Cross Media Attribution by Havas Digital

Havas Digital
Insight

Cross Media
Attribution
Building bridges across Paid, Owned and Earned Media
to optimize media mix efficiencies and effectiveness

May 2012

Havas Digital Insight Cross Media Attribution

Lead Contributors

Katrin Ribant
EVP, Data Platforms
Havas Digital Global
katrin.ribant@havasdigital.com

Sylvain Le Borgne
SVP, Insights & Data Solutions
Artemis
sylvain.leborgne@havasdigital.com

Arnaud Parent
Director, Research & Development, PhD
Havas Media
arnaud.parent@fr.havasmedia.com

Doug Watson
VP, Data Solutions
Artemis
doug.watson@havasdigital.com

Dejan Duzevik
Chief Technology Officer
Concentric
dejan@concentricroi.com

© 2012 Havas Digital 1


Executive summary

Increased fragmentation of the media space and constant innovation in the
digital media space pose a challenge to Marketers who need to understand how
to optimally combine communication vehicles to reach their marketing goals.

At the center of this challenge is the individual consumer who is confronted with
an extreme number of choices in brands, products, services and media messaging.
Today’s consumer behaviors and choices are getting more complex and harder to
understand. These complexities have rendered some of the traditional tools that
Marketers use for media mix optimization less efficient.

Boundaries between traditional and digital media are fading, as are limits between
Paid, Owned and Earned marketing actions. Silos make less sense than ever. A
holistic approach that considers the overall marketing strategy is needed to help
Marketers achieve their goals efficiently and effectively.

Havas Digital is proposing new approaches to help Market-
ers understand how different combinations of messaging vehicles
can help them achieve their goals, leveraging synergies between
channels using a 100% fact-based, data-driven approach. Artemis
Attribution for Paid, Owned and Earned Media helps Marketers
optimize spend whilst taking into account how different channels
impact different consumer segments in real-time.

Based on simulation methods born in the science of complexity, this new frame-
work for attribution management builds on algorithmic digital attribution and
has the capability to integrate results from econometric modeling to help Mar-
keters understand how their efforts can help get their message across to the right
people at the right time.

As we continue developing our toolset, we will publish more results in further Insights documents.
In the meantime, we would be delighted to discuss individual business issues and opportunities,
whether you are already a Havas Digital client or simply just interested in a more case-specific
perspective. Please contact your Havas Digital Account Director, the appropriate Havas Digital
country Managing Director or any authors to find out how the emerging opportunities in digital
marketing can play a key role in your overall marketing plans.



Why a new approach for performance
attribution?

Ad serving, social and web analytics data enable Marketers to have access
to more extended and precise insights on consumer behavior. This wealth of
information means that differences between consumer segments are better under-
stood today than ever before.

These differences are instrumental in designing effective and efficient campaign
architectures that drive the right message to the right people. Traditional market-
ing mix modeling methodologies, like econometrics, are not designed to easily
take these differences into account.

Increased complexity of the media space means Marketers need to optimize
campaigns that have multiple objectives and target groups. Moreover, the in-
creasing complexity that Marketers have to handle when measuring results of
multi-channel campaigns and business results means that there is not one answer
that fits a given set of circumstances. Rather, Marketers need the flexibility to
experiment with different scenarios and understand how a change of inputs in-
fluences different consumer segments (i.e. running TV and paid search together
increases web base sales for product A).

In this Insights piece, we look at 3 different client cases involving
the following:
• A CPG advertiser who wants to know if investing in their Facebook presence
can help to increase consumer engagement to eventually increase sales.

• An ecommerce advertiser using social media, including Twitter as a Customer
Relationship Management channel. This Marketer wants to maximize his most
profitable customer segment.

• A finance advertiser using TV, search and display as well as social to drive on-
line applications for insurance subscriptions. This Marketer’s goal is to increase
valid online applications.



How is Havas Digital’s
approach different?

We do not believe that there is one answer to any Marketer’s attribution ques-
tions. Therefore, we focus on enabling Marketers to experiment with “what if”
scenarios allowing them to understand how different mixes of media channels,
social connectivity, competitive offering and other contextual influences result in
different outcomes.

Enabling “what if” scenarios
To enable relevant “what if” scenario building, we create an ecosystem which
mirrors a given historical period of time. This is done in 4 steps:

step 1 step 2 step 3 step 4

Build multi-dimensional Experiment “what if”
Integrate data sets Create ecosystem
attribution model scenarios

What if?

Shift 5% Shift 3% from
to display TV to search

Phase TV
to search

Allocate 45% Modify
to brand campaign
campaigns flights

User data E-mail Twitter Facebook TV

Social Sites Analytics Search Display Radio



Step 1: Integrate data sets
We gather data relative to the Marketer’s activity. This ranges from digital/
offline campaign data to web analytics or social data, as well as data about the
Marketer’s competition and product offerings.

step 1

After a thorough analysis of business needs and available data sources, data is
selected and gathered according to how relevant it is to answer the Marketer’s
questions. This step is about identifying “useful big data” rather then simply
assembling all available data sets.

Step 2: Create ecosystem
Using Agent Based Modeling, a leading-edge, mathematical simulation meth-
odology, we create an ecosystem that will reproduce the outputs of the data
we integrated.

This ecosystem is based on a series of simulated users (the more the better, as
shown in the case studies in this paper, we often work with 1 Billion+ users) that
act as consumers, using media, social buzz and connectivity data to determine
their purchase behavior.

step 2



To check if the ecosystem gives credible results, we will calibrate it against historical
data. This means that an ecosystem should reproduce real historical results with
a high level of accuracy before we can use it to build the “what if” scenarios.

GEEK’S
CORNER
What is Agent Based Modeling?

Agent Based Modeling (ABM) aggregates disparate data to create “agents”
(simulated people) that are representative of the real world population. ABMs
are used to uncover the causes of complex and often surprising outcomes in
systems as diverse as molecules, the Internet, traffic jams and, now, online
consumer journeys.

Because ABMs are designed to understand individuals, they are suited to
help Marketers understand how different user segments behave as a function
of marketing campaign exposure. For more on ABMs see:

http://en.wikipedia.org/wiki/Agent-based_model

Here is an example of what a social network looks like for 2 different clusters
of users. The right cluster is clearly the denser of the two. This means that
information will propagate a lot faster in this cluster and, for example, influ-
ence how awareness of a product offering is increased among users.

Social Network with lower density Social Network with higher density

Analysis: Awareness of product Analysis: Awareness of product
or promotion propagates slower or promotion propagates quicker
Recommendation: This customer Recommendation: This customer
segment is better activated with media segment is better activated with media
that generates high awareness. that generates word of mouth.



Step 3: Build multi-dimensional attribution model
The system outputs an attribution model according to the role each influence
plays in the consumer’s journey to decision making. This model is fully transpar-
ent and can be tweaked and calibrated using the Marketers business knowledge
to connect potential skews.

step 3

Artemis Attribution for Paid, Owned and Earned Media is fully transparent,
evidence-based and data driven. We take all media vehicles into account in a
truly cross-channel approach that addresses the complexity and diversity of to-
day’s media landscapes and consumer behaviors.

Step 4: Experiment with “what if” scenarios
The purpose of creating “what if” scenarios is to answer questions about media
mix optimization. These questions could be:
• What is an optimal allocation between online and offline?
• What is the right allocation between search and display?
• What is the value of having a growing fan base?
• Does my connectivity in the social sphere positively influence sales?

Shift 3% from TV to search
Phase TV to search

step 4 Allocate 45% to
What if? brand campaigns

Shift 5% to display Modify campaign flights



Artemis Attribution for POE Media allows Marketers to create as many of
these scenarios as they wish to explore and compare effects of different
strategies on overall sales (or other variables defined as outcomes). Continuous
injection of real-time data informs allocation and re-allocation of spend according
to real-world results of these decisions. This allows for real-time piloting of media
strategies adapted to a rapidly changing context. In the following section, we will
outline three use cases showing how we answered some of our client’s questions.

CASE 1
CPG MarketER
Impact of fan base growth on sales
This case study looks at the CPG category. This CPG Marketer runs a loyalty
program on Facebook for one of their flagship products. The program focuses
on healthy food and lifestyle recommendations and is aimed at creating a moti-
vational community fostering better and healthier lifestyle habits.

Many Marketers struggle to understand how to properly balance investments
between new users and advocates. Using Artemis Attribution to analyze this CPG
Marketer’s Paid, Owned and Earned Media activities, we provided an integrated
view of performance and optimized their dual strategies.

Marketer’s concerns
• Digital budget setting and how to allocate spend between channels,
specifically share of spend between video and social.
• How to articulate digital campaigns with TV campaigns to:
— Maximize synergies with TV spend.
— Understand how to use channels to leverage reach on different
consumer segments as well as new/loyal customers.

KPIs
We selected a variety of online KPIs that are considered as indicators of engage-
ment and predictive of the consumer’s purchase behavior such as subscription to
the Marketer’s loyalty program, time spent/frequency of visits on the program’s
micro site and coupon downloads.



Strategy
The advertising program runs display, video and search, while promoting the
Marketer’s Facebook page and driving people to a reduction coupon on their
website.

Channels used:

Video Display Search Facebook
pages



The following chart shows how digital spend is concentrated on video and dis-
play. Search accounts for 15% of clicks for this marketing program. This media mix
helped the Marketer build a sizeable fan base of over 300,000 fans.

Digital Mix: Majority of volume is concentrated on video and display

Loyalty program has been
Video and display dominate
successful on Facebook,
the digital mix. Social ads
with the help of display,
campaign is minimal.
video and search ads.

Video and display clicks vs search clicks

The following section details our approach to:
a) Attribution: Last click versus Artemis Attribution for POE Media
b) Media Mix Scenarios: Shifting budget from video to display or
invest in building fan base?



a) Attribution: Last click versus Artemis Attribution
for POE Media
Video (the darkest blue bar on the chart below) takes the majority of attribution
based on the last click model. Despite the relative balance of display, video impres-
sions and clicks (see pie charts), it seems video has a greater impact than display.

Attribution: Last click attribution favors video and does not credit social

Artemis POE Attribution Display and the Marketer’s social
takes credit away from video presence on Facebook gain credit

Last click attribution favors video, does not credit social

-22% attribution

+12% attribution Fan Base
Artemis POE
Attribution 10%

The re-allocation of credit from video to display makes sense as display usually
plays a role in earlier stages of the funnel. Display and video have complementary
roles. Video takes over where display appears, diminishing returns and acting as a
complementary channel for TV. This exposes the Marketer’s message to consumer
segments that are difficult to reach through traditional TV actions and engages all
consumer segments with a direct link to the Marketer’s loyalty program.

Since coupon downloads from Facebook fans cannot be tracked directly, we ran
Artemis Attribution for Paid, Owned and Earned Media and determined that
10% of conversions could be credited to the advertiser’s fan base.



b) Media mix scenarios: Shifting budget from
video to display or invest in building fan base?
Based on the re-allocation of conversions credited to display and social by Ar-
temis POE Attribution, we explored two scenarios of media spend optimization:
• Move 10% of spend from video to dispaly
• Invest in building fan base

Move 10% of Spend from video to display

Based on the re-allocation of conversions credited to display and social by Artemis
POE Attribution, we explored a scenario of media spend optimization and pro-
posed a move of 10% of spend from video to display.

Shifting 10% of spend to display would result in less coupon downloads
Drop in conversions if
spend shifts to display Drop in conversion

Shift in spend to display causes 8% drop in coupon downloads
Conversion trend is
constant but volume
drops if spend shifts Drop in conversion
to display



Despite the fact that more credit was attributed to display by Artemis Attribu-
tion for POE Media, this scenario predicts an 8% drop in coupon downloads.
The explanation for this drop is that the display channel has reached its level of
diminishing returns for this Marketer. Additional spend in display will not result in
better performance. Therefore, we need to explore alternative channels.

Invest in building fan base

We explored what would happen if the Marketer was to increase their fan base
and created two scenarios based on our findings:
• Increasing fans by 20%
• Increasing fans by 100%

For this advertiser, investing in growing their social presence results in an increase
in conversions. Since the display channel is saturated and Artemis Attribution for
POE Media credits the Marketer’s social presence for 10% of conversions, we dis-
covered that growing their fan base can help them increase conversion volumes
in the short term and sales in the long term.

Conversions increase with fans

Increasing fan base increases conversions

Doubling fans increases
conversions by 23%

The more the fan base increases, the higher the projected growth in conversions. If
the Marketer were to double the size of their fan base, conversions would increase by
23%. We recommend investing in social ad campaigns and specific social ac-
tions that will help grow this Marketer’s Facebook presence. This will foster
engagement in their loyalty program and lead consumers to keep the Marketer’s
product top of mind, while resulting in higher sales volumes.



CASE 2
eCommerce Marketer
Impacting sales through social media

Internet is instrumental to this ecommerce advertiser’s media mix and sales.
Although their business model was traditionally bricks and mortar, they success-
fully shifted to the web as a distribution channel. Today, about 60% of sales hap-
pen on their website. Their products call for a purchase window from a few days
to several weeks and peer reviews are important to consumer’s choice.

60% of sales happen on the Marketer’s website

Brick and Mortar
Sales 40%

Online Sales 60%

This Marketer’s goal is to understand:
• What digital media mix will result in more customers
and more of their most valuable customers?
• Can they impact sales through the use of social media?

To answer these questions, we analyzed:
• 12 months of data • 33 billion events
• 100+ campaign • Digital and social media channels
• 1 billion user journeys



Channels used:

Display Search Price Affiliates E-mail Twitter
Comparison

Question 1: Optimizing the digital media mix
First, we looked at channel attribution to answer the Marketer’s question: What
digital media mix will result in more customers and more of my most valuable
customers?

a) Channel impact
We determined that credit for sales that were previously accounted to paid search
was shifting to display. In fact, attribution to display more than doubled. This
clearly indicates that display is helping customers make their choice at earlier
stages than search.

Channel attribution shifts credit to display

Attribution reallocates 15% credit from search to display We found more
evidence of the
impact of display
at earlier stages of
the decision making
15% reallocation to display process by running
a channel impact
analysis.

Last Click attribution by Channel Attributed conversions by Channel

Display’s
attribution
more than 2x



The left part of the chart below represents the moment of purchase. Both search
(lighter blue line) and display (darker blue line) have the greatest impact close to
the moment of purchase, with search being more impactful than display.

Display has a greater impact than search 6 to 14 days prior to purchase (the darker
blue line is higher than the lighter blue line from 6 to 14 days prior to purchase).

Display has a greater impact than search at early stages of the purchase funnel

Impact of display and search up to 14 days before purchase

Display and search have maximal
impact close to purchase

6 to 14 days prior to purchase, display
has a higher impact than search

Purchase 1 week before purchase 2 weeks before purchase

b) Customer value
To determine customer value, we segmented customers into three categories
according to their revenue/purchase ratio.

As shown on the pie chart on the following page, about half of the revenue comes
from Platinum customers (darkest blue), the top 20% most valuable customers.
So the 20/80 rule becomes the 20/50 rule for this Marketer.

Platinum customers are six times more valuable than Silver customers and three
times more valuable than an average customer as shown on the bar/line chart on the
following page. This means that focusing on attracting an additional Platinum cus-
tomer should bring three times more revenue than acquiring an average customer.
Therefore, this Marketer’s strategy should focus on analysis of parameters that grow
the acquisition and lower the levels of churn of Platinum customers as a priority.



20% of customers account for 50% of the revenue

Platinum customers 6x more valuable then Silver, 3x vs average

Platinum customers 6x more
valuable than Silver customers

Revenue by customer segment

Platinum customer
account for 50%
of revenue

c) “What if” scenarios: Optimizing for the most valuable customers
In order to maximize overall sales volume with a focus on maximizing Platinum
customer acquisition, we analyzed two scenarios for moving spend from search to
display. First, moving 5% of spend to display and then moving 10% of spend
to display.
Both scenarios resulted in increased sales. Moving 5% of spend to display is the
most efficient scenario, both for overall sales volume increase and for Platinum cli-
ents volume increase. Moving 10% of spend to display increases overall sales vol-
ume less than moving 5% of spend to display, resulting in acquisition of less valuable
customers.



Moving 5% of search spend to display brings best results

What If Scenarios: impact on customer segments (absolute values)

Moving 5% of search
spend to display results
in increased sales

What If Scenarios: impact on customer segments (percentages)

Proportion of Platinum
customers increases if 5% of
spend is moved to display

Question 2: Can social media impact sales?
First, we looked at channel attribution to answer the Marketer’s question: What
digital media mix will result in more customers and more of my most valuable
customers?



a) Connectivity in the social space influences sales
During the concerned time period, a news event negatively impacted this Mar-
keter’s category. After this event, sales dropped over several weeks. We built
scenarios examining how spend allocation and efforts in social media could have
helped sales grow back to normal quicker.

The first chart looks at a projection of sales using the aver-
age connectivity of the Marketer’s space. We project what
the recovery (dark blue line) would have looked like if the
Marketer’s connectivity in the social space was on par with
the average for their industry. If the Marketer had aver-
age connectivity in the social space, the dip in sales would
have been less and the recovery would have been faster.
Average social connectivity

Sales projection if Marketer had average connectivity in the social space.

seasonal peaks
are higher
recovery is
faster

In this graph, we compare sales for the same time period
as above but have projected a scenario in which the Mar-
keter has higher connectivity than the industry average.
Not only is the recovery faster but also most seasonal
peaks are amplified by the spread of the Marketer’s pro-
motion through online word of mouth.
High social connectivity

Sales projection if Marketer had higher than average connectivity in the social space.

higher connectivity helps message
spread and increase sales



As Artemis Attribution maps the effect of Paid Media on Earned and Owned Me-
dia, it helps Marketers who are faced with unforeseeable events affecting their
sales. It assists with the design of Paid Media actions that help boost their social
presence in the recovery phase of such an event.

CASE 3
FINANCE MARKETER
Phasing TV and search to drive subscriptions
In our third case, we look at a Finance brand whose sales process involves driv-
ing people to their website where they can apply for an insurance policy. To drive
people to apply online, our Finance Marketer uses a mix of digital and offline
channels including paid search and TV.

Channels used by Finance brand:

TV Search

Although this Marketer’s media mix is far more complex and makes use of multiple
channels, including display, social and radio, we chose to focus on one particular
campaign and narrow down to TV and search only. This has been done in order to
better assess the Marketer’s questions about digital and offline phasing.

TV’s main role for this Marketer is to raise awareness and drive online search for
specific keywords. Search engine marketing is directly aimed at views on the Mar-
keter’s website where people consider applying for an insurance policy.

Once the prospect posts their insurance policy application online, the lead gen-
erated goes through a validation process, resulting in a data passback between
the Marketer’s data systems and Artemis.

Online Validation
Valid insurance
application subscription



The Marketer’s goal is to drive more succesful applications, meaning more appli-
cations that actually result in an insurance subscription.

KPIs
Online applications validated through passback of completion data from the
Marketer’s database.

The 2 scenarios we explored involve shifting spend from TV to paid search in order
to increase valid applications:
• Shifting 3% of spend to paid search adding $210k to current $567k spend
• Shifting 5% of spend to paid search adding $350k to current $567k spend
Both scenarios result in an increase of valid applications.

Since shifting 5% of spend results Paid search represents 8% of TV spend
in a higher increase in valid applica-
tions, we recommend up weight-
ing the paid search campaign and
reassessing performance during
the following month.

However, shifting spend from TV to
search in order to improve results
needs to be implemented carefully.

Moving spend to search increases valid applications

Baseline



Search conversion rate is 14% higher when TV is on air

Paid search conversion rates are 14% higher on average when a TV campaign is
aired. Therefore, we recommend that additional budgets are concentrated on the
time periods where TV is active.

Adapting phasing of additional search budgets in real-time according to how they
are impacted by TV actions could help boost this Marketer’s KPIs even further by
maximizing digital and offline synergies. In further stages of optimization, we will
broaden the scope of the analysis to include social and other paid channels.



Conclusion

In the light of the ever growing complexity of the digital media landscape, few Mar-
keters still believe that there is one perfect answer to their spend allocation challeng-
es. If there were to be such a solution, it would have a short lifespan and quickly be
disrupted by a shift in consumer behavior fostered by the digital media revolution.

Havas Digital has made certain the continuous development of tools and method-
ologies that help Marketers manage and optimize their efforts, in accordance with
the level of complexity of their vertical and consumer segments. We do not believe
in one size fits all marketing strategies nor relationship management.

As we continue developing our toolset, we will publish more results in further In-
sights documents. In the meantime, we would be delighted to discuss individual
business issues and opportunities with you, whether you are already a Havas Digital
client or simply just interested in a more case-specific perspective. Please contact
your Havas Digital Account Director, the appropriate Havas Digital country Manag-
ing Director or any authors of this Insight to find out how many of the emerging op-
portunities in digital marketing can play a key role in your overall marketing goals.



Contacts details
We encourage you to contact us directly to discuss, in more details, any concerns you
may have regarding this Havas Digital Insight issue. We will be happy to assist you.
· katrin.ribant@havasdigital.com
· sylvain.leborgne@havasdigital.com
· arnaud.parent@fr.havasmedia.com
· doug.watson@havasdigital.com
· dejan@concentricroi.com

Or contact your Havas Digital LOCAL OFFICE:

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HAVAS DIGITAL NETHERLANDS
Burg. A. Colijnweg 2. 1182 AL Amstelveen, Netherlands phone +31 20 54 50 580 fax +31 20 54 50 581
country manager Freek de Steenwinkel email freek.de.steenwinkel@nl.mediacontacts.com

HAVAS DIGITAL peru
Av. Victor Andrés Belaunde 147, Torre Real Uno, Oficina 902. Centro Empresarial San Isidro, Lima - Perú
phone +511 611 8800 fax +511 611 8803 country manager Gonzalo Parra email gonzalo.parra@havasdigital.com

HAVAS DIGITAL PHILIPPINES
Unit 2104-A East Tower, Philippine Stock Exchange Center, Exchange Road, Ortigas Center, Pasig City. Philippines
phone +632 689 8012 fax +632 910 6420 country manager Eduardo Mapa email eduardo.mapa@ph.mediacontacts.com

HAVAS DIGITAL Poland
Marynarska 15 str, 02-674 Warszaw, Poland phone +48 22 843 66 60 fax +48 22 843 66 61
country manager Robert Bernaciak email robert.bernaciak@mediacontacts.com

HAVAS DIGITAL Portugal
Avenida Duque de Ávila, 46 - 5ºAv. 1050-083 Lisboa, Portugal phone +351 21 791 3388 fax + 351 21 791 3340
country manager Nuno Antunes email nuno.antunes@havasdigital.com

HAVAS DIGITAL singapore
137 Amoy Street, #02-02 Far East Square, Singapore 0499065 phone +65 6645 4700 fax +65 6645 4701
country manager Gautam Dutt email gautam.dutt@sg.mediacontacts.com

HAVAS DIGITAL spain
madrid Avda. General Perón, 38, 14ª. 28020 Madrid, Spain phone +34 91 456 90 50 fax +34 91 770 15 86
barcelona Dr. Fleming, 17. 08017 Barcelona, Spain phone +34 93 205 87 71 fax +34 93 414 72 13
valencia C/ Roger de Lauria, 19-4c. 46002 Valencia, Spain phone +34 96 353 08 74 fax +34 96 351 15 69
country manager Javier Navarro email javier.navarro@havasdigital.com

HAVAS DIGITAL thailand
Jasmine City Building, 19th Fl. 2 Sukhumvit 23, Klongtoey Nua, Wattana, Bangkok 10110, Thailand phone +66 2 259 9030
fax +66 2 259 9499 country manager Rajeev Balasubrahmanyam email rajeev.bala@sg.mediacontacts.com

HAVAS DIGITAL uae
Choueiri Building , 2nd Floor. Al Sufouh 2 Street – Dubai Knowledge Village P.O.Box 21448, Dubai – UAE
phone +971 4455 6700 fax +971 4391 8001 country manager Piero Poli email piero.poli@havasdigitalme.com

HAVAS DIGITAL uk
60 St Martins Lane, WC2N 4JS London, UK phone +44 (0) 20 7393 9000 fax +44 (0) 20 7393 2525
country manager Paul Frampton email paul.frampton@uk.mediacontacts.com

HAVAS DIGITAL USA
boston 101 Huntington Avenue, 16th Fl. Boston MA 02199 USA phone +1 617 425 4100 fax +1 617 425 4101
new york 195 Broadway, 12th. New York, NY 10007 phone +1 646 587 5000 fax +1 646 587 5005
chicago 36 East Grand, 5th Floor. Chicago, IL 60611 phone +1 312 640 4700 fax +1 312 337 3898
manager (Boston, New York, Chicago) Andrew Altersohn email andrew.altersohn@havasdigital.com
miami 5301 Blue Lagoon Drive, Suite 850, Miami, FL 33126 phone +1 305 377 1907 fax +1 305 377 1906
manager (Miami) Fernando Monedero email fernando.monedero@havasdigital.com


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