1. As seen in
p2pi.org
Best Practices in
Shopper Marketing Measurement
Part 6:
Directions
for the
Future
Underwritten by:
©iStockphoto.com/ryasick
By Liz Crawford, Senior Industry Analyst Executive Summary
The following is the final installment in a six-part series n Comparing marketing efforts across platforms has been
examining best practices for the measurement of shopper the Holy Grail for a generation of marketers. “Single source
data” has finally brought this goal into view.
marketing. This article explores directions for the future. To n The term “single source” refers to tracking a specific shop-
read the first five articles in the series, visit www.p2pi.org. per by recording all of her advertising exposures and all of
her purchases over a given period of time.
n The ideal single source data stream would provide a true
T
360-degree picture of a shopper’s day from a media-expo-
he ability to compare mar- a defined period of time. The ideal sure standpoint and include all purchase behavior. So far,
keting activity across plat- single source data stream would the best models track exposure from three channels: online,
forms has been a highly provide a true 360-degree picture television and in-store; data streams from mobile devices may
desired but unattainable goal for of a shopper’s day from a media-ex- be added in the foreseeable future.
a generation of marketers. Today, posure standpoint and also would n Single source data offers five major benefits to shopper
however, the Holy Grail the indus- include all of her purchase behavior. marketers:
try seeks is on the horizon – if not So far, the best available models 1. Enhanced ability to rationalize and optimize
within immediate reach. can track a shopper’s exposure in investments
So what specifically is this Holy three channels: online, television 2. Accurate picture of in-market responsiveness by
Grail? According to the Coalition and in-store. These areas constitute shopper segment
for Innovative Media Measurement the term cross-platform in CIMM’s 3. Assessment of the opportunity costs of media plans
(CIMM), “Single source data for statement. While this new ap- 4. Ability to better optimize media plans
5. Better understanding of the role each medium plays
passive media measurement is the proach is a great leap forward, it still
in driving sales
Holy Grail for cross-platform adver- excludes numerous other channels
n When consumers use the Internet, they leave behind trails
tising effectiveness.” This is a fairly of media exposure such as radio,
of data that serve as a record of their behavior. There are
technical statement that deserves outdoor and mobile. lots of trails generated by both man and machine that,
to be explained in detail. Gathering the data works rough- taken cumulatively, constitute “big data.”
First of all, the term single source ly this way: Purchase behavior is n Since the turn of the millennium, shopper marketers have
refers to tracking a single shopper, tracked using scanner data derived called for function-centric silos to be eliminated. Big data may
recording all of her advertising ex- from credit /debit card transac- ultimately be the catalyst.
posures and all of her purchases, for tions. Each shopper is assigned an
© Copyright 2012. Path to Purchase Institute, Inc., Skokie, Illinois U.S.A. All rights reserved under both international and Pan-American copyright conventions. No reproduction
of any part of this material may be made without the prior written consent of the copyright holder. Any copyright infringement will be prosecuted to the fullest extent of the law.
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2. special Report
Single Source Additionally, more than one company is always
involved in matching the data, so a specific
Shopper Data individual’s identity can’t be revealed, even
from a logistical standpoint. The tags and data
TV Viewers hand-offs are important, therefore, because
they are crucial to preserving anonymity of in-
dividuals; otherwise, this kind of analysis could
be perceived as surveillance.
Marketing Mix Analysis
Marketing mix models have been used since
the 1980s to understand the impact of various
marketing tactics on sales. Until now, mar-
Retail Buyer Online Surfers keters haven’t had access to this enormous
exhaust data, which lets them observe media
consumption in conjunction with purchase
behavior on a mass scale. So older mix mod-
els used statistical techniques to examine the
correlation between sales and various inde-
pendent marketing variables. This was a foren-
sic exercise in which analysts would infer the
anonymous tag, which is then matched to on- pers, outdoor media and radio. Further, the causes of sales increases based on advertising
line activity connecting that shopper to a spe- industry is still working to link TV and re- impressions, spending and other factors. The
cific online surfer. So the single source becomes tail consumption to digital platforms such as “shoppers” were a gross, unified force behind
a specific shopper. In a final step, certain house- mobile applications. At this stage, the most the statistical relationships.
holds that have their TV viewing monitored are interesting addition to the current database The picture changes when marketing mix
matched to the anonymous tags, completing would be smartphone user behavior (which models get the high-octane input of single
a single source, in-store/out-of-store tracking may not be too far away). source data. Models are still run, but they are
system. (See Venn diagram, above.) Until all these links are established, media used to analyze the relationship between real
An enormous advantage to this approach is consumption is ascertained using old-fashioned “opportunity to see” ad exposure and an actual
that it can report recorded behavior, which is surveys to fill in the gaps on a per-person basis. purchase. How likely is a shopper to buy Brand X
captured digitally as the passive observations There is another big issue with this nascent after exposure to Online Ad Y? After exposure to
noted in CIMM’s statement. The individual approach. While these three databases are Online Ad Y and TV Ad Z? These kinds of ques-
isn’t a “respondent,” so there are no ques- robust enough to find and track individuals, tions get very accurate, reality-based answers
tionnaires to fill out or incentives to dangle. sample sizes sometimes inadequately represent due to the extensive records available today.
Instead, this technique is one of the first to populations. Weighting and other statistical
take advantage of “big data.” techniques can be used to compensate for sam- How We’ll Roll: New Outputs
Big data is the huge set of “exhaust data” ple sizes until more observations are collected, Single source data will revolutionize how
that is emerging. When consumers use the but this is a bit of a drawback in the short term. companies go to market and gauge success
Internet, they leave behind trails of data that Beyond these two issues, there is the social by delivering five prominent new benefits to
serve as a record of their behavior. There are (some might even say “moral”) issue of pri- shopper marketers.
a lot of trails generated by both man and ma- vacy. Research companies engaged in tagging 1. An Enhanced Ability to Rationalize and Op-
chine. Like consumers, machines also gener- and tracking are quick to assert that they are timize Investments: Without even tapping into
ate exhaust data, which includes monitoring scrupulous in their use of anonymous tags. modeling or analytics, it is possible to simply
records of every stripe, as well as
machine-to-machine communi-
cation trails like electronic data
transfer messages. Because these
data include passively observed “ The data itself will break the
records of consumer behavior,
they are more accurate than ask- silos. You can’t have data that
ing respondents to remember
and report their activity. speaks to everything and people
While this new methodology
is exciting, there are issues with who don’t talk to each other.”
the approach. First, as previously
noted, many media platforms are Bill Pink, senior partner,
missing. Notably absent at this Millward Brown
point are magazines, newspa-
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Example of Brand Penetration by Frequency
25
In season
Out of season 20.0 19.5
20 18.3 18.4
16.1
% of HHs 15.0
Buying 15
Brands
11.8
10
10.5
9.7 9.8 9.4
9.1 8.8 9.0
5
3
8
15
5
5
+
po TV
1-
4-
-2
-4
46
d
9-
Ex ot
16
26
se
N
Cumulative TV Exposures Per Household
Source: Millward Brown
examine tracked shoppers to reveal the per- other methodologies such as central location optimal placement. That is really different.
centage of households that were exposed to testing, a technique that ultimately may be 4. The Ability to Better Optimize Media Plans:
various media and their actual contribution to relegated to prelaunch diagnostics and com- The “rule” of three exposures as the optimal
revenue in the same time period. This is not munications refinement. frequency has been accepted for years. Single
modeled behavior but observed, in-market 3. An Assessment of Media Opportunity Costs: source data inputs may not completely debunk
behavior. Additionally, it is possible to model Interestingly, this technique allows marketers that, but they can create a more fact-based
the incremental household penetration gener- to look at the buying rates among shoppers discussion of optimal frequency, as seen in the
ated by each marketing activity. who were exposed to advertising and those sample chart above.
Armed with this information, a marketer can who were not. It also can show the buying While this kind of chart has been available in
optimize investments across platforms because rates of those not reached through online or the past, it was harder to gather the data, so
the technique reveals the relationship between television advertising. For example, category only the biggest brands could produce them.
marketing activities and sales response much buyers who were not exposed may constitute Alternatively, this graph could have been gen-
more accurately than models of the past. This an opportunity cost (lost sales) that can be erated through modeling, which theoretically
is a thought-provoking advantage, because it pursued in subsequent media plans – when at least makes it less accurate. As cross-plat-
inches marketing closer to an era of “perfect tracked consumption patterns could identify form analysis becomes more prevalent, the
information” – not quite grasping
the Grail, but nearing it.
2. An Accurate Picture of In-
Market Responsiveness by Shop-
per Segment: Because shopper
“
The new team leads will manage a
behaviors are observed and not joint venture between brands and
generated through statistics, it
is possible to separate groups of retailers, going after pockets of
shoppers into multicultural, gen-
erational or other segments. Mar- demand and allocating resources to
keting responsiveness then can be
read and compared. maximize returns very specifically.”
Such in-market, passive obser-
vation is likely to be more revealing Patrick Fitzmaurice, principal, The Capré Group
of real-world responsiveness than
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4. special Report
Tracked Vehicles and Proven Impact cause the data will “speak to everything,” forc-
ing heretofore discipline-focused marketers to
on Fast-Moving Packaged Goods do the same.
It also may level the playing field somewhat
Vehicle Proven Role between large and small brands – and large
and small marketing efforts. If the cost of digi-
Trade promotion Bring in frequent shoppers tal data output declines (as it has consistently
in the past), the cost of measuring campaigns
TV Bring in new users may become affordable for most marketers.
The implication is that smaller, savvy players
may better be able to give big brands a run for
Coupons Drive loyalty and usage
their money.
While these data techniques are still na-
Internet Bring in new users
scent, one thing is certain: Big data is coming.
Source: Millward Brown It’s time for shopper marketers to prepare.
data should become more accurate and less keters have been calling for their companies
expensive, allowing even smaller brands to get to “break down the silos” within entrenched About the Author
better decision-making tools. legacy departments, which were developed in
5. An Understanding of the Role Each Vehicle response to the marketplace needs of 20 years
Plays in Driving Sales: Because opportunity-to- ago. What was an efficient practice in 1995 is
see data is tied to sales figures, it is possible to hampering growth in 2012.
understand the role each marketing element “We need to break down the silos. These
has had on the business. Now, marketers can conversations will not be easy because of the
look at the real impact of TV or in-store, for mindset that trade is trade, brand dollars are
instance. These vehicles play different roles in one bucket and shopper dollars [are] in an-
that will be tracked – not merely modeled. (See other,” Jim Fuqua, Supervalu’s then-director of
chart, above.) shopper marketing, told Shopper Marketing in
This is great news for shopper marketers, early 2011. Booz & Co. has similarly called for
who are looking to create effective messages the change: “To maintain its growth and fulfill
at different points along the path to purchase. its promise, shopper marketing must evolve
Strategy and creative teams can leverage this beyond a siloed, tactical practice and become
Liz Crawford has more than 20 years
information to drive specific behaviors at dis- a strategic capability that is better integrated
of brand management and consulting
tinct touchpoints. with other major investments and across the
marketing and media ecosystem.” (Shopper experience with a concentration in
Big Data, Big Implications Marketing 3.0: Unleashing the Next Wave of strategic innovation. Over the last
Since the turn of the millennium, shopper mar- Value. Booz & Co./GMA, 2010) few years, Crawford has focused
Repeated calls like those have met with a on developing integrated shopper
marketing strategies for Fortune 500
Series Schedule slow – even obstinate – industry response.
While intentions are often sincere, reorganizing clients. Currently, Crawford is an
can be painful and, therefore, is often resisted. analyst and contributing writer for the
Part 1: Rationalizing the But big data will force the change. According Path to Purchase Institute. McGraw-
Investment to Bill Pink, senior partner at Millward Brown, Hill released her book, “The Shopper
New York, “The data itself will break the silos. Economy,” in March.
Part 2: Measurement of You can’t have data that speaks to everything
Shopper Behavior and people who don’t talk to each other.”
Patrick Fitzmaurice, principal of The Capré
JWT/OgilvyAction Inc., conducting busi-
Part 3: Measurement of Brand Group consultancy in Atlanta, envisions a new
ness under the OgilvyAction and JWT Ac-
Impact role for customer-facing talent that “will be
tion brands, is a fully integrated, end-to-
very different from the rates-and-dates mental-
end shopper marketing and experiential
Part 4: Effective Integration ity of the past. The new team leads will manage
marketing agency with main offices in
a joint venture between brands and retailers,
Practices going after pockets of demand and allocating
New York, Chicago and Akron, Ohio. It is
part of the WPP Group.
resources to maximize returns very specifically.”
Part 5: Retail Collaboration The effective use of big data promises to an-
swer the need to rationalize marketing invest-
Part 6: Directions for the ments by tracking individual shoppers as they
Future are exposed to multiple marketing elements.
Further, it potentially can erode silo walls be-
4