ArticlePDF Available

Numbers, Please: Big Data: Friend or Foe of Digital Advertising? Five Ways Marketers Should Use Digital Big Data to Their Advantage

Authors:

Abstract

The author offers opinions on Big Data, the information generated by consumers by their Internet use and automated point-of-sale systems, in Internet advertising media planning and marketing management. While acknowledging that Big Data has provided benefits to consumers in creating pricing transparency, the author states this poses the danger to marketers of focusing on lower pricing at the expense of brand equity. Targeting of Internet advertising based on data analysis is said to offer a means to maintaining or improving brand equity.
DOI: 10.2501/JAR-53-4-000-000 December 2013 JOURNAL OF ADVERTISING RESEARCH 91
In recent years
, much has been written about
the emerging importance and value of “Big Data.”
From my perspective, however, Big Data actually
have been around for decades—ever since low-
cost computing power and powerful relational
multi-dimensional software were made broadly
available. Twenty-five years ago, Big Data gener-
ated by UPC point-of-sale scanners changed the
face of marketing in the consumer packaged goods
(CPG) industry by causing marketing spending to
tilt ominously in favor of price discounts and away
from advertising.
Today, real-time digital Big Data generated by
the Internet offer the ostensible benefits of pro-
viding consumers with an easy way to find the
lowest price for any product while also arming
marketers with dramatically expanded advertising
optimization capabilities.
Marketers would be wise, however, to heed the
lessons of history and recognize that for all the
benefits Big Data afford, they also come with per-
ils that may not be as readily apparent. Ultimately,
real-time digital Big Data must be used correctly if
they are to have a positive impact on brand health
and improve marketing return on investment (ROI)
both today and in the future.
HISTORICAL PERSPECTIVE
How the Availability of Data Has
Transformed Markets
Back in the 1980s, the motivation for retailers to
invest $150,000 to equip a typical supermarket
with UPC scanners was not the value of the data
they would obtain but rather the cost savings from
not having to price mark each of the hundreds of
thousands items on stores’ shelves. With scanners,
it was necessary only to display each SKU’s (stock-
keeping unit’s) price via a sign at the shelf because
the checkout cash register obtained the price for
each individual item by looking up the item’s UPC
code in the store’s UPC/price file as the item was
scanned. And, any time a SKU’s price changed, all
that was required was to change the shelf price sign
along with the price in the computer file. Using
scanners, running a supermarket suddenly became
simpler and cheaper.
The full informational value of “Big Scanner
Data” was only realized after the scanners were
installed. One could say that the data were the
“exhaust fumes” resulting from the primary use of
the scanners to eliminate the costs of price marking
(just as today, Big Data are often defined to be data
that are a by-product of the use of a computer to
solve an operational problem).
From the Analog Audit to Digital Scanning:
The Impact on Short-term Marketing Strategies
Before the advent of scanner data, CPG marketers
had to rely on bi-monthly manual audits of stores
to understand the trends in their brand sales and
market share at retail (See Figure 1). The data were
not available until six weeks after the end of the
bi-month period.
Then, suddenly, retailers and manufacturers had
timely access to weekly (and even daily) scanner
data. The granularity of these new data clearly
revealed the substantial impact of short-term mar-
keting tactics, including temporary price reductions
supported by newspaper advertisements (which
communicated the price) along with prominent in-
store merchandising support—often in the form of
end-aisle displays (See Figure 2).
Though auditing data showed a relatively stable
bi-monthly sales trend, weekly scanner data clearly
revealed the large and volatile sales increases that
occurred when newspaper feature advertisements
announced price reductions and in-store merchan-
dising support was implemented. Armed with this
type of granular information, retailers were able to
pressure manufacturers for more trade-promotion
dollars, and manufacturers—as a result of the
retailers’ pressure along with their own desire for
a short-term sales lift—willingly increased their
trade-promotion spending.
Big Data: Friend or Foe of Digital Advertising?
Five Ways Marketers
Should Use Digital Big Data to Their Advantage
GIAN FULGONI
comScore, Inc.
gfulgoni@comscore.com
Numbers, Please
92 JOURNAL OF ADVERTISING RESEARCH December 2013
BIG DATA: FRIEND OR FOE OF DIGITAL ADVERTISING?
The results were dramatic (See Figure 3).
Manufacturers increased their annual
spending on trade deals by a staggering
$40 billion, all because of the insights pro-
vided by timely and granular sales and
market share data. With this advent of
these new data sources, CPG marketing
underwent a fundamental marketing shift
from advertising to price discounting.
Today, software giant SAP AG reports
that the average CPG manufacturer spends
fully 67 percent of its marketing budget on
trade promotion and 10 percent on direct-
to-consumer promotions (mainly cents-off
coupons), whereas less than 23 percent is
spent on branding advertising. With so
much being spent on retailer incentives
that, in turn, then are used to temporarily
reduce price, the concern that resonates
through the industry is that brand equity
is being eroded as consumers become
“trained” to buy on the basis of price dis-
counts alone.
That’s an unhealthy situation for
any brand.
Big Data in the Digital World: A Threat to
Brand Equity
Over the past decade, the growth of the
Internet has generated seemingly end-
less amounts of digital Big Data. In turn,
digital Big Data have been used to provide
consumers, retailers, and marketers with
information that has created efficiencies,
enabled new capabilities, and opened
up previously unrealized opportunities.
Despite such clear and compelling value
creation, however, real-time digital Big
Data are a double-edged sword that also
has the potential to erode long-term brand
equity because of its tendency to cultivate
a short-term decision-making mindset.
Big Data are seductive in their ability to
help optimize results at any given point in
time, but the cumulative effect of this opti-
mization can mean that brands stop see-
ing the forest for the trees. For marketers to
… but weekly scanner data revealed to retailers and manufacturers
the huge short-term impact of trade promotions.
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
–10
0
10
20
30
40
50
60
70
Jan 12 03
Jan 19 03
Jan 26 03
Feb 2 03
Feb 9 03
Feb 16 03
Feb 23 03
Mar 2 03
Mar 9 03
Mar 16 03
Mar 23 03
Mar 30 03
Apr 6 03
Apr 13 03
Apr 20 03
Apr 27 03
May 4 03
May 11 03
May 18 03
May 25 03
June 1 03
June 8 03
June 15 03
June 22 03
June 29 03
July 6 03
$m%
% Volume Sold (Newspaper/Display/Price Discount)
Dollar Sales
Figure 2 Brand X Weekly Dollar Sales and Trade Promotion
Activity
Business often looked quite stable
Bimonthly brand sales
$ Millions
0
10
20
30
40
50
Jul–AugMay–JunMar–AprJan–Feb
Figure 1 Market Information in CPG Before Scanners: Brand
Sales Measured by Bimonthly Manual Store Audits
Brand Sales Trends:
Manual Store Audits vs. Weekly Scanner Data
December 2013 JOURNAL OF ADVERTISING RESEARCH 93
BIG DATA: FRIEND OR FOE OF DIGITAL ADVERTISING?
avoid this trap, here are five recommenda-
tions that can help maximize the positive
benefits of Digital Big Data:
• Avoid the Race to the Bottom on Pric-
ing: There can be no denying that the
Internet and the Big Data it generates
have brought pricing transparency to
consumers. Some go as far as to say
that pricing power has moved to the
consumer. By using search queries or
comparison shopping engines (which
spider the Web and then show the range
of prices for any product of interest),
consumers quickly and painlessly can
navigate their way to the lowest price
available for any product.
That is terrific news for the consumer,
but it puts huge pressure on retailer and
manufacturer profit margins, leading to
what some critics have called “a pricing
race to the bottom.”
Because of this, it is critical that mar-
keters establish a clear point of differ-
entiation for their brands that helps
them justify a higher price point versus
their competitors. One potential way to
accomplish this could be well-crafted
branding advertising that clearly com-
municates a brand’s unique value and a
persuasive rationale for the consumer to
pay a higher price.
Fortunately, the Internet provides
marketers with powerful new targeted
advertising capabilities that, when used
in the correct manner, can help maintain
or build brand equity.
• Stop Optimizing to the Click: Since the
Internet provides a real-time measure
of clicks on advertisements, it originally
was believed that the click could be used
as an indicator of a digital advertise-
ment’s effectiveness. This has turned out
to be valid for search advertising, where
the click-through rate for paid advertise-
ments averages about 3.5 percent. As a
result, search advertising has grown rap-
idly, to the point where the Interactive
Advertising Bureau reports that in 2012,
search accounted for almost 50 percent
of all online advertising dollars, while
growing 14 percent versus 2011.
In the case of display advertising,
however, the reality is that clicks are piti-
fully low. DoubleClick reports that, on
average, only 1 in 1,000 ad impressions
in a display campaign are clicked, and
comScore data show that slightly more
than 80 percent of Internet users do not
click on any advertisements in a month.
ComScore research also shows that there
is no statistical relationship between
clicks on display advertisements and
the effectiveness of the advertisements.1
Important, however, is that the
research also showed that even without
a click, display campaigns can increase
site visitation, brand search queries, and
both online and offline sales.1
In addition, clickers demographically
skew toward younger and lower-income
audiences—segments that are not gener-
ally favored by marketers. So, by opti-
mizing against clicks, marketers often
are pursuing the wrong audience. None-
theless, in a recent comScore survey,
30 percent of advertisers, publishers, and
agencies said they always/frequently
use the click to measure the effectiveness
of their display ad campaigns.
The reasons would appear to be that
the click is simple, fast, and inexpen-
sive to compute. Unfortunately, it is also
a misleading metric, and advertisers
who optimize against it are proceeding
down the wrong path. The click might
reflect a consumer’s immediate reac-
tion to an advertisement—akin to direct
response—but it ignores the impact of
frequency of exposure and can lead to
short-term errors when trying to build
long-term brand equity.
1 Fulgoni, G. M., and M. P. Morn. “Whither the Click?
How Online Advertising Works” Journal of Advertising
Research 49, June 2 (2009): 134–142
In 2003, U.S. supermarket + supercenter sales were $500B with $60B spent on trade marketing
Source: Accenture
Trade Marketing
Consumer Promotion
Advertising/Media
6%
4%
5%
1978
15%
5%
4%
13%
1995
22%
2000
4%
6%
13%
23%
2003
5%
5%
12%
23%
eMarketing
Scanning
Introduced
Scanning
Complete
<1%
Increase of
$40B/Year
With availability of POS scanner data, manufacturers’ marketing spending
shifted dramatically to trade-promotion and price incentives.
Figure 3 CPG Marketing Spending (as Percentage of Sales)
94 JOURNAL OF ADVERTISING RESEARCH December 2013
BIG DATA: FRIEND OR FOE OF DIGITAL ADVERTISING?
It’s not far-fetched to imagine some
marketers’ being so consumed with
short-term clicks that they pursue ill-
advised ways to increase click-through
rates. For example, one way might be to
include more price incentives in a brand’s
marketing plan and communicate these
with digital advertising in an attempt
to get clicks. That’s a recipe for brand
equity problems similar to the ones we
saw in the case of CPG manufacturers’
increasing trade promotion spending
and focusing on price discounts.
• Understand the Limitations of the Ad
Cookie: The third-party cookie—that
small piece of code inserted into brows-
ers by ad servers as a way to identify
computers and target advertising—gen-
erates massive amounts of valuable Big
Data that can help target digital adver-
tisements in a manner far superior to
traditional media.
There are two important cookie-
related issues, however, that advertis-
ers and their media agencies need to
consider as they plan and execute their
digital campaigns:
Cookies get deleted frequently. Com-
Score data has shown that about
30 percent of U.S. Internet users delete
their digital-advertising cookies in a
month and do so at an alarming rate
of five times per month.
This means that an ad server can
never be really sure of how may ad
impressions it has delivered to a
given computer. Typically, this causes
an over-delivery of frequency and an
under-delivery of reach—both on the
order of 2.5 times different from what
was planned.
Consequently, both these factors can
cause a digital media plan to be deliv-
ered in a manner far different from
what was intended and for an adver-
tising campaign’s effectiveness to fall
significantly below what was planned.
It’s tough to accurately target demo-
graphics. On multi-user computers
(which are used by 60 percent of U.S.
Internet users), the ad cookie cannot
identify accurately the person who
is using the computer at any point
in time. As a result, the demographic
characteristics of the audience reached
by digital ad campaigns can differ
markedly from what was planned.
Fortunately, there are ways to address
these issues that, though not perfect
solutions, represent a marked improve-
ment to the status quo: Services now are
available that provide real-time, in-flight
campaign information to advertisers and
their agencies regarding the accuracy
of audience targeting and impression
frequency delivered at the individual
publisher level.2
Using this information, smart mar-
keters can re-allocate ad dollars to the
publishers who deliver superior results,
even as their campaigns still are run-
ning. In addition, digital publishers are
beginning to guarantee specific target
audiences to advertisers by providing
free “digital make-goods” if necessary.
2 Flosi, S., G. Fulgoni, and A. Vollman. “If an Advertise-
ment Runs Online and No One Sees it, Is It Still an Ad?”
Journal of Advertising Research 63, June 2 (2013):
192–199
This mirrors the audience guarantees
offered in the buying of advertisements
in the annual television “upfront.”
The ultimate benefit to marketers is
that digital advertising campaigns that
are delivered as planned will be more
likely to have a positive impact on con-
sumer behavior and brand health. In fact,
the Kellogg’s Co. has reported a five- to
six-times increase in the financial ROI
from its digital campaigns since it began
to use in-flight campaign optimization.2
• Don’t Ignore Potential Customers
by Over-Targeting: Digital advertis-
ing always has boasted more precise
audience targeting capabilities than
traditional media, and its efficiency
is only gaining over time as new data
sources are deployed.
More recently, a powerful new capa-
bility has emerged as leading digital
retailers such as Amazon and eBay are
powering advertisements—both on-site
and around the Web—that are targeted
according to consumers’ retail brows-
ing and purchase behavior. ComScore
research has shown that a brand’s aver-
age sales lift per exposed consumer as
a result of “purchase-based targeting” is
double that obtained when such target-
ing isn’t used.3
The availability of mechanisms to
efficiently target one’s most likely or
highest-value consumers would lead
marketers to use hyper-targeted cam-
paigns to increase sales while reducing
wasted impressions.
A word of caution, however, is in
order: Although targeting can improve
both efficiency and effectiveness, mar-
keters also must carefully consider the
3 comScore Press Release, October 11, 2011. Retrieved from
http://www.comscore.com/Insights/Press_Releases/2011/
10/comScore_and_dunnhumbyUSA_Research_
Shows_Online_Advertising_Lifts_In-Store_CPG_
Brand_Sales
Clickers demographically skew toward younger
and lower-income audiences—segments that
are not generally favored by marketers.
December 2013 JOURNAL OF ADVERTISING RESEARCH 95
BIG DATA: FRIEND OR FOE OF DIGITAL ADVERTISING?
extent to which this strategy foregoes
the serendipity benefits that can result
from the use of advertising campaigns
with broader reach. This should be of
particular concern to CPG marketers
because of the high buyer penetration of
many CPG product categories. Instead,
marketers should seek to strike the right
balance between strategies so they can
yield the benefits of targeting but not at
the expense of serendipity.
• Accurately Determine Attribution: Des-
pite an abundance of data, an accurate
measurement of the impact of the vari-
ous elements of a brand’s digital market-
ing plan has been challenging for many
marketers. One of the main reasons has
been a fascination with “last-click attri-
bution,” wherein the click on a paid
search ad that then leads to a purchase is
given virtually all the credit for the sale.
This is another example of short-term
thinking that can lead to an erosion of
brand equity.
The reality is that branding adver-
tising has been shown1 to increase the
effectiveness of search advertising by
boosting awareness and interest in the
advertised brand long before that final
search click happens. This increases the
likelihood that the consumer will click
on the search ad for the brand.
Put another way: Display builds the
equity that search converts into sales.
Another important point to under-
stand is that though search ads gener-
ate a higher sales lift than display ads
among those exposed, one must also
take campaign reach into account—
and the reach of display is generally
far higher than search. (After all, the
reach of a search campaign is limited to
only those people who searched using
the terms being targeted.) By contrast,
the reach of a display campaign can
be increased by spending incremental
money to deliver impressions across
as many people as desired. The reality
is that, despite a higher lift among
the people exposed to a search ad, the
greater reach of display campaigns typi-
cally results in a higher total sales lift for
display. That said, savvy marketers now
understand that the maximum sales
lift can be obtained by overlaying dis-
play on search. This is smart long-term
brand building, coupled with powerful
bottom-of-the-funnel call to action.
To correctly understand the impact
of all the elements of their digital mar-
keting plans, marketers can use longi-
tudinal consumer panels and deliver
a cookie with each digital marketing
event to which consumers are exposed.
By then analyzing the behavior of panel-
ists with persistent cookies (i.e., those
that are not deleted during the period
of analy sis) and utilizing sophisticated
covariate regression analysis, it is pos-
sible to accurately determine the value
of various digital events in driving an
action such as Web site visitation, brand
search queries, or e-commerce buying.
And by linking the panelists to their
offline buying (for example, through
retailers’ loyalty-card data), it is possible
to measure the impact on in-store sales.
The future will include the regular use
of even more powerful advertising-
effectiveness measurement systems, done at
scale via the use of Big Data. For example,
using persistent ad cookies that are linked
to retailer loyalty card data, it is possible to
compare the buying behavior of millions of
ad-exposed consumers with a control group
of a similar size that was not exposed.
As marketers gain this increasingly gran-
ular understanding of display campaign
effectiveness, they also must avoid the
temptation to hyper-optimize their display
campaigns to only their best customers at
the expense of long-term brand equity
among a wider base of consumers.
CONCLUSIONS
History shows that the availability of new
and timely Big Data does not always lead
to desired outcomes. In the case of point-
of-sale scanner data, many CPG market-
ers took a short-term focus and ended up
increasing their trade deal spending far
beyond what they had originally antici-
pated. It is likely that this has had a nega-
tive impact on brand loyalty with some
consumers having been “trained” to buy
on the basis of price discounts alone.
Digital Big Data generated by the Internet
now are providing consumers with pricing
transparency across many product catego-
ries, allowing them to easily and quickly
find the lowest price for any product.
Marketers should remember that the “past
is prologue” and seek to avoid a pricing
race to the bottom in today’s digital world.
Much has been learned about how best
to deploy digital advertising to reach target
audiences in a powerful and cost-effective
manner. Savvy marketers will leverage
that knowledge to make more informed
advertising decisions that build long-term
brand equity.
Gian FulGoni
is the co-founder and executive
chairman of comScore, Inc. (NASDAQ:SCOR).
Previously, he was president and CEO of Information
Resources, Inc. During a 40-year career at the
c-level of corporate management, he has overseen
the development of many innovative technological
methods of measuring consumer behavior and
advertising ef fectiveness. He is a previous
contributor to the Journal of Adver tising Research.
History shows that the availability of new and timely
Big Data does not always lead to desired outcomes.
... From a marketing and customer perspective, the academic literature in the last three years has produced many articles, guidelines, and case studies that largely support the notion that Big Data, Advertising Analytics, and data mining are here to stay (Davenport et al., 2013;Erevelles et al., 2015;Fulgoni, 2013;Tirunillai, & Tellis, 2014;Wan et al., 2014). The top story of the year 2012 from Advertising Age is simply titled "Data Dominates". ...
Article
Full-text available
The present study has developed a good fit model using Structural Equation Modelling which validates relationship between marketing mix elements and customer satisfaction through brand awareness. It proves that brand awareness is a strong mediating variable between marketing mix elements and customer satisfaction with respect to consumer durable sector. The relationship between marketing mix elements and brand awareness, and also that between brand awareness and customer satisfaction has been observed to be significant. Marketing mix elements do not have a significant effect on customer satisfaction but have indirect effect on it. Convenience sampling has been used to collect data from 350 consumers of durables products in Punjab (India). Keywords: 4Ps, Brand awareness, Consumer durables, Marketing mix, Customer satisfaction
... Processing data has become less costly with the advancement of sophisticated technologies (Fulgoni, 2013). The decrease in data storage costs for organizations also encourages people to generate huge volumes and varieties of data (Richards and King, 2014). ...
Article
Purpose This study aimed to determine the antecedents of privacy concerns and their impact on consumers' online information disclosure. It also investigated the moderating role of government regulation on the relationship between privacy concerns and online information disclosure. Design/methodology/approach With the help of literature review and theories, a theoretical model was developed and then validated using the partial least squares structural equation modeling technique to analyze data from 309 respondents. Findings The study found that online users' privacy awareness, privacy experience, personality and cultural differences significantly and positively impact their privacy concerns, which in turn positively and significantly influence their online information disclosure. The study also found that government regulation has a significant impact on online information disclosure. Research limitations/implications The study is cross-sectional in nature and cannot be generalized, and therefore, a longitudinal study could be conducted. Also, the study identified four antecedents of online users' privacy concerns. More antecedents and more sample data with other boundary conditions could have increased the predictive power of the model. Practical implications This study will help practitioners to better understand the privacy concerns of online users, which could help them to develop better products and enhance service quality. Policymakers can develop regulations as per the online users' requirements to increase their confidence in disclosing personal information online and other online activities. Originality/value Few studies have dealt with online users' information disclosure and their privacy concerns or the moderating role of government regulations on online information disclosure. The study is unique as its proposed model is the first that accounts for both online users' privacy concerns and government regulation and their online information disclosure.
... Gandomi and Haider (2015) have provided a consolidated description of Big Data by integrating definitions from practitioners and academics. There are some studies (e.g., Fulgoni, 2013;Lazer, 2014;Mishra, Singh, Rana, & Dwivedi, 2017;Tihanyi, Graffin, & George, 2015) that show that analyzing customers through Big Data models generates benefits in precision marketing, new product development, and realigning business strategy to maintain sustainable competitive advantage. Big Data methods such as text mining, web mining, social network analysis, mobile and multimedia mining constitute foundational technologies in organizational business intelligence and analysis (Chen et al., 2012). ...
Article
Over recent years, organizations have started to capitalize on the significant use of Big Data and emerging technologies to analyze, and gain valuable insights linked to, decision-making processes. The process of Competitive Intelligence (CI) includes monitoring competitors with a view to delivering both actionable and meaningful intelligence to organizations. In this regard, the capacity to leverage and unleash the potential of big data tools and techniques is one of various significant components of successfully steering CI and ultimately infusing such valuable knowledge into CI strategies. In this paper, the authors aim to examine Big Data applications in CI processes within organizations by exploring how organizations deal with Big Data analytics, and this study provides a context for developing Big Data frameworks and process models for CI in organizations. Overall, research findings have indicated a preference for a rather centralized informal process as opposed to a clear formal structure for CI; the use of basic tools for queries, as opposed to reliance on dedicated methods such as advanced machine learning; and the existence of multiple challenges that companies currently face regarding the use of big data analytics in building organizational CI.
Chapter
The fuzzy analytical network process (FANP) is introduced as a potential multi-criteria-decision-making (MCDM) method to improve digital marketing management endeavors. Today's information overload makes digital marketing optimization, which is needed to continuously improve one's business, increasingly difficult. The proposed FANP framework is a method for enhancing the interaction between customers and marketers (i.e., involved stakeholders) and thus for reducing the challenges of big data. The presented implementation takes realities' fuzziness into account to manage the constant interaction and continuous development of communication between marketers and customers on the Web. Using this FANP framework, the marketers are able to increasingly meet the varying requirements of their customers. To improve the understanding of the implementation, advanced visualization methods (e.g., wireframes) are used.
Chapter
We have previously discussed big data analytics as part of smart information systems, but we will revisit them in this chapter in tandem with the idea of transparency and how this affects the overall quality of experience of the users in smart information systems. Previously, we have looked at the data itself and the motivation for the use of synthetic data, whereas now we will approach the area of big data and big data analytics more holistically. In fact, when we say big data, we are referring to extremely large datasets that are quite challenging to work with with traditional database management tools. These have provided new opportunities but also new risks explored in this chapter, along with how this is experienced from the user perspective in terms of trust.
Article
Full-text available
Industry advocates argue that the focus of advertising production has shifted from the creativity of practitioners to consumer analytics and the potential advantages of big data. Although a little empirical research offers valuable insights about the changing role of advertising practitioners, it lacks a critical perspective to situate it in a broader social context. On the other hand, digital labor and branding literature over-concentrate on user labor and neglect the role of practitioners in advertising production. By deploying the concept of immaterial labor, this article reevaluates the findings of mainstream marketing-advertising literature within the context of post-Fordist labor. This article aims to create a resonance between theories of immaterial labor and advertising literature and to call for further empirical research from a labor perspective. It argues that advertising practitioners put more strategical, relational and communicative powers into work to manage a data-oriented market. Keywords: Advertising Practitioners, Immaterial Labour, Big Data, Media Work, Autonomist Marxism
Chapter
The rapid ascent of data-driven advertising practices has allowed advertising professionals to develop highly-targeted and personalized advertising campaigns. The success of data-driven advertising relies on if future professionals are proficient with basics of Big Data analytics. However, past research of undergraduate advertising curricula around the world has shown that higher education institutions tend to fall behind in offering the most up-to-dated training for advertising students. Findings have shown that undergraduate advertising programs have slowly taken advantage of the potential of the data analytics tools and techniques. This trend is observed among higher education institutions around the world. Practical, research, and pedagogical implications are discussed.
Article
The attention of the academic and professional world to the potential benefits of Big Data is growing, as well as the awareness that they can represent fundamental drivers of organisational value creation. Indeed, Big Data is a critical intangible resource and source of value for organisations that can support the achievement of superior performance. Understanding the value of Big Data and how it contributes to value creation mechanisms defines an important area of research that needs to be further developed. The paper analyses the links between Big Data and organisational knowledge assets and proposes a framework to explain how Big Data contributes to organisational value creation mechanisms. It also highlights the role of knowledge assets as factors that influence the use, development and deployment of Big Data for organisational value creation dynamics.
Article
Purpose The purpose of this study is to investigate the impacts of regulations and governance of artificial intelligence (AI) on personal data sharing (PDS) in the context of sociolegal, technology and policy perspective. Design/methodology/approach With the help of theories and literature review, some hypotheses have been formulated and a conceptual model has been developed. These are statistically validated. The validated model has been compared again using impact of regulation and governance of AI as a moderator. The validation has been done using survey by PLS analysis. Findings The study found that there is a high level of positive impact of regulation and governance of AI on the online PDS by the users. Research limitations/implications This study has provided a statistical model which can provide the antecedents of PDS by the online users with the impact of AI regulation and governance as a moderator. The proposed model has explanative power of 92%. Practical implications The study highlighted that there is a necessity of having appropriate AI regulations so that users could share their personal data online without any hesitation. Policymakers and legal fraternity should work together to formulate a comprehensive AI regulation and governance framework. Originality/value To the best of the authors’ knowledge, there is no study on the impact of AI regulation and governance towards PDS and how it impacts on the security, privacy and trust of the online users.
Article
Full-text available
This study presents findings from three charter studies involving leading global advertisers in three key geographical regions: the United States, Europe, and Canada. The goal of the research was to identify and better understand the incidence of suboptimal digital campaign delivery as it pertains to viewability, audience delivery, geographic targeting, and brand safety. Through an evaluation of the study findings, several significant empirical generalizations emerged, and this article highlights these generalizations and discusses their implications for the digital advertising ecosystem.
Article
Full-text available
Online advertising spending in the United States exceeds $20 billion annually. However, click rates on display advertisements average only 0.1 percent. Are low click rates evidence that display advertisements have no impact on consumer behavior? Or, does display advertising work in a manner similar to traditional "branding" advertising, with multiple exposures being required to effect a change in consumer behavior? This article shows that the click is not an accurate indicator of the effectiveness of online display advertisements. Even when click rates are minimal, display advertisements can generate meaningful increases in site visitation, trademark search, and both online and offline sales.