The Acceptance of Online Behavioral Advertising: A Study of the Perceptions of Young Adults
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The Acceptance of Online Behavioral Advertising: A Study of the Perceptions of Young Adults

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In order to complete summa cum laude honors I extensively researched online behavioral advertising. I conducted my own research on the perceptions of young adults on this new type of online ...

In order to complete summa cum laude honors I extensively researched online behavioral advertising. I conducted my own research on the perceptions of young adults on this new type of online advertising.

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The Acceptance of Online Behavioral Advertising: A Study of the Perceptions of Young Adults The Acceptance of Online Behavioral Advertising: A Study of the Perceptions of Young Adults Document Transcript

  • 
 The
Acceptance
of
Online
Behavioral
Advertising:
A
Study
of
 the
Perceptions
of
Young
Adults
 
 Jeanine
Lilke
 

 School
of
Journalism
and
Mass
Communication,
 University
of
Minnesota
 
 Fall,
2009
 
 Abstract:
This
paper
explores
a
conceptual
framework
that
impacts
the
adoption
of
 online
behavioral
advertising.
The
paper
identifies
four
primary
stakeholders
 (information
technology,
government,
marketers
and
consumers)
that
all
have
 separate
points
of
view
on
this
emerging
technology
and
greatly
influence
the
success
 of
tailored
advertising.
It
is
argued
consumers’
perspectives
and
opinions
regarding
 online
behavioral
advertising
are
key
indicators
of
the
future
success
of
this
type
of
 advertising.
In
order
to
further
investigate
the
opinions
of
consumers
a
series
of
 interviews
were
conducted
amongst
18
to
24
year
olds.
Grounded
in
the
Uses
and
 Gratification
Expectancy
(UGE)
concept
it
was
found
that
interviewees
view
moderate
 benefits
and
risks
with
tailored
advertising.
Main
benefits
cited
were
convenience
and
 increased
interest
due
to
personal
relevancy,
while
the
largest
drawbacks
were
largely
 linked
to
data
privacy
concerns.
The
results
indicate
marketers
would
likely
benefit
 from
being
transparent
about
their
practices,
being
more
reactive
to
consumers
 concerns
and
testing
new
advertising
programs
before
launch.
By
lessening
the
 perceived
as
well
as
the
actual
risks
consumers
are
likely
to
become
more
comfortable
 with
a
process
they
are
largely
hidden
from.

 
 
 INTRODUCTION Online behavioral advertising has been getting plenty of attention and it is no wonder why. Often cited as the Holy Grail for marketers, tailored advertising promises unmet effectiveness and a wealth of future opportunities. The term online behavioral advertising is used to describe advertising that tracks a users online behavior and uses that information to deliver individualized messages. Imagine as a marketer for Amazon’s Kindle being able to deliver an advertisement to a consumer exactly when their deciding whether or not to buy the Kindle or Barnes and Noble’s 
 Lilke‐1

  • Nook for the holiday season. No other advertisement system can present such personally relevant messages to consumers. However, behavioral advertising is not without its critics. Concerns regarding data privacy are emphasized by highly publicized media stories such as Facebook’s flopped ad program Beacon. Since advertising is the lifeblood of the digital age, online behavioral advertising is a key area for marketers to understand. When used with the consumers best interest in mind tailored advertising can create great value for advertisers and the people who see them. To explore my research topic, I delved deep into the four stakeholders of tailored advertising: information technology (IT), government, marketers and consumers. Each group plays an essential role in the development, acceptance and future success of behavioral advertising. Grounded in the Uses and Gratification Expectancy (UGE) concept, I conducted a series of interviews, which explore the perceived benefits as well as the risks of online behavioral advertising. Interviews with 18 to 24 year olds provided a glimpse into the mindset of this influential age group and revealed various insights into this new area of advertising. But first, I examined academic research and media coverage of online behavioral advertising in order to present a holistic picture. RESEARCH QUESTION The basis of my thesis stems from the results of a 2009 telephone survey reported in the article Contrary to what marketers say, American reject tailored advertising and three activities that enable it (Turow et al., 2009). Princeton Survey Research Associates International conducted the survey through the use of telephone interviews with a nationally representative, 
 Lilke‐2

  • English speaking sample of 1,000 adult Internet users. The margin of sampling area for the data is ±3.6 percent at a 95% confidence level (Turow et al., 2009, pg. 12). In it, Turow et al. defines behavioral targeting as involving two types of activities. First, a company follows users online behaviors and then they use this information to tailor advertisements based on those behaviors. Using this definition Turow et al. identified two opposing points of views when it comes to behavioral targeting: the perspective of marketers and the perspective of privacy advocates. The purpose of the survey was to see if Americans sided with a particular view. The overarching finding of the survey was Americans reject tailored content with an average 60% of all groups and 55% of 18 to 24 year olds objecting to the activity (Turow et al., 2009, pg. 19). Turow et al. broke the survey into four areas of focus (2009). The first explores Americans opinions about tailored content as well as three different forms of behavioral tracking (ads, discounts and news). As shown in the table below, 66% would not want to see ads that are tailored to their interests (Turow et al., 2009, pg. 15). However, respondents appear to be more lenient towards tailored discounts and news. 
 Lilke‐3

  • The survey also notes Americans’ negative responses to tailored ads and news increases with a person’s age. Discounts were not included in the age analysis because the results were not statistically significant. 55% of 18 to 24 year olds object to tailored ads compared to 77% and 82% of 50 to 64 year olds and 65 to 89 year olds, respectively. A less dramatic difference is shown with tailored news with 54% of 18 to 24 year olds objecting to tailored news compared to 63% of 50 to 64 year olds and 68% of 65 to 89 year olds. As seen below, Turow et al. also examine the age breakdowns regarding respondents who said Not OK or OK to tailoring and three specific tailoring strategies (2009, pg. 17). Across all age groups, there is not a significant statistical difference between the ages, but the authors identify three broad patterns with the data. First, older groups reject tailoring and forms of behavioral tracking in higher percentages than younger groups of Americans. Secondly, all age groups have more tolerance for behavioral advertising when carried out for discounts in 
 Lilke‐4

  • comparison to advertisements and news. Finally, every age group has more tolerance for behavioral tracking when it exists solely online and does not jump into offline areas, such as stores. A second area of focus was evaluating people’s understanding of rules of the marketplace when it relates to sharing information. Turow et al. found the majority of survey respondents do not know the correct answers to most true-false statements about companies’ rights to share and sell information (2009, pg. 20). A third area inquires into American’s opinions about laws that ought to relate to behavioral targeting. Findings showed that 69% feel they have a right to know everything that a Web site knows about them. Additionally, Turow et al. point out suggestions of concern and even anger by the public when it comes to misusing information. Most notably, 35% agree, “executives who are responsible should face jail time” (2009, pg. 20). Finally, a fourth area of questions looks into people’s beliefs about their control over their personal information. Results indicated that beliefs about personal control and social protection did correlate with opinions towards tailored ads. Respondents who feel they have no control over personal information were more likely to not want tailored ads. In contrast, respondents who have confidence that companies and existing laws protect people increased the likelihood that they would be in favor of tailored advertising. Turow et al. conclude the majority of Americans do not want a company following their digital trail and adapting content based on their actions (2009). These findings strike a chord with proponents of tailored advertising because the success of online behavioral advertising 
 Lilke‐5

  • largely depends on consumers’ receptiveness to it. However, the research conducted by Turow et al. does not answer why consumers object to tailored advertisements, which is a key area of this issue. Based on the aforementioned study, two general research questions are established to guide my study. The first research question focuses on identifying how four different forces (IT professionals, marketers, government and consumers) frame the argument for and against online behavioral advertising. A literature review will identify major themes and predominant theories in each of the four areas. Each of these sources ultimately impacts why the majority of Americans, according to Turow et al., object to tailored advertisements (2009). In this regard, the second research question asks: Why do 18 to 24 years olds accept or reject online behavioral advertising? Little empirical research has been conducted to examine young adults perception and opinions towards online behavioral advertising. This study aims at systematically researching why American consumers’ between the ages of 18 to 24 accept or reject tailored advertisements. It focuses, from the consumer perspective, specifically on the factors, which may influence consumers’ opinions towards online behavioral advertising. Conducting in-depth interviews with 18 to 24 year old college students, this study begins to explain the extent to which external forces affect the acceptance of online behavioral advertising. 
 Lilke‐6

  • CONCEPTUAL FRAMEWORK Existing communication theories shapes the conceptual framework for this study. Specifically, this study focuses on the Uses and Gratification Expectancy (UGE) concept. The UGE concept provides a framework for understanding the processes by which people evaluate a type of media (Ruggiero, 2000). To understand the reasons why a consumer would object or accept online behavioral advertisements I examined four groups of people that influence the acceptance of online behavioral advertising. Each of the four groups, information technology professionals (IT), government regulators, marketers and consumers view online behavioral advertising through a different lens. Figure 1 illustrates that the abilities of information technology through data mining directly affect how the Federal Trade Figure 1: Conceptual Framework Commission and other legislative bodies revise privacy guidelines and laws. Furthermore, these legal decisions impact how advertisers handle, record and display online data. Ultimately, these three groups affect what consumers are exposed to and how they perceive online tailored advertisements. I would argue the framework is circular. This means that consumers’ perceptions are often the driving force of privacy laws and self- regulatory guidelines as well as affect what type of advertisements marketers are willing to place. The following example of Facebook’s behavioral advertising program Beacon will be used throughout the literature review. It will help illustrate how the conceptual framework can be 
 Lilke‐7

  • used to understand the forces behind the acceptance of online behavioral advertising. Facebook’s Beacon was an online tool where third-party advertisers, like Blockbuster, tracked and monitored Facebook users activities on their site and then portrayed the actions taken by the user in an ad placed on Facebook (Story & Stone, 2007). Facebook’s Beacon provides a dynamic example because it was one of the first social networks to use this type of tracking and it proved to be highly controversial among the government, marketers and Facebook users, who are largely 18 to 24 year olds (Corbett, 2009). Figure 2 demonstrates how the program affects the four primary stakeholders and how consumers impact the actions of the government and marketers. The framework begins with the IT department that develops the ability to track information. This flows down to the government who decides if the tool is legally acceptable. At this time, minimal guidelines existed about behavioral online advertising and therefore the program was not restricted. From here, marketers subscribed to the program Figure 2: Conceptual Framework, Facebook Beacon Example 
 
 Lilke‐8

  • and it was put into action on Facebook. It is important to note these steps do not always occur in sequence. When the tool was introduced in November 2007 all three parties assumed Facebook users would accept the program; however, Facebook users and privacy groups publically shunned the program saying it infringed upon their privacy rights (Story & Stone, 2007). Each stakeholder relationship within the Facebook Beacon example will be examined more closely in the upcoming literature review. Overall, this example shows how a more accurate prediction of consumer attitudes towards online behavioral advertising could have reduced the need to take corrective action. The framework also shows how a proper understanding of the Uses and Gratification Expectancy concept can help predict and create more successful programs in the future. The Uses and Gratifications Expectancy (UGE) concept is a body of approaches that seeks to study a particular subject through the lens of its audience. According to Thomas Ruggiero in his article, Uses and gratifications theory in the 21st century the UGE approach is especially useful in the initial stages of a new communication medium, like tailored advertising (2000, pg. 28). Ruggiero states that the nature of the Internet is likely to lead to profound changes on how users interact with media (2000, pg. 28). It is likely UGE research will play a major role in understanding how consumers interact with and perceive this new type of advertising. For the purpose of this study, I will use the UGE model in the following ways: (1) Further understand college students’ perceptions, thinking and actions towards online behavioral advertising including the perceived benefits and drawbacks colleges students receive from tailored advertising (2) Forecast the acceptance and success of online behavioral advertising (3) 
 Lilke‐9

  • Serve as a starting point on prospective quantitative and qualitative research on online behavioral advertising. LITERATURE REVIEW Information Technology The Federal Trade Commission (FTC) defines online behavioral advertising as, “the practice of tracking an individual’s online activities in order to deliver advertising tailored to the individual’s interests” (2007, December 20, pg.2). It is with this technology advertisers and firms possess unprecedented and a rapidly improving ability to track a users actions and adjust advertising to synch their ads with the inferred interests of their audience. Marketers hope this technology will help take the guesswork out of ad targeting. The extent and complexity of online advertising varies greatly. A large majority of advertising on Web sites is contextual advertising, which matches ads to the content a user is viewing. For example, a company that sells pet food may sell advertising on a Web site all about pets; however, these ads do not include any information about the person viewing it. This can be compared to behavioral advertising, also known as tailored advertising or behavioral targeting, that does depend on the interests of individual Internet users. Over time behavioral advertisers build profiles of individual Internet users based on the activities they do online. Advertisers are able to use this data to tailor ads to each individual (FTC, 2007, December 20, pg.2). At the simplest level are “first-party” or “intra-site” collection. This is the collection and use of personal information so a company’s Web site can tailor its content based on an individuals’ previous search patterns. In order to do this the Web site uses cookies, which is a 
 Lilke‐10

  • small piece of text that is saved on a computer and retrieved when the user revisits the site (Center for Democracy and Technology, 2008). When an individual first visits a site the firm deposits a cookie containing a unique ID, which keeps tracks of different activities including the items a person views and how long each individual stays on each page. This information is stored to a database, which is linked to the individuals’ unique cookie ID. When the individual returns to the site the users browser automatically sends the individuals cookie back to the site. From here, the site looks up the cookie ID in its database and serves the user product recommendations and ads based on their previous behaviors. First-party behavioral advertising can increase in complexity when the site requests personal information such as a zip code, age, gender or email address. The site can then incorporate this information into the profile of the individual or buy data from other companies that have previously collected an individuals email address (Center for Democracy and Technology, 2008). Some Web sites require users to develop an account before making a purchase. This is also first-party behavioral targeting, but has two notable differences. First, the sites are able to combine information in a users account with their search behavior. For example, Facebook members who say they are single are likely to receive advertising for dating services whereas members who say they are engaged might see ads for wedding vendors. Second, sites that use accounts sometimes typically allow users to decide if they want their data to be collected and used for behavioral advertising; however, clarity of privacy statements vary greatly (Center for Democracy and Technology, 2008). 
 Lilke‐11

  • These accounts include two different types of information: personally identifiable information (PII) and non-personally identifiable information (Non-PII). PII may include an individual’s name, address, telephone number, email address or other identifiers, which allows marketers to link the data back to a specific person. In contrast, Non-PII does not use any data that can be linked to a specific person, but rather uses cookies, log files and analytics technologies to better learn where users are going and what they view on a specific site (Center for Democracy and Technology, 2008). Differing from first-party behavioral advertising is third-party advertising, which tracks a users online behavior across multiple Web sites in an ad network (Center for Democracy and Technology, 2008). The ad network takes the position of the third party and the individual Web sites are the first-party. The ad network can identify if a user visits multiple sites within the network and adds the users behavioral information to its profile about individual visitors. Like first-party behavioral advertising, third-party behavioral advertising has multiple variations. One includes the use of not just ad networks and Web sites, but Internet Service Providers (ISPs). In this scenario, ad networks contract with ISPs in order to gain information about subscribers. This allows the advertiser to monitor the Web browsing occurring on the ISPs’ networks and create profiles about the users in order to deliver tailored advertising (Center for Democracy and Technology, 2008). If we move back to the Facebook Beacon example cited in the conceptual framework we see how the online behavioral technology works in a real example. The Beacon ad system tracks the activities of users on its third-party partner sites including those who have never signed up for Facebook or who have deactivated their account. On third-party sites the Beacon system 
 Lilke‐12

  • captures the actions users take and sends the information back to Facebook with the users ISP address (Perez, 2007). The information captured may include the addresses of Web pages a user visits and the actions the user performs while visiting the site. For instance, the program can publish the purchases an individual makes on eBay to their group of Facebook friends. From here, these activities may be reported back to the user’s set of Facebook friends unless the user has opted out of the feature. After receiving criticism Facebook changed this policy so users have to agree to make activities on third-party sites public to their Facebook friends (Perez, 2007). It is with this technology advertisers are able to more accurately reach their targeted consumer. However, the ability of this technology, which is illustrated through the Facebook Beacon example, has raised as many concerns as it has opportunities. Marketers In a meeting regarding online behavioral advertising president and CEO of the Association of National Advertisers (ANA) Bob Liodice stated, "Strong and comprehensive self-regulation strikes a balance that both protects the public interest and allows marketers to provide relevant advertising, which is particularly critical during this period of economic downturn" (Jones, 2009). The balance between advertising effectiveness and protection of consumer privacy is becoming more important as data mining technology improves and more advertisers use tailored advertising. For marketers the benefits of online behavioral advertising are plentiful. Online behavioral advertising offers significant advantages from contextual advertising because marketers are able to reach an even tighter audience with more relevant ads. Linking back to the 
 Lilke‐13

  • Facebook example it is evident the Beacon program provided marketers multiple benefits. At the top of this list is the value of personal recommendations, which many believe increases the effectiveness of advertising. Additionally, tailored ads are often more disruptive and draw more attention than the typical banner ad (Jones, 2009). In 2007, Jupiter Research conducted a study, which found behavioral advertising converts at a significantly higher rate than contextual advertising (Leggatt, 2007). In theory, this allows marketers to show and pay for fewer ad impressions, while enjoying a higher click- through-rate as well as a higher conversion rate. Additionally, the Jupiter Research study showed those that are more receptive to behavioral advertisements generally have a higher income, shop more frequently online and spend more money online in comparison to those that are contextually receptive (Leggatt, 2007). This effective targeting leads to less wasted efforts towards a higher value audience and in turn reduces overall marketing costs. Risks for marketers primarily center around alienating consumers by infringing on their privacy rights. As seen with the Facebook Beacon example, a poorly designed system can lead to much negative feedback and press from consumers. When Blockbuster used Facebook Beacon to advertise visitors’ movie rental history a few users sued the company citing the 1987 Videotape Privacy Protection Act (McCarthy, 2008). In this situation, only Blockbuster was sued and Facebook went unharmed. Additionally, since the ads target the computer and not the specific user there is frequent “misfiring” of advertisements, which lessens the effectiveness. Currently, the argument boils down to if marketers who make money by effectively advertising to people who surf the Web should be allowed to continue with self-regulation, or if 
 Lilke‐14

  • state or federal legislators should step in to the limit the amount of information that online advertisers can collect and use. Bureau of Consumer Protection attorney Peder Magee, who oversees behavioral advertising at the FTC provided this warning to marketers, “If the industry ignores the principles, they might not like the results” (Baldas, 2009). Government In recent years, the call for regulation of behavioral advertising is getting louder. Again, Facebook’s Beacon adds color to this discussion. Complaints to the Federal Trade Commission (FTC) from privacy groups led to a few marketers ceasing participation and Facebook changing the program from opt-out to opt-in, which means users had to click a box to give the program approval to share their purchase behaviors on third-party sites (Story & Stone, 2007). A lawsuit filed in August 2008 alleged that Facebook and advertisers who used Beacon, like Blockbuster and Overstock.com, violated a series of laws, including the Electronic Communications Privacy Act (Lane v. Facebook, Inc., 2008). The lawsuit claims Facebook’s Beacon, invaded a person’s “intellectual privacy,” which states that publicizing a user’s choice of books, music, film or Web site may constrain a users ability to explore ideas freely. Finally, in a few cases Facebook’s Beacon provided unwanted disclosure by publicizing purchases that were gifts (McGeveran, 2009, pg. 8). The settlement involves Facebook setting up and funding a privacy foundation, paying attorneys’ fees to the extent deemed reasonable by the court and paying plaintiffs from $7,000 to $15,000 for their time and effort (Lane v. Facebook, Inc., 2008). Facebook’s Beacon provides one example of how sensitive this topic is to consumers and how consumers are demanding to have a more active role in deciding how their information is collected, used and displayed. 
 Lilke‐15

  • Due to increased attention by privacy advocacy groups and consumers the Federal Trade Commission continues to refine their self-regulation guidelines for online advertisers. Since 1995, the Federal Trade Commission has examined the impact online behavioral advertising has on consumer privacy and has made suggestions as to how marketers should handle privacy information. A brief history of the development of the self-regulatory guidelines of online behavioral advertising proposed by the FTC provides a healthy understanding of multiple sides of the debate—industry, consumer and privacy organizations as well as individual consumers. Town Hall In November 2007, the FTC held the first Town Hall, which invited interested parties to discuss online behavioral advertising in a public forum. For the Town Hall, the FTC defined online behavioral advertising with a wide stroke. For the purpose of the discussion, they focused on “all tracking activities engaged in by diverse companies across the Web” (FTC, 2007, December 20). According to the FTC staff report, Online behavioral advertising: Moving the discussion forward to possible self-regulatory principles, the Town Hall discussions revealed three core issues and concerns (FTC, 2007, December 20). First of all, participants of the Town Hall noted the practice itself is highly invisible and unknown to consumers. Many consumers value the benefits of behavioral advertising such as free content subsidized by advertising and reduction in ads that are irrelevant to them. However, few consumers understand how the data is collected and how the process directly impacts them. Second, consumer and privacy advocacy groups are champions for transparency and consumer autonomy when it comes to building and maintaining the trust of online consumers. Finally, all 
 Lilke‐16

  • groups concluded there is reasonable concern if the collected data falls into the wrong hands and is used for unanticipated purposes such as theft (FTC, 2007, December 20). Principles From this discussion, the FTC devised five general principles to encourage more meaningful and enforceable self-regulation in regards to online behavioral advertising (FTC, 2007, December 20). I. Transparency and consumer control Description: All Web sites should provide a clear statement that data about consumers’ online activities is being collected in order to provide advertising tailored to consumers’ interests. Consumers can also choose whether or not to have their information collected. II. Reasonable security and limited data retention, for consumer data Description: Any company that engages in online behavioral advertising should provide reasonable security of the data. These protections should be based on factors such as the sensitivity of the data, nature of the business and types of risks a company faces. III. Affirmative express consent for material changes to existing privacy promises Description: A company must maintain its original promise on how the data collected will be used. If a company wants to use the data in a different manner they should obtain affirmative express consent from impacted consumers. IV. Affirmative express consent to (or prohibition against) using sensitive data for behavioral advertising Description: Sensitive data for the use of behavioral advertising should only be collected if the firm obtains affirmative express consent from affected consumers. V. Using tracking data for purposes other than behavioral advertising Description: All Web sites should provide a clear statement that data about consumers’ online activities is being collected in order to provide advertising tailored to a consumer’s interests and consumers can choose whether or not to have their information collected. The Town Hall and the subsequent self-regulatory principles did lead to some individual companies, industry organizations and privacy groups taking action. Notably, Yahoo! Inc. (Yahoo!) announced the use of new tools that will allow consumers to opt out of tailored advertisements (Benander, 2008). Microsoft also stated that their new version of its Internet 
 Lilke‐17

  • browser would include a tool that will automatically clear the browser cache at the end of each session (Keizer, 2008). Adjusted Self-Regulatory Principles In February 2009, the FTC published their most recent report, Self-regulatory principles for online behavioral advertising. This report summarizes the main issues raised by more than 60 comments the FTC received in regards to the proposed principles listed previously. This report responds to main issues raised by the comments and sets forth revised principles. The report emphasizes most of the public comments received were concerning the scope of the proposed principles. Specifically, commenters asked if it was necessary to provide privacy protections for data that is not personally identifiable. The report states privacy protection should cover any data that could be reasonably connected back to a particular consumer or device. Additionally, many commeters questioned if it was necessary to apply the principle to first-party behavioral advertising and contextual advertising. The FTC concludes there are fewer privacy concerns with these two fields of behavioral advertising and it is not necessary to include these within the scope of the principles. The adjusted report also states that information collected outside of a traditional Web site context, like a mobile device, should also develop disclosure mechanisms to inform the user of their privacy policies and provide a clear way for consumers to choose whether to have their information collected. Future Privacy Concerns As online behavioral marketing continues to grow the FTC will need to update and elaborate upon privacy laws and self-regulatory guidelines. It is likely new technology will fall through the 
 Lilke‐18

  • cracks between current regulations. Two areas that are becoming an emerging issue is behavioral advertising at the ISP level and personal data collected by social networking sites. Behavioral Advertising—ISP Level In 2008, online behavioral tracking company NebuAd announced plans to pay Internet service providers for the right to track users’ Web site visits and searches (Singel, 2008). The agency engaged in Deep Packet Inspection, which is the act of inserting Internet packets to record a users URLs and search terms in order to classify each user’s interests and tailor advertisements based on those interests. This led to privacy advocates such as Public Knowledge and Free Press to object to the plan because NebuAd did not receive consent from users (Singel, 2008). These concerns led to the House Subcommittee on Telecommunications and the Internet to look further into NebuAd, which evoked Charter to end their partnership with the agency in order to avoid negative publicity (Singel, 2008). In November 2008, a class action lawsuit alleges NebuAd of violating the Electronic Communications Privacy Act, Computer Fraud and Abuse Act, California’s Invasion of Privacy Act and California’s Computer Crime Law. Since the lawsuit NebuAd has ceased the use of Deep Packet Inspections (Singel, 2008). A recent Congressional hearing regarding Deep Packet Inspection led to the major ISPs including AT&T, Verizon and Time Warner Cable to agree to stop the practice and only engage in online behavioral advertising that is transparent to the end-user (Raysman & Brown, 2009). Due to personal invasion, it is likely that the use of Deep Packet Inspection among ISP’s will continue to be a point of concern for privacy advocates, Congress and consumers. Behavioral Advertising—Social Marketing 
 Lilke‐19

  • The open nature of social networks provides a wealth of creative opportunities for marketers. In the article Disclosure, endorsement and identity in social marketing, William McGeveran examines potential concerns associated with social marketing regarding unwanted disclosure of information, unknowing or inaccurate endorsement of products and the impact social marketing may have on the identity of a person (2009). Currently, privacy law in the U.S. does not address social marketing practices. Lawsuits regarding social marketing concentrate on sensitive matters, which is rarely a focus of social marketing. U.S. law does not provide protection regarding unwanted disclosures or general surveillance (McGeveran, 2009, pg. 14). Due to the high interactivity of social marketing it is likely to disrupt current laws regarding privacy, intellectual privacy and free speech. Future actions by lawmakers are likely to be driven by how marketers engage in behavioral advertising as well as consumers’ reactions to the advertisements. Consumers The final stakeholders in the conceptual framework are consumers. Their approval or disapproval impacts the other three areas, which ultimately alters the success or failure of online behavioral advertising. In numerous examples it was consumers who embraced or rejected advertising programs. For Facebooks’ Beacon, consumers let their voices be heard through Facebook groups, thousands of blog posts and several members even sued the company (Perez, 2007). Additionally, The Center for Digital Democracy and the U.S. Public Interest Research Group jointly petitioned the U.S. Federal Trade Commission to launch an investigation into the mobile marketplace. As voices for consumers these two groups presented their concerns about unfair 
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  • and deceptive mobile advertising practices and weak protection against youth (Teinowitz, 2009). Google has seen to learn from the experiences of others and is attempting to be more transparent with their use of tailored advertising. Their new ad program will allow targeted ads to be displayed on unrelated sites or in response to unrelated searches. In order to ease consumer concern, Google has clearly described the program in a blog and video, which describes the program, its benefits and how to adjust settings or opt-out of the program. In addition, Google has set boundaries on what categories advertisers can target, such as health status interest categories or interest categories geared towards children (Wong, 2009). However, consumers who do not want the tailored advertising will have to opt-out of the system, which is achieved by obtaining an “opt-out cookie” through Google’s Ad Preferences Manager (Wong, 2009). Unfortunately, it is too early to tell if these preemptive steps will help Google more successfully implement the ad program. To explore more into the perspective of consumers I conducted in- depth interviews guided by the Uses and Gratifications Expectancy concept RESEARCH
 In
my
opinion,
there
is
still
much
research
to
be
done
on
how
consumers
impact
the
 acceptance
of
online
behavioral
advertising.

The
efforts
of
the
three
other
parties
are
often
 held
back
or
lost
altogether
unless
they
are
in
line
with
and
respect
the
perceptions
of
the
 consumer.
The
Uses
and
Gratifications
Expectancy
concept
calls
for
understanding
the
 reasons
why
consumers
use
a
particular
form
of
media
and
the
gratifications
they
receive
 from
it.
I
used
in‐depth
interviews
to
facilitate
this
type
of
evaluation.
The
one‐on‐one
 interviews
allowed
me
to
explore
young
adults
perspectives
of
tailored
advertisements
and
 evaluate
their
future
receptiveness
to
online
behavioral
advertising.
Specifically,
I
explored
 
 Lilke‐21

  • college
students’
perceptions,
thinking
and
actions
towards
tailored
advertising
and
 identified
specific
advantages
and
disadvantages
college
students
associate
with
behavioral
 advertising.
These
discussions
helped
me
forecast
the
acceptance
and
success
of
online
 behavioral
advertising
amongst
this
age
group.

 What
follows
is
a
detailed
outline
of
the
study
and
the
results
drawn
from
the
data
 collected.
An
overall
discussion
of
the
results
and
the
implications
for
the
research
 questions
as
well
as
limitations
and
areas
for
future
research
continues
after
the
outline
of
 the
research
studies.

 Method
 
 In‐depth
interviews
were
chosen
as
a
research
method
because
it
moved
the
 discussion
forward
in
many
ways.
First,
since
online
behavioral
advertising
is
a
relative
 new
technology
it
was
necessary
to
use
an
exploratory
research
method
in
order
to
relate
 findings
back
to
the
Uses
and
Gratifications
Expectancy
concept.
Second,

 it
was
important
to
collect
data
in
a
way
that
allowed
for
an
analysis
of
common
themes
 within
the
data
and
not
just
a
pure
analysis
of
numerical
statistics.
Additionally,
in‐depth
 interviews
are
proven
to
be
effective
for
collecting
information
regarding
the
perceived
 advantages
and
disadvantages
of
online
behavioral
advertising
because
interviewees
could
 respond
to
questions
in
great
detail,
which
allowed
unanticipated
perspectives
to
emerge.
 Participants
 College
students
from
the
ages
of
18
to
24
were
the
chosen
focus
for
this
research
for
 multiple
reasons.
First,
18
to
24
year
olds
represent
a
driving
force
for
changes
in
 
 Lilke‐22

  • technology
and
new
media.
In
the
future,
this
group
of
consumers
is
likely
to
set
the
 standards
on
tailored
advertising.
Furthermore,
this
age
group
provides
an
interesting
area
 of
focus
because
the
study
conducted
by
Turow
et
al.
claims
18
to
24
years
olds
object
to
 tailored
advertising,
which
contradicts
marketers
previous
beliefs
about
this
age
group
 having
less
privacy
concerns
when
it
comes
to
data
collection
(2009).
Turow
et
al.
 addresses
this
contradiction
and
offers
hypothetical
reasons
why
this
age
group
may
object
 to
tailored
advertising;
however,
no
systematic
research
is
conducted.
Finally,
this
age
 group
was
conveniently
available
to
the
principal
investigator
through
a
subject
pool
 consisting
of
undergraduate
college
students.

 I
recruited
participants
using
the
Sona
System
database
through
the
University
of
 Minnesota’s
School
of
Journalism
and
Mass
Communication.
Undergraduate
students
in
 introductory
journalism
courses
are
offered
course
credit
for
participating
in
studies.
 Through
an
online
site
students
can
self‐select
what
studies
they
would
like
to
participant
 in.
For
this
study,
the
criterion
for
participants
was
that
they
were
between
the
ages
of
18
 to
24
and
frequently
used
the
Internet,
which
I
defined
as
three
or
more
times
a
week.
11
 students
signed
up
for
the
study
and
6
more
class
acquaintances
were
recruited
by
the
 principle
investigator.
59%
of
the
interviewees
were
female
and
41%
were
male.

 Procedures
 In
order
to
finalize
the
range
of
questions
five
pilot
interviews
were
conducted
with
 acquaintances
of
the
principle
investigator.
The
pilot
interviews
were
not
included
in
the
 final
analysis.
However,
these
initial
interviews
allowed
the
principle
investigator
to
get
 
 Lilke‐23

  • feedback
from
interviewees
about
ambiguous
wording
or
other
confusing
elements.
The
 pilot
tests
also
allowed
me
to
become
more
comfortable
with
asking
questions.
As
a
result
 slight
revisions
were
made
to
the
original
questionnaire.

 At
the
beginning
of
each
interview,
the
participant
was
guided
through
a
consent
 form
outlining
the
purpose
of
the
research,
the
type
of
questions
that
will
be
asked,
the
 confidentiality
of
the
information
obtained
and
the
incentive
provided
upon
completion
 (See
Appendix
A).

Before
the
interview
began
the
principal
investigator
provided
a
 background
on
online
behavioral
advertising,
which
included
a
simple
example
of
how
the
 process
works
and
ways
in
which
the
process
can
become
more
complex.
All
participants
 were
asked
if
they
had
any
questions
regarding
tailored
advertising
before
the
 questionnaire
process
began.
This
ensured
all
participants
defined
online
behavioral
 advertising
in
the
same
way.
A
discussion
guide
provided
the
framework
for
the
questions,
 but
all
interviews
followed
their
own
organic
conversation.
Participant’s
responses
to
the
 interview
questions
were
recorded
and
later
transcribed.
Each
of
the
17
interviews
lasted
 between
20
to
35
minutes
depending
on
the
depth
of
participant
responses.

 Instruments
 The
discussion
guide
was
divided
into
four
main
sections:
observations
and
opinions
 regarding
general
advertising,
perceived
value
of
tailored
advertisements,
perceived
risks
 of
tailored
advertisements
and
future
of
tailored
advertisements.
The
following
questions
 were
asked
of
each
interviewee
during
the
one‐on‐one
interview.
The
questions
were
 
 Lilke‐24

  • purposefully
designed
to
be
open
ended
and
various
follow‐up
questions
were
asked
 depending
on
the
interviewee’s
answer
(See
Appendix
B).

 Questions
regarding
general
advertising
allowed
the
principal
investigator
to
gauge
 the
interviewees
overall
perception
of
advertising.
These
questions
also
helped
the
 interviewee
become
more
comfortable
with
the
interview
process
and
helped
me
develop
a
 report
with
the
respondent.

 General
Advertising
Questions:
 1. How
would
you
describe
advertising?
 2. Can
you
give
me
some
examples
of
it?

 3. As
your
day
goes
by,
where
do
you
mostly
see
advertising?

 4. What
are
some
consumer
benefits
of
advertising?
 5. What
are
some
consumer
drawbacks
of
advertising?

 
 In
order
to
reduce
bias,
the
principal
investigator
randomly
selected
to
start
with
the
 set
of
questions
about
the
value
of
tailored
advertisements,
but
rotated
the
value
and
risk
 questions
every
other
interview.
So
the
second
interviewee
received
the
questions
related
 to
risk
before
the
questions
related
to
value.
The
goal
of
this
was
to
reduce
unintended
 question
bias.

Many
follow‐up
questions
were
asked
in
order
to
obtain
more
detailed
 answers
from
respondents.

 Questions
about
the
Benefits:

 6. What
personal
value
may
you
receive
from
tailored
advertisements?

 7. How
certain
are
your
feelings
in
this
area?

 
 Questions
about
the
Risks:

 8. Do
you
see
any
risks
connected
with
tailored
advertising?


 9. Do
you
see
anything
about
this
you
don’t
like?

 10. How
certain
are
your
feelings
in
this
area?
 
 
 Lilke‐25

  • Finally,
the
principal
investigator
asked
interviewees
questions
regarding
their
future
 openness
to
tailored
advertisements.
These
questions
intended
to
weigh
the
importance
 the
interviewee
placed
on
the
value
versus
the
risk
involved
with
tailored
advertising.

 Future
Opinions:

 11. If
a
search
engine
gave
you
a
choice
to
opt‐out
of
tailored
ads
what
would
you
 decide
to
do
today?

 12. How
likely
are
you
to
be
more
open
about
this
topic
in
the
future?

 13. How
certain
are
your
feelings
in
this
area?

 
 Coding
the
Data
 Before
outlining
the
results
of
the
research,
an
explanation
of
how
the
data
was
coded
must
 be
provided.
Responses
to
the
questions
regarding
the
perceived
value
and
risk
of
tailored
 advertisements
were
the
focus
of
the
analysis
because
they
directly
relate
to
the
research
 question.
Responses
to
the
other
questions
were
incorporated
into
the
coding
categories
as
 was
applicable.
In
the
coding
process,
the
data
was
analyzed
three
times
to
ensure
 reliability
of
the
analysis.
After
an
initial
analysis
of
all
interviewees
responses
categories
 were
created
for
both
the
value
and
risks
associated
with
online
behavioral
advertising.
 This
scheme
of
categories
was
also
made
to
be
mutually
exclusive
for
the
purpose
of
 validity
and
therefore
a
category
of
“other”
was
always
included.

 
 After
reading
through
all
the
responses
and
placing
the
data
into
categories,
 responses
in
each
category
were
counted
to
help
in
the
process
of
reporting
the
results
of
 the
data.
An
explanation
of
each
category
used
in
the
coding
process
beginning
with
 perceived
value
is
provided
here.

 
 Lilke‐26

  • 
 Three
different
themes
were
revealed
in
relation
to
online
behavioral
advertising
 providing
value
for
the
respondent.
First,
respondents
noted
tailored
advertising
might
 simplify
a
person’s
life.
Responses
involving
the
discussion
of
tailored
advertising
as
a
 means
to
assist
with
making
decisions,
make
the
search
process
more
convenient
or
reduce
 time
spent
looking
for
information
were
placed
under
this
category.
An
example
of
this
 category
comes
from
a
respondent
who
provided
the
following
response
to
the
question
 regarding
the
value
of
tailored
advertising:
“I
guess
if
the
products
I
am
most
interested
in
 are
always
in
front
of
me
it
makes
life
easier
because
I
don’t
have
to
sift
through
everything
 to
find
what
I
want.”

 
 The
second
value
related
theme
that
emerged
about
tailored
advertising
was
that
it
 might
provide
more
interesting
material
because
it
is
personally
relevant
to
the
individual.
 Responses
were
deemed
to
fit
in
this
category
if
they
talked
about
the
advertisements
 being
more
interesting
or
better
aligned
with
the
participants’
personal
interests.
This
is
 exemplified
by
a
participant
who
talked
about
a
personal
experience
of
having
ads
tailored
 to
their
car
preferences
as
they
searched
for
a
new
car,
which
greatly
increased
their
 interest
in
the
online
advertisements.

 
 Finally,
participants
cited
the
tailored
ads
increase
the
users
knowledge
regarding
a
 product
or
service.
Responses
that
were
included
in
this
category
revolved
around
 providing
unknown
information
or
helps
one
make
more
informed
decisions.
An
example
 of
this
type
of
response
came
from
a
respondent
who
said,
“Some
tailored
ads
can
help
you
 
 Lilke‐27

  • understand
more
about
a
product.
I
would
rarely
seek
this
information
out
myself,
but
the
 [tailored]
ads
I
receive
act
as
constant
updaters.”

 
 Responses
were
also
categorized
regarding
perceived
risks
associated
with
tailored
 advertisements.
An
analysis
of
the
interviews
revealed
four
common
themes
related
to
 perceived
risks.
First,
interviewees
remarked
tailored
advertisements
might
reduce
 options
available
to
an
individual.
Responses
were
grouped
into
this
category
if
they
 included
thoughts
about
tailored
advertising
limiting
ones
choices.
For
example,
one
 respondent
stated,
“I
want
to
know
everything
that
is
available
to
me
and
this
limits
my
 exposure.
I
guess
I
don’t
know
what
I
am
missing
out
on
and
that
bothers
me.”
In
addition,
 another
respondent
said,
“These
ads
could
give
you
a
shallow
view.
Only
show
you
the
 options
that
you
already
looked
at
and
you
could
miss
a
good
opportunity.”

 
 Another
category,
which
emerged
from
the
responses,
was
an
overall
privacy
 concern.
Responses
related
to
concerns
over
what
parties
have
control
and
access
to
the
 data,
how
they
use
the
data
and
what
type
of
data
they
collect.
Privacy
concern
responses
 were
those
that
discussed
potential
for
the
advertising
to
be
invasive
and
overly
intrusive.
 One
respondent
noted
a
privacy
concern
with
the
statement,
“It’s
pretty
creepy
when
you
 think
about
it.
It’s
kinda
like
Big
Brother
always
watching
you
and
you
never
know
if
they
 could
use
that
information
against
you.”

 
 Third,
interviewees
expressed
concern
that
online
tailored
advertising
might
poorly
 use
their
personal
time
and
financial
resources.
They
stated
tailored
ads
might
make
them
 less
efficient
because
they
are
more
likely
to
be
attracted
to
the
advertisements
due
to
their
 
 Lilke‐28

  • increased
relevance.
In
addition,
individuals
may
be
enticed
to
spend
more
money
on
items
 that
they
would
not
have
known
about
before.
Responses
related
to
decreasing
personal
 efficiency
or
enticing
one
to
spend
more
money
was
included
in
this
category.
An
example
 of
this
type
of
response
was
collected
from
an
interviewee
who
indicated
tailored
 advertising
is
like,
“big
flashing
lights
that
are
always
distracting
me
from
what
I
am
 suppose
to
be
doing.”
Another
respondent
commented,
“It
might
motivate
someone
to
 spend
more
than
they
can
afford.”

 
 A
final
category
under
perceived
risks
revolves
around
the
idea
that
tailored
 advertising
is
likely
to
be
a
poor
indicator
of
ones
likes.
A
sort
of
“none
of
your
business”
 attitude
categorized
a
range
of
responses
including
feelings
that
they
are
capable
of
finding
 their
own
information
and
that
their
search
behavior
is
not
necessarily
an
indicator
of
their
 interests.
One
respondent
commented,
“I
search
things
for
work
and
school
that
I
have
 absolutely
no
interest
in
and
those
ads
are
a
complete
waste
of
ad
dollars.
And
it’s
sort
of
 unfair
that
they
are
creating
a
profile
about
me
that
has
nothing
to
do
with
me.”

 RESULTS
 After
reviewing
the
data
collected
in
the
in‐depth
interviews
I
have
grouped
the
statements
 into
the
nine
categories
as
seen
in
the
table
below.

 
 
 
 
 
 Lilke‐29

  • 
 Number
 Category
 of
 Mentions
 Value:
Simplifies
my
life
 15
 Value:
Increases
my
knowledge
 7
 Value:
More
interesting
than
regular
ads
 12
 Value:
Other
responses
 4
 Risk:
Reduces
options
 10
 Risk:
Waste
of
time/financial
resources
 8
 Risk:
Privacy
uncertainty
 17
 Risk:
Poor
indicator
of
interests
 9
 Risk:
Other
responses

 5
 
 After
dividing
all
of
the
interviewees’
responses
into
the
nine
categories
of
the
coding
 scheme,
results
reveal
the
majority
of
responses
in
terms
of
perceived
value
of
tailored
 advertising
fall
under
the
category
of
simplifying
ones
life.
Responses
relating
to
tailored
 ads
being
more
interesting
than
regular
ads
had
the
next
largest
number
of
responses
 among
this
audience.
It
is
evident
respondents
were
able
to
identify
multiple
benefits
 associated
with
tailored
advertisements;
however,
certainty
that
these
benefits
will
be
 realized
varied
greatly
with
respondents.

 
 In
terms
of
risks
associated
with
tailored
advertisements,
all
respondents
identified
 some
level
of
privacy
concerns.
An
analysis
of
the
data
collected
shows
as
respondents
 expressed
greater
privacy
concerns
they
are
less
likely
to
be
open
to
using
tailored
 advertising.
Out
of
the
17
people
interviewed
the
principle
investigator
identified
six
 
 Lilke‐30

  • (35%)
of
the
respondents
as
having
high
privacy
related
concerns.
These
people
were
 identified
due
to
the
language
used
when
referring
to
data
privacy
and
the
degree
of
 certainty
the
respondents
expressed
about
the
topic.
For
example,
respondents
who
 claimed
tailored
advertising
is
“unacceptable”
or
“overly
invasive”
were
perceived
to
have
 higher
privacy
concerns
than
respondents
who
used
language
such
as
“a
little
creepy”
or
 “weird.”
All
but
one
of
the
respondents
with
high
privacy
concerns
stated
they
would
opt‐ out
of
tailored
advertising
if
given
the
opportunity
to
do
so.

 
 The
second
most
cited
risk
is
tailored
advertising
may
reduce
ones
options.
This
 was
followed
closely
by
the
ads
being
poor
indicators
of
ones
likes
and
a
waste
of
time
as
 well
as
financial
resources.

These
categories
did
not
show
a
correlation
between
a
 respondent
stating
they
would
likely
opt‐out
of
tailored
advertising.

 DISCUSSION As was determined earlier in this paper, the best approach to answering the research question at hand is to analyze the data collected in terms of the Uses
and
Gratifications
Expectancy
 concept. In terms of this research project the UGE concept provides an audience-centered analysis on the gratifications individuals receive from online behavioral advertising. Through the interviews I was aiming to capture a greater understanding of the following issues: • Understand college students’ perceptions, thinking and actions towards online behavioral advertising including the gratifications and drawbacks 18 to 24 year olds receive from tailored advertising • Forecast the acceptance and success of online behavioral advertising The above areas will guide the following discussion of the data collected in the in-depth interviews. 
 Lilke‐31

  • College Students Perceptions As expected college students perceptions and attitudes towards online behavioral ads vary greatly with participants concerns for data privacy and previous knowledge as well as experiences with tailored advertising. From this study we have learned interviewees view tailored advertising as having clear trade-offs. With convenience and increased personalization on the one hand and the misuse of data on the other hand. An analysis of positive responses reveals interviewees perceive modest benefits from tailored advertising. Language such as “saves time” and “more interesting” highlight these benefits. It was also clear convenience is the most valued benefit to respondents because most participants appreciated that tailored advertising could be a time saver. The secondary benefits of increases knowledge and provides more interesting messages were seen as nice perks, but not overly beneficial. It is also interesting to note some participants view tailored advertising as giving them more information then they would have without tailored advertising. On the other hand, other respondents view tailored advertising as limiting the information they are exposed to because it is designed to only show a user messages they are already familiar with. Overall, respondents connect moderate, but not overwhelming benefits to online behavioral advertising. Privacy infringement is the primary drawback mentioned by interviewees. However, an understanding of how data is collected varied greatly with most respondents being unaware of how collected data was stored and used by marketers. In order to increase consumers’ comfort level with tailored ads firms are going to need to be more transparent on how the data is collected, what data is collected and how it is specifically used. However, most respondents 
 Lilke‐32

  • admit they are more reactive than proactive when it comes to data privacy, only looking into privacy settings when something unfavorable occurs. Additionally, numerous respondents mention the tailored ads may be too intriguing as a drawback. In the eyes of a marketer this would be seen as a great advantage. In addition, this was viewed as a slight drawback and it is unlikely participants would remove tailored advertising due to this. Finally, poor data accuracy was also a frequently cited disadvantage. Many respondents stated that as students they research a lot of topics that are of no personal interest to them and as a result are highly annoyed when an ad pops up on every screen they visit. Also, many noted that the ad networks assume everything someone searches is something they like and are interested in. In actuality, many people search things due to curiosity, hatred or as a requirement for work or school. In the future, ad networks should give users more control over what ads they see and allow users to delete search terms that are personally irrelevant to them. Overall, student perceptions of tailored advertising vary greatly, but there is a slight higher focus on drawbacks than gratifications, which is likely to impact future acceptance. Forecast Future Success The success of tailored advertising is going to depend largely on the amount of control and transparency ad networks and search engines provide users. Even among 18 to 24 year olds, who have been classified as having the least amount of privacy concerns, it is evident they too want to be aware of the information firms are collecting about them. With proper transparency tailored advertising could prove to be very successful among this target because 18 to 24 year olds are 
 Lilke‐33

  • more comfortable with data collection and associate various benefits with personalized advertising. It would be in marketers best interest to make sure any tailored advertising they use is well received by their target audiences. As seen with the Facebook Beacon example, poor reception can quickly lead to unsatisfied users. Additionally, marketers are going to need to provide straightforward privacy settings, which will allow users to adjust their settings to their comfort level. Providing consumers with greater levels of transparency and control will likely mitigate the moderate risks 18 to 24 year olds associate with tailored advertising. It is important for all four groups to work to create value for consumers. LIMITATIONS The largest limitation to the research was the small and select sample size used for the in-depth interviews. It would have been more telling had I been able to interview a more diverse group of 18 to 24 year olds and not just college students from the University of Minnesota. However, taking into account the time frame and feasibility of interviewing individuals outside of the university I was able to capture a glimpse into the perspectives of this age group on tailored advertising. In addition, my interviewees were also more highly educated than many 18 to 24 year olds. Every respondent had some college experience. Since most participants were students at the School of Journalism and Mass Communication it is likely they were more experienced with online advertising and more aware of the privacy implications. Furthermore, since many of the interviews are working on majors in advertising it is likely they have a favorable bias towards advertising in general. 
 Lilke‐34

  • Additionally, the interview questions were largely focused on the perceived benefits and risks of tailored advertising. Consequently, this narrow range of questions resulted in a narrow range of answers. A broader range of questions may have offered a different set of results. Asking questions regarding the types of behavioral ads respondents encounter, the actions they may take to avoid them or how they respond to behavioral ads in various contexts would offer a richer understanding of how 18 to 24 years engage with this medium. Finally, the research was limited by the Uses and Gratifications Expectancy concept. I have identified the most relevant drawbacks of the UGE concept as it pertains to this research project. A primary criticism of this approach is a lack of internal consistency because there is no formal procedure. In addition, the UGE concept is often criticized for being too individualistic because it is difficult to expand the findings onto larger populations. Finally, self-reports may be a poor measure of ones behavior due to different interpretations of ones behavior (Ruggiero, 2000). In light of the drawbacks the UGE concept still provides a systematic way to explore a new area of advertising that should allow for future approaches that are more quantitative in nature. FUTURE RESEARCH This research was meant to serve as a first step into understanding 18 to 24 year olds perceptions of tailored advertising as well as their evaluation of the risks and benefits. This is a relative new area of study, which deserves future attention. As seen with the conceptual framework the opinions and tolerance of the consumer greatly impacts the future success of tailored advertising. In order to overcome the limitations of the convenience sample future research could recruit 18 to 24 year old participants who are more culturally diverse, live in areas besides the 
 Lilke‐35

  • Midwest and non-college students. In addition, researching the perspectives of all age groups may provide a more holistic analysis and may reveal different findings and offer different implications for marketers. Another topic to address is whether or not an individual’s opinion regarding tailored advertising makes them more or less likely to opt-out of these advertising programs or take more privacy precautions. It would be interesting and useful to know if people’s attitudes result in behavior changes such as opting out of tailored ads or regularly clearing cookies. CONCLUSION With tighter pocket books and increasingly fragmented media it is likely online behavioral advertising will take a larger role in future advertising plans. However, tailored advertising is often met with concern from consumer and privacy advocates as well as consumers. The survey conducted by Turow et al., revealed the majority of consumers object to tailored advertising (2009). My findings show 18 to 24 year olds have privacy concerns about tailored advertising due to limited knowledge about online behavioral advertising. However, most consumers showed interest and did not relay as strong objections to tailored advertising as found in the Turow et al. survey. I feel much can be done to increase the acceptance of tailored advertising and it all revolves around a greater understanding of consumers. In order to take productive actions information technology professionals, the government and marketers must have a firm understanding of consumers’ beliefs about this new technology. My research project was positioned as a first step to obtaining a greater understanding of consumers’ perceptions towards tailored advertising. 
 Lilke‐36

  • I began with two primary research questions in mind. First, I wanted to identify how four different forces (IT professionals, marketers, government and consumers) frame the argument for and against online behavioral advertising. In order to accomplish this I performed an in-depth literature view with a focus on understanding the perspectives of each group. As noted, each group has a unique perspective towards online behavioral advertising and it was made clear that consumers and the government act as the driving forces. Secondly, I was interested as to why the key audience of 18 to 24 year olds accepts or rejects tailored advertising. Conducting in-depth interviews with 18 to 24 year old college students allowed me to explore the extent to which external forces affect their acceptance of online behavioral advertising. Interviewees’ insights were grouped into nine categories, which revealed an emphasis on respecting data privacy as well as advantages of convenience. Overall, respondents identified moderate risks and benefits with tailored advertising. With consumers and government acting as the largest bottlenecks for the success of tailored advertising it is increasingly important IT develops ad programs, which are transparent in nature and clearly define what type of information is being collected. A more consumer- focused perspective will help all three parties (IT professionals, marketers and government) be more efficient and develop better solutions to today’s advertising dilemma. As shown through the conceptual framework and the Facebook Beacon example it is consumers who hold the ultimate control in whether tailored advertising will become a successful future advertising model. This study supports and encourages the further exploration of consumer’s opinions and reactions to online behavioral advertising. 
 Lilke‐37

  • WORKS CITED Baldas, T. (2009, August 19). Everybody’s getting on case against bad ads. The National Law Journal. Benander, K. (2008, August 8). Yahoo! announces new privacy choice for consumers. [Press Release]. Yahoo! Inc. Center for Democracy and Technology. (2008, July 31). A briefing on public policy issues affecting civil liberties online from The Center of Democracy and Technology. Policy post 14.12. Corbett, P. (2009, January 5). 2009 Facebook demographics and statistics report. Federal Trade Commission Town Hall (2007, November 1-2). Ehavioral Advertising: Tracking, targeting & technology. Federal Trade Commission Staff Report (2007, December 20). Online behavioral advertising: Moving the discussion forward to possible self-regulatory principles. Federal Trade Commission. (2009, February 12). FTC staff revises online behavioral advertising principles (Press release). Federal Trade Commission Staff Report. (2009, February 12). Self-regulatory principles for online behavioral advertising. Washington, DC: U.S. Government Printing Office. Keizer, G. (2008, August 25). Microsoft adds privacy tools to IE8. Computerworld.com. Lane v. Facebook, Inc., Case5:08-cv-03845-RS (N.D California 2008). 
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  • Leggatt, H. (2007, September 13). Behavioral advertising attracts more consumer attention. Biz Report. McCarthy, C. (2008, August 17). Blockbuster sued over role in Facebook’s Beacon ad program. CNET. McGeveran,W. (2009) Disclosure, endorsement and identity in social marketing. The Board of Trustees of the University of Illinois: University of Illinois Law Review. Perez, J. (2007, December 3). Facebook’s Beacon ad system also tracks non-Facebook users. PC World. Raysman, R., Brown, P. (2009, February 10). Technology initiatives in the new administration. Media Law & Policy. Singel, R. (2008, June 18). Report: NebuAd forges packets, violates net standards. Wired. Story, L., Stone, B. (2007, November 30). Facebook retreats on online tracking. The New York Times. Teinowitz, Ira. (2009, February 12). FTC to marketers: Self-regulate behavioral targeting. Ad Age. Turow, J., King, J., Hoofnagle, C. J., Bleakley, A., & Hennessy, M. (2009). Contrary to what marketers say, Americans reject tailored advertising and three activities that enable it. University of Pennsylvania and University of California-Berkeley. Wong, N. (2009, March 11). Giving consumers control over ads. Google Public Policy Blog. 
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  • APPENDIX A CONSENT FORM Online
Behavioral
Advertising:
Weighing
the
Risks
and
Benefits
 
 
 You
are
invited
to
be
in
a
research
study
on
the
subject
of
online
behavioral
advertising
or
 tailored
advertising.
You
were
selected
as
a
possible
participant
because
you
are
taking
a
 course
at
the
School
of
Journalism
and
Mass
Communication.
I
ask
that
you
read
this
form
 and
ask
any
questions
you
may
have
before
agreeing
to
be
in
the
study.
 
 This
study
is
being
conducted
by:
Jeanine
Lilke,
Undergraduate
senior,
School
of
Journalism
 and
Mass
Communication
 Background Information The
purpose
of
this
study
is:
To
further
understand
the
perceptions
of
18
to
24
year
olds
 towards
online
behavioral
advertising.
Tailored
advertising
occurs
when
a
company
such
 as
a
search
engine
or
a
Web
site
follows
an
individuals’
online
behavior.
Then,
they
tailor
 advertisements
based
on
those
behaviors.
I
will
be
asking
you
to
evaluate
your
perceived
 risks
and
benefits
of
online
behavioral
advertising.
I
will
not
ask
any
specific
questions
 regarding
your
online
behavior.

 
 Procedures:
 If
you
agree
to
be
in
this
study,
we
would
ask
you
to
do
the
following
things:
 • Answer
questions
regarding
your
familiarity
of
online
behavioral
advertising
 • Answer
questions
regarding
your
perceived
risks
of
online
behavioral
advertising
 • Answer
questions
regarding
your
perceived
benefits
of
online
behavioral
 advertising
 
 Risks and Benefits of being in the Study There
is
a
minimal
privacy
risk
because
participants
will
be
asked
to
weigh
the
risks
and
 benefits
of
online
behavioral
advertising.
Participants
will
also
be
asked
questions
about
 their
opinions
towards
these
types
of
ads.
All
questions
are
voluntary
and
participants
can
 skip
any
question
they
feel
uncomfortable
answering.
Due
to
this,
the
risk
is
minimal.
 
 The
benefits
to
participation
are:
First,
participants
will
learn
more
about
the
process
of
 conducting
an
in‐depth
interview
by
being
an
active
participant
in
the
process.
Second,
 participants
have
the
ability
to
learn
more
about
online
behavioral
advertising.
Finally,
 participants
will
be
able
to
earn
credit
or
extra
credit.


 
 Compensation:
 You
will
receive
payment:
two
credits
to
apply
towards
the
Sona
System
database.
Credits
 will
be
rewarded
within
24
hours
of
completion
of
the
study.

 
 
 Lilke‐40

  • Confidentiality:
 The
records
of
this
study
will
be
kept
private.
In
any
sort
of
report
we
might
publish,
we
 will
not
include
any
information
that
will
make
it
possible
to
identify
a
subject.
Research
 records
will
be
stored
securely
and
only
researchers
will
have
access
to
the
records.
The
 principal
investigator
will
have
access
to
the
tape
recording
up
to
30
days
after
the
 interview.
At
that
time
the
interviews
will
be
transcribed
and
the
tape
recordings
will
be
 erased.
The
transcribed
versions
of
the
interviews
will
use
code
identifiers
and
any
 information
that
may
be
used
to
identify
the
participant
will
be
edited.

 
 Voluntary
Nature
of
the
Study:
 Participation
in
this
study
is
voluntary.
Your
decision
whether
or
not
to
participate
will
not
 affect
your
current
or
future
relations
with
the
University
of
Minnesota.
If
you
decide
to
 participate,
you
are
free
to
not
answer
any
question
or
withdraw
at
any
time
with
out
 affecting
those
relationships.

 
 Contacts
and
Questions:
 The
researcher
conducting
this
study
is:
Jeanine
Lilke.
You
may
ask
any
questions
you
have
 now.
If
you
have
questions
later,
you
are
encouraged
to
contact
them
at
763.218.4701
or
 jeaninelilke@gmail.com.

 
 This
research
is
being
conducted
under
the
advisement
of
Professor
John
Eighmey.
He
can
 be
reached
at
eighmey@umn.edu
or
612‐626‐5528.

 
 If
you
have
any
questions
or
concerns
regarding
this
study
and
would
like
to
talk
to
 someone
other
than
the
researcher(s),
you
are
encouraged
to
contact
the
Research
 Subjects’
Advocate
Line,
D528
Mayo,
420
Delaware
St.
Southeast,
Minneapolis,
Minnesota
 55455;
(612)
625‐1650.
 
 You
will
be
given
a
copy
of
this
information
to
keep
for
your
records.
 
 Statement
of
Consent:
 I
have
read
the
above
information.
I
have
asked
questions
and
have
received
answers.
I
 consent
to
participate
in
the
study.
 
 
 Signature:
________________________________________________
Date:
__________________
 
 
 Signature
of
Investigator:
_____________________________________
Date:
__________________
 
 Lilke‐41

  • Appendix B Interview Discussion Guide For my thesis project at the University of Minnesota, I am conducting research on the perspectives 18 to 24 year olds have towards tailored advertising. I am not looking for a particular answer, just the perspective of young adults. I will begin with a brief overview of tailored advertising provided by the Federal Trade Commission. Tailored advertising occurs when a company follows an individual’s online behavior. Then, they tailor advertisements based on those behaviors. This practice allows businesses to align their ads more closely to the inferred interests of their audience. In many cases, the information is not personally identifiable in the traditional sense, that is, the information does not include the consumer’s name, physical address or similar identifier. Instead, businesses generally use “cookies” to track consumers’ activities and associate those activities with a computer. Here is an example of how behavioral advertising might work. A consumer visits a car Web site to browse new models. Later, the consumer visits another Web site such as a news site or a social network. While here, the consumer receives an advertisement for the car brand they searched before. This is a simple example. In a slightly more sophisticated example, a company might combine information from two different activities. Before we get started, do you have any questions regarding tailored advertisements? General Advertising Questions: 1. How would you describe advertising? 2. Can you give me some examples of it? 3. As your day goes by, where do you mostly see advertising? 4. What are some consumer benefits of advertising? 5. What are some consumer drawbacks of advertising? So now I’m going to ask you more about tailored advertising. Questions about the Benefits: 6. What personal value may you receive from tailored advertisements? 7. How certain are your feelings in this area? Questions about the Risks: 8. Do you see any risks connected with tailored advertising? 9. Do you see anything about this you don’t like? Future Opinions: 10. If a search engine gave you a choice to opt-out of tailored ads what would you decide to do today? 11. How likely are you to be more open about this topic in the future? 12. How certain are your feelings in this area? Thank you so much for your input. 
 Lilke‐42