User Perception of Targeted Ads in Online Social Networks

Table of Contents

List of Figures

List of Tables

1 Introduction
1.1 Background and Importance of the Topic
1.2 Problem Statement and Disposition of This Paper

2 Social Media
2.1 Social Networks - Real vs. Virtual Networks
2.2 Online Social Networks
2.3 Typology of Online Social Networks
2.4 Profile Visibility and Information Disclosure
2.5 Privacy and Data Security in Online Social Networks
2.6 Facebook

3 Online Advertising
3.1 Types of Online Advertising
3.1.2 Targeted vs. Non-Targeted Online Advertising
3.1.2.1 Behavioural Targeting
3.1.2.2 Social Targeting
3.2 Social Media Marketing
3.2.1 Features of Social Media Marketing
3.3 Advertising on Online Social Networks
3.3.1 User Perception of Targeted Ads in Social Networks

4 Recapitulation

5 Empirical Study
5.1. Methodology
5.1.1 Data Collection
5.1.2 Survey Structure
5.1.3 Organisation, Execution, and Sample Group
5.1.4 Data Analysis
5.2 Survey Results
5.2.1 Socio-Demographic Factors
5.2.2 Internet and Online Social Network Usage
5.2.3 Privacy and Data Security
5.2.4 Advertising

6 Discussion of Results
6.1 Privacy and Data Security (Hypotheses 1 & 2)
6.2 User Perception of Advertising on Facebook
6.2.1 Hypotheses 3 & 4
6.2.2 Hypotheses 5 & 6
6.2.3 Hypothesis 7

7 Conclusion and Future Work

Reference List

Appendices
Appendix A – Glossary of Terms
Appendix B – Features of Online Social Networks
Appendix C – Facebook
Appendix D – Expert Interview Prof. Dr. Klemens Skibicki
Appendix E – Expert Interview Dr. Stefan Lachenmeier
Appendix F – Survey Structure
Appendix G – Survey

List of Figures

Figure 1: Comparison of social media vs. Web 2.0, screenshot Google trends 27.06.2010

Figure 2: Social network typology (adapted from Markus, 2002:3)

Figure 3: US social network growth (adapted from AdChap, 2009)

Figure 4: Demographic distribution of German Facebook users July 2010 (adapted from Roth, 2010a)

Figure 5: Official Coca Cola fanpage, screenshot Facebook 26.08.10

Figure 6: Targeted ad on Facebook (adapted from Facebook, 2010b)

Figure 7: Factors impacting on user perception of targeted ads on social networks (own illustration)

Figure 8: Gender distribution (own illustration)

Figure 9: Age distribution (own illustration)

Figure 10: Current occupation (own illustration)

Figure 11: Time spent online (own illustration)

Figure 12: Time since opening of Facebook account (own illustration)

Figure 13: Other social network usage (own illustration)

Figure 14: Number of logins to Facebook (own illustration)

Figure 15: Time spent on Facebook per day (own illustration)

Figure 16: Profile visibility (own illustration)

Figure 17: Information that is tracked for targeting purposes (own illustration)

Figure 18: Attitude toward tracking (own illustration)

Figure 19: Leaving Facebook because of privacy concerns (own illustration)

Figure 20: Trust in Facebook (own illustration)

Figure 21: Potential reasons for ad blindness (own illustration)

Figure 22: Frequency of ad clicks (own illustration)

Figure 23: User perception of Facebook advertising (own illustration)

Figure 24: User perception of targeted ads (own illustration)

Figure 25: Influence on ad delivery (own illustration)

Figure 26: Willingness to pay usage fee (own illustration)

List of Tables

Table 1: Traditional media vs. social media (adapted from Farley, 2010: 26)

Table 2: Traditional marketing vs. social media marketing (adapted from Kabani, 2010: 34)

Table 3: Age distribution (own illustration)

Table 4: Willingness to pay usage fee (own illustration)

Table 5: Summary of survey results (own illustration)

1 Introduction

1.1 Background and Importance of the Topic

In 2010, 221 million people in the US will be online, about 71% of the population. Their numbers will continue to grow, reaching two hundred and fifty million in 2014 (Philipps, 2010). The story is consistent across the world: More than thirty-nine million UK residents used the Internet in 2009. By 2013, nearly forty-four million will be online - over 70% of the total population (Von Abrams, 2009). Today’s young people are growing up with the Internet, and the Internet is growing up with them. It is evolving: Web 2.0, user-generated content, and social media are the buzzwords of the current evolutionary phase of the Internet. The Web is no longer about corporations telling users what to do, think, or buy; it is about the content people create themselves. Participation, not publishing, is the keyword (O’Reilly, 2005).

The rise of social networking sites such as Facebook, which is currently by far the world’s largest online social network with over five hundred million users, has been nothing short of phenomenal. eMarketer estimates that 58% of all Internet users will visit a social network at least once a month in 2010, and the sector will account for over 10% of all Internet time. Social media has overtaken email as the most popular consumer activity, according to a recent Nielsen study (Nielsen, 2010). Ninety-five percent of teens and tweens across the globe report their participation in social networks. Adults, however, will be driving most of the growth in the next few years. By 2014, 139.6 million US adults will be regular users, up 56% over 2009 (Williamson, 2010a).

Even though users, not companies, are the leading actors in today’s Web, online social networks are becoming increasingly interesting to advertisers. Many businesses are beginning to notice the potential for reaching out to their target audiences through this new medium. It is assumed that due to the high level of personal information disclosure in online social networks, advertising on such networks enables companies to reach users with relevant adverts and to target individual consumers with personalised messages in their private environment (Kelly et al., 2008; Skibicki, 2010). Already, more than one-half of marketers are engaging with some form of social media, and $3.3 billion will be spent on social network advertising worldwide in 2010, according to eMarketer’s forecasts. A majority of that will be allotted to Facebook. However, the landscape surrounding the use of these tools is still nebulous. Given the intense interest, the big question is: Are marketers doing it right? (Nielsen 2010; Williamson, 2010b).

There is considerable academic research into Internet advertising (Grant, 2005; Namiranian, 2006; Rappaport, 2007). However, owing to the rapid growth of social networking sites in recent years, there is very limited academic research published in the area of social networks as an advertising medium (Boyd & Ellison, 2007). Many questions regarding this topic are still unanswered. The reason for that lies in the fact that the popularity of online social networks and their recognition as an advertising medium have grown so fast that the research studies were not able to follow (Bearne, 2009; Hadija, 2007).

While many experts highlight the benefits of modern targeting technologies for both consumers and advertisers (Skibicki, 2010; Mughal, 2010), some researchers and interest groups caution against the tracking of personal information for ad targeting purposes on social networks (Hoy & Milne, 2010; Tijdink, 2010). Apart from this debate, previous research studies in the area of user perception of targeted online advertising do not yield a clear picture. Some studies have revealed a positive attitude towards ad targeting (McEleny, 2009), while other researchers have concluded that most people still object to this process, mostly on privacy grounds, resulting in advertising avoidance (Kelly, et al., 2008; Bearne, 2009).

Privacy and data security are definitely important issues. When Facebook launched its “Beacon” advertising system in November 2007, allowing it to broadcast what users bought on external sites and to target ads based on this information, the resulting consumer backlash was immense. In September 2009, a class-action suit against Facebook resulted in the program being shut down. This, plus the recent strategic marriage of Google and Double-Click, the Google Streetview data scandal, and Microsoft’s advertising deal with Yahoo have brought the issue of online privacy to the fore (Perez, 2009; Drischerl, 2010).

1.2 Problem Statement and Disposition of This Paper

Despite the impressive rise of Facebook and the growing popularity of online social networks as advertising media, very little is known about how users perceive targeted advertisements on the world’s most popular network. In theoretical terms, advertising on Facebook should enable marketers to reach users with relevant ads and to target individual consumers with personalised messages. Such targeting is supposed to increase the value of advertising for both users and advertisers: users see ads that are interesting to them and advertisers maximise their return on investment. However, there is no empirical evidence for this assertion and it is not known if social network advertising really generates the promised results for marketers.

Due to the lack of research in this area, this thesis aims to investigate user perception of targeted ads on online social networks using the example of Facebook. More specifically, based on a critical literature review, previous research studies, and expert interviews with social media practitioners, the key issues that may impact on user perception will be identified and compiled in a conceptual framework. Moreover, corresponding research hypotheses will be developed and, thereafter, a survey among Facebook users will be conducted to validate the framework. The results of the empirical study are supposed to provide insights into user perception of Facebook advertising that may serve as a guideline for network operators and advertisers as well as a basis for further studies in this important area of research.

The next chapter of this thesis, part two, will be devoted to social media and online social networks; after defining the terms, the different applications of social media will be presented. Then, online social networks, a typology of networks, their major features, and privacy issues will be discussed. At the end of the chapter, Facebook as the leading social network will be introduced.

The third part is concerned with online advertising; after defining the relevant terms, a typology of online advertising will be presented. Then, the concept of ad targeting will be discussed in detail. This leads the discussion to social media marketing and, more specifically, to advertising in online social networks. At the end of part three, expert opinions and results of previous empirical studies on user perception of targeted ads on social networks will be presented.

In part four, the author will summarise the conclusions from the literature review and the expert interviews. Based on that, a conceptual framework of factors that might influence user perception of targeted ads on Facebook and corresponding research hypotheses will be proposed.

Part five is dedicated to the empirical study – a survey among Facebook users. After outlining the research purpose and the methodology of the study, the survey results will be presented.

The sixth part is concerned with the analysis and interpretation of the survey results against the background of the literature review and the research hypotheses.

In part seven, conclusions that summarise the main findings of this thesis will be presented. Moreover, the author will give suggestions for further research.

2 Social Media

The term social media is relatively new; there is a lot of debate about its origin, and there is no widely accepted definition in the literature. It can be seen in Google Trends (Figure1) that people started using this term in 2007^[1]. Today, it is even more popular than the buzzword Web 2.0^[2], which peaked in 2007.

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Figure 1: Comparison of social media vs. Web 2.0, screenshot Google trends 27.06.2010

Evans (2008: 33) defines social media as follows:

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Similarly, according to the Interactive Advertising Bureau (IAB), the defining feature of social media is its participatory element where an individual not only receives information but also has the ability to take part in the creation and distribution of content. Before the proliferation of social media, the primary way for users to receive advertiser information was one-way, but social media has changed the paradigm of how people consume online media (IAB, 2008). Kaplan and Haenlein also highlight the importance of user participation, which seems to be one of the defining features of social media across the literature. Kaplan and Haenlein (2010: 60) define social media as follows:

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Farley (2010) states that social media is very different from what we consider traditional media, such as TV or print. He describes the characteristics of each media type as follows:

Abbildung in dieser Leseprobe nicht enthalten Table 1: Traditional media vs. social media (adapted from Farley, 2010: 26)

The current social media landscape can be broken down into three distinct categories (IAB, 2008; Hass et al., 2008):

- Social media sites (online social networks/online communities)^[3],
- Blogs^[4],
- and widgets and social media applications^[5].

Social media sites or online social networks as the major applications of what is defined as social media will be discussed in more detail in the coming chapters.

2.1 Social Networks - Real vs. Virtual Networks

Every human being is part of some form of society, community such as a school, family, or religious group. The sociologist Thiedeke (2003) states that participation in communities or networks is a natural desire of humanity, as it creates a feeling of support, acceptance, and belonging; this notion is well accepted among sociologists. In most cases, “real” groups only exist for a limited time, as they have to be sustained by intermittent face-to-face contact (Brunold et al., 2000; Thiedeke). The Internet, however, enables users to communicate with virtually anybody at any time. Users can connect to a much larger group of people without geographical boundaries (Brunold et al.).

The Web promotes the establishment of so-called weak ties. In sociological terminology, relationships can be classified into those with strong ties and those with weak ties. The former term describes relationships that are characterised by strong emotional support and close interactions, whereas the latter describes relationships that are less intense (Graef, 1997). Technological advancements and the rise of social media applications enable Internet users to build, foster, and maintain a large network of relationships (Jones & Soltren, 2005). Online social networking sites not only allow individuals to meet strangers, but they also enable users to articulate and make visible their social networks. This may result in connections between individuals that would not otherwise have been made (Haythornthwaite, 2005).

In the next chapter, online social networks will be discussed in more depth.

2.2 Online Social Networks

With the advent of popular Web destinations such as Facebook, online social networks now occupy center stage in the online world (Bausch & Han, 2006). These sites are increasingly attracting the attention of academic and industry researchers intrigued by their affordances and reach (Boyd & Ellison, 2007). eMarketer estimates that social networks will account for over 10% of all Internet time in 2010. By 2014, nearly two-thirds of all Internet users will be regular users of social networks (Williamson, 2010a).

Due to the strong multidisciplinary interest that this topic inspires, most existing definitions reflect a disciplinary perspective. Sociologists focus on networks of social relations and characteristics such as group size (Wellman, 1997). Technology-oriented definitions distinguish between different developing and supporting software of online communities (Mercer, 2006; Seufert et al., 2002). Commercial-oriented definitions are mainly concerned with the business or revenue model (Preece, 2003). Therefore, finding a suitable definition of online communities that everyone can agree with is a difficult task.

Boyd and Ellison (2007) define social networking sites as follows:

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The definition of Boyd and Ellison focuses on two crucial features of online social networks: profiles and connections^[6]. It neglects, however, other aspects that are of importance. In 2000, Jennifer Preece developed a working definition of online communities, which is still widely accepted today. It is broad enough to apply to a range of different networking sites and embraces key components of definitions put forth in previous literature. According to Preece, the following elements are common to all online social networks (2000: 10):

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People or members develop new ideas, continually change content, are central to any online community, and make it unique (Preece, 2000; Döring, 1999; Hagel & Armstrong, 1997). A common and clearly defined purpose is crucial for an online community to retain existing members and attract new ones (Preece, 2000; Abras et al., 2003). Further, an online community needs certain rules or policies that direct and improve community life and the interactions between members (Freyermuth, 2002; Kim, 2000). In computer-meditated communication, the underlying software or user-interface is a crucial prerequisite for the other aspects and should support all facets of community life (Dumas & Redish, 1999; Preece et al., 2001).

In the next chapter, a typology of online social networks will be introduced.

2.3 Typology of Online Social Networks

As with the definition of online social networks, there is no single, widely accepted typology of these networks due to the high diversity of dimensions used to categorise them. Researchers often typify online social networks based on one or a few variables that are of importance to their scientific discipline. Furthermore, differentiation and classification becomes more and more difficult as the number and complexity of online communities steadily increases (Porter, 2004).

Brunold et al. (2000) distinguish between three different motives to join an online social network; they use those motives to characterise the online community type: (1) information exchange, (2) common activities, and (3) buying and selling. Furthermore, they introduce seven special forms of online networks, which cannot solely be described with one of the above motives to join, such as instant messaging systems (e.g., ICQ, MSN), virtual realities (e.g., SecondLife), or gaming communities (e.g., Gamefriends.com)^[7].

Markus (2002) suggests another approach for classifying virtual communities. His scheme has recently gained in importance, and many researchers make use of it (Porter, 2004). At the top level of the structure, a distinction is made between social, professional, and commercial online networks. These types can be broken down further. Markus states that social communities “(…) are the original community type from which all other community types have evolved.” Most online communities that exist today belong to the social category (Markus: 3). Figure 2 gives an overview of Markus’ typology, including some examples.

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Figure 2: Social network typology (adapted from Markus, 2002:3)

Although the classification scheme of Markus is widely accepted, no existing approach is all embracing, as new online communities that cannot be categorised unambiguously and do not clearly fit into a scheme are born every day (Porter, 2004)^[8].

Facebook could best be described as a community with a social orientation. It is not instrumental, however, to try to put Facebook in either one of the sub-categories of communities with a social orientation, as it encompasses aspects of both sub-categories (e.g., hobby/common interest (Facebook groups), game (Facebook gaming apps), and communication (Facebook chat and private messaging)). Moreover, Facebook encompasses features of communities with a professional orientation (special Facebook groups, learning apps) and commercial orientation (company fan pages).

Online social networks can be very different in their composition and often integrate various features, leading to a high level of complexity. Their backbone consists of visible profiles that display an articulated list of connections (friends or contacts) who are also users of the system. Due to the limited scope of this thesis, a detailed description of online social network features can be found in Appendix B.

In the next chapter, social network profiles will be examined in more detail with a focus on profile visibility and information disclosure. This leads the discussion to general privacy and data security concerns with regard to online communities.

2.4 Profile Visibility and Information Disclosure

The visibility of a profile varies by site and according to user discretion. On Facebook, for example, information that users share with everyone, their name, profile picture, gender, and networks can be seen by anyone on the Internet, regardless of users’ privacy settings (Facebook, 2010d). In their large study of privacy in online social networks, Acquisiti and Gross (2006) found that though most Facebook users are aware of their profile visibility, a sizeable portion is not (n=4000).

Recent studies document the extent to which users reveal personal information on their social network profiles. The research suggests a high level of personal information disclosure, including real names, images that enable identification of the person, birth dates, hometowns, and other sensitive information. About 90% of users admitted that they have shared such personal information online. These studies also reveal the factors that influence information disclosure (Tufekci, 2008; Kolek & Saunders, 2008):

- the perceived benefits of selectively revealing information to strangers outweighing the costs of potential privacy invasion,
- the influence of peer pressure and herding behaviour,
- a casual attitude regarding personal privacy,
- ignorance about the possible implications of information disclosure,
- trust in the participants and host site,
- and required acceptance of the site’s default privacy settings

In analysing trust on social network sites, Dwyer et al. (2007) claim that trust and usage goals may affect what people are willing to share. Facebook users, for example, expressed greater trust in Facebook than MySpace users did in MySpace and thus were more willing to share information.

The above findings are of importance, as privacy awareness and trust may also impact on user perception of ads on social networks, which will be investigated in the empirical part of this thesis. In the next chapter, privacy and data security will be discussed in more depth.

2.5 Privacy and Data Security in Online Social Networks

According to Acquisiti and Gross (2006), there is often a disconnect between people’s desire to protect privacy and their behaviours, the so-called “privacy paradox” that occurs when users are not aware of the public nature of the Internet. Acquisiti and Gross analysed four thousand Facebook profiles and outlined the potential threats to privacy contained in the personal information included on the site, such as the potential ability to reconstruct users’ social security numbers using information often found in profiles, such as hometown and date of birth.

In a study examining privacy issues in online social networks, Jagatic et al. (2007) used freely accessible profile data from online communities to create a phishing scheme that appeared to originate from a friend on the network. Their targets were much more likely to give away information to this friend than to a stranger. Recent surveys offer a more optimistic perspective on privacy, suggesting that young people are aware of potential privacy threats online and that many are proactive about taking steps to minimise potential risks. Lenhart and Madden (2007), for example, found that 55% of online teens have profiles in online networks, 66% of whom report that their profile is not visible to all Internet users. Forty-six percent of teens with completely open profiles included at least some false information (Lenhart & Madden).

According to Jones and Soltren (2005), privacy on Facebook is undermined by three principal factors: users disclose too much, Facebook does not take adequate steps to protect user privacy, and third parties (such as advertisers) are actively seeking out end-user information. Rapp et al. (2009) argue that even when consumers recognise that some portion of their personal data is publicly available, few fully understand the widespread access and use by marketers.

Many things have changed since the study of Jones and Soltren in 2005; however, their main conclusions are still up-to-date. Most Facebook offerings have expanded access to user information and generated privacy concerns. For example, Facebook is using opt-out mechanisms for its privacy settings instead of opting-in^[9] (eMarketer, 2010). Moreover, in their study of one hundred and fifty popular Facebook applications, Felt and Evans (2008) found that more than 90% of apps access personal information that is unnecessary to deliver the app. Another concern is Facebook “Connect,” which allows members to use a single Facebook sign-in to access other sites. When members use this single sign-in, the visited Website gets one-day access to the user’s profile information (Hoy & Milne, 2010). In February 2009, Facebook created another controversy by changing its terms of service without prior announcement. The major cause of concern was the clause that stated that Facebook retained the license to the information, including the ability to use, retain, and display posted content (Hoy & Milne). Privacy issues also occur when users attempt to control impressions and manage social contexts. Boyd (2006) asserts that Facebook’s introduction of the newsfeed feature disrupted users’ sense of control, even though data exposed through the feed were previously accessible.

To summarise this chapter, privacy and data security are very important issues. Although research shows that a sizeable portion of users is unaware of or not interested in the accessibility of their data, social networks such as Facebook repeatedly make the headlines when it comes to privacy online. User attitudes towards privacy are also a major concern with regard to targeted advertising on Facebook, which will be examined in the empirical study in Chapter 5. In the next chapter, Facebook as a company will be introduced.

2.6 Facebook

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Facebook is the world’s most popular online social network – it surpassed MySpace in terms of active users in January 2009 (Kazeniac, 2009). Facebook can be divided into five main parts: (1) profiles, (2) groups, (3) pages, (4) events, and (5) apps^[10] (Boyd & Ellison, 2007; Zarrella, 2010). Groups and pages are especially interesting with regard to social media marketing, which will be discussed in Chapter 3.2.1.

Some of the impressive statistics of Facebook include the following (Facebook, 2010a; Roth, 2010a):

- there are more than five hundred million active users, with a growth rate in the US of 3.8% per month over the last year,
- 50% of active users log on to Facebook on any given day,
- an average user spends one hour on Facebook every day,
- an average user has one hundred and thirty friends,
- there are over nine hundred million objects that people interact with (pages, groups, and events),
- an average user is connected to eighty pages, groups, and events,
- an average user creates ninety pieces of content each month,

Today, Facebook is by far the largest and fastest growing online social network in terms of members, unique visitors, active users, and most other key indicators. Figure 3 shows the year-to-year growth in unique visitors of the leading social networks in the US.

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Figure 3: US social network growth (adapted from AdChap, 2009)

The demographic distribution of Facebook users is another interesting area to examine. While the majority of users belong to the 25-34 age group, the fastest growing group is 54+. From July 2009 to July 2010, the 54+ group grew by 19.3%; the 25-34 group grew by only 2.4% in the same time (Roth, 2010a). Figure 4 displays the demographic distribution of Facebook users in Germany in July 2010.

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Figure 4: Demographic distribution of German Facebook users July 2010 (adapted from Roth, 2010a)

A detailed outline of Facebook’s company history can be found in Appendix C. The next part of this thesis is concerned with online advertising and, in particular, advertising on social networks.

3 Online Advertising

Online advertising (also known as digital or Internet advertising) can be defined as “(…) the delivery of advertising messages and marketing communications through the Web” (Papadopoulos, 2009 : 1). It has presented sustainable revenue growth since its inception in the mid-90s: eMarketer estimates that US online advertising spending will reach $25.1 billion in 2010, representing 10.8% growth over last year. This growth is mainly driven by the ongoing shift of marketing dollars away from traditional media toward the Internet (eMarketer, 2009). The UK has become the first major economy where advertisers spend more on online advertising than on television advertising, with a record £1.75 billion spent online in the first six months of 2009. The Internet now accounts for 23.5% of all advertising money spent in the UK, while TV ad spend accounts for 21.9% of marketing budgets (Sweney, 2010).

In examining social media and how to use them for marketing purposes, it is important to realise that Internet advertising is still relatively young, having begun in 1994. Moreover, for much of the first decade of its existence, failure was more common than success. Ill-fated attempts to apply principles from other media led to online advertising formats such as pop-up ads or banner ads^[11], which contributed to these early failures (Taylor, 2009).

Over the last six years, multiple factors have, however, contributed to the Internet achieving the status of a major medium for advertising. First, a very large portion of the population has access to the Internet as compared to earlier periods (Smalla, 2008). In June 2009, approximately 1.67 billion people worldwide used the Internet, as compared to 0.69 billion in 2003 – and there is no end in sight to this upward trend (Internetworldstats, 2010). Today, the Internet is a mass medium, and we can observe a habitualisation of Internet usage: users spend up to 118 minutes per day online (Smalla). Second, technological advancements such as the advent of broadband allow for more effective use of the Internet and rich media content, allowing more options for advertisers. Third, by 2005, advertisers realised the unique potential of search engines as an advertising medium. By this time, advertisers as well as search engine companies such as Google understood how consumers searched for information online and noticed an immense opportunity for behavioural targeting^[12] by matching ads to searches. Subsequently, online advertising grows at faster rates than other media, and new forms of Internet advertising such as social media marketing have also begun to grow (Taylor, 2009).

In the next chapter, different types of online advertising and mechanisms to deliver ads (targeting) will be introduced.

3.1 Types of Online Advertising

Many different types of Internet advertising can be found online. Due to a lack of agreed standards, there is no widely accepted terminology or typology of online advertising formats (Smalla, 2008).

According to Matin (2007), Internet advertising can simply be categorised as display-based and search-based advertising. The difference between the two is described as the pattern in which the ads appear. Display-based ads present a mixture of old media technology, banner ads, and new rich media, while search-based adverts are displayed based on search engine queries.

Goldhammer and Fölsch (2002) took a different approach and divided online advertising into three categories. Their typology is not supposed to be exhaustive; they focus on the most common formats. They differentiate between (1) standard formats, (2) advanced formats, (3) interactive formats, and (4) special formats. Examples of the different formats can be found in Table 2.

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Table 2: Formats of Internet advertising (adapted from Goldhammer & Fölsch, 2002: 284)

Banners are the oldest and most common advertising format on the Internet; banners are graphics that are shown on Websites, separated from the actual content, which communicate the advertising message. Pop-ups and interstitials, on the other hand, can be described as more disruptive, as they require the user to see (and close) the ad before the content of the Website can be viewed. Nano- and microsites enable the user to interact with the ad – this format is relatively new and growing in popularity. Special formats include all other formats such as keyword advertising on search engines^[13] (Goldhammer & Fölsch, 2002).

With regard to the delivery mechanism, online advertising can be categorised as targeted or non-targeted advertising. There is debate among researchers and practitioners about the benefits and drawbacks of targeting (Smalla, 2008). In the following chapter, some of those aspects will be discussed.

3.1.2 Targeted vs. Non-Targeted Online Advertising

The number of advertisements and the magnitude of information that consumers see every day are immense; this flood may lead to information overload or advertising avoidance. Hermes (2007) found that most consumers try to avoid traditional, non-targeted advertisements. Seventy percent of respondents try to opt-out of such advertisement by switching TV channels. A similar development can be observed on the Internet: Adtech (2007) found that the average click-through-rates for banner ads decreased from 0.33% in 2004 to 0.18% in 2007. This phenomenon is often described as “banner-blindness” in the literature. Some researchers believe that the habitualisation of Internet usage makes users focus on the content that is relevant to them while ignoring everything else (Alby, 2008). The involvement of users becomes more likely if ads are targeted to the information that is known about the recipient (Hamm, 2000; Goldhammer & Fölsch, 2002). In a survey of eighty-three media experts, 88% of respondents saw the main benefit of targeting methods in its cost-efficiency. Moreover, the experts believe that targeting will be one of the most important aspects of media planning in the forthcoming years (InteractiveMedia, 2006).

Targeting can be defined as “(…) a means of planning, which is based on user data, in order to deliver personalised ads to a predefined group of users with the goal to increase relevance and minimise waste circulation” (Smalla, 2008: 46). Targeting is supposed to increase the value of advertising for both users and advertisers: users see ads that are relevant to them, and advertisers achieve a better ROI (Skibicki, 2010; Mughal, 2010). Because advertising is not free and consumers are heterogeneous in their responses to it, advertisers strive to focus their efforts on a subset of the great multitude of consumers, suggesting that an enhanced ability to target ads may be highly valuable. This may be especially true for niche firms that otherwise find themselves locked out of traditional marketing channels, unable to reach their target groups efficiently. The idea that improved targeting is especially important to niche firms is often referred to as the “long tail of the Internet” (Johnson, 2009).

In theory, there are a variety of different targeting methods. In practice, however, a combination of different targeting methods is often used (Smalla, 2008). The most important methods include technical targeting, geographic or regional targeting, keyword or contextual targeting, socio-demographic targeting, behavioural targeting, and social targeting.

Behavioural and social targeting are of particular importance for this paper and will be discussed in more detail in the following two chapters. Definitions of the remaining targeting methods can be found in Appendix A.

3.1.2.1 Behavioural Targeting

Behavioural targeting is an outcome of behavioural tracking of consumers’ activities online. It is not a new concept, but the Internet has made it easier to do because of its ability to track users’ movements. Behavioural targeting involves tracking Web searches, Websites visited, and the content viewed in order to tailor pages, offers, and prices and to deliver relevant advertising targeted to the individual customer’s interests. These activities typically take place without users’ awareness, and critics argue that behavioural targeting violates users’ privacy (Lenatti, 2007; Turrow et al., 2009). Mughal (2010: 26) states the following about behavioural targeting:

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However, according to a study by Addvantage Media and YouGov (n=2000), 53% of respondents claim that they would make behavioural targeted adverts go away if it was possible (Roberts, 2010). A similar study by new media age (n=1000) found that the number of consumers interested in relevant ads had increased to 69% in 2009 from 58% in 2008 but that 66% of people still objected to behavioural targeting on privacy grounds, which highlights the area of conflict between relevance and privacy (Bearne, 2009). A study by Coremetrics of one thousand UK consumers in 2008 revealed a more positive attitude towards behavioural targeting: 45% were happy with it (providing they were able to opt-out), compared to 41% who were not (McEleny, 2009). In summary, research suggests that people’s attitudes towards behavioural targeting are not straightforward and that they are influenced by a variety of factors. There is a clear need for further research in order to investigate under which circumstances users perceive behavioural targeting as beneficial.

Facebook’s efforts to introduce obvious behavioural targeting through its Beacon advertising program, and the resulting consumer backlash, suggest that such covert information gathering may not be welcomed on social networks. Beacon was a part of Facebook’s advertisement system that sent data from external sites to Facebook, ostensibly for the purpose of allowing targeted advertisements and allowing users to share their activities with their friends (Facebook, 2007). In September 2009, a class-action suit against Facebook resulted in the program being shut down (Perez, 2009). The shutdown of Beacon, however, did not imply that Facebook had stopped working on its targeting technology, which tracks user data to deliver targeted ads. Facebook’s targeting technology will be discussed in more detail in the next chapter.

3.1.2.2 Social Targeting

Social targeting is a technique that is used to deliver targeted ads on social networks. In order to do so, users’ profile information and their behaviour on the site are tracked and analysed (Hermanns et al., 2008; Hermes, 2007). Social targeting integrates all other targeting techniques, as users usually provide all the necessary information themselves. Therefore, information disclosure on online social networks could be described as some form of self-segmentation; there is no need for advertisers to conduct market research, as users segment themselves (Hermes).

As the leading online social network, Facebook offers sophisticated social targeting technologies that promise advertisers to achieve the best returns possible^[14]. In their section for advertisers, Facebook (2010b) states the following:

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The connections targeting feature could best be described as a form of behavioural targeting, as it is based on how users behave on Facebook. In their FAQ section about connections targeting, Facebook (2010c) states, “Connections targeting allows you to target your ads to users who have become a fan of your Page, a member of your Group, RSVP’d to your Event or authorized your Application.”

The results of social targeting are targeted ads on social networks – a very new and unexplored area of research (Zeng et al., 2009; Bearne, 2009; Hadija, 2007; Todi, 2008). In the next chapters, the author will outline the concept of social media marketing and then proceed to discuss advertising on social networks.

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^[1] The squares (A, B, C…) in figure 1 mark certain events that may have impacted on the popularity/usage rate of the terms. For details, refer to Google Trends: http://www.google.com/trends?q=social+media%2C+Web+2.0&ctab=0&geo=all&date=all&sort=0.

^[2] A definition of the term will be presented in the glossary of terms in Appendix A.

^[3] The terms social networking sites, online social networks, virtual communities, and online communities are used interchangeably in the literature (Zeng et al., 2009). A definition will be presented in Chapter 2.2.

^[4] A definition will be presented in Appendix A.

^[5] A definition will be presented in Appendix A.

^[6] An outline of social networking features can be found in Appendix B.

^[7] For a review, refer to Brunold et al. (2000).

^[8] Due to the limited scope of this thesis, the typologies of social networks will not be discussed in more detail. For a review, refer to Brunold et al. (2000); Markus (2002); Porter (2004).

^[9] A definition is presented in Appendix A.

^[10] As far as relevant to this paper, definitions and descriptions of these elements can be found in Appendix B and Chapter 3.2.1. For a detailed review, refer to http://www.facebook.com/facebook?v=app_143615955650480#!/FacebookPages?__a=6&ajaxpipe=1.

^[11] Defintions of these terms will be introduced in Chapter 3.1.

^[12] Behavioural targeting will be outlined in more detail in Chapter 3.1.2.1.

^[13] Due to the limited scope of this paper, the different online advertising formats will not be discussed in more detail. For a review, refer to Goldhammer and Fölsch (2002: 284).

^[14] Facebook’s targeting technologies and filters are updated regularly. For a review, please refer to
http://www.facebook.com/adsmarketing/index.php?sk=targeting#!/adsmarketing/index.php?sk=targeting. [NN1]Missing Table 2.