eMarketer_Data_Management_Platforms-Using_Big_Data_to_Power_Marketing_Performance.pdf

7/27/2019 eMarketer_Data_Management_Platforms-Using_Big_Data_to_Power_Marketing_Performance.pdf

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DATA

MANAGEMENT

PLATFORMSUsing Big Data to Power

Marketing Perormance

MAY 2013

Lauren T. Fisher

Contributors: David Hallerman, Tracy Tang, Mitchel Winkels

Read this on

eMarketer or iPad
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DATA MANAGEMENT PLATFORMS: USING BIG DATA TO POWER MARKETING PERFORMANCE 2013 EMARKETER INC. ALL RIGHTS RESERVED 2

CONTENTS

3 Data, Todays Digital Advertising Currency

7 Targeting

10 Digital and Cross-Platform Attribution

12 eMarketer Interviews

13 Related eMarketer Reports

13 Related Links

13 Editorial and Production Contributors

EXECUTIVE SUMMARY

Theres a big to-do about Big Data and data

management platorms (DMPs) in the digital

advertising space. From audience targeting to

cross-platorm measurement and attribution, DMPs

enable marketers to use their Big Data to make

smarter and more efcient marketing decisions.

But like any new trend, buzz currently surpasses expert

adoption and usage. Brands are using Big Data to build a

holistic picture o their potential and real customers and

then target those users, but many still nd it challenging

to extract cross-channel insight rom that data.

For now it seems most brands have access to DMPs

through their programmatic inventory providers, like

demand-side platorms (DSPs) or ad exchanges. Because

o this, the majority o DMP use comes in the orm o

audience targeting. But the real value o DMPs is their

ability to provide a more strategic view o digital or

cross-platorm perormance. Though marketers are just

beginning to use them or this purpose, many are already

hopeul DMP usage will yield real-time campaign insights.

KEY QUESTIONS

What are Big Data and DMPs?

How are marketers using DMPs or

audience targeting?

How are publishers using DMPs or audience

targeting?

How are marketers using DMPs or digital and

cross-platorm attribution?

How are DMPs dierent rom CRM platorms?

% of respondents

Important Priorities for Future Data ManagementPlatform (DMP) Support According to US MarketingProfessionals, Sep 2012

Customer insight development 93%

Targeted media buying 90%

Campaign/channel attribution 86%

Multichannel integration & optimization 84%Emerging channel deployment 84%

Channel optimization 83%

CRM program optimization 76%

Creative content optimization 73%

Site content optimization 69%

Advertising yield optimization 59%

Note: respondents include advertisers, marketers, publishers, technologydevelopers and marketing service providersSource: Winterberry Group and Interactive Advertising Bureau (IAB), "TheData Management Platform: Foundation for Right-Time CustomerEngagement," Nov 12, 2012

153583 www.eMarketer.com


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DATA: TODAYS DIGITAL

ADVERTISING CURRENCY

Nearly every action taken in the digital space requires

data input and results in data output, putting

a massive amount o inormation at marketers

disposal. Data is the currency o todays digital

advertising ecosystem, and everything rom media

planning to analyticsand every campaign execution

in betweenruns on it.

Columbia Business School and New York American

Marketing Association (NYAMA) ound 91% o US

marketers surveyed believed successul brands used data

to drive marketing decisions.

But research suggests this is no easy task. Zi Davis

ound 49% o companies polled worldwide had enacted

a data management strategy as o all 2012, andaccording to a survey rom IT stang service Robert Hal

Technology, just 23% o US chie inormation ocers

(CIOs) said they were collecting customer data such

as demographic inormation or buying habits. O that

small percentage, less than hal (46%) reported having

the resources or systems to analyze the inormation

they gathered.

Yes23%

No76%

Don'tknow2%

% of respondents

Collection of Customer Data and the Use of the Datato Generate Strategic Reports and Insights Accordingto US CIOs, Nov 2012

Note: *email addresses, demographics, buying habits, etc.; **have atechnology team with sufficient personnel to access and generate strategicreports and insights from the customer data they collectSource: Robert Half Technology as cited in press release, Jan 24, 2013


Companies thatcollect customer data*

Companies that havesufficient resourcesto utilize** the datathey collect

Yes46%

No53%

Don'tknow2%

To address the Big Data surplus and begin to convert this

currency into actionable results or digital advertising and

uture marketing initiatives, many marketers are looking

to DMPs.

BIG DATA

The high value placed on data in todays advertisingecosystem has heightened ocus on Big Data: a

catch-all phrase that describes any data or inormation

a company collects on its audience, customers or

users. A very general term, Big Data can reer to

rst-party customer inormation, third-party audience

data, ofine purchase data, online advertising behavioral

data, campaign analytics and much more. Alone, each

o these data assets describes some aspect o a users

actions, interests and intent. When combined, they

become Big Data.

According to Dr. Mark Grether, COO o Xaxis, GroupMsagency trading desk, Big Data typically alls into

three categories:

First-party data. This is any inormation the advertiser

or company owns and collects, or example, customer

relationship management (CRM) data, in-store sales

data or advertising campaign data. First-party data is

the oundation or any audience insight, analysis and

attribution and is the cornerstone o any Big Data strategy

Third-party data.This is any inormation purchased rom

a data reseller or provider, most commonly in the orm

o cookies. Companies like BlueKai, Bizo and eXelate

are common third-party data providers. Such cookie data

could be demographic in nature; it could be psychographic

or even behavioral. This inormation is commonly used

in campaign targeting, identiying additional prospects

and enhancing campaign analytics. Data can be either

native to digital (or example, rom ecommerce sites or

publishers) or rom a traditional data source (or example,

customer loyalty data or ofine purchase data). Any

advertiser or publisher can rent this data, so it is not

uncommon or many companies to be using the same

set o cookies to power their audience targeting or other

display advertising eorts.


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Second-party data.This is any inormation that display

ad inventory providers such as a DSP, ad exchange,

agency trading desk or supply-side platorm (SSP) owns.

All o these inventory providers and sellers collect data,

which they make available to companies using their

services. For example, advertisers using a DSP to execute

their display ad buys can have access to any number o

user cookies or ad placements across the DSPs network

o partners. Companies that do not use one o theseservices would not be privy to second-party data.

Grether also noted another data type that companies

could include in their data management strategy.

Reerred to as external data, this category included

other inormation sets that can be tied in to determine

causal relationships and ad perormancesuch as the

weather, nancial trends and current events. For example,

a nancial investment rm might track stock market

fuctuations to determine the eect on new account

sign-ups. What is dierent about this inormation is that it

does not pertain to any one individual or user.

Bear in mind that hundreds, i not thousands, o data

assets can t into each o the categories mentioned

above. As a result, marketers have the potential to include

just as many datapoints in their Big Data strategies.

However, most marketers agree that when it comes to

Big Data, bigger isnt always better.

Its not Big Data that were interested in, said Troy

Lerner, president o Booyah Advertising, an ad agency

that recently built is own agency trading desk. Its resh

data and rst-party data. Thats what we want.

Determining which data is right or a Big Data plan is only

one step toward converting those assets into actionable

insight. Companies must then organize and standardize

the inormation into meaningul segments.

It can prove challenging to integrate disparate sets o

data coming rom social media, campaign analytics,

ofine sources or third parties. In act, Big Data solution

provider Inochimps surveyed IT proessionals in North

America, and 83% o respondents said processing such

inormation was a leading Big Data challenge, ollowed

by managing the inormation (42%) and analyzing the

data (41%).

% of respondents

Leading Big Data Challenges According to ITProfessionals in North America, 2012

Processing the data

83%

Ongoing management of the data

42%

Analyzing the data

41%

Source: Infochimps, "CIOs & Big Data," Feb 6, 2013


The one thing thats so dicult about Big Data is that

at the end o the day, its about those big insights, said

Sean Muzzy, CEO o Neo@Ogilvy. People want those

key nuggets that, having all o this data in one place, you

can actually uncover.

To uncover those insights by organizing, processing and

analyzing this data, most marketers are turning to DMPs.

For more on how marketers are using Big Data

or ecommerce, please see eMarketers May 2012

report, How Retailers Are Leveraging Big Data to

Personalize Ecommerce.

DMPSI data is the currency o digital marketing, then the DMP

is the bank. Big Data is stored and standardized here so

that each data asset can be tied to a particular customer

or audience segment. Once standardized, marketerscan use that inormation to power multiple unctions,

both within digital and across a companys broader

marketing program.

The DMP is really a central nervous system that allows

you to compile all o these data sources and turn them

into a meaningul set o [audience] segments that you can

use or multiple purposes, said Tim Waddell, director o

product marketing or AudienceManager, Adobes DMP.

Waddells analogy highlights both the uniqueness o a

DMP as well as its place within the ad tech ecosystem.

As he states, a core use o the DMP is to organize and

house a variety o data sourcesa unction thats not

much dierent rom other marketing databases like a

CRM system, analytics tool or call center database.
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As the primary repository or customer data, one might

assume a database such as a CRM system would

suce or Big Data. But CRM tools are only capable o

housing certain sets o customer inormation and data

and in limited amounts. What sets a DMP apart is its

ability to house a much larger and broader spectrum o

inormation. Marketers use DMPs to integrate inormation

rom all marketing databases, including a CRM system, in

addition to many other data sources.

DMPs can house both structured data, typically

quantitative in nature, as well as unstructured data, oten

qualitative in natureor example, social network data.

Once all o these disparate sources are entered, DMPs

can standardize them to build a larger, more descriptive

picture o a customer or audience base marketers can

act on.

The DMP is undamentally dierent in that it allows

us to generate a much broader view o the consumer

journey than most digital technologies would have accessto, said Richard Lloyd, Xaxis data management platorm

director. In an ad server, or example, you might only

see a subset o the total volume o events a consumer is

participating in. The DMP gives us a complete history o

that journey that we can use to really understand which

components o that journey are actually driving value rom

an engagement or conversion perspective.

The DMPs central role within the advertising technology

ecosystem makes it possible to act on this audience

intelligence in a variety o ways. It is one o the ew

technologies that integrate with nearly every other

system required to execute and track digital advertising

programs: marketing automation, CRM systems, ad

servers, dynamic content servers, email marketing tools,

attribution tools, ad verication sotware and much more.

This positions the DMP as the urnace o the digital ad

enginea capability that has only been leveraged within

the past couple o years.

Eighteen months ago, a DMP was just a big box sucking

in data, said Mark Zagorski, CEO o data provider

eXelate. Now you have two branches emerging: There

are data marketing platorms, which allow us to activate

all o that data or targeting and more ecient ad delivery,

and then theres the data analytics side, which allows

us to use the data to better inorm online and ofine

marketing decisions.

For more about the DMPs place within the digital

advertising ecosystem, please see our October 2012 report

eMarketers Guide to the Digital Advertising Ecosystem:

Mapping the Display Advertising Purchase Paths and

Ad-Serving Process.

Its important to note that though DMPs in a general

sense can have both capabilities, not all have the same

set o unctions. Many o the DMPs used to powerprogrammatic ad buying and selling platorms like DSPs

and SSPs, or example, are primarily used or display

ad targeting. Today, the majority o marketers are likely

accessing a DMP through these inventory sources.

Not many publishers or advertisers are using standalone

DMPs, said Grether. I think that will shit as brands and

publishers become more amiliar with the space and

understand those DSPs and SSPs only oer some o the

unctionality that a ull DMP can.

Standalone DMP providers, or those that build their ownDMPs to power an agency trading desk, would likely build

in additional unctions beyond targeting. For example,

many incorporate attribution capabilities to tie in data rom

other ad ormats and channels.

Because o this, Laurent Colard, global managing partner

at GroupM, sees DMP unctionality as more o a T-shape

vs. two distinct branches.

The base o the T pertains to the digital unction o

the DMP. Here lies the ability to track and analyze

that cookie-level data within digital or the purpose oidentiying individual audience insights. Thats where

the traditional denition o the DMP alls, Colard said.

Its very, very narrow but goes extremely deep and

is extremely actionable because you can tie it back to

trading decisions and targeting decisions, as well as

individual cookies.

On top o that sits a broader unction o the DMP, the

ability to provide what Colard calls a 360-degree view

o all communication channels and all measures o

success, with or without an individual user-level view.

Such a unction is used or cross-platorm analysis and

attribution modeling.
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I you think about the 360-degree broad view o our

clients business, the primary use cases around [the

DMP] are the ability to do cross-channel attribution, he

explained. Ater that, its the ability to do act-based

budget setting and act-based allocation o media across

those channels. When youre talking about channels or

which there are highly trackable, digital data, the use

case or the DMP then turns more into digital attribution

and segmentation.

Findings rom a Radar Research survey urther supported

the concept o using a DMP or both targeting and

larger campaign analytics. The research rm ound that

beyond the obvious expectation o increased return on

investment or DMP use, 55% o marketers worldwide

used a DMP to better target using online and ofine data;

46% used it to drive audience analytics.

% of respondents

Reasons for Using a Data Management Platform

(DMP) According to Marketers Worldwide, Nov 2012

To drive higher ROI

64%

To more effectively centralize, organize and leverage own (orclient's) first-party online and offline audience data for targeting

60%

To create a targeting profile of audience

55%

To drive audience analytics

46%

To house all audience data in a centralized location wheremultiple partners can log on

28%

To automate more of the ad planning and buying process

25%

To extend audience

24%

To increase campaign scale

21%

To optimize ad creative

19%

To control ad costs

18%

To ensure compliance with data collection and privacyregulations

15%

To keep up with competitors now using a DMP

3%

Other

2%

Note: n=67Source: Radar Research, "Data Management Platforms" commissioned byBlueKai, Dec 4, 2012


Lloyd also cited targeting and analytics or attribution as

the two main use cases o the DMP. He bucketed them

into what he reerred to as orward- and rearward-acing

use cases.

Targeting and audience segmentation alls into the

orward-acing bucket. The rearward-acing bucket

contains analytics and attribution, used to understand

why consumers took a certain customer journey andhow the advertising and marketing they were exposed

to infuenced that journey. This particular use case is less

common and a bit more dicult to execute, particularly

when looking to uncover cross-platorm eects.


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TARGETING

Xaxis Lloyd considers targeting a orward-acing

unction given its active, direct use o audience data.

What were trying to do is use the data within the

DMP to predict uture consumer behavior by putting

them into some kind o demographic or interest

category, he said. That kind o segmentation and

targeting use case is pretty well established.

Data rom eXelate supports that statement. According to

the rms April 2013 study, nearly 94% o agencies and

83% o advertisers in the US used audience targeting.

% of respondents

US Ad Agencies, Advertisers and Ad Platforms thatUse Audience Targeting in Their Digital Display Ads,April 2013

Agencies 93.7%

Ad platforms (networks/exchanges/DSPs) 90.7%

Advertisers 82.5%

Source: eXelate, "State of the Industry," April 22, 2013


The DMPs ability to take all o that Big Data rom

rst-, second- and third-party sources and organize it into

meaningul audience segments makes it an ideal tool or

audience targeting. This unction, particularly or rst- and

third-party data, was also the top reported competency

o DMPs by US marketing proessionals surveyed by

Winterberry Group.

% of respondents

Current Core Competencies of Data ManagementPlatforms (DMPs) According to US MarketingProfessionals, Sep 2012

Integration of first- and third-party data

85%

Segmentation

79%

Digital data aggregation77%

Audience analytics

73%

Digital data warehousing

68%

Data transfer/export to channels

60%

Modeling

57%

Integration of digital and traditional data

52%

Note: respondents include advertisers, marketers, publishers, technologydevelopers and marketing service providersSource: Winterberry Group and Interactive Advertising Bureau (IAB), "TheData Management Platform: Foundation for Right-Time CustomerEngagement," Nov 12, 2012


Not only can marketers use DMPs to identiy and crat

specic audience segments, or example, sports ans

or senior-level business executives, the platorms can

oten identiy members o these segments down to the

individual level, which is what more and more advertisers

are ater.

One o the biggest discoveries we had last year as

we got more involved in the programmatic side o our

business was the realization that its not about marketers

looking to target audiences; its really about targeting

individuals at scale, said Mark Howard, senior vice

president o digital advertising strategy at Forbes.

First-party data provides the oundation or most

companies audience segmentation, given that it already

pertains to individual customers, users or prospects.

Marketers can use it to extend their reach via lookalike

targeting or to enhance their retargeting eorts.

Nearly every DMP uses rst-party data. Winterberry

Group ound 96% o marketers in North America polled

managed rst-party behavioral data in their DMPs. An

additional 92% managed third-party behavioral data,

which is commonly used alongside rst-party data

to identiy similar audience segments, or lookalike

segments, across the web.


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The most valuable data is your own rst-party data,

said Adobes Waddell. Everything else is a way to extend

your reach or rene what youve already got with your

rst-party data, and theres real value in being able to pull

that all together.

There are multiple types o rst-party data marketers

might use to build a more holistic view o their audience.

Research rom CMO Council and SAS ound severalcommon data assets marketers worldwide hoped

to incorporate as o Q1 2013. Many o the data sets

ocused on sales, customer service and other rst-party

data sources.

% of respondents

Types of Data that Marketers Worldwide Would Liketo Add to Their Customer Data Profile, Q1 2013

Predictive analytics around lifetime value

71%

Online customer profile/use profile 53%

Customer service and support feedback

45%

Social media data

42%

User survey and preference data

42%

Third-party demographic and profile data

35%

Sales executive insights

24%

Order history

20%Finance/customer payment data

19%

Anything is better than what we have now

14%

In-store/agent exchanges

12%

Note: respondents who feel they are missing important datapoints toprovide a more comprehensive view of their customerSource: CMO Council and SAS, "Aligning the CMO & CIO," March 28, 2013


Once marketers have incorporated rst-party data into

their DMPs, they have multiple targeting methods to

consider: behavioral, retargeting and lookalike.

BEHAVIORAL TARGETINGBehavioral targeting is one method used to deliver ads

to intended audience segments based on site-specic

actions or behaviors. For example, i a shoe retailer

advertising on Yahoo! recognizes one o its top-spending

customers or Nike running shoes reading an article on

a Yahoo! sports page, the retailer can opt to show that

consumer ads or the latest Nike running shoe model.

Here, the DMPs ability to integrate with a dynamic

content system is particularly useul in that it allows

marketers to customize their ad creative based on

known audience attributes or prior user behaviors. This

lets marketers create a more relevant, personalized

experience. In the case o retargeting, it can even be

used to urther point an audience toward an intended

conversion action by either inserting a recently viewed

product or an oer into the display ad creative.

RETARGETINGRetargeting is another common audience targeting

method the DMP supports. It enables companies to

recognize that a specic individual has already seen one

o its ads and allows them to either show the same ad to

the user or a dierent ad based on past actions.

Building on the example above, i the top-spending,

Nike-buying customer does not show interest in the latest

Nike running shoe model ad, or clicks on the ad and looks

at the shoe but does not buy it, the retailer can elect to

show that consumer a slightly dierent ad the next time

he or she visits a Yahoo! web property.

For example, i the user clicked on the ormer Nike ad but

did not buy, the shoe retailer might show that consumer

a second ad with a 15% discount. Or, i he or she ailed

to interact with the ad on the rst exposure, the marketer

might redisplay that ad.

Findings rom a Radar Research study showed how

important it is or marketers to collect and use website

inormation or retargeting purposes. Website retargeting

data was deemed a critical data asset or marketing

eorts by 54% o marketers worldwide.


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% of respondents

Data Assets that Are Critical to Their MarketingEfforts According to Marketers Worldwide, Nov 2012

Email data 62%

Media campaign data 57%

Website retargeting data 54%

Offline data 34%

Third-party audience data 34%

Mobile data 32%

Third-party mailing lists22%

Note: n=95Source: Radar Research, "Data Management Platforms" commissioned byBlueKai, Dec 4, 2012


But marketers arent just interested in the actions and

activities o their known audience base. They also want

to identiy new audiences in order to grow their business

and increase their brand ootprint. DMPs also enable

them to do this via another orm o targeting known aslookalike targeting.

LOOKALIKE TARGETINGLookalike targeting allows marketers to identiy additional

audience members based on traits or characteristics

shared with their present audience.

To create this new audience base, marketers typically

purchase cookie data rom third-party data providers

or resellers. They can then add those cookies to theDMP so that when a user appears, the platorm knows

to treat that consumer a specic way based on its

audience characteristics.

For instance, the shoe retailer above might opt to

purchase third-party data rom a customer loyalty

company that has identied users who have purchased

Nike-brand products within the past six months. The

retailer can then overlay this data with additional

third-party segments that include sports ans to build

a new audience segment that mirrors the one already

present in its DMP.

Grether was quick to note that though third-party data

can provide value or tactics such as lookalike targeting,

marketers should look to validate that audience data using

ad verication tools or analytics tools. Theres this big

debate about data accuracy, he said. I a data source

tells you a cookie is a male, is it indeed a male? You need

to be able to conrm whether or not you reached your

intended audience.

PUBLISHER USE OF DMPS FOR

AUDIENCE TARGETINGBrands and agencies arent the only ones using DMPs

or greater audience intelligence. As more and more

publishers oer audience targeting and programmatic

buying options to their advertisers, they too are doing so

through DMPs.

Forbes, or instance, is using a DMP to divide itssite into distinct, trackable audience segments to

provide companies actual audience data when selling

ad inventory.

The old way o responding to RFPs was to do a

syndicated research run via comScore or any other

service that shows a general audience composition and

projected potential reach o that audience on a site, said

Forbes Howard. Advertisers dont want that anymore.

They want to know exactly who you have on your site.

Once it segmented the site, Forbes was able to trackrst-party behavioral data on users activities on Forbes

properties. It then layered this data with third-party

behavioral data rom sources such as Bizo and eXelate

to get an even greater sense o its audience makeup.

We can now look at each channel or section [o the site]

and say, Hey, in the last 30 or 60 days, this is the exact

composition o the audience in that area, and this was the

reach, said Howard.

He also noted that one o the biggest benets o using

a DMP or this purpose is the ability to mix and match

attributes rom multiple third-party sources to build aneven larger and more precise target audience.


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A lot o people come to us looking or senior-level

decision-makers, and in the past wed use just one data

provider to target that segment across our site, he said.

By stringing together dierent cookies rom multiple

sources, we are now much more eective at nding

the people our advertisers want and can oer them that

audience with much greater scale within Forbes.

And, because the DMP is able to analyze and processad perormance resulting rom such targeting and

placements, Forbes can now oer advertisers

midcampaign analytics. We do a midway and then

post-campaign analysis o the data overlays to be able to

tell our clients things like 57% o the people exposed to

their advertising in our CIO section actually carried an IT

job unction, he said.

One o the additional benets to Forbes o using a DMP

or both creating audiences and analyzing them against ad

perormance is its ability to identiy new target audiences

that could be o value to advertisers. Howard oeredone example in which the DMP revealed that an auto

advertisers campaign was seeing a high response rate

among what he labeled luxury travel contenders. Forbes

was then able to go back to the auto advertiser and share

this insight.

Advertisers are very happy to be having those

conversations, he said. And they like the act that we

can proactively bring them inormation like that and leave

it up to them to make the decisions on what they want

to do.

DIGITAL AND

CROSS-PLATFORM ATTRIBUTION

The ragmented, renetic nature o todays media

consumption has complicated the measurement o

both digital and traditional marketing channels.

For the past several years, the advertising industryhas been working to address this issue through

attribution, a measurement approach that considers the

infuence o each advertising channel or touchpoint on a

specic outcome.

The end goal is to get that campaign-level view o

optimization across channels or each customer. Its about

building a more complete view o the customer, said

Neo@Ogilvys Muzzy.

Because DMPs are already audience-centric, they

are a prime tool or gauging campaign infuence and

perormance both within digital and across platorms.

Theres real value in being able to address the audience

rst to determine what to buy, said eXelates Zagorski.

By looking at your audience and how theyre interacting

with a particular ad or promotion, you can take those

learnings and eed them into your current eorts and your

next campaign.

Xaxis Grether shared one example o how Godiva used

attribution to justiy its digital eorts and increase uture

investment. He said the agency ran a digital campaign

o video and display or the chocolatier aimed at driving

sales. By combining the ad perormance with third-party

data detailing ofine purchase inormation in the DMP,

Xaxis was then able to segment those who purchased

chocolate into ad-exposed vs. nonexposed audiences. In

doing so, the agency expected to inorm uture targeting

decisions and justiy Godivas digital investment.

According to Grether, Xaxis was able to determine

Godiva earned $2 in sales or every $1 invested in digital.

As a result, the brand ended up spending even more

money online.

But digital attribution is only one piece o the larger

attribution unction the DMP can provide. Marketers are

also using it to understand broader channel relationships

across platorms.


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We know the idea o doing just digital attribution

modeling on the directly observable events you see at the

cookie level is fawed, because it ails to take into account

all o that rich exposure and interaction thats happening

outside o the digital domain, said Xaxis Lloyd.

Lloyds colleague, Colard, cited another example or a

technology client taking a much more cross-platorm

approach to attribution. During a new product launch, theagency monitored all o the clients paid communication

channels in both traditional and digital, in addition to its

website and call center. By inputting all o these channels

into the DMP, Colard said it was easy to identiy that, early

on, TV was driving a signicant number o searches, 90%

o which was coming rom Google.

In addition, Colard noted that the client used this

inormation to make sure its paid search investment

was optimized to drive all o the interest generated rom

TV ads to its web properties where the users could

eventually purchase that product.

Because we had this integrated view o our

communication investment and perormance, we

knew very rapidly that the reason why consumers

were searching is because we were doing all o the

mass media advertising in the rst place, he explained.

Without that integrated view, someone looking at

the website analytics might have just seen the bulk o

the trac coming rom search and assumed that we

shouldnt bother doing cable advertising.

And as more brand dollars move to digital and

programmatic buying, cross-platorm attribution is crucial.

Grether noted hes seen a shit in DMP use rom pure

direct response to more branding-ocused campaigns. As

a result, it is becoming increasingly important or brands

to understand the perormance o their digital advertising

eorts in conjunction with their traditional programs.

Its important to be able to get data rom TV

consumption into the DMP, he said. The more branding

campaigns that are being run, the more important it

becomes to bridge online and connect it with TV.

Grether went on to say the value in being able to do so

doesnt just eed back into media planning and ad spend

justication or TV or digital. It also aects the audience

targeting unction o the DMP.

On a user level, I need to know who was actually

exposed to an ad on TV, he said. Once I know that, I can

then determine whether or not I want to show him an ad

hes already seen. This can help me to maximize the net

reach between both channels, or i the requency was not

yet reached in TV, I can show him the ad online as well to

get optimum requency.

However, such intelligence remains dicult to gain,considering most traditional media channels dont track

ad perormance down to the user level. Xaxis technology

client mentioned earlier was able to do so by driving

traditional media to digital, a trackable medium, but most

traditional ad exposures and in-store purchases cannot be

tracked. Though cross-platorm attribution is possible even

in these circumstances, it is more aimed at justication o

media spend and less at real-time campaign optimization.

[Cross-channel attribution] is a very powerul approach,

and its antastic when you can get it right, said

Lloyd. The fip side is that its much more complex toimplement, and the output tends to be less actionable.

Data rom the CMO Council and SAS showed how

dicult it is to implement cross-platorm analytical

capabilities. Just 3% o marketers worldwide said their

online and ofine analytic capabilities were completely

integrated across all unctions as o Q1 2013. The majority

(46%) said they were getting better at this but still had

room or improvement, and 43% were either struggling to

integrate or ailing to integrate at any level.

DMP inrastructure also lacks this capability. Just 40%

o US marketing proessionals surveyed by Winterberry

Group said existing DMP technology supported

multichannel integration and optimization, though 84%

said it was a uture priority.

According to a all 2012 study by Zi Davis, another

priority or companies worldwide was to obtain the

real-time data analysis and reporting rom data

management that cross-platorm attribution

currently lacks.


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% of respondents

Leading Priorities for Their Data ManagementStrategies According to Companies Worldwide,Fall 2012

Real-time data analysis and reporting

27%

App and technology consolidation

26%

Storage and hardware optimization19%

Platform integration

16%

Mobile apps and accessibility

12%

Source: Ziff Davis, "Strategic IT Survey Results: Data Management," Nov 5,2012


Though the end goal or marketers is real-time

analytics and insight, or now, most attribution modeling

is done post-campaign, or as Lloyd aptly describes

it, rearward-acing. Most agencies would say thatattribution modeling is more used or post-rationalization

and proving that the decisions made were the right ones,

rather than trying to identiy learnings to use on uture

campaigns, he said. I think thats changing, but theres

still a airly big gul between the insight thats generated

and the ability to translate that insight into some kind o

meaningul change in your media planning process.

Still, Lloyd sees hope or DMPs to be able to make this

real-time action a reality.

Again, one o the benets o DMPs having bothrearward- and orward-acing capabilities is its ability to

close that loop, he said. You can take the insights you

generate rom an attribution modeling perspective and

immediately apply them to new orms o targeting or

renements in your existing advertising strategies to get

the maximum value out o those attribution models.

For more on cross-platorm ad measurement, please

see eMarketers December 2012 report, The State o

Cross-Platorm Ad Measurement: Industry Trends and

Current Practices.

EMARKETER INTERVIEWS

How Urban Outftters Uses Data to Segment and

Serve Furniture Customers

Jim Davis

Director, Web and Customer Analytics

Urban Outftters

Interview conducted on April 26, 2013

Dissecting Data Management Platorms

Dr. Mark Grether

COO

Xaxis


Understanding Big Data and DataManagement Platorms

Troy Lerner

President

Booyah Advertising


Laurent Colard

Global Managing Partner

GroupM


Mark Howard

Senior Vice President of DigitalAdvertising Strategy

Forbes


Pete Kluge

Product Marketing Manager,Adobe AudienceManager

Adobe


Richard Lloyd

Director, Data Management Platform

Xaxis


Sean Muzzy

CEO

Neo@Ogilvy

http://totalaccess.emarketer.com/Reports/Viewer.aspx?R=2001021http://totalaccess.emarketer.com/Reports/Viewer.aspx?R=2001021http://totalaccess.emarketer.com/Reports/Viewer.aspx?R=2001021http://totalaccess.emarketer.com/Interview.aspx?R=6001074http://totalaccess.emarketer.com/Interview.aspx?R=6001074http://totalaccess.emarketer.com/Interview.aspx?R=6001072http://totalaccess.emarketer.com/Interview.aspx?R=6001073http://totalaccess.emarketer.com/Interview.aspx?R=6001073http://totalaccess.emarketer.com/Interview.aspx?R=6001073http://totalaccess.emarketer.com/Interview.aspx?R=6001073http://totalaccess.emarketer.com/Interview.aspx?R=6001072http://totalaccess.emarketer.com/Interview.aspx?R=6001074http://totalaccess.emarketer.com/Interview.aspx?R=6001074http://totalaccess.emarketer.com/Reports/Viewer.aspx?R=2001021http://totalaccess.emarketer.com/Reports/Viewer.aspx?R=2001021http://totalaccess.emarketer.com/Reports/Viewer.aspx?R=2001021


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Ben Plomion

Vice President of Marketing and Partnerships

Chango


Tim Waddell

Director of Product Marketing,Adobe AudienceManager

Adobe


Mark Zagorski

CEO

eXelate


RELATED EMARKETER REPORTS

eMarketers Guide to the Digital AdvertisingEcosystem: Mapping the Display Advertising Purchase

Paths and Ad-Serving Process

How Retailers Are Leveraging Big Data to

Personalize Ecommerce

The State o Cross-Platorm Ad Measurement:Industry Trends and Current Practices

RELATED LINKS

Adobe

Booyah AdvertisingChango

eXelate

Forbes

GroupM

MEC Global

Neo@Ogilvy

Urban Outftters

Xaxis

EDITORIAL AND

PRODUCTION CONTRIBUTORS

Cli Annicelli Senior Editor

Kaitlin Carlin Copy Editor

Joanne DiCamillo Senior Production Artist

Stephanie Gehrsitz Senior Production Artist

Dana Hill Director o ProductionHeather Price Copy Editor

Nicole Perrin Associate Editorial Director

Allie Smith Director o Charts
http://totalaccess.emarketer.com/Reports/Viewer.aspx?R=2000966http://totalaccess.emarketer.com/Reports/Viewer.aspx?R=2000966http://totalaccess.emarketer.com/Reports/Viewer.aspx?R=2000966http://totalaccess.emarketer.com/Reports/Viewer.aspx?R=2000907http://totalaccess.emarketer.com/Reports/Viewer.aspx?R=2000907http://totalaccess.emarketer.com/Reports/Viewer.aspx?R=2001021http://totalaccess.emarketer.com/Reports/Viewer.aspx?R=2001021http://www.adobe.com/http://www.booyahadvertising.com/http://www.chango.com/http://www.exelate.com/http://www.forbes.com/http://www.groupm.com/http://www.mecglobal.com/http://www.neoogilvy.com/http://urbn.com/profile/urban.htmlhttp://www.xaxis.com/http://www.xaxis.com/http://urbn.com/profile/urban.htmlhttp://www.neoogilvy.com/http://www.mecglobal.com/http://www.groupm.com/http://www.forbes.com/http://www.exelate.com/http://www.chango.com/http://www.booyahadvertising.com/http://www.adobe.com/http://totalaccess.emarketer.com/Reports/Viewer.aspx?R=2001021http://totalaccess.emarketer.com/Reports/Viewer.aspx?R=2001021http://totalaccess.emarketer.com/Reports/Viewer.aspx?R=2000907http://totalaccess.emarketer.com/Reports/Viewer.aspx?R=2000907http://totalaccess.emarketer.com/Reports/Viewer.aspx?R=2000966http://totalaccess.emarketer.com/Reports/Viewer.aspx?R=2000966http://totalaccess.emarketer.com/Reports/Viewer.aspx?R=2000966


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