This document summarizes a study on young adults' perceptions of online behavioral advertising. The study explores how different stakeholders (IT professionals, government, marketers, and consumers) view behavioral advertising and influence its acceptance. Through interviews with 18-24 year olds, the study found they view moderate benefits and risks to tailored ads. Benefits included convenience and relevance, while largest drawbacks related to data privacy concerns. The results indicate marketers could benefit from increasing transparency, being responsive to consumer concerns, and testing ad programs before launching them. Addressing actual and perceived privacy risks may increase consumer comfort with a process they are largely unaware of.

1.
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
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2. 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,
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3. 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.
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4. 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
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5. 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
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6. 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.
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7. 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
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8. 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
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9. 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)
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10. 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
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11. 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).
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12. 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
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13. 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
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14. 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
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15. 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.
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16. 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
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17. 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
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18. 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
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19. 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
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20. 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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21. 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
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22. 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

23. 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

24. 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

25. 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

26. 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

27. 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

28. 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

29. 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

30. 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

31. (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

32. 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

33. 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

34. 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

35. 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

36. 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

37. 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

38. 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
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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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39. 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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40. 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

41. 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

42. 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