1. April 2017
Today, consumers are convenience-driven, which often means device-agnostic.
They’re picking the channel that’s the most convenient, whether that’s looking down
at their mobile phone or ahead at the store shelf. For marketers wanting to
effectively tie consumer behavior to specific campaign activities, this is where
multichannel attribution comes in. eMarketer has curated this Roundup of articles,
insights and interviews to help you understand how crucial multichannel attribution
is for marketers now more than ever.
MULTICHANNEL ATTRIBUTION
ROUNDUP
presented by

2. Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 2
MULTICHANNEL ATTRIBUTION ROUNDUP
Overview
Attribution is crucial for US companies to
track the impact of their marketing efforts.
Although the majority have some type of digital
attribution model in place, the need for more
advanced multichannel attribution is important
so marketers can determine which components
of their marketing program led to a consumer’s
specific action.
Attribution—which is a method of assigning credit to a
particular marketing-driven interaction or other brand-
related touchpoint—is important to marketers to help
inform their media planning and buying decisions. Overall,
the majority (81%) of US companies with at least 100
employees using more than one digital channel for their
marketing campaign have an attribution model in place this
year, according to eMarketer estimates.
Yet, as the number of digital channels, platforms and ad
formats continue to grow, it’s critical that marketers sink
their teeth into more advanced, or multichannel attribution
models. This way, they can pin down which channels are in
fact driving ad performance.
Take a look at just how fragmented consumers’ time is
being spent across all media. According to eMarketer
estimates, while US adults spend just over 4 hours a day
watching TV, they’re also consuming upwards of another
nearly 6 hours on digital. Break that down further, and the
numbers show that adults are investing 3 hours on mobile
(nonvoice) and another 2 on desktop/laptop.
While multichannel attribution models had not been widely
used in the past, eMarketer numbers suggest adoption
is growing. This year, 50.2% of US companies that are
using more than one digital marketing channel currently
use multichannel attribution models. By 2018, eMarketer
predicts that 58.5% will use a multichannel attribution
model for tracking their digital marketing efforts..
% of total
Share of US Companies Using Digital Attribution
Models, 2014-2018
2014
61%
2015
68%
2016
75%
2017
81%
2018
86%
Note: companies with 100+ employees that use more than one digital
marketing channel; an attribution model is a way to differentiate the
respective contributions of various marketing channels to a desired
outcome; includes first- and last-touchpoint models and more complex
multichannel models
Source: eMarketer, Oct 2016
217117 www.eMarketer.com
Total per day=12 hours 7 minutes
Digital
hrs:mins
Average Time Spent per Day with Major Media by
US Adults, 2017
Note: ages 18+; time spent with each medium includes all time spent with
that medium, regardless of multitasking; for example, 1 hour of
multitasking on desktop/laptop while watching TV is counted as 1 hour for
TV and 1 hour for desktop/laptop; *excludes digital; **includes all internet
activities on desktop and laptop computers
Source: eMarketer, April 2017
225407 www.eMarketer.com
Digital
5:50
TV*
4:04
Radio*
1:26
Print*
0:25
Other*
0:21
Mobile
(nonvoice)
3:14
Desktop/
laptop**
2:08
Other connected devices
0:28

3. Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 3
Marketers Renew Interest in Cross-Channel Attribution
But focus on programmatic buying for mature formats slips
When it comes to collecting and evaluating
audience data, marketers can choose from a
multitude of tactics. Recent research suggests
there’s an increased interest in cross-channel
measurement and attribution this year, edging
ahead of former go-to tactics like general
audience analytics and programmatic
media buying.
Almost 60% of US digital marketing and media practitioners
polled in January 2017 by the Interactive Advertising
Bureau (IAB) and Winterberry Group said they expect to be
engaged in cross-channel measurement and attribution
this year.
But there is a caveat: When IAB and Winterberry conducted
this same survey back in January 2016, a little over a half
of marketers said they expected to spend more time with
cross-channel measurement and attribution. Yet, according
to the recent data, only a third of those polled actually
engaged more effort on cross-channel measurement and
attribution in 2016.
For 2017, marketers have predicted similarly, so it isn’t clear
that time spent on cross-channel analysis will actually grow
in line with marketers’ proposed intentions. It apparently
didn’t last year.
That aside, there’s certainly interest in the tactic and it’s
justified. Attribution is key for marketers looking to optimize
media channels in this increasingly fragmented world.
“Attribution is key for marketers looking
to optimize media channels in this
increasingly fragmented world.”
For instance, the retail industry is taking a more serious
stance on cross-channel marketing by incorporating both
online and offline tactics, and gaining greater insight into
their customer base. About four in 10 retail marketers
worldwide said they will implement cross-channel
attribution initiatives in 2017, according to a Yes Lifecycle
Marketing survey.
While doubling down on cross-channel attribution, the
IAB/Winterberry Group survey found there were some
tactics that respondents said they’d be spending less
energy on. These included general audience analytics,
programmatic media buying for more mature markets and
predictive modeling.
The decreasing interest in programmatic for established
formats is particularly interesting, considering recent news
about advertisers boycotting Google over objectionable
content near ads. Apparently, marketers want to take a
more hands-on approach in deciding where their ads
appear and don’t appear.
% of respondents
Tactics that Occupied vs. Will Occupy Their Time/
Resources According to US Digital Marketing/Media
Practitioners, 2015-2017
Cross-channel measurement
and attribution
Programmatic media buying for
established formats
Cross-channel audience
identification/matching
Advertising content/experience
optimization
General audience analytics
Predictive modeling or
segmentation
Programmatic media buying
for emerging formats
Yield optimization
Online retargeting
Online-to-offline (or offline-to-
online) retargeting
Site content/experience
optimization
Single-channel measurement
and attribution
Occupied
in 2015
35.4%
50.5%
45.5%
27.3%
47.5%
44.4%
37.4%
32.3%
34.3%
14.1%
25.3%
25.3%
Occupied
in 2016
33.3%
48.8%
33.3%
26.2%
52.4%
45.2%
29.8%
28.6%
33.3%
25.0%
21.4%
25.0%
Will occupy
in 2017
57.1%
47.6%
42.9%
40.5%
40.5%
38.1%
38.1%
33.3%
22.6%
22.6%
22.1%
-
Note: respondents selected up to 5
Source: Interactive Advertising Bureau (IAB) and Winterberry Group, "The
Outlook for Data 2017: A Snapshot Into the Evolving Role of Audience
Insight," Jan 30, 2017
222736 www.eMarketer.com

4. Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 4
Marketers Turn to Cross-Device Targeting to Better Understand
Their Audience
Cross-device analysis is broadening beyond simply IDing individuals
Over the past 12 months, advertisers’
understanding of cross-device targeting and
the identity matching methodologies behind
the technology have improved. With that
improvement comes added expectations for
the types of data that can be added to these
identity graphs and the locations in which that
targeting can be applied, such as in living
rooms and in stores.
Demand for cross-device targeting is high, and there is
no shortage of ad tech players and solutions providers
that have made headlines in the past year boasting such
offerings. But advertisers are still incorporating these
capabilities into their marketing programs.
Among the marketers in North America polled by
Econsultancy in a September 2016-released survey, less
than half reported the ability to understand cross-device
behavior, understand cross-channel purchase paths and
tailor creative to meet those understood behaviors. Slightly
more than half reported the ability to utilize customer data
to find similar audiences, but it’s important to acknowledge
that such a capability might be applied to a single platform
or channel, not a cross-device or cross-channel strategy.
“Ironically, there are probably more companies that are
targeting media across devices than there are companies
that actually understand the cross-device behavior of
their customer base,” said Brandon Wishnow, executive
director of measurement and activation for Ovative/
group, a media consulting firm that specializes in helping
clients with managing their audience data in order to
carry out essential digital functions, such as omnichannel
measurement. “They’re using any number of targeting
technologies that are out there to buy media, but they’re
not necessarily close-looped with their measurement.”
Such a distinction is becoming more important. Cross-
device may have started as a solution for identifying
individuals across multiple devices and screens, but it is
broadening into something buyers and sellers turn to for a
much more complete understanding of their audiences.
“In the last year or so, marketers have begun to realize that
it’s not just cross-device targeting and measurement,” said
Tomer Naveh, chief technology officer at Adgorithms, an
artificial intelligence marketing firm. “It’s cross-device and
cross-channel to look at the holistic journey that the users
go through to understand how to optimize those journeys.”
“It’s cross-device and cross-channel [that’s
needed] to look at the holistic journey that
the users go through to understand how to
optimize those journeys,” said Adgorithms
CTO Naveh.
As a result, buyers, sellers and other tech players requiring
audience identification capabilities are moving quickly to
change how they vet cross-device solution providers.
% of respondents
Consumer-Related Capabilities at Their Company
According to Marketers in North America, March 2016
Use data about our customers to find similar audiences
58%
Understand our customers' typical cross-channel buying
journeys
48%
Deliver dynamic content across digital formats, such as display,
mobile and video advertising, in response to individual's
behavior
46%
Understand our customers' cross-device behaviors
39%
Note: n=212
Source: Econsultancy, "Customer Recognition: How Marketing is Failing at
its Top Priority" in partnership with Epsilon and Conversant, Sep 14, 2016
216902 www.eMarketer.com

5. Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 5
Viewthroughs Gain Attention as Attribution Tactic
Platforms such as Snapchat, Instagram aren’t oriented around a click
Click-based attribution models have long been a
staple of digital advertising. These legacy models
have endured despite mounting research against
their validity, thanks to issues associated with
click fraud and because so few conversions are
influenced by a single channel or touchpoint.
Many marketers are keen to turn to blended
attribution models that take clicks and
viewthroughs into account.
New data shows that times are changing. A recent survey
of marketing professionals in the US and Europe conducted
by Qualtrics for AdRoll found that although 65% of
respondents said they use single-click attribution, 57% plan
on changing their model.
The reason?
Consumer engagement on platforms that marketers
increasingly rely on to drive conversions are not necessarily
click-based anymore. “Just a few years ago, we were in
a search-dominated market,” said Shane Murphy, vice
president of marketing at AdRoll. “If consumers wanted to
buy something, they would search for a product, see some
search ads, click on them and convert. In that world, a
click-based model makes sense.”
But the prevalence of visual social platforms such
as Instagram and Snapchat have changed the way
consumers shop.
“These new platforms aren’t oriented around a click,”
Murphy said. “Instagram, for example, is all about building
a brand and targeting people across multiple different
platforms in order to drive conversion. Given how much
the customer journey has changed, marketers can’t just
measure clicks anymore.”
As the survey suggests, this has many keen to turn to
blended attribution models, which the firm defines as
models that take clicks and viewthroughs into account.
Thanks to that growing recognition, marketers appear to
be placing greater emphasis on conversions generated by
viewthroughs, or instances when consumers see ads but
don’t actually click on them. Findings from the same survey
examined a three-year period, finding that the importance
or weight assigned to viewthrough conversions has
increased over that timeframe.
In 2014, only 14% of marketers polled in the US and
Europe assigned 50% or more conversion influence to
viewthroughs. But in 2016, nearly half (46%) of respondents
said they attributed at least 50% of the weight to
viewthrough conversions.
Overall, only 1% of respondents said they didn’t count
viewthrough conversions at all in 2016, down from 8%
in 2014.
Across the broader industry, others are also looking to
enhance their viewthrough capabilities.
Google, for example, announced recently that it will
decrease the viewthrough conversion window in its
AdWords tool from 30 days to one day, because ads
are more likely to drive a purchase on the day they’re
seen. For marketers using Google AdWords to measure
ad effectiveness, that means that only sales that take
place within 24 hours of an ad view will be counted as
a conversion.
% of respondents
Weight that Marketing Professionals in Europe and
the US Assign to Viewthrough Conversions, 2014-2016
2014
7% 38% 33% 14% 8%
0%-9%
10%-24%
25%-49%
50%-100%
Don't count viewthrough
conversions
Note: read as 6% of respondents attribute <10% of conversions to view-
through action in 2016; numbers may not add up to 100% due to rounding
Source: AdRoll, "2017 State of Performance Marketing" conducted by
Qualtrics, March 7, 2017
224207 www.eMarketer.com
2015
5% 19% 45% 29% 2%
2016
6% 17% 29% 46% 1%

6. Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 6
Cross-Device Attribution is Crucial, But Challenging for Marketers
Nearly three-quarters say matching customers across multiple devices
is a priority
Understanding consumers’ behavior as they
switch between devices remains one of the
toughest challenges facing marketers today.
According to recent research investigating
marketers’ digital capabilities, the problem
doesn’t seem to be getting any easier.
In a September 2016-released survey by Econsultancy
investigating the gaps between digital priorities and
capabilities at companies in North America, “matching
customers across multiple devices” was mentioned as a
digital priority by nearly three-quarters of the marketers
polled. Yet only 14% of marketers in the same survey said
their company had the capability to handle such matching,
a gap of 60 percentage points.
Even though cross-device attribution did not have the
biggest gap between company priorities and capabilities,
additional data from Econsultancy emphasizes the
challenge that the tactic poses for many organizations.
When asking the same group of executives about the
consumer-related capabilities of their companies, only 39%
said they were able to understand their customers’ cross-
device behaviors, lower than any other
capability mentioned.
% of respondents
Digital Priorities vs. Capabilities at Their Company
According to Marketers in North America, March 2016
Associating conversion events with marketing
84%
10%
Tailoring messaging by channel
76%
13%
Understanding customer behavior over time
75%
12%
Matching customers across multiple devices
74%
14%
Priority Capability
Note: n=184
Source: Econsultancy, "Customer Recognition: How Marketing is Failing at
its Top Priority" in partnership with Epsilon and Conversant, Sep 14, 2016
216903 www.eMarketer.com
% of respondents
Consumer-Related Capabilities at Their Company
According to Marketers in North America, March 2016
Use data about our customers to find similar audiences
58%
Understand our customers' typical cross-channel buying
journeys
48%
Deliver dynamic content across digital formats, such as display,
mobile and video advertising, in response to individual's
behavior
46%
Understand our customers' cross-device behaviors
39%
Note: n=212
Source: Econsultancy, "Customer Recognition: How Marketing is Failing at
its Top Priority" in partnership with Epsilon and Conversant, Sep 14, 2016
216902 www.eMarketer.com

7. Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 7
The Advantages of Marketing Mix Models
Matt Krepsik
Global Head of ROI
Nielsen
Most marketers rely on either marketing mix
models or a form of attribution modeling to
measure how effectively their marketing efforts
are driving sales. There are pros and cons to
both approaches, especially as both continue
to mature, but marketing mix models take some
elements into account that attribution models
often do not. Matt Krepsik, global head of ROI at
Nielsen, spoke with eMarketer’s Maria Minsker
about making the case for marketing mix models
and how brands can benefit from them.
eMarketer: A growing number of vendors are offering
marketing mix models for measuring the impact of
marketing tactics on sales. Can you explain how these
models work?
Matt Krepsik: Marketing models enable companies to
understand and assess the incremental value of their
investments. What makes marketing mix models unique
is their capability to take effective frequency and reach
into account. For example, the models can identify that if a
brand is launching a TV campaign, it needs to drive a reach
of around 60% of viewers. That percentage is identified as
a saturation point, and after it’s reached the brand will start
to see diminishing returns.
On top of that, there’s the concept of effective frequency,
which is the number of times a company should invest
in order for a customer to see an ad and respond to it.
The embedded intelligence behind marketing mix model
decisioning is based on an understanding of reach and
frequency, which enables marketers to make better
decisions and optimize their expense.
eMarketer: How effective are these models at predicting
how marketing drives sales?
Krepsik: When the models control other factors that
influence businesses, they produce a fairly strong level
of accuracy. Our Benchmark Media Optimizer tool uses
a marketing mix model, for example, and we typically
make predictions within 5% to 6% of the actual in-
market performance.
eMarketer: In what ways can marketers take the
insight they gain from marketing mix models and make
it actionable?
Krepsik: Let’s say I’m a brand owner and I’m trying to
figure out what my media plan will look like next year.
Perhaps I want to shift dollars to a digital campaign.
What’s amazing is a marketing mix model not only allows
marketers to make those budgetary decisions with really
solid intelligence, but can also push those decisions
forward into other activation platforms, such as the
marketing cloud.
eMarketer: What happens when a brand uses a marketing
mix model from one vendor, but relies on a different
marketing cloud provider? Do integration challenges arise?
Krepsik: No brand owner in the world is going to use
the same tool for everything. [That’s why it’s important
to] build direct integrations to the buying platforms of
choice, whether those are agency platforms or third-party
platforms, such as the Adobe Marketing Cloud.
eMarketer: What’s the next phase for marketing mix
models? Are they going to become smarter and more
accurate over time?
Krepsik: We already know so much about how brand
owners make investments in their media buys that artificial
intelligence [AI] is the next phase. An AI prediction engine
will be able to make two or three recommendations on
media buys before even building a model. Rather, the
prediction will be based on a brand’s profile and what is
generally known about consumers in a specific category
and in a specific country.

8. Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 8
Still Targeting Devices Rather than Users? Why that Is Problematic
for Programmatic
Marc Grabowski
Executive Vice President, Global Supply and
Business Development
Criteo
Marc Grabowski, executive vice president of
global supply and business development at ad
retargeting firm Criteo, spoke with eMarketer’s
Lauren Fisher about the importance of taking a
user-centric view when buying programmatically
and shared his observations on the latest trends
in header bidding.
eMarketer: What are some of the big trends you are
seeing unfold in the programmatic space today?
Marc Grabowski: We’re seeing a number of things,
but the first is mobile cross-device or omnichannel.
We’ve obviously been seeing this area unfold for years,
with revenues and purchase behavior moving over from
desktop to mobile and tablets. We are continuing to see
that in 2017.
Criteo works with a lot of ecommerce and retail, and we’ve
seen that the number of conversions taking place on
smartphones is up enormously year over year. In our latest
study, “The State of Cross-Device Commerce,” we found
it’s up 41%, so a big number. That probably doesn’t come
as a big surprise, but we are also seeing that the customer
journey is longer and involves more devices than a lot of
people previously suspected.
“The customer journey is longer and
involves more devices than a lot of people
previously suspected.”
A lot of people still look at things in terms of device view
vs. user view. Device view is if you look at how people are
interacting with the brand on a single device. User view is if
you look at the user across all devices.
We found that if you look at a device-centric view, about
43% of transactions take place in the first visit to a website.
But if you look at a user-centric view, you see that it’s only
32% on the first visit. That means that, looking at a user
across multiple devices along their journey, they have a
much longer path to purchase than [if you look] at the user
on just a single device.
So it’s important for us to examine the value of that user
and attribute that properly across those devices, because
it then allows us to bid more for those users and find them
in much more valuable areas than if we just took a single
device view.
eMarketer: Does moving from a device-level view to a
user-level view substantially change your bid strategy? It
seems like it would, given the numbers you shared above.
Grabowski: In programmatic, it makes a big difference. We
can bid more for that user because we can assure a higher
value to an advertiser longer-term, because we know more
about their user behavior. If we’re only attributing sales to
a user on a single device, the challenge is we’re attributing
too low. Instead of assessing a bid based on the likelihood
for a user to convert on a particular device, we need to
assess a bid based on the likelihood of that user to
convert, period.
If we look at a device-centric view of conversions in the US,
we see about a 6% conversion rate. But if we look at a user-
centric view, we see [that rate] go up to about 9%. That
allows us to bid 1.4 times higher, and allows the advertiser
to capture more value for that user when they’re bidding
than if they were just looking at a single device.
eMarketer: I know Criteo is very active in the header
bidding arena today. What big trends are you seeing?
Grabowski: We are definitely seeing that header bidding
is important, and it’s a big topic. There are some benefits
and drawbacks for header bidding. One of the big benefits
is it brings a lot of demand forward for the publisher,
and it’s definitely an advantage for savvy buyers. But it

9. Multichannel Attribution Roundup Copyright ©2017 eMarketer, Inc. All rights reserved. 9
becomes very difficult for smaller, less sophisticated buyers
to evaluate inventory across platforms, which is probably
going to lead to greater consolidation it the space.
“If we look at a device-centric view of
conversions in the US, we see about a 6%
conversion rate. But if we look at a user-
centric view, we see [that rate] go up to
about 9%.”
When people were buying in the waterfall in the past, you’d
see an impression. You’d evaluate the impression. Then
you’d determine if you wanted to bid or not. But now, if
you’re buying across multiple [supply-side platforms] SSPs
as well as publisher direct, you might see that impression
come up in 10 or 15 different auctions. It becomes much
more difficult for buyers to understand where they should
be buying that [impression] and what they should be
bidding on it.
Over the past year, we’ve actually had a lot of the [demand-
side platforms] DSPs coming to us and saying, “Look,
it’s getting more and more difficult for us to buy across
multiple SSPs. Can you help us do that? Can you do the
bidding on our behalf so that we can actually end up
buying some of that inventory through you?” That’s been
a big trend for a lot of companies, and I think it’s going to
lead to greater consolidation in the next year or two.
“Publishers are trying to figure out how to
do server-to-server, but they just moved
over to header bidding or to a wrapper
and have now realized they have to make
another move.”
eMarketer: Many of the conversations about
consolidation have to do with the transition to server-to-
server header bidding, in which the publisher chooses a
primary header partner though which the auction with
all other header partners will run. There’s a lot of hype
around server-to-server, since it enables publishers to
take the auction out of the browser—thereby improving
some of the page-load latency issues header has caused.
Are you seeing many publishers transitioning to server-to-
server setups?
Grabowski: We see a lot of publishers asking questions,
but we haven’t seen a lot of publishers make that move
yet. There are definitely pockets where they have, and I
think that over the next six to nine months, it’s going to
pick up a lot of steam. Publishers are trying to figure out
how to do server-to-server, but they just moved over to
header bidding or to a wrapper and have now realized they
have to make another move. It does take time, and a lot of
publishers don’t have the IT resources to be able to roll out
new infrastructure that quickly.
Now the benefit for server-to-server is less latency, as well
as potentially feeling less data risk and leakage. And as
more inventory moves over to mobile, server-to-server is
not only going to address the latency, but it can also serve
in-app much better. There’s no question a lot of the space
will move there, but it hasn’t moved yet.

10. ©2017 AOL Inc. All rights reserved.
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