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International Journal of Business and Social Science Vol. 3 No. 18 [Special Issue – September 2012]
114
The Importance of Online Behavioral Advertising for Online Retailers
Gresi Sanje, PhD
Istanbul Bilgi University
Faculty of Communication
Department of Advertising
Turkey
Isil Senol, PhD
Istanbul Bilgi University
Faculty of Communication
Department of Advertising
Turkey
Abstract
Online behavioral advertising refers to the delivery of ads to targeted users based on the behavioral information
collected on each individual user’s web search and browsing behaviors. Although only 8% of all online
advertising is behaviorally targeted, it is expected to expand its market share due to its cost-effectiveness and
reach to a selected target audience. Since online behavioral advertising uses a targeted approach and the
advertisement of the retailer is directed to the most appropriate and interested consumer and online retailers
interact with online consumers for their transactions, online behavioral advertising becomes a very important
tool especially for online retailers. In this scope the study aims to develop an understanding about the
relationship between online shopping and online behavioral advertising and therefore investigates the
relationship between behaviour in online shopping and attitude towars online behavioral advertising. As the
result, the study suggests that individuals, who shop online for various reasons, tend to have positive attitude
towards online behavioral advertising.
Key Words:
Online Advertising, Online Behavioral Advertising, Online Shopping
1. Introduction
The increasing popularity of the internet as a business vehicle in general, and an advertising medium in particular,
is due to its current size, future growth forecasts, wide demographics, ability to facilitate the global sharing of
information and resources, potential to provide an efficient channel for advertising as well as marketing and
potential as a sales channel (Hoffman and Novak 1996). Besides being a business vehicle, internet is providing
users with tremendous access to information about products and brands from different sources from everywhere
in the world. Moreover with the combination of less time available for shopping and limited offline information-
processing capability, consumers are showing more interest in shopping online (Shergill and Chen 2005). And
inevitably companies are taking this huge opportunity to use internet as a medium to attract and maintain current
and potential customers offline as well as to make sales online (Ling et al 2010).
In this vein, in order to reach the online consumer, satisfy a need and make transaction happen, companies and
especially online retailers must understand consumers’ perceptions, interests and needs. Today, by correlating the
individual’s visits to websites, clicks of the ads, inferences about age range and sex, and approximate physical
location based on the computer's IP address, advertisers and the agencies are able to build profiles of that
individual's characteristics and likely interests (McDonald and Cranor 2010) and place the advertisement
accordingly. This approach is named as online behavioral advertising.
Online behavioral advertising refers to the delivery of ads to targeted users based on the behavioral information
collected on each individual user’s web search and browsing behaviors (Yan et al 2009).
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Although it is a very beneficial tool both for individuals and companies, it is considered to be one of the most
controversial forms of advertising due to its implementation process. The process starts by collecting data,
through cookies, from a particular computer or device regarding internet viewing behaviors across multiple
domains (Advertising Internet Bureau). Although data collection on the internet is not done for advertising
purposes it is collected in the internet cloud in general, still targeted advertising can irritate or make individuals
suspicious and feel as their confidentiality rights are violated. But on the hand targeted advertising offers
individuals to get news and learn the offers about products and services that they are interested in.
Inspite of the contradictions and discussions, the popularity of online targeted advertising is increasing among
advertisers and websites. It is especially a very useful tool for online retailers. Since online retailers actualize thier
transactions in the virtual world, to reach the most interested target audience becomes vitally important and online
behavioral advertising gives the opportunity to reach this interested audience. Although online behavioral
advertising is continuously being studied, it is still underexplored in academia (Yan et al, 2009). Therefore this
paper aims to make a contribution to academia by explaining online behavioral advertising and its relation to
online shopping. Within this scope a research is conducted among 122 college students from various faculties in
order to understand the connection level between online shopping and online behavioral advertising. As for the
findings, it has been found that individuals, who shop online for various reasons, tend to have positive attitude
towards online behavioral advertising.
2. Literature Review
This section presents a review of previous studies on online advertising and online behavioral advertising. After
online advertising and online behavioral advertising is reviewed the relation between online behavioral
advertising and online shopping is examined.
2.1. An Overview to Online Advertising
Just like every other medium such as TV or newspapers, online needs advertising on websites to fund its content
so that users can reach the majority of the content for free, rather than pay a subscription to visit (Advertising
Internet Bureau). And advertisers use and allocate a budget for online advertising since it will be a major mistake
for the advertiser to ignore such a common medium. There are several forms of online advertising and as Varnalı
(2012) mentioned it is nearly impossible to group the types of online advertisements. Yet there are some online ad
formats that became more common or popular in recent years such as email advertisement, display advertisement,
text advertisement and online video advertisement (Varnalı 2012). Email advertising is sent by advertisers to
consumers subscribed to their mailing lists. (Breuer et al. 2011). The consumer's permission distinguishes email
advertising from unsolicited commercial email messages such as spam or junk (Breuer et al. 2011). After internet
access became common, advertisers found the chance of reaching more consumers with high-quality photography
and sophisticated email messages (Miller et al. 2006).
Online display advertising is defined as static or moving banners which either goes at the top, side or middle of a
webpage (Advertising Internet Bureau). This type of online advertising is placed on other websites and when
clicked the advertisement redirects the user to the advertiser’s website (Breuer et al. 2011). Without intending to
do so, in 2000 Google initiated text advertisement by accepting from its first advertisers’ text ads that were strictly
limited in length and in aggressiveness of punctuation and phrasing (Miller et al. 2006). Today text advertising is
defined as an online advertising type that embeds advertisements within the text of Web sites which except to host
them (PC Magazine Encyclopedia). But as the online users started to spend more and more time on the internet,
users began to demand more entertainment aside from the demand of information (Miller et al. 2006) and this
created a new popular online advertising known as online video advertising. Online video advertising is defined
as video clip advertisement that is shared through the Internet, typically through blogs and other media-sharing
websites (Feed Company 2008).
When it comes to purchasing and measuring, online advertising is generally purchased or measured in three
contexts: Cost per mille, Cost per click or Cost per acquisition. Cost per mille refers to per a thousand of
impressions and payment is done depending on the exposure of the message (Brajnik and Gabrielli 2010). If a
banner is being shown 100,000 times its CPM is 200. The second method is known as cost per click measures
clicks.
International Journal of Business and Social Science Vol. 3 No. 18 [Special Issue – September 2012]
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In this method, the advertiser makes the payment through the number of redirection to their websites or clicks on
their listing (Yan et al. 2009). And the third popular and most common method especially among online retailers
is cost per acquisition (TLVMedia). Cost per acquisition is based on performance and the payment is done
explicitly per transaction based on lead generation, online inquiries, registrations, referrals, orders, or purchases
(Brajnik and Gabrielli 2010).
Today information technology enables online advertisements to be targeted to a selected audience. In other words,
online advertising can be targeted to users most likely to be interested in a particular product or service
(McDonald and Cranor 2010). Users can benefit from since they will be exposed to ads that are related to their
personal interests. There are three major targeting methods in online advertising, contextual targeting, behavioral
targeting and geographical targeting. Contextual targeted ads are based on the related content that the user is
reading or browsing online (Webadvantage.net). For instance if the user is reading a news on a news website
about entertainment, the user may see contextual ads for a movie or an event. This type of targeted advertising is
the similar approach that is used for text advertising. Behavioral targeting is the practice of collecting data about
an individual's online activities for use in selecting which advertisement to display (Donald and Cranor 2010).
The third targeting method is geographical targeting. In this method, online advertising is based on the user’s
geographical location and geographical targeting also includes network buys through radio, television and
newspaper websites, as well as localized search engines and directories such as Yahoo! Local or Google Local
(webadvantage.net).
2.2. Online Behavioral Advertising
Keyword search activities and clicks enable advertisers to tailor their advertisement for a specific group of online
users by linking their advertisement messages to some pre-identified words and clicks (Yoo 2011) and this
targeted advertising is known as online behavioral advertising. Online behavioral advertising refers to the delivery
of ads to targeted users based on information collected on each individual user’s web search and browsing
behaviors (Yan et al. 2009). As IAB Europe describes, online behavioral advertising is “the collection of data
from a particular computer or device regarding Web viewing behaviors over time and across multiple Web
domains not under Common Control for the purpose of using such data to predict consumer preferences or
interests to deliver online advertising to that particular computer or device based on the preferences or interests
inferred from such Web viewing behaviors.” In short, it is a way of targeting advertisements based on the online
behavior and exposing the ads according to the user’s interests (Advertising Internet Bureau).
The word behavioral refers to type of data that is collected and this data is mainly collected and stored through
cookies and most commonly this behavior relies on users’ behavior rather than the identity of the users (IAB
Europe). Cookies are small text files that are placed on the user’s computer by websites visited and cookies
provide information to the website about how users interact with the site (McDonald and Cranor 2010). When a
user access to a website the cookies are placed on the computer and cookies start with recording the IP address
(Komanduri et al 2010). In this way website can navigate and identify the particular interest of the user and when
a website agrees on sharing the information, it can be used for advertising purposes. Yet if a user decides to
remove the cookies, the user can remove the cookies at any time by the settings on the browser. After gathering
the necessary data from the hosts or websites, online behavioral advertising is implemented through grouping the
shared interests of the users, based upon their web browsing activities (Advertising Internet Bureau). User
segmentation and user segments ranking are the common general steps in behavioral targeted advertising. The
first step aims to segment users according to their online behaviors whereas the second step, user segments, is
applied to rank targeted user segments for an advertisement (Yan et al. 2009).
After grouping the user interest, advertisement is displayed to them every time the user visits a website which
agreed on this advertising activity. For example, after booking a flight on an airline’s website might, the user
might be exposed to a travel-related advertisement about the destination the user is planning to fly while ordering
a burger from the local burger joint or surfing in a book website. Generally it is accepted that greater relevance of
online behavioral advertising often generates higher click-through than other types of online advertising such as
email advertising or banner advertising (Yoo 2011) since it is tailored to the behavior and therefore the interest of
the user (Advertising Internet Bureau). Because it generates higher click-through and appeals directly to the
users’ interest by determining the users’ actions (Slegg 2006), transaction rates of these types of targeted
advertisements are higher than the other online advertising types (Yoo 2011).
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In general all providers have to comply with the law and the information that is used for providing the targeted
advertisements is not personal (Advertising Internet Bureau). And to provide confidence of the users institutions
such as Advertising Internet Bureau or Federal Trade Commission is publishing several self-regulatory reports on
online behavioral advertising. But this doesn’t concretely answer the scrutiny issues or gain the users trust to these
types of advertisements. The legality of some behavioral advertising business practices is still a question to be
answered (McDonald and Cranor 2010) and the guidelines for self-regulation may not be enough to convince the
users since some users get nervous about being targeted with ads today because of a website they visited
yesterday (Slegg 2006). Another problematic issue of online behavioral advertising is the lack of knowledge
among the users. Although there is a majority that understands the role of the cookies, most of the users are
unclear about the important details such as cookies may be combined with other data, what type of data is stored
in cookies, can they block online behavioral advertising and if blocking cookies is enough for privacy or not to
receive any keyword ads (McDonald and Cranor 2010). This confusion and lack of knowledge of the users about
cookies and how safe or dangerous they really are make the user less likely to accept third-party cookies (Slegg
2006) or well, online behavioral advertising. Considering this problem Advertising Internet Bureau launched an
icon in 2012 in order to give the option of blocking these online behavioral adverts and gain trust in online
behavioral advertising activities.
Although it is a very useful channel both to the web server and the advertiser, they face problem other than the
user refusal to accept the ads which is the inability of making a differentiation between multiple users' on the
same computer (Slegg 2006). For instance if the computer is used in the family household and shared with all
family members, it will make it harder, if not impossible, to find the right exact audience of the family. In that
case the targeted advertisement is not targeted to the interest and eventually these advertisements result in very
low click-through and conversion rates. Anyhow online behavioral advertising is getting a huge acceptance from
the hosts and websites. Google and Yahoo use online behavioral advertising since the beginning of the century
and announced their interest in applying online behavioral advertising to public at the end of 2009 (McDonald and
Cranor 2010). Currently, only 8% of all online advertising is behaviorally targeted (Slegg 2006), but since it is a
very cost-effective way of executing an online advertising campaign it is very likely that the popularity may
increase rapidly in coming years.
2.3. The Link between Online Advertising and Online Shopping
Advancement in the internet technology has facilitated the growth of internet and thereon internet became one of
the most rapidly growing forms of shopping. There are 2,267,233,742 internet users that accounts for 32.7% of
the world population (Internet World Stats, 2012). Global online shopping are forecasted to exceed 1 Trillion
dollars US by 2013, with sales growth of 19% per year (CartConnoisseur 2012) which makes online shopping as a
very valuable market. Online shopping is defined as the process consumers go through to purchase products or
services over the internet (Ling et al. 2010). Online shopping allows firms to conduct business with consumers in
the virtual environment without investing on personnel or real estate property. The company’s, by using internet
as a commerce channel, cut their marketing costs thereby they can either reduce price or increase profit (Shergill
and Chen 2005) and reach the target audience that they cannot reach due to geographic limitations. From the
consumer’s viewpoint, online shopping allows individuals to seek information and compare various alternatives
from around the world without any geographic limitation (Ling et al. 2010). Moreover the interactive nature of the
internet offers opportunities for consumers to use the online shopping offerings from every location in the world,
enable direct comparison of brands and products, and reduce prospective buyers’ information search costs (Alba
et. al. 1997).
Yet while shopping online, consumers interact in the virtual environment, consumers cannot touch, see or
demonstrate the product, moreover have the give personal information and credit card number. Therefore online
shopping is perceived to be more risky. As the result trust and risk factors play a prominent role for online
shopping and transactions (Ling et al. 2010). Although online shopping is still suspicious to some online users, on
the other hand, it is a known fact that consumers that are accustomed to shop online, are less likely to have
security concerns and more likely to shop online again compared to consumers that are less familiar with online
shopping (Shergill and Chen 2005). This fact causes the basic of repetitive buying behavior and it makes the
online shopping category a growing industry. Since online shoppers are the repetitive buyers, with a good
understanding of online shoppers, online retailers can develop effective and efficient online shopping marketing
strategies to retain existing customer and attract new customer (Ling et al. 2010).
International Journal of Business and Social Science Vol. 3 No. 18 [Special Issue – September 2012]
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Most online shopping sites use online advertising as one of their main marketing communication channel by
which they can interact with online consumers for transactions (Kim et al. 2010). Yet the success of an
advertisement depends on how close the advertiser and the agency understand the needs, desires and interests of
the consumer. The virtual world today gives the opportunity to get a closer look at the consumer by analyzing
their online behavior. By analyzing their behavior and learning their interest, online retailers can reach to a
targeted audience. By targeted advertising, the message will send to the selected audience that will find the offer
most relevant and thereby all parties, consumers and retailers, will benefit from this targeted advertising approach.
Consumers will receive information and offers about products and services they are interested in and retailers will
spend their efforts to a relevant customer base. Since online behavioral advertising uses a targeted approach and
the advertisement of the retailer is directed to the most appropriate and interested consumer, online behavioral
advertising becomes a very important tool especially for online retailers and online shopping environment in
general.
3. Methodology: Procedures and Participants
The aim of the study is to develop an understanding about the relationship between online shopping and online
behavioral advertising. In this scope, the relationship between behaviour in online shopping and attitude towars
online behavioral advertising is investigated. In order to develop an understanding regarding the relationship
between behaviour in online shopping and attitude towards online behavioral advertising, a questionaire is
conducted among 122 Istanbul Bilgi University students studying different majors. The homogenity of our sample
was important for the study since the research was done in order to understand if there existed a direct correlation
between two variables. In this context, the hypothesis of the research was determined as;
H
1
: Individulas that conducted online shopping will have a positive attitude towards online behavioral
advertising.
During the research period, a three scaled questionaire was prepared and published through
www.freeonlinesurveys.com where data collection took approximately a month. In order to understand whether
the participants shop online or not, a three itemed scale was designed. Delafrooz, Paim, Kahatibi’s (2011)
“orientations of online shopping” scale is used for measuring both behaviour in and attitude towards online
shopping, and lastly Ducoffe’s (1995) ‘Attitude Toward General Web Ads’ scale is implemented, and statements
for this scale is updated for for measuring attitude towards online behavioral advertising. For all three of the
scales, a six point likert scale is applied and participants are asked to evaluate the statements as 1 for strongly
disagree and 6 for strongly agree.
4. Findings
4.1. Analyses
Reliability estimates were obtained for each of the construct domains. Cronbach’s α values are above 0.75 for
each construct (Table:1).
Table 1: Characteristics of the variables measured in the study
# of
Items Min.
Max. µ SD.
α
Online Shopping
General
3 1 6 3,7486
1,44778
,829
Attitude towards
Online Shopping R. S.
10 1 6 3,2893
1,24022
,906
Atittude towards
Online Behavioral
Advertising
8
1 6 4,1168
,96420
,704
When the mean scores of all three scales are calculated, it is found out that, all mean scores are higher than 3.00,
which have shown that the participants are familiar with shopping online, have positive attitude towards online
shopping, and also have positive attitude towards online behavioral advertising broadly.
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The mean value of the item 1, ‘I do my shopping online’ was found = 3, 53. According to this score, it is possible
to say that most of the participants have marked ‘I agree’ and ‘I mostly agree’ amongst all other answers. The
high mean scores of statments A2 (I think it is practical to shop online) and A3 (I prefer to shop online instead of
going to a real store) also supports that the participants are highly familiar with online shopping (Table 2).
Table 2:
Descriptive Statistics for the Items of ‘General Online Shopping’ Scale
N Min. Max. µ
Std. Deviation
A1 122 1,00 6,00 3,5328 1,64736
A2 122 1,00 6,00 4,2787 1,66769
A3 122 1,00 6,00 3,4344 1,71521
Valid N (listwise) 122
The first three statements of “Attitude Towards Online Shopping” are basicly about saving time via online
shopping, and the mean scores show that participants find online shopping time-saving. The mean value of the
item 4, ‘I only buy the products that I really need via Internet’ was found = 3,8443. According to this score, it is
possible to say that most of the participants are agreed that they prefer shopping online when they find a product
that they really need. Related to statement 4, statement 5 suggests a link between new products and online
shopping. The high mean value of the item 5, ‘Shopping online is fun since it helps me to reach new products’
shows that the participants are agreed on this link.
Table 3: Descriptive Statistics for the Items of
‘Attitude Towards Online Shopping’ Scale
N Min. Max. µ Std. Deviation
B1 122
1,00
6,00
3,6230
1,72645
B2 122
1,00
6,00
3,6393
1,75370
B3 122
1,00
6,00
4,4508
1,72537
B4 122
1,00
6,00
3,8443
1,78618
B5 122
1,00
6,00
3,9754
1,83836
B6 122
1,00
6,00
2,6639
1,59861
B7 122
1,00
6,00
2,7705
1,65038
B8 122
1,00
6,00
2,6311
1,59130
B9 122
1,00
6,00
2,4918
1,53873
B10 122
1,00
6,00
2,8033
1,60906
Valid N (listwise) 122
The last five statements of the scale, try to examine if participants associate online shopping with fun. The mean
scores for these five statements change between 2.4 and 2.8, which can be interpreted as most of the participants
have marked “I mostly don’t agree” and “I don’t agree” as an answer for these statements. Overall mean scores of
the scale show that the sample is highly familiar with and have a positive attitude towards online shopping, since
they find it time-saving. On the other hand, the sample does not shop online for the hedonstic reasons, they use
online shopping only for their needs, and the new products that it is not possible to find outside (Table 3).
Table 4:
Descriptive Statistics for the Items of ‘Attitude Towards Online Behavioral Advertising’ Scale
N Min. Max. µ Std. Deviation
C1 122
1,00
6,00
4,0656
1,62998
C2 122
1,00
6,00
4,7869
1,64759
C3 122
1,00
6,00
3,9344
1,55737
C4 122
1,00
6,00
3,8525
1,50301
C5 122
1,00
6,00
3,5246
1,64750
C6 122
1,00
6,00
3,6230
1,68281
C7 122
1,00
6,00
5,3115
1,71566
C8 122
1,00
6,00
3,8361
1,75979
Valid N (listwise) 122
International Journal of Business and Social Science Vol. 3 No. 18 [Special Issue – September 2012]
120
Lastly, the mean scores for ‘Attitude Towards Online Behavioral Advertising’ show that the participants have
possitive attitude towards online behavioral advertising, and they find the advertising that are relevant to their
interest areas very informative, fun, valuable, essential, time saving, and helpful for decision making. Statements
2 and 7 are reverse coded in order to change their negative meanings into positive (Table 4). The independent
variable in the current study (attitude towards online shopping) were entered into a multiple regression analysis
with the dependent variable, attitude towards online behavioral advertising (Table 5).
Table 5: Regression Analysis of attitude towards online shopping and online behavioral advertising
Variable
B SE (B) β t Sig. (p) P
Attitude towards online shopping
,199 ,069 ,276 2,882 ,005 ,000
Independent variable: Attitude t/ Online Behavioral Advertising Total
Findings revealed that attitude towards online shopping (
β
= .276) significantly explained the attitude
towards online behavioural advertising, thus H
1
is accepted.
4.2. Discussions
Anticipating that online behavioral advertising is especially important to online retailers and useful for consumers
to learn about new products or offers that are suitable for their interests, the main hypothesis in this study was;
“Individulas that conducted online shopping will have a positive attitude towards online behavioral advertising”.
One of the main results of this study was that online shopping is highly popular and preffered amongst university
students because of its time saving feature. In accordance with the mean scores of “orientations of online
shopping scale”, the results of the “attitude towards online behavioral advertising” scale showed that most of the
participants have selected “I agree” and “I mostly agree” as an answer to the statements. From this point of view,
it is possible to say that, university students in Turkey would like to meet the new and offers products, but they
don’t want to spend so much time while doing it, thus, they find online behavioral advertising very helpful for
saving time while shopping online. Our hypothesis is supported by the findings, and a possitive attitude towards
online behavioral advertising is detected amongst university students.
5. Conclusion
Online advertisements can take advantage of addressable media technology to select appropriate advertisements
that are congruent with consumers’ online behaviors, thereby making the advertisements more relevant to
consumers (Kim et al. 2010). This online behavioral advertising approach is beneficial for everyone but since
online retailers do their transactions online, online behavioral advertising becomes more important to the online
retailers. And as found out in the study individuals that shop online have a positive attitude towards online
behavioral advertising. This supports the importance of online behavioral advertising for online retailers and
online retailers should give a special importance to these types of advertisements.
Regarding to the findings of the study, one could suggest that online shoppers should take online behavioral
advertising into consideration in their marketing communication plans since online shoppers have a positive
attitude towards them. In this approach the online retailer can reach to a selected audience and both the retailer
and the consumer may benefit from it. Yet, although online behavioral advertising and online advertising in
general is a powerful tool, it is suggested to companies to supplement Web advertising with traditional advertising
since online shoppers also from publications and other traditional media (Teo 2002).
As for the limitations and future research probabilities, this study was done in a selected demographic and
geographic area the same study could be applied to a different demographic and geographic area. Additionally the
study investigated the attitudes towards online behavioral advertising but a study that will investigate the
transaction rates of these online behavioral advertising, will make a meaningful contribution of the impact of
these type of advertising executions. Lastly the study have not investigated attitudes of non-online shoppers
attitudes towards online behavioral advertising, which is very important to companies that uses online advertising
but doesn’t determine any online sales. Since online behavioral advertising targets a selected audience it could be
a very cost-effective channel for online advertising campaigns.
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