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



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.
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
comScore, Inc.
Numbers, Please
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.
Jan 12 03
Jan 19 03
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Feb 2 03
Feb 9 03
Feb 16 03
Feb 23 03
Mar 2 03
Mar 9 03
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Mar 30 03
Apr 6 03
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July 6 03
% Volume Sold (Newspaper/Display/Price Discount)
Dollar Sales
Figure 2 Brand X Weekly Dollar Sales and Trade Promotion
Business often looked quite stable
Bimonthly brand sales
$ Millions
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
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
Increase of
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)
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):
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
Clickers demographically skew toward younger
and lower-income audiences—segments that
are not generally favored by marketers.
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.
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.
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