Effectiveness of online advertisement factors in recalling a product.
Alijani, Ghasem S. ; Mancuso, Louis C. ; Kwun, Obyung 等
INTRODUCTION
The emerging area of interactive advertising presents new
challenges for advertisers who have hitherto adopted an interruptive
strategy. In contrast to conventional forms of interruptive advertising,
the viewer has actually chosen to see the commercial. This new mindset,
not surprisingly, holds for the way in which the audience is willing to
engage with ads. Online advertising reduces costs, increases efficiency,
provides more flexibility and as a global medium, the Internet enables
buyers and sellers to interact and manage business transactions. The
promotion of online sales and advertising revenue in the US has grown
from $8.23 billion in 2000 to $12.5 billion in 2005. According to a
survey conducted by the American Advertising Federation, the percentage
of media budgets allocated to online advertising represented 14.1% in
2005, a figure that is projected to hit 19.1% by 2006. Perhaps it is its
immediate responds that make online advertising one of the fastest
growing methods of targeting consumers (Homer, 2005). However, there
have been growing concerns about invasion of privacy Aaker &
Stayman, 2005) and access to advanced technology.
From the buyer's perspective, the limitations include the
inability to touch, smell and taste or try-on tangible goods before
making an online purchase. A survey of 410 marketing executives
indicated that insufficient ability to measure impact, a lack of
internal capability, and difficulty convincing senior management as the
top three barriers to entry for large companies looking to market
online. However, as Advertisers increase and shift more of their budgets
online, it is now overtaking radio in terms of market share (Clark,
2002). The objective of this research was to study the type advertising
factors that motivate consumer recall of online advertisements.
According to Internet World Stats, as of September 2007, the
world's population is estimated to 6,574,666,417, where
1,244,449,601 are using the Internet. In fact, the United States of
America had the greatest contribution with regards to the number of
Internet users, since 212,080,135 or 70.2% of USA's population had
been captured by the power of Internet. Such great population of
Internet users had now undoubtly encouraged businesses and entrepreneurs
to advertise online (Bruner, 2000; Ducoffe, 2004).
BACKGROUND
Online advertising requires effective strategies in reaching
customers Zinkhan & Watson, 2004) These strategies may include
personalization and integration of multimedia and real-time
interactions. The largest revenue shares within Internet advertising are
generated by display-based and search-based advertising. The latter
utilizes the Internet user's search engine query to determine which
advertisements are displayed. Search-based advertising accounted for
approximately $5.1 billion in 2005, 41% percent of total Internet
advertising revenue. Google and Yahoo are leaders in the search-based
advertising market (Goldberg & Gorn, 2005). Unlike traditional
media, online advertising generally through its search engine provides
advertisers with access to large affiliate networks as well as
opportunities for display-based and search-based advertising (Green,
2001; Chen & Wells, 2005). In addition to keyword-based
advertisements, advertisements can be delivered based on geographical
data contained in a consumer's IP address. For example, a user with
an IP address originating from Baltimore might receive an offer to
purchase Baltimore Ravens tickets while visiting a football-related
website. Visiting the same website at the same time, a user from
Philadelphia might instead receive an ad for Philadelphia Eagle tickets
(Toon, 2004)
Unlike traditional media, online advertising provides real-time
information of an advertisement's efficacy using the clickthrough
rate (CTR) metric. There are several reasons for low CRTs including lost
of interest of potential customers and "invalid clicks'. Thus,
along with effective strategy one should consider the significance of
online frauds in generating revenue (Spar, 2004; Goldsmith &
Bridges, 2001). In 2005, the fraudulent clicking cost the advertisers
over 800 million. An estimated 14.1% of online sale referrals generated
by clicks on text advertising links were fraudulent. Nearly 12.8% of the
clicks generated from the two leading search engines, Yahoo and Google,
were found to be fraudulent. Because there is no industry-accepted
definition for an "invalid click," estimates for the
prevalence of online fraud vary (Donthu, 2003). In 2005, 99% of its $6.1
billion revenue was derived from advertising." Similarly, 87% of
Yahoo's $5.3 billion revenue was generated from its marketing
services. With total revenues for both companies so strongly dependent
upon online advertising and the satisfaction of advertisers, fraudulent
clicks could jeopardize future earnings and organizational viability
(Hempel, 2007).
METHODOLOGY
A survey method was used as the means by which data is collected
within the New Orleans area. The online questionnaire was distributed by
emails and posted on New Orleans Craigslist, MySpace, Yahoo blog, Face
Book, and YouTube online. The survey was started in October 2007 and
continued through February 2008. The data was collected in two forms
using online survey and face-to-face interviews. The primary data were
derived from answers the participants gave during the survey process.
Over the period of five months, 3,483 participants responded to the
questions. However, only 858 (25 per cent) respondents were accepted
since they met both condition of having online purchasing history and
answering all the questions. All of these respondents were selected
through a relatively large sample size of different groups. There was
354 men (41.3%) and 504 women (58.7 %) participants. Ages of
participants ranged from 18 to 65. Majority of the sample (55.5 per
cent) was between the ages of 18-34. The 2,625 participants did not have
a history of online shopping or completed the questionnaire. The
participants qualified for sample selection must have purchased product
or service also be resident of New Orleans, Louisiana. Table I shows the
survey questions, choices, and number of responses to each question.
The questionnaire contains various recall online advertising
factors and socio-demographic characteristics of the respondents such as
age, gender and income. These questions are weighted as a four-point
scale (strongly disagree, agree, disagree, and strongly agree) and a
five-point scale (very important, important, moderately important, not
so important, and unimportant). To validate the data, participants were
asked whether online advertisement had anything to do with their online
purchasing. As the following figure shows, the majority of the
participants who purchased a product or service online were
significantly influenced by the online advertisement.
Applying data-driven and quantitative approach, the data was
collected from participants and tabulated as it is shown in the
following table.
FINDINGS
There were a number of motivating factors that can be discovered
through the analysis of the collected data. We looked at those which are
most effective and played significant rules in customer decision. These
factors are grouped into three categories: Product, Motivation, and
Demographic.
Product Factors
Product factors' is concerned with the product itself. In this
category the participants were asked how important the price, value, and
usefulness factors are in making decisions and attract them in recalling
online advertisement. The scale was as follows: Very Important (5),
Important (4), Moderately Important (3), not so Importance (2), and
Unimportant (1). As Table 3 shows, majority of the respondents agreed
that the price of the products indeed attract them the most in recalling
online advertisement.
Important Factors
Motivation Factors
There are several factors that motivate consumers to recall online
advertisements. In Table 4, the respondents were asked whether the
Advergame, Celebrity Humorous, Embedded Video, or Music would motivate
them in recalling online advertisement. As the following Table shows,
there was sufficient evidence to conclude that the participants all
agree that embedded video advertisements has the most influence in
recalling online advertising.
Demographic Profile
For the profile of the respondents, the questionnaire asked for the
participants' age, gender, and income. The following figure shows
that the most active group are age between 25 and 34 follow by group
45-54 years old.
The result of survey on gender indicated that two-third of the
total 858 participants are females. The data on the gender was collected
as an independent factor with no correlation with age group. However,
the base argument on the age issue that was presented is valid as an
independent factor for both male and female.
[FIGURE 2 OMITTED]
The other demographic factor that was independently surveyed was
concerning the range of income of participants. As the following figure
shows, the most active group was the $30,000 $40,000 income range.
[FIGURE 3 OMITTED]
As stakeholders, the participants were asked what type of online
advertisement would appeal to them the most. The responses in the
following table show that embedded video advertisement (40%) followed by
animations are the types of online advertisements that catch the
consumer's attention.
Finally, the participants were asked how many actual purchases or
transactions they made within the five months period through online
advertisements. The responses indicated that the highest number of
transaction was 26 or greater, followed by 21-25.
CONCLUSIONS
Online Advertising can be an effective tool if it is implemented
properly. New technologies have opened the door to a new era of
interactivity and creativity. There are a variety of factors of Internet
advertising methods that one can use to drive a potential customer to
his/her site. These factors may include consumers, products, technology
and media. This research project was focused on recalling factors. It
applied a data-driven model and quantitative methods to determine the
most effective factors in recalling online advertisements. Over 3,400
participated in the survey process among them, 858 selected as the group
who answered all the questions and at least made one time online
purchase. The results show that embedded videos, price, product or
service, along with credibility make online advertisements a very
effective tool in motivating consumers to recall online advertisements
and eventually making business transactions. The research concluded that
advertisers need to advertise their product or service based on what the
consumers want in their advertisement. Banner plan text advertisement,
floating advertisement, pop-up advertisement, and music advertisements
are not as effective as embedded video which enhance online
advertisement and motivate consumers.
REFERENCES
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Chen, Q. & Wells, W.D. (2005). Attitude Toward the Site,
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Clark, Steven Philip (2002). Unconscious Processing of Internet
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Ghasem S. Alijani, Southern University at New Orleans
Louis C. Mancuso, Southern University at New Orleans
Obyung Kwun, Southern University at New Orleans
Adnan Omar, Southern University at New Orleans
Table 1: Online Purchasing
Question Choice Number of Reponses
Did Online Advertisement have anything Yes 584
to do with your Online purchasing? No 274
Table 2: Survey Questions
Question Choices Response
Have you Yes 858
purchased No 0
product(s) or
service(s)
through the
Interne, due to
Recall of Online
Advertisement?
Did Online Yes 584
Advertisement No 274
have anything to
do with your
Online
purchasing?
Would Strongly Agree 224
Advergame Agree 459
Online Disagree 137
Advertisement Strongly Disagree 38
motivate your
ability to recall
Online
Advertisement?
Would celebrity Strongly Agree 266
Online Agree 373
Advertisement Disagree 199
motivate your Strongly Disagree 19
ability to recall
Online
Advertisement?
Would humorous Strongly Agree 234
motivate your Agree 350
ability to recall Disagree 236
Online Strongly Disagree 38
Advertisement?
How important is Very Important 464
Value of the Important 169
Product or Moderately important 173
Service in Little Importance 41
recalling Online Unimportant 12
Advertisement?
What is your Under $20,000 13
Household $20,000 to 29,999 96
Income? $30,000 to 39,999 346
$40,000 to 49,999 244
$50,000 and over 159
Would Strongly Agree 243
background music Agree 16
motivate your Disagree 32
ability to recall Strongly Disagree 567
Advertisement?
Would embedded Strongly Agree 194
video motivate Agree 145
your ability to Disagree 302
recall Online Strongly Disagree 217
Advertisement?
What makes a Credibility 478
celebrity effective Appearance 269
in your ability to Performance 106
recall the Online Popularity 5
Advertisement?
For you as a Animated Ad 192
consumer, to Banner Plan Text 76
recall Online Embedded Video 342
Advertisement, it Floating Ad 103
should be: (Select Pop up Ad 145
your first top
choice)
What is your 18-24 108
Age? 25-34 279
35-44 197
45-54 125
55-64 101
65-Over 47
How important is Very Important 383
Price of the Important 213
Product or Service Moderately important 99
in recalling Online Little Importance 47
Advertisement? Unimportant 16
How important is Very Important 445
Usefulness of the Important 188
Product or Service Moderately important 130
in recalling Online Not So Important 65
Advertisement? Unimportant 30
Table 3: Important Factors
Product Factors Scale Weighted Interpretation
Average
5 4 3 2 1
Price of the Product 475 193 172 7 11 4.49 Very Important
or Service
Value of the Product 463 109 32 182 72 3.82 Important
or Service
Usefulness of the 145 188 430 65 30 3.41 Important
Product
Table 4: Motivating Factors
Motivating Factors Scale Weighted Interpretation
Average
4 3 2 1
Advergame 224 159 137 338 2.31 Agree
Celebrity 266 374 199 19 3.03 Agree
Humorous 234 350 236 38 2.9 Agree
Embedded Video 478 270 106 5 3.42 Strongly Agree
Music 165 22 21 750 1.76 Disagree
Table 4: Popular Advertisement Types
Type of Ad Respondents Percentage
Animated 192 22%
Banner Plain Text Ad 76 9%
Embedded Video Ad 342 40%
Floating Ad 145 17%
Pop up Ad 103 12%
Table 5: Online Transactions
Choices Responses Percentage
1-4 44 5%
5-10 34 5%
11-15 148 17%
16-20 90 10%
21-25 233 27%
26 and above 309 36%
Figure 1: Age of Active Participants
Age Distribution of the Total Sample
18-24 13%
25-34 32%
35-44 22%
45-54 15%
55-64 12%
65-Over 6%
Note: Table made from pie chart.
