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Internet Advertising: The Medium is the Difference
October 4, 1999
Xavier Drèze
Fred Zufryden
Internet Advertising: The Medium is the Difference
October 4, 1999
Xavier Drèze
Fred Zufryden
The underlying full-duplex networked organization of the Internet transforms the
traditional one-way relationship between advertisers and consumers that is
inherent in standard advertising. Internet content providers take on both the roles
of conduits and interaction enablers in a two-way interaction with prospective
consumers.
2
Introduction
Internet advertising is growing at an impressive rate. A recent report by
PriceWaterhouse-Coopers estimates 1998 online ad revenues at $1.92 billion, more than twice
those of 1997. By year 2000, it has been projected that ad revenues will grow to a level of $ 4.3
billion (IAB, 1998). This spectacular growth comes as no surprise if one considers that on the
one hand, advertisers are always looking for new ways to reach their target audience, and on the
other hand, web site operators are always looking for new sources of revenues to finance their
ever-mounting operating costs. The willingness of both parties to work together does not mean
however that the blending of Internet content and Internet advertising will be painless. For
reasons that we will investigate in this paper, one cannot simply transpose current advertising
practices from television, or newspaper, to the Internet. Indeed, in order to take full advantage of
the potential of Internet advertising, and to avoid its pitfalls, one needs to rethink the consumermedium
interaction as it applies to Internet advertising.
In this article, we show how the underlying full-duplex networked organization of the
Internet transforms the traditional one-way relationship between advertisers and consumers that
is inherent in standard advertising. On the Internet, content providers take on roles of both
conduits and interaction enablers in a two-way interaction with prospective consumers. This
new model profoundly affects the relationship between each player. Consumers now interact
with both content providers and advertisers. Content providers are not responsible for
advertisement fulfillment anymore. It also affects how content providers are compensated for
their services. As conduits, their compensation scheme was simple. As relationship creators,
their value is harder to assess.
3
We focus on two key differences between advertising in traditional broadcast media (e.g.,
Radio or Television) and that online. We first look at how the two-way networked organization
of the Internet contrasts sharply with traditional broadcast media. Second we look at how the
advertising messages are imbedded on the Internet and other media. We examine some of the
implications of the fact that banner ads typically share the screen real estate as opposed to take
over it, in a linear fashion, during the broadcast of the advertising message, as television
advertising does.
Contrast of Broadcast and Request-based Media Frameworks
In traditional media settings, the flow of information between advertisers and consumers
follows a unidirectional, and linear, path (see figure 1). Advertisers enter in an agreement with
content providers whereby they purchase space on a provider’s medium where their promotional
messages will be inserted. The content provider then merges all the advertising material he has
contracted for with his own content and transmits the whole to prospective consumers. In turn,
consumers elect to receive (i.e., view) or bypass the advertising message (e.g., they can zap by
switching to another channel). For those who are exposed to the ad, the attention given to the ad
message will depend on numerous behavioral factors (e.g., demographics, life style
characteristics, product awareness, product need, use behavior, etc.). In this setting, there is no
direct contact between advertisers and consumers. What advertisers know about their audience
comes from industry reports such as those from AC Nielsen (www.acnielsen.com) or Arbitron
(www.arbitron.com). These reports provide advertisers with information such as Reach (the
number of unique individuals who have been exposed to an ad campaign at least once),
Frequency (the average number of ad exposure for the individuals who have been exposed at
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least once), Gross Rating Points (GRP = Reach x Frequency), and some demographic
information about the reached audience.
The information reported to advertisers is generated through surveys or panels of
consumers that measure audience viewing, or listening, patterns. For example, in the TV
industry, Peoplemeter devices are used to monitor TV viewing patterns (i.e., whether a TV set is
on or off and what program, if any is tuned at a given point in time), and consequently audience
viewing habits, for a representative sample of households. However, for the television medium,
content providers have imperfect information about their audiences. This is because marketing
research firms are merely able to monitor the TV set patterns of a sample subset of the
population rather than the actual viewing patterns of their audiences. Thus, the monitoring of
broadcasts does not provide completely accurate information concerning who is tuned in to
particular programs. Print media, such as newspapers and magazines, fare a little better in that
they can readily estimate the size of their audience from the number of copies they sold.
However, they still experience uncertainty as to the characteristics of their audience as they do
not readily possess information about consumers who chose to buy their publications at a
newsstand rather than those who subscribe.
The Advertiser->Content Provider->Consumer framework, which we call broadcast, is
very efficient in reaching mass markets. It requires a minimum number of interactions and has
been used for more than a century. It is very different from the request-based mode of
information dissemination that occurs on the Internet (see figure 2). On the Internet, advertisers
still contract with content providers to insert advertisements within the programming offered to
consumers. But from this point on, everything is different. First, content providers do not push
their content on consumers at pre-established points in time. Rather, they wait for consumers to
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request the information when they are ready to consume it. Second, content providers do not
broadcast the advertisements linearly along with their content. Rather they send their content to
consumers with an instruction to retrieve the appropriate piece of advertisement directly from the
advertiser. Upon reception of the location of the advertisement, consumers then contact the
advertiser themselves to retrieve the ad. We review the key implications of this drastic change in
the nature of the advertiser-consumer relationship in the next section. To facilitate our
discussion, Table 1 provides a contrasting summary of the features of the Internet and Broadcast
frameworks.
Advantages of Advertising on the Internet
The multiplicity of interactions that come about by the modus operandi of the Internet
creates a wealth of opportunities for marketers (some have called the Internet the Holy Grail of
marketers). First of all, since consumers directly request the content they would like to access, it
becomes easy (at least theoretically) to measure the size of the audience of a particular ad
campaign. Second, since consumers who subscribe to several different content providers
displaying the same ad have to request the ad from the advertisers themselves rather than from
the content providers, it becomes potentially easy for the advertisers to measure the true
frequency of exposure. Third, because the advertiser only serves the actual ad content at the time
when the consumer is ready to consume it, advertisers don’t have to commit on the ad content
until the last instant. This provides considerable opportunity for tailoring an advertising message
to a particular prospective consumer. We now explore some of these opportunities.
6
Accurate measurement
Now that consumers and advertisers interact directly on the Internet, great improvements
in quality of marketing research can be made by shifting from a survey-based to a census-based
method of assessing advertising effectiveness. Figures 1 and 2 suggest the benefits of a censusbased
advertising tracking methodology. In figure 1, the advertiser reaches Consumer 1 through
both Provider 1 and Provider 2. However, given the lack of consumer level data, all the
advertiser knows is that Provider 1 and Provider 2 reach similar demographics. He will have no
indication of the actual overlap between the magazines or television stations. In contrast, the
Internet advertiser will see Consumer 1 come twice (figure 2), once send by Provider 1 and a
second time send by Provider 2. Hence, the advertiser now has an accurate measurement of the
number of consumers who see its ad (Reach) and of the number of times each consumer sees the
ad (Frequency).
The interactive nature of the Internet medium has lead to new criteria for the
measurement of advertising effectiveness: "page views" (or impressions) and "click-throughs."
Impression represents an opportunity for a surfer to see and click on a banner ad within a
publisher's Web page, and click-through represents the committed action of a surfer who actually
clicks on a banner ad in response to its message. This immediate measure of advertising
response is a new concept that can only be measured on the Internet. Many see it as the ultimate
measure of advertising effectiveness.
Potential integration of advertising and marketing research functions
The standard broadcast medium environment only permits the dissemination of
advertising messages to customer prospects. However, because of the bi-directional nature of
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the request-based Internet advertising environment, both the dissemination of information (in the
form of advertising messages) and the gathering of information (in the form of market research
data) are made possible. Because the dissemination and gathering of information can be done
simultaneously at a given Web site, the Internet medium offers considerable advantages relative
to the integration of the advertising and marketing research functions. First, the Internet medium
provides for timely and speedy gathering of research information (e.g., information regarding
page views, visit duration, and even on-line purchase statistics can be gathered as a customer
navigates through the pages of a Web site). The cost of gathering research information in this
manner is less than that of standard research methods such as off-line surveys (i.e., information
can be gathered very cost effectively on the Internet by means of available tracking software that
may be installed on a Web site's server). As was mentioned before, the information gathered on
the Internet is census-based and thus does not incorporate any sampling error. Further, the data
can be collected in an unobtrusive manner and thus does not produce response biases1.
The ability to instantaneously measure the response of consumers to a particular banner
ad is a powerful tool to optimize advertising effectiveness. Drèze and Zufryden (1997) showed
how the market research technique of conjoint analysis could be used to develop a Web site
design configuration that would maximize the average number of pages viewed by visitors as
well as the average amount of time spent by visitors on the Web site. A similar methodology can
be used to test and develop advertising message design configurations (e.g., in terms of type of
appeal, colors, font types and sizes, location on page) that would maximize an advertiser's
objective (e.g., maximizing awareness, product interest, or even purchase response).
1 When consumers know they are being surveyed or monitored, they often alter their behavior to conform to what
they believe the researcher thinks is an appropriate behavior, thus invalidating the research. This response bias is
8
Potential integration of advertising and transaction functions
With the growth of e-commerce, the Internet medium provides the additional facility for
consumers to conduct product transactions directly on the Internet. Thus, the bi-directional
nature of the Internet environment provides a way to not only direct advertising appeals and
stimuli to target customers in an effort to encourage customer response but also provides for the
potential realization and tracking of the purchase response on the medium itself. This provides
considerable opportunities for the development and fine-tuning of advertising and marketing
strategies that best stimulate prospective customer's purchase response behavior.
Adaptive Advertising
First, it should be noted that ads from standard media come to prospective customers
whereas prospective customers on the Internet medium come to ads. Furthermore, in contrast to
the mass, or segmented, marketing strategies that are afforded by standard media (e.g., a TV
advertisers can focus their efforts on a given demographic or geographic segments), Internet
advertising creates the potential opportunity of micro-level marketing. This means that an
Internet advertiser can specifically design and tailor a given advertising message to target a
particular individual consumer. For example, an advertiser can chose to deliver a specific ad to a
given individual only after the individual has exhibited a particular type of behavior (e.g., has
expressed a given level of interest in a particular product in view of his origin or previous
clickstream history). As such an individual consumer who comes to an advertiser's site for the
first time might be given advertising in the form of general product information. In contrast, a
repeat visitor might be given more detailed product information in an effort to move him/her
towards a product purchase decision. If one refers back to Figure 2, Customer 1 is in a situation
the marketing equivalent of the Heisenberg uncertainty principle.
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where he retrieves the same ad twice. In this web-based environment, the advertiser can decide
whether he wants the consumer to see the same ad twice, or see two different ads. Further, by
limiting the number of repetitions a consumer is exposed to, advertisers can limit burnout and
maximize their return on marketing expenditures.
An advertiser also has the ability to tailor the ad campaign to the environment the
consumer is involved in at a particular moment. For instance, specific advertising messages can
be tailored to specific search engine keywords. Thus, a particular key word (e.g., PC hardware)
may be used to generate ads and for PC brands whereas a combination of key words (PC
hardware and storage media) might be used to generate ads for CD-ROM, removable hard
drives, or DVD drives.
Challenges in Maximizing Ad Effectiveness on the Internet
The previous section is very upbeat about the potential of online advertising. This
potential is very real and has been demonstrated in case studies in numerous occasions.
Unfortunately, there is a big gap from case studies to large-scale working production-grade tools.
When attempting to unleash this potential on a large scale, marketers have encountered many
implementation issues. The problems generally fall in two broad categories. First, the ability to
track individuals is significantly impaired by the physical implementation of the Internet (e.g.,
caching or IP sharing). Second, although we have information about a lot of users, we know
very little about each one of them. We will now review some critical roadblocks one encounters
when trying to implement the techniques we have just developed.
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Difficulties in identifying unique visitors
As noted in Drèze and Zufryden (1998), in order to develop accurate measures of
unduplicated audience reach for Internet-based advertising, it is necessary to identify unique
visitors' page requests. However, on the Internet, visitor request patterns, Web site traffic, and
flow patterns are generally established on the basis of visitors' (or requestors') Internet Protocol
(IP) addresses. Unfortunately, as Drèze and Zufryden point out, IP addresses are not necessarily
uniquely assigned by a visitor's Internet Service Provider (ISP). In fact, it can be shown that
several Internet users can be assigned the same IP address. To make matter worse, visitors may
be assigned different addresses even within a single Internet session. These idiosyncrasies make
it very difficult to identify unique visitor requests on the basis of IP addresses alone. In fact,
Drèze and Zufryden report significant errors in the measurement of Reach and Frequency of
advertising when IP addresses are used for this purpose.
Problems in measuring multiple ad exposures
A key determinant of the measurement of banner advertising effectiveness is the number of
pages requested by a particular surfer on the Internet. The accurate determination of this measure
is essential for an accurate measurement of the average frequency of advertising exposure on the
Internet. In this regard, one must remember that a Web page is often a complex composite
document that may contain text as well as graphics, sounds and video files. In order to speed up
the retrieval process of the Web page when a surfer uses the back button to return to a page, a
browser will often store (or "cache") the Web page, at the time of the surfer's first request, on the
surfer's hard drive. If, and when, the Web page is requested again, the browser will draw the
Web page from the hard drive (cache) rather than go through a more time-consuming page
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request from the server. Unfortunately, this means that the server may not record subsequent
page views by the surfer. Therefore this leads to a potentially significant underestimation of the
magnitude of advertising frequency on the Internet.
Absence of standardization of ad effectiveness measures
Several third party market research tracking companies (e.g., MediaMetrix,
RelevantKnowledge, Nielsen) have attempted to focus on the development of standard
advertising effectiveness measures (e.g., Reach and Frequency) in an effort to promote the
standardization of advertising effectiveness and permit the comparability of Internet advertising
with that in standard media. Unfortunately, some of the measurement problems discussed above
have often led to dramatic disparities in reported advertising effectiveness statistics from
alternative third party companies (e.g., see Peter Kafa, 1999). Aside from the discrepancies due
to differences in measuring unique visitors and accounting for caching, disparities in reported
statistics from different Internet tracking organizations are also due to methodological
differences in sampling procedures. For examples, MediaMetrix recruits its panels by buying
population lists that includes PC users (some of whom do not currently use the Web) and
conducting random mailings and phone calls. In contrast, RelevantKnowledge relies on random
phone calls to recruit people who already use the Web.
Furthermore, some have questioned the relevance of the measures reported by these
companies. Briggs and Hollis (1997), and Drèze and Hussherr (1999) both question the
relevance of click-through as an advertising-effectiveness measure. They show empirically that
banner advertising has a significant impact on consumers even in the absence of click-throughs.
Constructs such as brand awareness or advertising recall are influenced by banner ads even after
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one or two exposures. This means that click-through measures underestimate the effectiveness
of online advertising and that more traditional ways of measuring this effectiveness should be
used.
Errors in current measurement
A recent study by Drèze and Zufryden (1998) investigated the very significant errors that
may be expected in current advertising measurement methods as a result of the problems
described with respect to identifying unique page requestors as well from page caching. They
found for example that current measurement methods, relying on IP addresses to identify unique
visitors, led to an overestimation of Web pages seen by a visitor by about 64%. In terms of
standard measures of advertising effectiveness, they found that the use of IP addresses led to an
overestimation of Reach (within the range of 12% to 42%), an underestimation of Frequency
(within the range of -13% to 9%), and an overestimation in GRPs (Gross Rating Points) of about
23%. In examining the effect of caching on the recording of multiple exposures, it was found
that about 38% of page requests were cached and thus not recorded by servers.
Absence of demographics
In standard media, demographic characteristics are typically gathered from survey
information and reported to advertisers. For example, AC Nielsen reports audience measures for
the TV medium by for various age and geographic groups. Unfortunately, comparable
information is not readily available on the Internet. Although certain Web sites collect this
information on the basis of registration data, the accuracy of the information is unknown. One
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problem is that Web surfers often try to maintain their anonymity. Therefore, the reliability of
information that is supplied via registration procedures is subject to question.
One possibility is to develop demographic data on the basis of geographic information.
That is, it may be possible to determine a visitor's geographic location in view of his IP address
and the ISP providing his/her service. From this information, it may be possible to develop
demographic distribution statistics such as those that are available from geodemographic sources
of data (e.g., Claritas Prizm).
Content Multiplexing
In addition to delivering content through a different model framework, the Internet differs
from broadcast media in the way it integrates the advertising message into the content that
consumers are accessing. When delivering an advertising message, Radio or Television
operators need to interrupt the broadcast of their message, in a linear fashion, in order to
broadcast the ad (see figure 3). That is, the broadcaster alternates between sending content (e.g.,
music or news) and sending advertisements. At all times, one hundred percent of the available
bandwidth is allocated to one of the two alternatives. By contrast, Internet content providers
embed advertising within their content, allocating only a fraction of their bandwidth to the
advertisement (see figure 4). This results in spatial multiplexing rather than temporal
multiplexing.
This spatial versus temporal multiplexing has far reaching consequences on how
consumers process ads. This, in turn, has significant implications on the design and placement of
banner ads on a page. In terms of information processing, online banner ads are at a
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disadvantage. Two factors are contributing to the difficulty for banners to influence web surfers:
"involvement" and "size".
Television is a low involvement medium. Viewers generally choose a program to watch
and sit back to enjoy the show. When commercials interrupt the broadcast, some might switch to
another channel, but they constitute a small minority (less than 5% per Siddarth 1999). Most
viewers simply watch the commercial waiting for the show to resume. By contrast, the Internet
is a high involvement medium. Surfers are actively choosing what material to see. They are
often searching for information (e.g., Stock Quotes, Football results, or the latest MP3 files) and
are processing the content of the pages they are accessing in order to find that content in the least
amount of time. During this search, banner ads are irrelevant objects that tend to slow down the
process. Hence, by default, surfers will avoid processing banners. Drèze and Hussherr (1999)
have shown using an eye-tracking study that surfers tend to avoid looking at banner ads and that
only 50% of banners are attended to.
Size of the advertising stimulus is another problem for online advertising. Banners
typically take less than 10% of a screen’s real estate. This is a far cry from television ads that
take up the whole screen for 30 seconds or one minute. This means that while television ads can
be akin to small movies, with an introduction, a plot development, and a climax (in full color and
surround sound), banner ads are limited to simple one-line messages with maybe some primitive
animation.
In short, banner ads are at a disadvantage because, by default, surfers are looking at
something else they are interested in, and due to their size limitation, banners have only limited
ability to grab the attention of surfers and convince them to take action. As such, banners are
closer to highway billboards than anything else. This means that Internet advertisers are faced
15
with a formidable task and will need to engage in a lot of concept testing in order to find a
banner that works. Fortunately, the ease of implementing only marketing research procedures
(e.g., split-cable ad testing in order to examine which ads are most effective (Drèze and Zufryden
1997)) may help to mediate this problem.
Conclusion
To benefit from the unique Internet medium environment, advertisers and managers need
to consider the idiosyncrasies of Internet advertising. A unique advantage of the Internet
Medium is its bi-directional framework that incorporates two-way links between advertiser and
prospective consumers. A beneficial byproduct of this linkage is that customers can be targeted
individually at the micro-consumer level. In addition, because of the interactivity afforded by
the medium, the advertiser can tailor individual advertising and formulate advertising messages
adaptively. Because of the two way flow of information that characterizes the medium, the latter
can deliver advertising messages to individual consumers and, at the same time, gather consumer
information on a continuous basis as prospective consumers surf the publisher or advertiser's
Web sites. The integration of the transaction function within the medium provides for a closing
of the marketing-response loop which permits the potential development of appropriate
advertising and marketing strategies that will best influence a prospective consumer's purchase
behavior.
Despite the promises of the Internet as an advertising medium, there are continuing
challenges that make the effective implementation of advertising strategy difficult. Measurement
problems exist due to lack of standardized advertising unit of measures, measurements, as well
as difference in the tracking methodologies that are used by third party companies. Current
16
measurement methods typically have limited accuracy. It is generally not possible to provide
measures of ad effectiveness on the Internet that may be appropriately compared with those of
standard media. Thus, relative media effectiveness across media, including the Internet, is
difficult to assess. The different methods of pricing advertising on the Internet (on the basis of
impressions or click-throughs) also make it difficult to assess the cost/effectiveness of
advertising in this new medium and thus hamper the implementation of advertising budgeting.
Because Internet advertising involves a partial allocation of bandwidth to advertising
messages, it is more difficult to draw a prospective consumer's attention to an ad on the Internet
as it is shared with other contents including potentially competing ads on the same Web page.
This suggests that ad design and placement aspects may be of great importance to insure that a
consumer will be drawn to the banner ad. This means that it is important for advertisers to gain a
greater understanding about how prospective consumers process information, including ads, on
Web pages.
In sum, there are great opportunities for advertisers on the Internet. However, as was
pointed out, considerable challenges still remain. Nevertheless, it is expected that the
opportunities and promises of the Web will be realized as advertisers and researchers continue to
gain a better understanding of the unique characteristics of the Web as a medium as well as the
nature of consumer search and response behavior on the Web.
17
References
Briggs, R. and N. Hollis (1997), “Advertising on the Web: Is There Response before Click-
Through?,” Journal of Advertising Research, 37 (2), 33-45.
Drèze, Xavier and François-Xavier Hussherr (1999), “Internet Advertising: Is Anybody
Watching?,” USC Working Paper.
Drèze, Xavier and Fred Zufryden (1997), “Testing Web Site Design and Promotional Content,”
Journal of Advertising Research, Vol. 37, No. 2.
Drèze, Xavier and Fred Zufryden (1998), “Is Internet Advertising Ready for Prime Time?,”
Journal of Advertising Research, Vol 38, No. 3, 7-18.
Internet Advertising Bureau (1998), "Internet Advertising Approaches $ 1 billion," April 6,
[URL:http://www.iab.net]
Kafa, Peter, (1999), "Unaccountable," Forbes, Technology the Internet, (May 3), 194-95.
Siddarth, S. (1999), “Describing the Dynamics of Attention to TV Commercials: A Proportional
Hazards Model of the Time to Zap an Ad,” USC Working paper.
Content Provider 1 Content Provider 2 Content Provider 3
Advertiser
Consumer 1 Consumer 2
Figure 1: Content Flow -- Traditional Media
Content Provider 1 Content Provider 2 Content Provider 3
Advertiser
Consumer 1 Consumer 2
Requests
Replies
Figure 2: Content Flow -- Internet
t
100%
Input Output Bandwidth
Advertising Content
Temporal
Multiplexing
Figure 3: Temporal Multiplexing – Broadcast Media
t
100%
Advertising Content
Spatial
Multiplexing
Input Output Bandwidth
Figure 4: Spatial Multiplexing -- Internet
22
Table 1: Contrast of Internet vs. Broadcast frameworks
Internet Broadcast
Two-way communication One-way communication
Passive (impressions) and Active ad
viewing (click-through)
Passive ad viewing
Micro-level audience targeting Macro-level or segmented audience
targeting
Census-based audience information Sample-based audience
No sampling error Sampling error
Advertising message can be tailored "on
the fly" to the individual
Fixed advertising message is prescheduled
in space and time
Shared bandwidth Utilizes 100% bandwidth
Potential concurrent integration of
advertising and marketing research
functions
Advertising and marketing research
functions conducted separately
Potential integration of advertising and
purchase transaction functions
Advertising and transaction functions
occur through different channels