system, as well as the Google Chrome OS browser-only operating system, found on specialized netbooks called Chromebooks. Google has increasingly become a hardware company with its partnerships with major electronics manufacturers on its high-end Nexus series of devices and its acquisition of Motorola Mobility in May 2012, as well as the construction of fiber-optic infrastructure in Kansas City as part of the Google Fiber broadband Internet service project. Google has been estimated to run over one million servers in data centers around the world, and process over one billion search requests and about twenty-four petabytes of user-generated data every day. As of December 2012, Alexa listed the main U.S. focused google.com site as the Internet's most visited website and numerous international Google sites as being in the 14

top hundred, as well as several other Google-owned sites such as YouTube and Blogger. In 2011, 96% of Google's revenue was derived from its advertising programs. For the 2006 fiscal year, the company reported $10.492 billion in total advertising revenues and only $112 million in licensing and other revenues. Google has implemented various innovations in the online advertising market that helped make it one of the biggest brokers in the market. Using technology from the company DoubleClick, Google can determine user interests and target advertisements so they are relevant to their context and the user that is viewing them. Google Analytics allows website owners to track where and how people use their website, for example by examining click rates for all the links on a page. Google advertisements can be placed on third-party websites in a two-part program. Google's AdWords allows advertisers to display their advertisements in the Google content network, through either a cost-per-click or cost-per-view scheme. The sister service, Google AdSense, allows website owners to display these advertisements on their website, and earn money every time ads are clicked. Google Search, a web search engine, is the company's most popular service. According to market research published by comScore in November 2009, Google is the dominant search engine in the United States market, with a market share of 65.6%. Google indexes billions of web pages, so that users can search for the information they desire, through the use of keywords and operators. In May 2011, the number of monthly unique visitors to Google surpassed one billion for the first time, an 8.4 percent increase from May 2010 (931 million). In January of 2013, Google announced it had earned $50 billion in annual revenue for the year of 2012. This marked the first time Google had reached this feat, topping their 2011 total of $38 billion.

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Google Inc. Currently owns and operates six data centers across the U.S., plus one in Finland and another in Belgium. On September 28, 2011, the company announced plans to build three data centers at a cost of more than $200 million in Asia (Singapore, Hong Kong and Taiwan) and purchased the land for them. Since 2001, Google has acquired many companies, mainly focusing on small venture capital companies. In 2004, Google acquired Keyhole, Inc. The start-up company developed a product called Earth Viewer that gave a three-dimensional view of the Earth. Google renamed the service to Google Earth in 2005. Two years later, Google bought the online video site YouTube for $1.65 billion in stock. On April 13, 2007, Google reached an agreement to acquire DoubleClick for $3.1 billion, giving Google valuable relationships that DoubleClick had with Web publishers and advertising agencies. Later that same year, Google purchased GrandCentral for $50 million. The site would later be changed over to Google Voice. On August 5, 2009, Google bought out its first public company, purchasing video software maker On2 Technologies for $106.5 million. Google also acquired Aardvark, a social network search engine, for $50 million. In April 2010, Google announced it had acquired a hardware startup, Agnilux. Google is known for having an informal corporate culture. On Fortune magazine's list of best companies to work for, Google ranked first in 2007, 2008 and 2012 and fourth in 2009 and 2010. Google was also nominated in 2010 to be the world's most attractive employer to graduating students in the Universum Communications talent attraction index. Google's corporate philosophy embodies such casual principles as "you can make money without doing evil," "you can be serious without a suit," and "work should be challenging and the challenge should be fun."

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1.31 Timeline of Google Figure 1 shows timeline of Google since 1998 i.e. foundation of Google to 2011, when google acquired Motorola Mobility google diversify into market and product globally.

Figure No-1: Timeline of Google Inc.

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1.32 Vision and Mission The company's vision statement is "to develop a perfect search engine" and the company's mission statement from the outset was "to organize the world's information and make it universally accessible and useful" and the company's unofficial slogan is "Don't be evil". 1.33 Products offer by Google Inc. This list of Google products includes all major desktop, mobile and online products released or acquired by Google Inc. This list also includes prior products, that have been merged, discarded or renamed. Web-based products These products must be accessed via a web browser: Google search – web search engine, which is Google's core product. It was the company's first creation, coming out of beta on September 21, 1999, and remains their most popular and famous service. It receives 100 billion search queries per month and is the most used search engine on the Internet. Google Books (was Print) – search engine for the full text of printed books. Google scans and stores in its digital database. The content that is displayed depends on the arrangement with the publishers, ranging from short extracts to entire books. Etc. Communication and publishing tools FeedBurner – news feed management services, including feed traffic analysis and advertising facilities. Google Docs – document, spreadsheet, drawing and presentation application, with document collaboration and publishing capabilities.

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Google Drive – an online backup service and storage space. This service is connected with Google Docs. Gmail (also termed Google Mail) – free Webmail IMAP and POP email service provided by Google, known for its abundant storage, intuitive search-based interface and elasticity. It was first released in an invitation-only form on April 1, 2004. Mobile access and Google Talk integration is also featured. Operating systems Android – an operating system for mobile devices such as smartphones and tablet computers. Google Chrome OS – Linux-based operating system designed by Google to work exclusively with web applications. Runs on the "Chromebook" and the nettop "Chromebox", the first of which (Samsung Series 3) was released in May 2012.[11] Google TV – smart TV platform that integrates Android and the Linux version of Google Chrome to create an interactive television overlay on top of existing internet television and WebTV sites to add a 10-foot user interface.

Hardware Google Enterprise Search Appliance – a search appliance designed for indexing corporate data. Motorola Mobility – mobile manufacturer. In August 2011, Google, Inc., announced that it had reached a deal to acquire the company for $12.5 billion USD in cash. The deal closed on 23 May 2012. Nexus One – Smartphone running the Android open source mobile operating system. Chromebook – Laptop personal computer running the Google Chrome O

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1.34 SWOT Analysis of Google Inc. Strengths 1. Google controls 83.7% of the global desktop search market. 2. Google controls 89% of the global mobile search market. 3. Google has $45.72 billion in cash and only $3 billion in long term debt. 4. Google's Android system accounted for 72.4% of all smartphones sales in Q3 2012 according to Gartner. 5. The Samsung Galaxy S3 (which runs on Android) has been selling very well (outpaced the iPhone 4S in Q3) and many are saying that it is better than the iPhone. 6. Vast app ecosystem with tons of apps and developers. 7. The Nexus 7 got great reviews and is selling very well right now, eating into Apple's market share. 8. US paid click traffic is up 27% year over year in Q3 2012. Weaknesses 1. It is Dependent on Microsoft's operating system on desktops (which controls over 90% of the desktop OS market) for its desktop search engine, yet it competes with Microsoft in numerous different sectors. 2. It Missed earnings expectations last quarter and saw its stock price fall. 3. Gross Margin is coming down (65.29% TTM versus 59.76% in the latest quarter) as more searches come from developing countries where the revenue per click is lower than in developed nations. 4. Google is losing map services market share (has fallen by 50% in China) as Apple continues to box out Google in this very lucrative industry.

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Opportunities 1. Total paid clicks continue to rise, with most of the growth coming from developing nations. Google's paid click traffic was up 28.8% in the US year over year (for Q3 2012). 2. Google is making a lot of headway into the tablet market. 3. The smartphone market in the US isn't saturated yet and millions still need smartphones, many of which will come with Android's OS. 4. Lots of cash means it can buy up strategic assets (like Twitter) to boost profits. 5. S&P just raised Google's corporate credit rating to AA and it could rise higher. 6. Google is pushing into the cable industry, starting up a fiber optic network in Kansas City. 7. Location Based revenue is expected to grow from $2.8 billion in 2010 to $10.3 billion in 2015 according to Pyramid Research. Threats 1. Apple is trying to box Google out of the fast growing location service industry. 2. Microsoft is aggressively pushing into the smartphone and tablet industry with the launch of Windows 8. 3. Bing is gaining some market share in the US search industry; going from 19.4% in Q4 2011 (Google had 80.6% of the market) to 21.3% in Q3 2012 (Google now has 78.7% of the market). Keep in mind this is just the US search market. 4. While this is a long shot, antitrust issues could ensue, especially if Google tries to push into the fiber optic industry with its dominance in the search market.

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5. The Smartphone industry remains one of the most competitive markets in the world and you must always be on top of your game. One year of bad phone line ups and you could end up like Blackberry. 6. Companies like Facebook and Twitter can take up a lot of internet viewing time, decreasing the chance that consumers search the web.

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1.4 Objectives of Study Every research is conducted for achieving some objectives & the objectives of the study are:  To study the marketing mix strategies comprising of 4P’s of Google Inc.  To study the online services extended to offline products of Google Inc.  To study the relationship among some important variables of Brand extension.  To analyze the significance of some important variables towards the extensions. 1.5 Scope of Study The scope of the study is limited and the approach of the study focuses mainly on the perspective of consumers who are using Google online services and offline products in and nearby Rohini locality at New Delhi, for this purpose the researcher is expected to go through data analysis based on the primary data of 100 respondents along with the secondary data. This study is also useful for understanding the extension of brands for others organizations as well. 1.6 Research Methodology: a) Research Design The research is descriptive in nature as it tries to assess the significance of some important variables which affect the brand extension. Descriptive research is an exploration of the certain existing phenomenon. It is mostly done when a researcher wants to gain a better understanding of the topic.

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b) Universe of the study The universe of the study is users of the Google online and offline products and services. c) Population of study The samples will be collected from Rohini, Delhi. d) Sampling technique The sampling technique will be adopted as convenience sampling. The samples will be collected from Rohini, Delhi. Convenience sampling is used as it is a non probability sampling technique where subjects are selected because of their convenient accessibility and proximity to the researcher. e) Sample size The sample size for the study is 100 because of a rule of thumb. It means that (Number of variables x 100). In this study there is only one variable i.e. customer preference. That’s why researcher will use 100 as a sample size. f) Tools for data collection A Structured questionnaire is used to collect the data as respondent asked to give his/her opinion on the different factors that affect brand extension of Google Inc. A questionnaire is prepared by taking into consideration the various factors which affect the decision regarding brand extension of Google.

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g) Sources of data collection 1. Primary Data Primary data are collected from a sample of 100 respondents, chosen by convenience sampling method. Structured questionnaire based on Likert Scale is used to obtain first hand primary data. 2. Secondary Data Secondary data is the data that have been already collected by and readily available from other sources. For the purpose of the study secondary data has been collected from: 

Research Papers



Books



Journals/ Magazines



Other websites

h) Methodology used for Data Analysis: a. Regression Analysis : Regression analysis is a statistical technique for estimating the relationships among variables. Regression analysis helps one understand how the typical value of the dependent variable changes when any one of the independent variables is varied, while the other independent variables are held fixed. b. Correlation: Correlation is the study of mutual relationship between two or more things. Correlation has been used in order to understand the high degree of association between two or more variables towards the extensions evaluation. 25

i) Tools for Data Analysis: Tool proposed to be used in this project for data analysis are: 

MS Excel and



SPSS (Software Package for Social Sciences)

j) Reliability Statistics The reliability of the questionnaire is checked by collecting the data by filling the questionnaires from 20 respondents. The reliability statistics is given in Table 3.

Table No-3: Reliability Statistics From the above statistics, we get the value of coefficient of alpha (α) is 0.826. The questionnaire is said to be reliable when the coefficient of α value must be above 0.70.

1.7 Hypothesis In this section we focus on the acceptance of brand extensions for google. Specifically, we focus on Brand Awareness, Perceived Quality, Brand Loyalty, Perceived Similarity, and Innovativeness as factors influencing the acceptability of brand extensions. 1.7.1 Brand knowledge Aaker defined brand awareness as the salience of the brand in the customers mind and identified six levels of awareness: recognition, recall, top-of-mind, and brand

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dominance, brand knowledge and brand opinion. The brand extension research has focused its attention on brand knowledge in order to explain extension evaluations. H0: Consumer knowledge of the online brand, original product category and offline extension category has negative effects on the extension evaluation. H1: Consumer knowledge of the online brand, original product category and offline extension category has positive effects on the extension evaluation.

1.7.2 Perceive quality Perceive quality designates a global assessment of a consumer´s judgement about the superiority or excellence of a product. The perceived quality construct has been included in diverse brand extension articles. Aaker and Keller suggested that when consumers have a high overall perception about the quality of the brand, the extension should be assessed more positively than when they infer a low overall quality. Nevertheless, they found that quality only affected the attitude towards the extension favourably when it was accompanied by a high degree of similarity. H0 Higher quality perceptions toward the original online brand are associated with negative attitudes toward the offline extension. H2 Higher quality perceptions toward the original online brand are associated with more favourable attitudes toward the offline extension. 1.7.3 Brand loyalty Brand loyalty has also had a significant relevance in studies focused on brand extension evaluation in the online context. Its mention the difficulty of earning and maintaining customer loyalty for Internet companies where the cost of switching 27

between online services is extremely low, and thus online companies often face constant competition with numerous others companies which are just one click away.

H0 Online brand loyalty has a negative effect on consumer attitude towards the offline brand extension launched by online companies. H3 Online brand loyalty has a positive effect on consumer attitude towards the offline brand extension launched by online companies.

1.7.4 Perceived similarity Perceived similarity has been found to be a major determinant of brand extension evaluations. According to Gierl and Huettl, (2011), the rationale behind the effects of similarity on attitude towards extensions is explained by the application of the categorization theory to the brand extension domain. In this line, consumers compare their knowledge category related to the parent brand to the characteristics presented by the extension product and, if there is a sufficient level of similarity, this information about the brand, stored in consumers’ memories, is transferred to the extension product. Therefore, consumers evaluate more favourably those extensions that present a high degree of similarity or fit with the parent brand. This overall dimension of similarity leads to the following hypothesis:

H0: The overall perceived similarity between the online parent brand and the extension has a negative effect on consumer attitude toward the offline extension. H4: The overall perceived similarity between the online parent brand and the extension has a positive effect on consumer attitude toward the offline extension.

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1.7.5 Innovativeness Innovativeness is a personality trait related to an individual’s receptivity to new ideas and willingness to try new practices and brands.

The importance of innovativeness

has been examined extensively in the literature on diffusion of innovation and consumer behavior. In evaluating brand extensions, consumer innovativeness has been considered as an antecedent of positive consumer attitude towards extensions. The authors found consumer innovativeness as a moderating factor of similarity, stating that consumers with high degree of innovativeness do not base their extension evaluation on perceived similarity. H0: Consumers with a high degree of innovativeness will evaluate negatively offline brand extensions from Internet brands. H5: Consumers with a high degree of innovativeness will evaluate more positively offline brand extensions from Internet brands.

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1.8 The Hypothesized Model Following the procedures of the previous research the hypotheses proposed above are studied within a linear regression model, where the dependent variable, the attitude towards the extension, is explained by ten explicative factors that represent the independent variables of the regression. The linear regression model is as follows:

ATT = α + β1BK+ β2 PQ+ β3 BLO + β4 PS + β5 CIN+ ε

Where the dependable variable: ATT= Overall attitude towards the brand extension, and where the independent variables are: BK = Brand knowledge or familiarity PQ = Perceived quality of the parent brand BLO = Brand loyalty PS = Perceived similarity CIN = Consumer innovativeness α = Constant ε = Standard Error

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Hypothesis

Factors Consumer knowledge of the online brand, original product

H1

category and offline extension category has positive effects on the extension evaluation.

Higher quality perceptions toward the original online brand H2

are associated with more favourable attitudes toward the offline extension.

Online brand loyalty has a positive effect on consumer attitude H3

towards the offline brand extension launched by online companies.

The overall perceived similarity between the online parent H4

brand and the extension has a positive effect on consumer attitude toward the offline extension.

Consumers with a high degree of innovativeness will evaluate H5

more positively offline brand extensions from Internet brands.

Table No-4: Hypothesis and Factors

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Chapter-2: Literature Review

2.1 Overview 2.1.1 Brand Extension Definition The ever-changing market characteristics have huge impact on the corporate decisions. The Global environment also poses several complexities to the marketer in understanding the market.

The companies constantly innovate newer marketing

strategies to stay ahead in the market and reap more benefits for its stakeholders. More number of companies is relying on launching new products in the market to meet the changing consumer needs and preferences. This strategy is proven but not without risk. Some authors estimate that 30-35% of all new products fail. Others estimate more negatively in that only two out of ten products launched are successful in the market. Adding to the difficulty in accurately predicting the market dynamics, the promotion cost and shelf space cost to face the competition makes the company’s new product launches even more difficult and invariably lead to loosing the market. Companies are taking hard steps to reduce these failure rates. One way of dealing with the rate of failures of new products is using a firm’s competence. Many business organizations are leveraging their brand names to reduce the risk of failure of new products. A brand extension is the use of well-known brand names for new-product introductions. A Brand Extension means a firm uses an established brand name to introduce a new product. BE is an act in which the firm markets a new product category with an established brand name; it does so to increase and lever on its existing brand equity. The existing core brand equity helps to bypass the otherwise lengthy and expensive new product promotion. However, if the Brand Extension strategy is not thoughtfully done, it can bring in significant risks resulting in diluted brand image. In practical cases, the failures of BE are at higher rate than the successes.

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A good BE strategy is one where the brand name aids the extension, while a very good Brand Extension also enhances the brand name. 2.1.2 Brand Extension Strategies In the interests of understanding Brand Extension (BE), researchers have developed various theories about extension strategies. Brand breadths and category similarity interact to influence BE attitude. It has been concluded that when a parent brand is extended into related (similar) categories, consumers are likely to perceive the new specific extension more favorably than when the extension is into dissimilar categories. All investigations into the determinants of successful BEs initially assume that a brand is an accumulation of associations and that parent brand associations can influence consumer’s reactions to BEs. Brands with strong associations are more successful if they differentiate from competing brands and can be more easily extended into other product categories. The attributes, benefits and attitudes are the key elements in brand associations, of which brand attitude being the highest form. Brand attitude can be measured via BT and brand affect. Brand attitude is the highest level of brand association and frequently forms the basis of consumer behavior (e.g., brand choice). Hence, the study employed Brand Trust and Brand Affect as the key elements in evaluating consumers brand attitude and further evaluated these with Brand Loyalty and their effects on Brand Extension. Customer loyalty can be determined via BT and by Brand Affect. Strong Brand Trust influences product evaluation because of the low purchase risk perceived by a consumer. Consumers transfer parent BT to products when consumers trust a brand and perceive it as safe. They also perceive that purchasing that brand’s products as being without risk. A

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positive relationship exists between BT and acceptance of BE. As verified by several studies, consumer’s perceptions of a parent brand also have an impact on their feelings toward the brand product categories. The research on brand extensions has particularly emphasized the role of consistency, adaptability or relation between the two classes of product implicated in the brand extension process. The Tauber (1988) study concluded that the perceptive adaptation is a key element to predict the success of the brand extension. Also the analysis carried out at the Consumer Behavior Seminar (University of Minnesota, 1987) gave empirical support to the notion that the bigger the similarity perceived between the product of the original brand and that of the extension leads to a bigger transfer of positive aspects to the latter. According to Bridges (1991), the underlying idea is that individuals store memory for people, objects and concepts in summary chunks known as categories. When a new stimulus “fits” into an existing category, the individual first will tend to infer properties of the stimulus based on knowledge of the category and second can transfer affect associated with the category to new stimulus (i.e. the new product). This can be interpreted as a process of integration and assimilation, which is conditioned by the information the consumer, has about the brand. 2.1.3 Brand Extension Evaluations Ever since the first relevant article on customer evaluations of brand extensions was published by Boush et al. (1987), researchers have focused their researches on invetigating the antecedents, processes, and consequences of brand extension evaluation, as well as achieving a generalization of these factors across product categories and parent brands. Boush et al. (1987) identified perceived similarity and parent brand reputation as

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explicative factors of positive customer evaluations of extensions. They concluded that similarities between product categories, original product and extension, enable the transfer of positive affection to the new product. On the other hand, the study suggested that a brand's good reputation in one product area cannot be transferred in the same way to a dissimilar product category, since it would produce negative evaluations from consumers. Following the research line supported by Boush et al., (1987), Aaker and Keller's (1990) seminal article assessed not only the role of similarity between original and extension product classes but also proposed that customer's quality perceptions about the parent brand and the difficulty of producing the extension determined the consumer acceptance of brand extensions. Despite of the fact this article stated the base of subsequent research on brand extensions and it has been applied to different contexts such as services or online extensions, replications have emerged about the validity and generalization of its conclusions. Moreover, additional factors such as consumer innovativeness, familiarity or marketing support were subsequently tested in brand extension literature with mixed conclusions. Brand Extension Attitude Model (Boush et al., 1987; Sheinin and Schmitt, 1994; Herr and Cramer, 1996; and Bhat and Reddy, 2001)

Brand Loyalty(BL)

Brand Affect (BA)

Brand Extension(BE)

Brand Trust (BT)

Figure No-2: Brand Extension Attitude Model 36

2.1.4 Factors related to the parent brand Factors related to the parent brand Factor

Consumers evaluate positively the extension if…

Perceived quality

The perceived quality of the parent brand is high.

Brand associations

They transfer positive brand associations to the Extension.

Brand Loyalty

They are loyal to the parent brand.

Familiarity

The familiarity with the parent brand is high. Similarity

Product category similarity

There is congruence between product categories

Brand concept consistency

Parent brand and extension share the same image

The extension´s marketing context Marketing support

The extension receives appropriate marketing support.

Advertising

The extension is well supported in terms of advertising. Consumer characteristics

Innovativeness

They are highly innovative (early adopters)

Motivation

They have a high motivation for purchasing the Extension.

Involvement

There is an involvement in the brand extension Category.

Table No-5: Main Factors of Brand Extension Evaluation

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2.1.5 The Four P's of Google Inc. Google’s marketing plan can be broken down into the four P’s of marketing; product, price, promotion and place. Google has taken into consideration each one of these areas of marketing and used them as an advantage over their competitors. Product Product is one of the components of the 4P’s of marketing. A company or an individual must have product to market and to offer to the people. A product is define as anything that can be offered to a market for attention, use, or consumption, and that might satisfy a want or need. Google offers services as a form of it product to its customers. The products they offer fall into industrial products; Google’s business products offer services to their customers such as advertising and providing their search technology to solve companies’ search problems within their intranet. Also, they also sell tangible items along with its service or hybrid offers and also sell “pure” products. Google categorizes their products into three classes: Advertising solutions, Business Solutions, and the Google Store. In their Advertising solutions, they offer Google’s AdWords. Google offers text-based ads that are precise to the search on the site of the user and the customers pay Google every time internet search users click on their site. They help the customers to set up their site as the volume of visitors to the customer site’s increases. In their Business Solutions Google offers a Search Appliance to companies who need solutions to the search problems that their employees conducting within their computers by bringing in Google’s search technology and intranet to their clients. Google provides both the hardware and the software to the customers. Google has

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three models of the Search Appliance: the GB-1001 for departments and mid-sized companies, the GB-5005 for dedicated high-priority search services such as customer-facing websites and company-wide intranet applications, and the GB-8008 for centralized deployments supporting global business units. Lastly, The Google Store sells tangible items such as shirts, notebooks, bags, caps, lava lamps to almost anything that they can print their company’s name on. Price Price is another component of the four Ps of the market mix. Price is defined as “The amount of money charged for a product or service or the sum of the values that consumers exchange for the benefits of having or using the product or service”. It is extremely important for marketers to remember that individuals in a market are highly receptive not only to the price of an item, but also to the value offered by the product. Successful companies such as Google take special consideration at the different parts involved in setting its prices. Item such as list price, discounts, allowances, payment periods and credit terms are items that work together to set the price of its merchandise. List price is one of the fundamentals components of setting a price. List price is defined as, “Price normally quoted to potential buyers” . It is the basic price offered to prospective consumers, yet in many instances the price listed could increase or decrease as costumers select options. Google’s price for AdWords is set on the amount of advertisement per day it provides its consumers. In Google’s case the list price is at five cents per day, however it can go as high as $50.00 per day. The price difference will depend on the amount of advertisement per day that the consumers are

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willing to pay and the amount of times individuals click to see the ads and how high these ads rank on a search page. Discounts are another element of price setting. The three types of discounts are quantity, trade and cash. Quantity discounts are offered to consumers for buying in bulks or in large quantities. Trade discounts is defined as, “Payments to a channel member or buyer for performing marketing functions; also called a functional discount”. Last but not least are cash discounts offered to customers for the punctual payment of their invoices. At the moment Google AdWords is not offering consumers any of the discounts mentioned above. Another necessary item to set price is Allowances. Allowances are very similar to discounts because it also offers to lower the list price, yet it includes extra items not covered by discounts. Two major types are trade-in and promotional allowance. Trade-ins are commonly used in reducing the amount consumers must pay for a product by recognizing the value of a used product. Car Dealerships are a good example of companies that provide allowance to consumer based on trade-ins. Promotional allowance are, “Promotional funds provided by a manufacturer to other channel members in an attempt to integrate promotional strategy within the channel”. Fast food franchisers are organizations that provide promotional activities, such as television ads, to attract customers to its franchisees. Google at the moment is not providing its customers with discounts nor allowances in its Google AdWords program. Marketers promoting a product need to take into consideration payment period offered to its customers. There are different ways in which a company can set the length of time required to pay a bill. For instance organizations can set the time based on the requirements of its competitors. Google payment period is based on its relationship

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with its customers. New customers located in specific countries need to make their payments with a credit card or by direct debit payments. As soon as the finance department receives the financial information and it is approved, the ads begin to run, yet if a customer has a long and positive relationship with Google its financial department might be able to set a monthly account. This is based on the credit history of the customer. Last but not least, the credit terms required by an organization to finalize the product price. Google’s structure tightly relates payment periods with credit terms, yet each organizations credit terms vary depending on the type of industry. As mentioned earlier, Google provides a monthly credit limit for those customers with good financial record. The credit limit starts at $50.00 a month and it can increase to more than $500.00 a month. Promotion Promotions are activities such as advertising, personal selling, and sales promotion which communicate the merits of the product and persuade target customers to buy it . Time and time again Google has refused to jumble its homepage with annoying advertisements, banners, or links to other websites, as reported by Ben Elgin in a recent issue of BusinessWeek. Other companies have flourished mainly due to their colossal advertising campaigns. For years, Google has committed itself to focus on search and avoids fancy graphics. Co-founders Larry Page and Sergey Brin dislike the idea of ads affecting search results. Consequently, Google does not do a whole lot to get their name out to the public. Surprisingly, the company has grown by word of mouth, not by advertising. Google relies greatly on word of mouth to develop and expand their innovative brand. The more credible a brand is, the more widely its

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reputation will spread. Google, like Kleenex and Xerox, has become so pervasive that the brand name is used as an ordinary word. Google’s convenient service and precise search results have made it one of the world’s best-known brands and search engines almost completely through word of mouth from satisfied users. Despite emerging onto the scene later than others, Google has risen to outdo all of its competitors becoming what is now the most popular Internet search engine. Several people like the fact that Google offers a minimal homepage, which loads immediately without annoying advertisements. Lycos and AltaVista advertise heavily and load their homepage with flash. People seem to like Google more because of its simple and direct approach. As a result of Google’s outstanding results it has compelled its dedicated users to inform everyone else about their remarkable search engine. Google’s growth is proof of the power of viral marketing, without the need for massive advertising budgets. Place An important decision when trying to determine the overall competitive marketing strategy is place. Place includes company activities that make the product available to target consumers. Google’s place is the internet. When it comes to Google and trying to target their consumers, the people on the Internet, no one does it better. In the past three years, Google has gone from processing 100 million searches per day to over 200 million searches per day and only one-third comes from inside the U.S., the rest are in 88 other languages. VeriSign, which operates much of the Internet's infrastructure, was processing 600 million domain requests per day in early 2000. It's now processing nine billion per day. A domain request is anytime anyone types in .com or .net. Within the next few

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years users will be able to be both mobile and totally connected, thanks to the pending explosion of Wi-Fi, or wireless fidelity. Using radio technology, Wi-Fi will provide high-speed connection from your laptop computer or P.D.A. to the Internet from anywhere; McDonald's, the beach or your library. Google introduced the language limit in April 2000 with eleven languages, which was expanded as of Aug. 2000 to 24. As of July 2001, Russian was added. In Nov. 2001, Arabic and Turkish and then in early 2002 Catalan, Croatian, Indonesian, Serbian, Slovak, and Slovenian joined the group for the following 34 language limit options. These are available on the Advanced Search page and their Language Tools page. Google is one of about four search engines that have significant results. There are many more than four engines, but only about four have the technology to crawl much of the web on a regular basis. Google and Alltheweb do the best crawling. As of July 2003, Yahoo owned Overture, Alltheweb, AltaVista, and Inktomi, and finally dumped Google in February 2004. Everything needed to turn Yahoo into a major search engine and pay-for-inclusion ad agency, at a level that can compete with Google, is under Yahoo's roof. Early evidence suggests that Yahoo will shoot themselves in the foot with all of this firepower; their desire to monetize everything appears to be high on the agenda. Google, on the other hand, has been selling out only recently, and still shows some "pure search" residue from its early roots. Even Microsoft, which is busy developing its own engine, is currently squeezed between the advertising engine of Overture and the search engine Inktomi; both of which are Yahoo property. Microsoft might like to buy Google as a way out but Google is not for sale. Even if it were, there might be antitrust problems that prevent such an acquisition.

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Just as Microsoft was late to recognize the importance of the Internet, they are once again unprepared to take on Yahoo and Google. In 2003 Microsoft began experimenting with their own crawler at a very low level. Good search engines need many months of practice before they can crawl the web effectively, and order the results so that searchers perceive them to be relevant. Some observers doubt that Microsoft has the coordination to achieve through in-house technical development, what they cannot achieve through acquisition and market manipulation. Even though they have announced that they are pouring resources into search engine development, this time it will take more than talk. The last search engine worth watching is Teoma/AskJeeves. Their search technology is good, and they seem serious about expanding their crawl. It remains to be seen how deeply and consistently they will be able to crawl websites with thousands of pages. Google is easily top dog. They provide about 75 percent of the external referrals for most websites and if you count Google's partners as part of the mix (particularly Yahoo and AOL), this figure is closer to 85 percent. There is no point in putting up a website apart from Google. It's do or die with Google.

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2.2 Literature Review Brand extensions represent an important growth strategy for companies facing a fierce competence within the marketplace. The use of an already existing brand when launching new products into the market increases the likelihood of success because consumers perceive a lower risk in their purchasing process and transfer positive consumer associations to the new product. Therefore, the way in which consumers evaluate the new extensions and the determinants involved in this process will determine the success or fail of brand extensions and, consequently, the image of the parent brand may be reinforced or harmed. In order to investigate how consumers evaluate brand extensions, scholars have proposed numerous explicative factors of consumer’s attitude towards the new products and they have applied them to different types of products, companies and markets. Following this idea, this chapter reviews the existing literature regarding consumer evaluation of brand extensions. 2.2.1 Bravo Rafael, E. Hem Leif (2012) explained the expansion of an online brand towards an offline product category through brand extensions and alliances. Specifically, the paper focuses on analyzing the effects on the online brand image as a consequence of this expansion, and it analyses them under different conditions of image and fit. An empirical study was conducted to 407 undergraduates in a Spanish University, and data are analyzed through multivariate analysis of variance. From the research “From Online to Offline Through Brand Extensions and Alliances” results can be summarized as the effects of extensions and alliances are mainly negative on the online brand image, the impact is focused specially on the functional and emotional dimensions of brand image, the effect is more negative for online

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brands with high image than for online brands with low image, and the effect is more negative in the case of an alliance with an offline brand with low image than in the case of an alliance with an offline brand with high image or in a brand extension.

2.2.2 Joji Alex N (2011) looked into product line Brand Extension attitude among users of brands of Maruti 800 and Dove soap. The study also examined the importance of Brand Affect, Brand Trust and Brand Loyalty in the parent brand, while consumers consider product line Brand Extension. The research question asked was: Does brand loyalty have an impact on product line Brand Extension attitude in highly competitive markets with plenty of fairly close substitutes? The respondents were just above neutral about their idea of brand loyalty, which indicated that a positive brand trust has led to a positive product line Brand Extension attitude. They were not likely to be loyal to the brands of Maruti or Dove in their next product purchase or upgradation. From the research "Consumer Evaluations of Product Line Brand Extension” the marketers were of the opinion that high brand equity will attract loyalty to their brands but for the customer, the cost of switching was lower and he/she also wished to try comparable substitutes. Even though Brand Trust exists, customers would have like to try different products belonging to comparable brands, hence loyalty may not have enhanced extension attitude.

2.2.3 Alam M. S, Faruq, Sharmin (Dec. 2010) research study is focused on low involvement products and opinion of consumers on extension of product. A very well known brand (PRAN brand Juice) its extension was chosen for this study. The study “Evaluation of Brand Extension (Similar and Distance Product Category) with respect to degree of fit and quality of core Brand” found that consumers perception

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was similarity between core and extension is successful if there is a good fit between core and the extension products. On the other hand a quality core product is not the guarantee to successful brand extension to a product category which is not similar to the core brand (distance brand extension). This product is limited only to one brand and limited to students. So more successful brand extension and diverse consumer categories are considered for future research is suggested.

2.2.4 Hakkyun K., Deborah R. J. (Jan. 2008) proposed the importance of perceived fit in extension evaluations was moderated by construal level. Researcher drew upon construal level theory, which posited that individuals can construe stimuli in their environments in terms of abstract and generalized features (high-level construals) or in terms of concrete and contextualized features (low-level construals). Results from the study “Consumer response to brand extensions: Construal level as a moderator of the importance of perceived fit” confirmed that consumers who construed their environment at a higher level place more importance on perceived extension fit in evaluating brand extensions. These consumers evaluated high fit extensions more favorably than moderate fit extensions, consistent with prior research. However, consumers who construed their environment at a lower level do not evaluate high and moderate fit extensions any differently, unless the importance of using fit perceptions is made salient.

2.2.5 UZTUG Ferruh (2008) focused on brand extension strategies in automotive industry. Automotive industry had very different character than fast moving consumer goods. Automotive industry used extension strategies for segmentation of vehicles. For that reason in this paper, segmentation and line extension were described and

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perception from automotive industry had shown. The comparisons of Turkish and global markets were used. The extension had different types in automotive. There were several types of extension; Commercial and Heavy Duty Vehicles, Industrial Engines, Clothing and Gifts were some of the type of brand extension strategies in automotive industry. However this research focused on brand extension in passenger vehicles market. The study "Segmentation and Brand Extension in Automobile Industry: Turkish vs Global" found that automotive companies which started business from upper segments were willing to extend their products lines in global markets. They did not differentiate their extension policy in different markets. As the brand had strong roots in business it did not hesitate to extend its brand both in product line and brand extension. However other brands which started business from lower segments had drawback in different markets. They had different strategies for different market in order to sustain high sales performance.

2.2.6 Busacca, Bruno (2008) examined the impact of brand relationship quality and naming strategies on the success of brand extension through research based on an experimental 2x2x2 design. The independent variables taken into consideration were: the perceived fit between the products categories involved in the decision to expand; the name chosen for the new product (predominance of the parent brand vs. sub-brand); the level of brand relationship quality (high vs. low). The dependent variable object of analysis was the consumer's evaluation of the expansion. The results of the study "Consumer evaluations of brand extension: The impact of brand relationship quality and naming strategy" showed that in the presence of high brand relationship quality, the consumers value extension more favourably, no matter what the level of category fit. However, in situations of high (low) category fit and

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high brand relationship quality, the evaluation of the extension was better if the predominance of the parent-brand (sub brand) was greater in the naming of the new product. If the brand relationship quality was low, the consumer's evaluation was not influenced by the naming strategies.

2.2.7 Thamaraiselvan N., Sivaram A. (2006) studied primarily focuses on how consumers evaluated brand extensions for FMCG (Fast Moving Consumer Goods) and service product categories in Indian market conditions. It explored how exactly the consumers evaluate different product categories based on factors like, similarity fit, perceived quality, brand reputation and perceived risk. It brought out the impact of brand reputation of the core brand and perceived service quality on the brand extensions evaluations. It highlighted the role of perceived risk involved in the extended product category in brand extensions evaluations. Most importantly, this study established the relationships among similarity fit, brand reputation, perceived service quality and perceived risk in extended product categories through appropriate multivariate analysis and this study strengthens the assumption that the service quality would enhance the reputation of the brand. The study "How do consumers evaluate brand extension: - Research findings from India." looked into the features of perceived risk and its impact on the brand extensions evaluations in the future studies. This study also paved the way for researchers to do a similar kind of brand extensions studies for the different categories of service sectors.

2.2.8 Van Riel, Allard C. R. (2005) investigated newly introduced service categories on a portal site as e-service brand extensions. Electronic services were preliminarily distinguished from traditional services, and factors are identified that enhance

49

consumer evaluations of e-service extensions. Findings confirmed the fundamentally sound structure of the Aaker and Keller brand extension model for electronic services. Only a limited number of studied have investigated the explicative factors of brand extension success in the online context. The study on "Extending electronic portals with new services: exploring the usefulness of brand extension models." introduced the first study on brand extension applied to online services. It categorized online services in four groups depended on the origin of the company (online or physical) and the type of product that provided (tangible goods and traditional services or virtual products). Van Riel and Ouwersloot, (2005) tested the model proposed by Aaker and Keller, (1990) for each of the aforementioned types of e-service providers, mentioned in the grid. They found that the variables of similarity, perceived quality and difficulty of produced the extension help explain consumer attitude towards online services extensions. Therefore, they concluded that consumers perceive online extensions in a similar way to other product categories. Despite these affirmations, the authors maintained that online services are subject to a more complex evaluation mechanism than offline goods or services.

2.2.9 Hansen Havard, Hem Leif E. (2004) investigated the effects of characteristics in the extension category. The purpose of this research was to explore the effects of different characteristics of the extension category on the evaluation of brand extensions. Based on the literature, it was suggested that at least five types of category characteristics influence the evaluation of brand extensions: (a) bundling, (b) price consciousness, (c) affective commitment, (d) involvement, and (e) perceived knowledge of the extension category. It was also hypothesized as in past research that similarity had a positive effect on brand extension evaluations. Data from a survey

50

involve an established car brand extended to a service product-category was used to test the relationships. The results of the study "Brand Extension Evaluations: Effects of Affective Commitment, Involvement, Price Consciousness and Preference for Bundling in the Extension Category " - Advances in Consumer suggested that affective commitment towards the incumbent brand in the extension category was negatively related to the intention to purchase the extension, and involvement with the entry category increased purchase intention. Furthermore, price consciousness had a positive effect on preference for product bundling, while similarity and preference for bundling positively influences the intention to buy a brand extension. The results underscored the importance of extension category characteristics for consumer evaluation of extensions.

2.2.10

Leon

Phang

(September

2004)

research

examined

whether

business-to-business brands can leverage their brands in the consumer market through brand extensions and link theory from consumer branding to corporate branding. For evaluating brand extensions hypotheses are tested by regression analysis on the basis of brand knowledge, attitude towards parent brand, innovativeness, brand association, perceived difficulty and perceptions of environmental concern. A new model was developed by combining Aaker and Keller’s brand extension model with theories from business-to-business branding as well as other consumer branding concepts, and tested quantitatively to understand how consumer evaluate brand extensions. The results of the study "Consumer Evaluations of Brand Extensions: Can B2B Brands be Extended into the Consumer Market?" indicated that in the context of business-to-business brand extensions, consumers used the transferability of skills and resources, and brand concept consistency with the parent brand category as major

51

cues to evaluated extensions. Innovativeness and corporate social responsibility were also relevant cues. As a consequence of these findings, branding strategies that stretch business-to-business brands into the domain of consumer markets can be successful in cases where consumers perceive a fit with respect to skills and resources, and brand concept, and when the parent brand was perceived as being innovative and socially responsible.

2.2.11 Jarlhem Manthana, Mihailescu Raluca (2003) intended to find consumers perception of the parent brand and the extended brand’s personalities. The research findings of the study "The study of consumer perception of the parent brand and its extended brand personality - A case study” underlined an important point which was that although consumers were the ones judged the brand and its extensions in terms of expectations, perceptions and attitudes, it still was essential for the brand managers to permanently managed the consumer’s brand knowledge structures by strengthening the brand, strategy which would not only allow future growth possibilities but also a shield against failed brand extensions. However, in the present environment, the consumer’s brand relationship with the brands was eroding due to an explosion of offers on the market. Strengthening a brand and permanently looking for ways to achieve growth has never been more demanding.

2.2.12 Iversen Nina M., Leif E.Hem (September2001) explored the impact of category similarity, brand reputation, perceived risk and consumer innovativeness on the success of brand extensions in FMCG, durable goods and services sectors. A set of hypotheses on the basis of perceived similarity, reputation, perceived risk and innovativeness were developed and tested by multivariate analysis technique in a 52

study amongst 701 consumers. The findings of the study “Factors influencing successful brand extensions” showed that extensions into categories more similar to the original brand tend to be more readily accepted. Likewise, the reputation of the original brand was an important factor influencing the success of the extension. These findings were consistent across FMCG, durable goods and services brands. However, perceived risk about the extension category was only found to enhance acceptability of extensions for durable goods and services brands. Innovative consumers were more positively disposed towards service brand extensions than FMCG and durable goods brand extensions.

2.2.13 Aaker, D. A. and Keller, K. L. (1990) conducted to obtain insights on how consumers form attitudes toward brand extensions, (i.e., use of an established brand name to enter a new product category). In one study of "Consumer evaluations of brand extensions", reactions to 20 brand extension concepts involved six well-known brand names were examined. Attitude toward the extension was higher when there was both a perception of "fit" between the two product classes along one of three dimensions and a perception of high quality for the original brand or the extension was not regarded as too easy to make. A second study examined the effectiveness of different positioning strategies for extensions. The experimental findings showed that potentially negative associations can be neutralized more effectively by elaborating on the attributes of the brand extension than by reminding consumers of the positive associations with the original brand.

2.2.14 SERRA Elisabete study of extension had based on a quasi-experimental methodology; this study identified the factors able to influence the perception of a 53

brand extension as well as to isolate the processes on which the evaluation of the brand extension was based on. This research work also explained the limits that the evaluation of new products imposes on the brand extension strategy, and those situations in which the introduction of brand extensions strengthen or weaken consumer's beliefs towards the established brand. For the purpose of evaluating brand extensions four brands i.e. Swatch, Rolex, Reebok and Adidas have taken and hypotheses have been tasted on the basis of innovativeness and brand image. The findings of the study “Brand Extensions : Evaluation and Reciprocal Effects” showed that when the individuals recognize that there exists consistency between the new product and the original product, based on innovativeness, its evaluation of the extension is more positive then when no consistency exists between these product categories and When the consumers recognize consistency between the beliefs associated to the new product and those contained in the original brand, its evaluation of the extension is more positive.

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Chapter-3: Data Presentation & Analysis

Brief Overview: Data presentation is a critical portion of making proposals, reports and other essential demonstrations during the course of daily meetings and important presentations. Most presentations are either visual in nature or rely on strong visual elements for clarity and information conveyance. Data presentation methods vary depending on the form the data taken within the presentation. When using graphs to display information, including items that list what each axis of the graph is meant to represent aids the audience in immediate understanding, and does not require the speaker to field constant questions about the basic message of the graph. On the other hand, data presentation is the process of evaluating data using analytical and logical reasoning to examine each component of the data provided. This form of analysis is just one of the many steps that must be completed when conducting a research experiment. Data from various sources is gathered, reviewed, and then analyzed to form some sort of finding or conclusion. There are a variety of specific data analysis method, some of which include data mining, text analytics, business intelligence, and data visualizations. This chapter “Data Representation and Analysis” has been divided in two parts, the first one is data presentation which contains an analysis and presentation of the demographic variables of the individuals from whom data was collected and the second part of this chapter is concerned with the relationship among the variables are discussed by means of correlation analysis. Then, a regression analysis is provided for an aggregated model, with the aim of testing the proposed hypotheses. Afterwards, regression results are discussed.

56

3.1 Demographic Features Demographic features incorporate four major aspects namely Gender, Age, Qualification and Profession, which are discussed below one by one: 3.1.1 Demographic features: Gender

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

1.00

65

65.0

65.0

65.0

2.00

35

35.0

35.0

100.0

Total

100

100.0

100.0

Table No-6: Percentage of Gender in Respondents

Figure No-3: Pie Chart of Percentage of Gender Respondent Profile (Gender): A total of 100 respondents were sampled which varied in age between 18 to 55+ years old, 65% were male and 35% were female in Table 6. (1= male and 2 = female). 57

3.1.2 Demographic features: Age

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

1.00

62

62.0

62.0

62.0

2.00

30

30.0

30.0

92.0

3.00

4

4.0

4.0

96.0

4.00

4

4.0

4.0

100.0

100

100.0

100.0

Total

Table No-7: Percentage Age Group

Figure No-4: Pie Chart of Percentage Age Group Respondent Profile (Age): In our survey most of the people (62%) were from 18-24 age groups, 30% were from 25-34 age groups, 4% were from both 35-45 and 45-55 age groups and no one was from 55+ age groups. (Table No-7) That means our demographic of people were very young. (1 indicates 18-24, 2 indicate 25-34, 3 indicate 35-45, 4 indicate 45-55 and 5 indicate 55+). 58

3.1.3 Demographic features: Qualification

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

1.00

12

12.0

12.0

12.0

2.00

37

37.0

37.0

49.0

3.00

51

51.0

51.0

100.0

Total

100

100.0

100.0

Table No-8: Qualification of Respondents

Figure No-5: Pie Chart of Qualified Respondents Respondent Profile (Qualification): In terms of level of education, the most important groups were Postgraduate school 51% and Graduate 37% from table no. 8 (1= Undergraduate, 2= Graduate, 3= Post Graduate/PhD, 4= Any Other).

59

3.1.4 Demographic features: Profession

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

1.00

60

60.0

60.0

60.0

2.00

25

25.0

25.0

85.0

3.00

8

8.0

8.0

93.0

4.00

6

6.0

6.0

99.0

5.00

1

1.0

1.0

100.0

100

100.0

100.0

Total

Table No-9: Percentage of Profession Respondents

Figure No-6: Pie Chart of Profession Respondents Respondent Profile (Professions): In terms of profession of people, most of the groups were students 60% and full time employed 25% from table 9. (1= student, 2= Full time employed, 3= Part time employed, 4= Self employed, 5= unemployed, 6= others).

60

3.2 Correlation Analysis A Correlation Analysis identifies how variables in the conceptual model relate to each other. The below given table is a Correlation Analysis table which has been used to analyze the relationship between some important variables of Brand extension.

Correlations ATT ATT

Pearson Correlation

CIN

PS

BLO

PQ

BK

1

Sig. (2-tailed) N CIN

PS

BLO

PQ

BK

Pearson Correlation

100 .227*

1

Sig. (2-tailed)

.023

N

100

100

.756**

.472**

Sig. (2-tailed)

.000

.000

N

100

100

100

Pearson Correlation

.150

.426**

.109

Sig. (2-tailed)

.137

.000

.279

N

100

100

100

100

.264**

.326**

.213*

.529**

Sig. (2-tailed)

.008

.001

.033

.000

N

100

100

100

100

100

.201*

.171

.406**

.015

.369**

Sig. (2-tailed)

.045

.089

.000

.881

.000

N

100

100

100

100

100

Pearson Correlation

Pearson Correlation

Pearson Correlation

1

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

Table No-10: Correlations 61

1

1

1

100

Interpretation: The correlation coefficients which are shown in Table No-10 (Appendix 2) prove that all variables have a positive relationship to attitude towards the extension except brand loyalty, particular Perceived Similarity i.e. PS

(0.756),

Consumer

Innovativeness i.e. CIN (0.227), Perceived Quality i.e. PQ (0.264) and Brand Knowledge i.e. BK (0.201). Brand Loyalty whose Pearson Correlation is 0.150 and significance level (p) is 0.137 (which is greater than 0.05), which means brand loyalty is not significantly correlated with attitude towards extension of Google Inc. Furthermore, a strong relationship is shown in the case of Consumer innovativeness and perceived similarity (0.472**). On the other hand, Brand loyalty is also strongly related to perceived quality (0.529**) which supports the idea that perceive quality and trust in the online brand help increase consumer e-loyalty and there is very weak relationship of Brand Knowledge to Attitude towards extension of Google Inc. It also shows that Brand Knowledge is not very significantly related to Brand Extension and it will not impact on Extension of Google Inc. This study also shows that there is no relationship between Brand Loyalty and Brand Knowledge, because there significance level is 0.881, which is greater than 0.05. Furthermore there is also no relationship between Brand Knowledge and Consumer Innovativeness because there significance level is greater than 0.05 and Brand Loyalty (BL) and Perceived Similarity (PS). Analysis: The analysis above reflects that consumer evaluate brand extension on factors like Consumer Innovativeness, Perceived Similarity, Perceived Quality and Brand Knowledge. Because these factors highly influence consumers when they consider online brand extension. On the other hand Brand Loyalty is not correlated with Attitude towards extension, because consumers are not brand loyal at all. 62

3.3 Regression Analysis The study employed regression analysis in order to test the followings hypotheses: H1: Consumer knowledge of the online brand, original product category and offline extension category has positive effects on the extension evaluation. H2 Higher quality perceptions toward the original online brand are associated with more favourable attitudes toward the offline extension. H3 Online brand loyalty has a positive effect on consumer attitude towards the offline brand extension launched by online companies. H4: The overall perceived similarity between the online parent brand and the extension has a positive effect on consumer attitude toward the offline extension. H5: Consumers with a high degree of innovativeness will evaluate more positively offline brand extensions from Internet brands. 3.3.1 Variables Entered in regression Analysis Variables Entered/Removeda Mode

Variables

Variables

l

Entered

Removed

1

BK, BLO,

Method

.

PS, CIN, PQb a. Dependent Variable: ATT b. All requested variables entered.

Table No-11: Variables

63

Enter

The Table No- 11 simply provides a list of the variables used in the calculation. The entry, removal, and method columns apply to certain automatic model fitting procedures. This table clearly shows Dependent Variables i.e. ATT and Independent Variables i.e. BK, BLO, PS, CIN and PQ. 3.3.2 Regression Model Summary

Mode

R

R Square

l 1

.806a

.649

Adjusted R

Std. Error of

Square

the Estimate

.630

1.36291

a. Predictors: (Constant), BK, BLO, PS, CIN, PQ Table No-12: Regression Model Summary Analysis: R Square provides an indication of the explanatory power of the regression model. RSquare is simply the percentage of variance in the dependent variable explained by the collection of independent variables. In this case, it’s about 64.9%. Regression was also conducted at a brand level in order to assess the effects of the independent variables on attitude towards extension when different types of online brands are involved. The proposed model explains 65% of the attitude towards the extension for Google. Interpretation: Higher dependability reflected from the analysis can be interpreted in the way that prediction of attitude towards extension on independent variables. This clearly indicates that brand loyalty, brand knowledge, perceived quality, perceived similarity and consumer innovativeness has a greater impact on attitude towards extension.

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3.3.3 Anova

Model

1

Sum of Squares

Df

Mean Square

Regression

322.752

5

64.550

Residual

174.608

94

1.858

Total

497.360

99

F 34.751

Sig. .000b

a. Dependent Variable: ATT b. Predictors: (Constant), BK, BLO, PS, CIN, PQ

Table No-13: ANOVAa

Analysis: The term “Sig.’ in SPSS refers to a significance test, which is another way of saying “Statistical hypothesis test”. In other words, numbers in columns labelled “Sig.” are p-values and therefore given the results of a hypothesis test. In this case, the p-values refer to a test of the entire model (i.e. the entire collections of independent variables) as a whole. If the p value is greater than 0.05 then accept the null that none of the independents predict the dependent. This means that the model is a bust and we should go no further. In this study the computed F-statistic is 34.751 for regression, which are significant at p=0.000 (Table No-13). Interpretation: From the above analysis it can be reflects that the study is feasible enough because the significance level (p) is less than 0.05 and some of the independents predicts the dependent. It can be due to high reliability of the questionnaire which is greater than 0.7.

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3.3.4 Coefficients Coefficientsa Model

Unstandardized Coefficients

Standardized

T

Sig.

Coefficients B 1

(Constant)

Std. Error

-1.323

1.998

CIN

-.291

.087

PS

1.138

BLO

Beta -.662

.509

-.257

-3.342

.001

.094

.908

12.093

.000

.110

.145

.060

.763

.447

PQ

.300

.123

.194

2.434

.017

BK

-.343

.127

-.196

-2.696

.008

a. Dependent Variable: ATT

Table No-14: Cofficientsa Analysis: These are regression coefficients. While we do not count the “Constant” among the independent variables, we do not count its coefficient as part of the regression equation estimated in this output. The coefficient for the constant is the value for the Y-intercept, b0. These values are used to calculate the possible attitude towards the extension. In our study significance level of Brand Loyalty (0.447) is greater than 0.05 (Table No-14), which means Brand Loyalty is not at all supported for evaluating attitude towards extensions for Google Inc. On the other hand Brand Knowledge and Consumer Innovativeness are also not supported for extension evaluation for Google Inc, because of negative values.

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Interpretation: From the above analysis it can be interpreted that, Consumer Innovativeness, Brand Loyalty and Brand Knowledge is not supported because consumers are not brand loyal to products of Google Inc, and there is no need of brand awareness & brand knowledge while consider brand extension of offline products. Moreover consumers are not innovative enough to buy new products with new features and they never associate offline extension to the parent brand. Which means first hypothesis i.e. H1 (Brand knowledge), third hypothesis i.e. H3 (Brand Loyalty), and fifth hypothesis i.e. H5 (Consumer Innovativeness) are rejected and null hypothesis is accepted. On the other hand Perceived Quality and Perceived Similarity are an important factor while evaluating brand extension because consumers perceive similar products and quality of existing products so, there hypotheses H2 and H4 are significant and supported while evaluating brand extension. The equation form this output is: ATT= -1.323 - (0.291×INN) + (1.138×PS) + (0.110×BL) + (0.300×PQ) – (0.343× BKN) +2.205

3.3 Hypotheses Testing

Hypothesis

Variable

Google Inc.

H1

BK

Not Supported

H2

PQ

Supported

H3

BLO

Not Supported

H4

PS

Supported

H5

CIN

Not Supported

Table No-15: Review of Hypotheses 67

In above equation Brand Knowledge (BK), Brand Loyalty (BLO) and Consumer Innovativeness (CIN) have no significant on attitude towards extension (ATT) of Google Inc, bbecause significance level of Brand Loyalty is 0.447 and the value of CIN and BK is in negative. On the other hand only 2 variables Perceived Quality (PQ) and Perceived Similarity (PS) have significant on attitude towards extension of Google Inc, because significance level of both are less than 0.05 and values are in positive. 3.4.1 Brand Knowledge The beta coefficient related to brand knowledge (BK) appear to be no significant at any level of significance (p>0.1) and negative (0.196), therefore the first hypothesis (H1) is rejected. Thus, consumer knowledge of the online brand, original product category and offline extension category has negative effect on the extension evaluation. 3.4.2 Perceived Quality From the regression analysis Perceived Quality (PQ) appears to be significant at any level, because the value of beta coefficient is in positive i.e. 0.908 and significance level is less than 0.05. So, hypothesis H2 is accepted towards brand extension of Google Inc, and perceived quality is an important variable while evaluating Brand extension of Google Inc. Thus, higher quality perceptions toward the original online brand and associated with more favourable attitudes towards the offline extensions. 3.4.3 Brand Loyalty From the regression analysis brand loyalty (BLO) is found no significant at any level p>0.1 for Google Inc which is 0.447, and H3 is therefore rejected. So, Brand Loyalty 68

has no any significance while evaluating brand extension of Google Inc. Thus, online brand loyalty has a negative effect on consumer attitude towards the offline brand extension launched by online companies.

3.4.4 Perceived Similarity From the regression analysis Perceived Similarity (PS) appears to be significant at any level, because the value of beta coefficient is in positive i.e. 0.194 and significance level is 0.017 which is less than 0.05. So, hypothesis H4 is accepted towards brand extension of Google Inc, and perceived similarity is also an important variable while evaluating Brand extension of Google Inc. Thus, the overall perceived similarity between the online parent brand and the extension has a positive effect on consumer attitude towards the offline extensions. 3.4.5 Consumer Innovativeness Beta coefficient related to Consumer Innovativeness (CIN) also appear to be no significant whose negative value is 0.257, therefore the fifth hypothesis (H5) is also rejected. So consumer innovativeness is not an important factor while evaluating brand extension of Google Inc. Thus, consumers with a high degree of innovativeness will evaluate negatively offline brand extensions from internet brands.

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Chapter-4: Summary & Conclusions

A total of 100 respondents were sampled which varied in age between 18 to 55+ years old, most of the population were male. In terms of level of education, the most important groups were postgraduate school. In the light of the results presented in the regressions and correlations analysis, certain findings can be drawn:  Brand knowledge, perceived similarity, perceived quality and consumer innovativeness are strongly correlated with the attitude towards extension. On the other hand brand loyalty is an unrelated variable.  The value of R-square i.e. regression is quite high which shows that there is greater impact on dependent variable (ATT).  From the significance level of Anova it can be found out that there is relevance of variables (Brand Knowledge, Perceived Similarity, Brand Loyalty, Perceived Quality and Consumer Innovativeness) within the model.  Brand knowledge does not present a significant effect on attitude towards the extension. So, consumers may perceive these extensions as typical or unrealistic.  The result shows that there is a significance of perceived quality (PQ) on attitude towards the extension when an online brand is extended to offline products. Therefore, the impact of perceived quality is its strength.  There is no significance of brand loyalty within the model over attitude towards extension.  The study showed that perceived similarity is considered significant within the 71

model. Thus importance of overall similarity within the model is in line with previous studies which considered it as the most important predicting factor of attitude towards extensions.  Based on results of the analysis it can be said that Product similarity is a significant determinant of brand extension success for Google. This explains that consumers evaluate more favourably those offline extensions which present complementarily with the product of the parent brand and use the same competences.  Consumer Innovativeness (CIN) does not present a significant effect on attitude towards the extension.

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4.1 Conclusion The marketers spent a lot of time and energy in creatively positioning brand extensions to overcome high risks associated with new product launch. The importance of brands is not only measured in terms of the competitive advantages that they provide in their present markets but also the future opportunities that they provide in untapped markets. This way, firms can enter new markets by using an existing, well-known brand name in order to reduce both the cost of launching new products and the risk of product failure. The study attempts to provide a better understanding of the factors that influence consumer’s evaluations of brand extensions in the context of online brands and, in particular, when these extensions are launched away from the Internet limits towards offline markets. The findings of this study suggested that the launching of offline brand extensions by online companies is indeed possible. More specifically, this study showed that consumers employ brand personality and perceptions of quality rather than brand loyalty and brand knowledge in order to evaluate the new offline extensions. Furthermore, this study seems to follow the line of previous research by supporting the role of product similarity as predictor of brand extension success. On the other hand, perceived similarity by the parent brand to the offline extension creates more positive consumer attitudes towards the extension as it is demonstrated in this study. In nutshell, the success of online brands extensions will depend on the positive brand personality, perceived quality and perceived similarity to build a strong and positive brand.

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4.2 Limitations The methodology that has been employed might have a few limitations.  The study examined one brand which is Google, which is one of the categories of e-portals online brands. However some other categories like that of e-tailers, e-sellers and company portal were not studied.  In this study only two offline extensions i.e. Android and Google Nexus were investigated for company. Apart from that the study only focused on five factors or variables which affect the brand extension evaluation by consumers but there are many more factors which affect the evaluation of brand extension.  The study only assessed the direct relationships between the determinants of brand extension success and consumer attitude toward the extension.  The study consists in a cross-sectional analysis of the collected data. However, the utilized variables were not statics.  This study may not fully capture consumer’s attitudes toward the extension across time.  The sample size is very small due to limited available time.  Number of male respondents were more than the female respondents this may affect the interpretation of the results.

74

4.3 Scope for further Study This study presents several ways in which it can be extended. Possible interactions between explicative variables may help improve the understanding of consumer’s evaluations of the extensions. In this way, variables such as brand loyalty or brand knowledge that appeared to be not significant within the model may play an important role when they interact with other explicative variables. More specifically, it would be interesting to investigate the interaction effects between brand loyalty and brand knowledge. Therefore, further research should investigate the existence of relationships between the proposed determinants of brand extension success. As already mentioned, this study only examined one brand categories of online brands of Google Inc. (e-portals) which stops results from being generalized. Therefore, further research should extend this research to the study of a broader number of companies in each category in order to generalize the findings to other e-portals.

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Chapter-5: Recommendations

Based on the researcher’s experience, limitations and analysis of the study, some recommendations can be laid down for the company while launching offline products into the market: Based on findings from analysis:  The company should consider brand knowledge, perceived quality, brand loyalty, perceived similarity and consumer innovativeness when they go for extension of their brand because these factors have a very strong relationship among them. 

The managers of online brands should decide the right kind of product that is to be extended as there is a significant role of product similarity on consumer’s evaluations of the extensions.

 Google should give attractive offers and discounts for increasing brand awareness and brand loyalty on the products and start loyalty program for the consumers who repurchase their products. 

The company should focus on making quality products as it has a big role in developing attitude of customers.

Based on experience while conducting the study:  The study considers only a few factors like brand knowledge, perceived similarity, brand loyalty, perceived quality and consumer innovativeness. Other factors like brand association, consumer involvement, market support and brand value can also be considered while going for extension.  Company should associate their product with the brand image of the company.

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Google Inc never launched its offline product, like Google Nexus from its own manufacturing house. As such it is difficult for the consumers to associate brand with the product.  Company should always launch its offline products with its brand name, which will give a strong brand association and product similarity for the consumers.

 The new products of Google must have perceived similarity to the current products. For this purpose, managers should select offline extensions which enable Internet access and can be used together with the products of the brand.

 The study shows that perceived quality and perceived similarity are the important factors when a company goes for extension. So, the company should focus on these two factors whenever they go for extensions.  For brand loyalty company should go for wider and further study. Because brand loyalty has a significant role in brand extension.  For brand awareness Google should launch and advertise their offline products

to tap a larger share of the Indian market. This would help the consumers to easily identify their offline products.

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Mihailescu, Raluca, Järlhem, Manthana (2004), “The study of consumer perception of the parent brand and its extended brand personality a case study”

Decision Support

Systems, vol. 49, no. 1, pp. 91-99. Song P., Zhang C., Xu Y., & Huang L. (2008), "Brand extension of online technology products: Evidence from search engine to virtual communities and online news", Decision Support Systems, vol. 49, no. 1, pp. 91-99. Thamaraiselvan N. (April 2008), “How Do Consumers Evaluate Brand Extensions Research Findings From India” Journal of Services Research, Vol. 8 Nbr. 1.

Van Riel A. & Ouwersloot H. (2005), “Extending Electronic Portals with New Services: Exploring the Usefulness of Brand Extension Models”, Journal of Retailing and Consumer Services, vol.12, no. 3, pp. 245-254.

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http://en.wikipedia.org/wiki/Brand_extension [Last accessed as on Monday, 04th February 2013] http://www.mba-tutorials.com/strategy/307-top-vision-statements.html [Last accessed as on Monday, 04th February 2013] http://www.managementstudyguide.com/brand-extension.htm [Last accessed on as Thursday, 07th February 2013] http://static1.businessinsider.com/image/4e4ab3ca6bb3f7092f00002e-590-568/google -timeline.jpg [Last accessed as on Friday, 22th February 2013] http://en.wikipedia.org/wiki/List_of_Google_productsen.wikipedia.org/wiki/Online_a dvertising. [Last accessed as on Wednesday, 27th February 2013] http://www.hoovers.com/industry-facts.telecommunications-equipment-manufacturin g.1565.html. [Last accessed as on Monday, 11th March 2013] http://en.wikipedia.org/wiki/Mobile_operating_system [Last accessed s on Sunday, 17th March 2013] http://www.brandchannel.com/papers_review.asp?sp_id=1222 [Last accessed as on Tuesday, 2nd April 2013]

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82

Appendix

Appendix 1: Reliability Analysis Case Processing Summary N Valid

% 100

100.0

0

.0

100

100.0

a

Cases

Excluded Total

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

Reliability Statistics Cronbach's

N of Items

Alpha .726

6

Appendix 2: Correlations Correlations ATT Pearson Correlation ATT

BL

BKN

BKN

.023

.000

.137

.008

.045

100

100

100

100

100

1

**

**

**

.171

Sig. (2-tailed)

.023

N

100

100

**

**

.756

PQ

.150

*

*

BL **

.227

.227

.472

.756

.472

.426

.264

.326

**

.001

.089

100

100

100

100

.109

.213

*

.279

.033

.000

100

100

100

1

**

.015

.000

.881 100

1

.000

N

100

100

Pearson Correlation

.150

**

.109

Sig. (2-tailed)

.137

.000

.279

N

100

100

100

100

100

**

**

*

**

1

.264

.326

*

.000

.000

.426

.201

.000

Sig. (2-tailed)

Pearson Correlation PQ

100

PS

Pearson Correlation

Pearson Correlation PS

1

Sig. (2-tailed) N

INN

INN

100

.213

.529

Sig. (2-tailed)

.008

.001

.033

.000

N

100

.529

.406

.369

**

**

.000

100

100

100

100

100

Pearson Correlation

.201

*

.171

**

.015

**

1

Sig. (2-tailed)

.045

.089

.000

.881

.000

N

100

100

100

100

100

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

84

.406

.369

100

Appendix 3: Frequencies

Statistics ATT

Valid

INN

PS

BL

PQ

BKN

100

100

100

100

100

100

0

0

0

0

0

0

10.9200

10.6000

13.0100

12.3300

12.1200

13.0200

.22414

.19797

.17894

.12231

.14514

.12790

2.24139

1.97969

1.78939

1.22314

1.45144

1.27905

5.024

3.919

3.202

1.496

2.107

1.636

Range

8.00

8.00

7.00

5.00

5.00

4.00

Minimum

6.00

7.00

9.00

10.00

10.00

11.00

Maximum

14.00

15.00

16.00

15.00

15.00

15.00

1092.00

1060.00

1301.00

1233.00

1212.00

1302.00

N Missing Mean Std. Error of Mean Std. Deviation Variance

Sum

Appendix 4: Word Count

85

Appendix 5: Excel Sheet 1

2

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4

4

4

5

5

5

4

3

4

4

4

3

5

5

5

4

4

3

4

4

3

5

5

5

4

4

5

4

4

4

3

4

4

3

4

4

3

4

4

4

4

3

4

4

3

5

5

5

4

4

5

1 0 1 2 1 2 1 1 1 1 1 1 1 1 1 5 1 3 1 2 1 1 1 2 1 2 1 5 1 1 1 1 1 5 1 1 1 1 1 5 1 3 1 2 1 1 1 1 1 1 1 1 1 1 1 5 1 3

3

3

4

4

5

5

4

4

4

4

4

4

3

5

5

5

3

4

3

4

5

4

4

4

4

4

5

4

4

3

4

4

4

4

4

4

4

4

5

5

4

4

4

3

4

4

4

3

5

5

5

5

3

4

3

4

5

4

4

4

4

4

5

4

4

3

4

4

4

4

4

4

3

5

5

4

3

4

3

4

5

4

4

4

4

4

5

1 0 1 4 1 2 1 2 1 3 1 2 1 2 1 2 1 3 1 1 1 2 1 2 1 3 1 3 1 1 1 1 1 5 1 2 1 2 1 2 1 3 1 1 1 2 1 2 1 3 1 1 1 2 1 2 1 3

3

4

3

3

4

4

3

3

3

3

3

3

2

2

3

4

2

2

3

2

4

3

3

4

2

3

3

3

3

4

3

3

3

4

4

4

4

4

4

3

4

4

2

3

4

3

3

2

4

4

2

3

3

3

2

4

4

4

4

4

2

3

3

2

3

3

4

4

4

3

3

4

2

3

3

3

3

4

3

3

3

4

4

4

4

4

4

3

4

4

4

3

2

2

3

4

2

2

3

2

4

3

3

4

2

3

3

3

3

4

3

3

3

4

4

4

88

1 3 1 4 1 2 1 1

4

3

4

11

2

3

4

9

4

4

4

12

4

4

4

12

3

4

3

10

4

4

4

12

4

3

4

11

3

3

3

9

9 1 4 1 1 1 3 1 5 1 5 1 3 1 2 1 3 1 2 1 6 1 0 1 4 1 4 1 1 1 3 1 5 1 5 1 5 1 1

3

1

3

7

4

3

2

9

4

2

3

9

4

4

4

12

4

3

2

9

2

2

2

6

2

2

4

8

4

4

4

12

4

5

4

13

5

4

4

13

4

4

3

11

4

4

5

13

3

3

3

9

4

5

4

13

3

5

4

12

4

3

4

11

3

4

4

11

5

4

5

14

4

3

4

11

4

4

3

11

4

3

4

11

5

4

4

13

4

3

3

10

3

2

2

7

5

5

5

15

3

3

4

10

4

2

3

9

4

4

4

12

4

3

2

9

2

2

2

6

2

2

4

8

4

4

4

12

4

5

4

13

5

4

4

13

4

4

3

11

4

4

5

13

3

3

3

9

4

5

4

13

4

3

4

11

3

3

3

9

9 1 4 1 1 1 3 1 5

3

1

3

7

4

3

2

9

4

2

3

9

4

4

4

12

4

3

2

9

2

2

2

6

2

2

4

8

4

4

4

12

4

5

4

13

5

4

4

13

Annexure

QUESTIONNAIRE

As a part of MBA program a survey is conducting on variables affecting brand extension evaluation for the respondents who have used Google online services and are aware of their offline products extension.

Name: ____________________ Gender: Age:

a) Male 18-24

Qualification:

b) Female 25-34

35-45

45-55

Undergraduate

Graduate

Post Graduate/Ph.D.

Profession: Student Self employed

55+

Specify, if any other __________

Full time employed

Part time employed

Unemployed

Others

Consider the following brand:

For the next several questions, please choose a number from 1-5 to each statement to indicate how much you agree with that statement. Non Familiar……….Very Familiar

Preference Statements 1. Are you familiar to the brand Google?

1

2. Are you familiar with the products offered by Google? 90

2

3

4

5

Strongly Disagree…Strongly Agree

Preference Statements 3. Google offers very good quality products.

1

2

3

4

5

4. Google offers products of consistent quality. 5. Google offers products with excellent features. 6. I use frequently Google products or services. Strongly Disagree…Strongly Agree

Preference Statements 7. It makes sense use Google's products or services instead of other competing companies, even if they are the same. 8. Even if other company has the same features as Google's products or services, I would prefer use Google. 9. I would definitely recommend Google to friends, neighbours and relatives.

1

2

3

4

5

Consider the following extension: a) Google Smartphone

b) Smartphone's and Tablet's Software

Not Very Similar……....Highly Similar

Preference Statements 10. Think of Google. How similar is the typical usage situation of Google's products with the usage of mobile phones? 11. Think of Google. How similar is Google compared with mobile phones regarding image? 12. Think of Google. How similar is the competence required to produce Google products and mobile phones? 91

1

2

3

4

5

Strongly Disagree……..Strongly Agree

Preference Statements 13. There is complementarily of Google's products and services and mobile phones. 14. Overall, I enjoy buying the latest products. 15. I like to purchase the latest products before others do. 16. Overall, it is exciting to buy the latest products. 17. Overall, I am very positive to Google mobile phone. 18. I am likely to try Google smartphone. 19. Overall evaluation of Google smartphone relative to existing brands in mobile phones category.

92

1

2

3

4

5