Big Data

1
BIG
DATA
May 2013
CRM’S PROMISED LAND

22
Why
Big
Data?Organizations are facing bigger and bigger challenges when it
comes to collecting and using data. Companies can access large
amounts of information, but do not know how to interpret it to
obtain results that provide added value for their businesses or
customers. Often this is due to the raw availability of the data and
its lack of structure, or the lack of the technological infrastructure
and knowledge needed to make use of it. But all of this is
changing, thanks to what has come to be known as “Big Data.”

3
The best way to start the conversation
about “Big Data” is to define it. Its name is
perhaps confusing and not quite apt, since
it implies that existing data is “small,” or
that we simply have a lot more data. The
reality is, the term Big Data is applied to
information that cannot be analyzed with
traditional tools or processes.
Big Data has three fundamental
characteristics: it involves managing a
large volume of information, processing
the data quickly or in real time, and
integrating a large variety of information
sources that may be able to draw
conclusions from data connections that
are not apparent from the start.

4
A recent study discovered that a large
amount of today’s business leaders are
aware that they do not have access
to all of the insights that would help
them improve decision-making in their
companies. The companies, in turn, are
facing increasing challenges in a time
in which data is being generated like
never before and in which they have the
capacity to store this information. This
represents a great opportunity for these
companies to equip themselves with real-
time knowledge that can truly help them
understand and adapt to individuals
and their needs, and make decisions
accordingly.
It may seem paradoxical, but while it
is possible for today’s businesses to
access information that can potentially
be decisive for their core strategies, their
capacity to process, filter and analyze
increasing quantities of information is
decreasing. The data – which could
represent a truly golden opportunity –
just continues to pile up. This is where
Big Data comes in as a key player for the
business.
1 https://www.ibm.com/developerworks/mydeveloperworks/blogs/SusanVisser/entry/fashbook_understanding_big_data_
analytics_for_enterprise_class_hadoop_and_streaming_data?lang=en

55
2,000
1,750
1,500
1,250
1,000
750
500
250
0
2005
DATA OVERLOAD
AVAILABLE, STORED INFORMATION WORLDWIDE
EXABYTES
SOURCE: IDC
2006 2007 2008 2009 2010 2011
INFORMATION
CREATED
FORECAST
AVAILABLE
STORAGE

6
$5 billion in Big Data software, hardware,
and services
$50 billion estimated for 2017
$1.1 billion revenue for IBM comes from
Big Data
70% of data storage is in North America
and Europe
60% potential increase in the operating
margin for the retail sector
$10 billion potential health-related market
for Big Data in 2020
180,000 Big Data experts will be needed
over the next 5 years in the USA
2,470 venture capital fund investments in
Big Data companies in the USA in 2011
1 billion gigabytes of data on the Internet
40% annual growth worldwide
Big Data
in Figures
2012 MARKET
GROWTH FORECASTS
LEADING COMPANY
GEOGRAPHY
RETAILERS
HEALTH
DEMAND FOR LABOR
INVESTMENT FINDS
INTERNET DATA
DATA GENERATION

7
The world is changing in leaps and
bounds. We use more and more
technological devices in our daily lives,
and thus we are able to capture more
things. It has been observed that when
we can capture things, we tend to hold
on to them.
Thanks to technological progress,
people and objects are increasingly
interconnected 24 hours a day without any
type of interruption. This interconnection
is rapidly escalating, and the flow of
data exchange that it inspires is growing
without bounds. The reduction in the
size and price of circuits, like those used
in smartphones, watches, heart rate
monitors, mp3 players, and tablets, etc.,
contributes to this growth. Thanks to the
decreased cost of these circuits, we are
now able to endow just about everything
with “intelligence”–even a floor cleaner like
the Roomba–and obtain answers from this
“intelligence” in the form of data.
These types of devices are highly
reliable, sufficiently enough to have been
implemented in security systems for
some time now. For example, a freight
train has hundreds of sensors that
monitor the climate conditions inside
the wagon, the status of certain pieces
of machinery, or shipments. These
processors interpret in real time the data
from sensors in parts that are prone
to wear, like the bearings, in order to
identify the components that are in
need of repair before they fail and
potentially cause a problem. The rails
also have sensors.

8
This data implies a fundamental change
in the way we analyze this data, since
it no longer follows a traditional
structure and therefore requires
more sophisticated technologies and
methodologies.
The success of an organization will
increasingly stem from and depend
on its ability to draw conclusions
regarding the diverse types of data
available to it. Getting ahead of the
competition requires, in the majority of
cases, identifying a trend, a problem,
or an opportunity microseconds before
anybody else. That’s why organizations
must be able to analyze this information
if they want to gain insights and
knowledge that will help them with their
business. They must start by identifying
the opportunities behind Big Data, as this
paper seeks to illustrate.

How much data
does social
media generate?
10
More than 144.8 million emails sent/received per day
More than 684,000 pieces of content and 34,000 brand “likes”
More than 340 million tweets per day
More than 72 hours (259,200 seconds) of video consumed
every minute
272,000 dollars transacted every day

11
3,600 new photos every minute
More than 2 million queries every minute
3,125 new photos every minute
Around 47,000 application downloads per minute
More than 2,000 check-ins every minute
27,000 new posts every minute
571 web pages published every minute
350 new entries every minute

1212
Accessibility
and
Technology
are Key
Big Data was one of the main subjects discussed
at the Oracle OpenWorld 2011 conference. The
focus on Big Data at this conference revolved
around offering enormous machines with massive
capacities, multi-parallel processing, unlimited
visual analysis, and treatment of heterogeneous
data, etc. In short, solutions designed to meet the
regular, massive needs of large organizations.

13
However, other types of companies opt
for approximations using cloud-based
and open-source tools, like Hadoop, a
popular open-source software framework
that allows applications to work with large
amounts of data and thousands of nodes.
Hadoop was inspired by tools used by
Google and by non-relational databases
necessary for storing and processing
the enormous complexity of all types
of data, which in many cases do not
follow the logic of ACID (Atomicity,
Consistency, Isolation and Durability)
guarantees, typical of conventional
databases. It seems that solutions of this
type will be increasingly adopted in the
future, although exciting questions about
their implementation and uses remain
unanswered.

14
It was precisely with the idea of increasing
Big Data’s reach that Google introduced
BigQuery some time ago, an online
service for processing large volumes
of information. The service, however,
is targeted towards professionals, and
therefore it is not free of charge.
With BigQuery, Google takes advantage
of all its knowledge on processing large
volumes of information and making it
available to companies that are unable
to purchase their own infrastructure, thus
offering them a cloud-based model
that provides storage space as well
as a data-mining service. Thanks to
BigQuery, companies can make their
first inroads into processing large
volumes of information, although,
logically, it may be necessary to hire a
specialized service in order to receive
more in-depth service or analysis. Even
so, Google’s initiative seems to be of
interest, as it is a way to advertise Big
Data around the world.

15
In any case, the utilities and applications
that Big Data can provide are already
within reach for many users, and in a
way that allows them to recognize and
understand the massive convergence of
data. Any user may consult and use the
tools that already exist on the Web.
For example, a user may go to Google
Maps, write an address, choose the
satellite view, and see the traffic in the
area that he/she wants to visit in real time,
based on information that other users
have sent to the network via an Android
terminal. Google has also discovered that
certain search terms are valid indicators of
the evolution of the flu, and the results
are shown on Google Flu Trends.2
Approximate calculations of flu activity
can thus be made for certain regions,
which could be of use when it comes
to taking preventive action. We can find
other similar examples to the one just
mentioned.
2 http://www.google.org/flutrends/

16
Another facet of Big Data that has a strong
potential for further development involves
citizen access to public data, which, until
now, was only available for analysis by
the public administrations. In 2009, the
government of the United States was a
pioneer by opening the doors to all of its
information on the website data.gov.
On data.gov, you can access a great deal
of information that has been available to
US residents for a while now. To date,
the site has received more than 100
million visits, and local authorities and
institutions have started to release their
data to citizens, following President
Obama’s lead. Cities like San Francisco
and New York, and the states of California,
Utah and Michigan, among others, have
launched their own websites based on the
data.gov model. The same is taking place
in countries like Canada, Australia and
the United Kingdom, and with such well-
known institutions as the World Bank.
Another public-interest use for Big Data
was developed by IBM.3
Using “Smart
Meters,” IBM analyzed a neighborhood’s
power consumption with sensors
that provided energy consumption
data, with the goal of making that
consumption more efficient. Based on
this information, the company was able
to determine inhabitants’ energy-usage
patterns throughout the day, see how
demand varied, and even change some
of those patterns by implementing
various strategies and client discounts.
3 http://www.ibm.com/smarterplanet/us/en/smart_grid/ideas/index.html

17
The benefits of intelligent analysis
The insights detected by Smarter Analytics help companies make faster and better decisions and automate
processes. In addition, they contribute towards building a solid foundation of product analysis and strategic
services in order to take advantage of all data sources, both structured and unstructured. All this data will
also support taking decisions at times of change and help companies move beyond the competition.
Increase data on
customers and retain
the most valuable ones
Continually
improve operational
efficiency
Prevent fraud
and
manage risk
Transform and
automate financial
processes

18
Even the Leicester Tigers rugby team has
started using Big Data to help prevent
injuries.4
Thanks to the increasing availability of
public data, people have developed
hundreds of applications that society can
benefit from, for example, applications
that allow you to see pollution levels by
region, that help travelers find the fastest
route to their destinations, and that inform
new homeowners about the safety of
their neighborhood. Never before has so
much valuable, objective information been
available to help people make the best
decisions possible in their day-to-day lives.
As opposed to the way things usually find
popularity, Big Data is being propelled by
the public sector, as it shows people its
value and potential. The time has come
for Big Data to expand into the private
sector, and for marketing and customer-
relations departments to take advantage
of the opportunity to increase their profits
and productivity, and to be able to adapt
their business strategies to the new
changes that are to come by using all the
information available through Big Data.
4 http://alt1040.com/2012/04/big-data-reduccion-lesiones-rugby

1919
1 in every 4
rugby players is
injured during
training sessions
Hamstring injuries
cause players to
have to sit out
an average of
14 games
Researchers are
using equations
to predict sports
injuries
The organizations
that apply predictive
analysis are 2.2
times more likely to
beat their opponents
Using data to stand up to rugby injuries

2020
Marketing
with
Big Data
Digital is the new frontier. Everything is going
digital. As a result, people, devices and
companies are managing larger and larger
amounts of data. Companies need to find a way
to innovate in terms of examining all this data, so
as to create actions and concrete strategies that
will add much more value.

21
“One of the biggest changes we’re seeing
in the online advertising industry is an
increased focus on data and analysis.
Marketers are hungry for information about
what their audiences do online and how
they’re responding to ads. At the same
time, it’s not always easy to navigate with
massive amounts of data, so, in order to
be meaningful, that data needs to be
combined with insights so marketers
understand how to activate on the
findings.”
–Lauren Weinberg, VP, Strategic Insights
and Research, Yahoo!

22
Large companies are aware of this and
are increasingly dedicating departments
and resources to data collection and
application.

2323
DEMOGRAPHIC DATA
CUSTOMER TRANSACTION DATA
USABILITY DATA FROM THE CUSTOMER
SOCIAL CONTENT CREATED BY CUSTOMERS AND TARGET
SOCIAL NETWORKS AND TIES BETWEEN CUSTOMERS AND TARGET
CUSTOMER CELLULAR PHONE/DATA DEVICES
TYPES OF «BIG DATA» COLLECTED BY US MARKETERS
FEB 2012
% OF SURVEYED
TRADITIONAL
DATA
DIGITAL
DATA
74%
64%
60%
35%
33%
19%

24
Big Data
and CRM
The large quantity of information being
uploaded to the Internet represents
a wonderful opportunity to segment
according to people’s behavior and
not just by socio-demographic factors.
Companies acquire transactional
information from their customers by
making them fill out forms, but the
challenge for brands is to enrich their
databases with information on the
customers’ daily habits and behavior,
which can be obtained from online chats
and then processed, crossed and enriched
with many other types of information
thanks to Big Data-based initiatives.
This way, we can build databases of
information available on customers
without needing to bother them again
and again, and then we can use this
information to offer proposals with a
higher added value.
Take, for example, something simple
like the opportunities for personalizing
promotions. Let’s imagine that we could
know that the customer is a member of
an online wine community, which clearly
indicates that he is a wine aficionado
and not just someone of the “I like wine,
but I like beer, too” type. Through a
digital customer loyalty card—like the
Passbook application on the new iPhone
5—we could keep a record of all of his
wine purchases, and even get an idea
of what wine he orders in restaurants.
Could an online supermarket then
personalize its newsletter for him with
wines similar to the ones he likes? Try
to sell him a bottle of wine that he had
tried the night before in a restaurant?
Or, imagine another case: a customer
starts to access an online real-estate
portal more and more often. Could
his bank or a competing bank be able
to offer him options from among their
housing in stock before he asked for
them? Perhaps someone tweets that
he is renting an apartment. Wouldn’t
this information be of interest to the
companies that offer home insurance?
If Google’s contextual advertising is
already working along these lines, why
not improve our own CRM systems in
the same way?

25
Using the same technology with the
correct platform and the appropriate
tactics, we can achieve more ambitious
objectives and provide very valuable
information for brands, which can then use
this information to enrich their customers’
experience. All we need are technical and
human systems that are able to collect,
standardize and mine the information.
The implications for customer-service
strategies are also significant.
Big Data has recently gained relevance
because companies are realizing what it
can do for them, and that it is a goldmine
for finding competitive advantages. When
it is applied to the realm of business or
marketing, the whole conversation about
Big Data revolves around consumer
trends, developing new products, and
other insights into the market. When
McKinsey wrote its report on Big Data5
last year, it identified five different ways
in which Big Data can be used to create
value, but only one of them mentioned
customers, and it did so in order to
discuss improvements in consumer
segmentation. The Wall Street Journal
describes several successful stories
from different brands in its blog on Big
Data,6
but focuses almost exclusively
on operational issues, process
management, and other efficiency-
improving aspects. Efficiency is clearly
a goal worth pursuing, but the use of
Big Data is much more relevant in the
realm of content or customer service.
Now that consumers have seen what
social media and mass personalization
are capable of, they increasingly expect
their favorite brands to provide these
engagement opportunities. They are not
merely passive users waiting to receive a
message. Rather, they want to be active
participants.
Customer experience designers are
aware of this. When a customer calls
the customer service number, sends an
email, or speaks with an employee in a
store, they are starting a conversation.
At that moment, the brand holds all of
the customer’s attention, even if he or
she is annoyed, which means that the
brand has been given an important
opportunity to define its relationship
with its users. The user knows that the
brand has gathered information about
its customers for its own needs, and he
in turn will ask why doesn’t the brand do
anything useful—for the customer, not
just the brand—with this data.
5 http://www.mckinsey.com/insights/mgi/research/technology_and_innovation/big_data_the_next_frontier_for_innovation
6 http://blogs.wsj.com/cio/category/big-data/

26
Listening to online conversations may help
companies provide better services and
integrate social channels with customer-
service channels, thus hugely improving
the user experience. Technically, this
can be very difficult to achieve, but
Amazon does it particularly well. Amazon
has grown quite a lot over the years,
but it has always stayed constant as a
unique organization. Other organizations,
however, have become larger by way
of acquisitions, which make data
synchronization an extremely technically
complex task, with a high demand for
resources and investments.
Even so, if the new pattern of
relationships between brands and
consumers is here to stay, companies
must invest in capturing, processing and
synchronizing data between channels
and platforms, which is something
unique to human interactions. If you talk
to a friend, for example, and constantly
ask him for information that you already
have, he would understandably get
annoyed. In the era of Big Data, the
same rules apply to brands. The ones
that follow the rules will win the trust and
loyalty of their customers.

27

Are you a new customer? Start here.

Sean’s
experience with
Amazon
28
Sean Madden is a consultant who has
purchased many items on Amazon for
over a decade. One day he contacted
the online customer service because
his Kindle was not working properly.
Thirty seconds after he reported the
problem, Amazon called him on the
telephone. The employee on the other
end of the line greeted him by his first
name and fixed the problem in less than
two minutes. Sean never had to provide
his product information, registration
number, or other details of the problem.
Sean writes in his blog that he
didn’t expect anything clear to
come out of that call, let alone that
Amazon would fix the issue. Like
most of us who have experience
with these types of calls, we
are accustomed to hearing a
cold, scripted, robotic voice, the
tone of which depends on how
sympathetic the operator feels
that day.

29
But, on the contrary, Sean’s experience
with Amazon was positive and fluid.
Amazon surprised Sean by using his data
and purchasing-history profile to provide
him with a fast and personal repair
service, as well as personalized advice,
based on his customer history profile.
The fact is that Amazon had been
collecting information on Sean for years,
not just his different addresses and
payment information. They created an
identity of Sean “as a person” and they
used it to build a two-way relationship
with him.
With what CRM is traditionally
able to offer, combined with social
data, that is processed extremely
quickly, and used to obtain
massive knowledge of all of the
customers as a whole, Big Data
becomes truly powerful.

30
One of the main ways that brands
can generate interesting content for
their targets using Big Data involves
self-quantification.
Self-quantification is not new. People
have always meticulously measured
many aspects of their lives, whether by
painting or drawing, recording where
they are, when and what they eat, or how
they feel. Journals and, in today’s world,
blogs are examples of this. But only
recently have technological advancements
facilitated a real explosion of these types
of activities. An ecosystem of content and
applications is developing on the basis
of an increasingly transparent and social
culture with the ubiquitous presence of
sophisticated devices and sensors that
make it possible to record and monitor
activities, such as the GPS, cameras,
microphones, accelerometers, etc. This
ecosystem is based on monitoring our
activities with systems that are less and
less declarative and more and more
objective.
Smartphones are the most comfortable,
convenient, and omnipresent technology
for the growth of this ecosystem.
Worldwide sales of smartphones grow at
a pace of 50% annually, and for 89% of
users,7
these phones have become their
constant companions throughout the
day. Never before has it been so easy for
people to collect and store their own data.
Big Data provides
new content
for consumers
7 The Mobile Movement study, by Google / IPSOS (April 2011).

3131
Smartphones as constant companions
OF SMARTPHONE USERS
HAVE THEIR PHONE AS A
CONSTANT COMPANIONS
THROUGHOUT THE DAY
89% 11%
DO NOT

32
General Electric, in conjunction
with the online medical community
MedHelp, has launched four
applications for the iPhone that track
sleep, weight, pregnancy, and state
of mind. As the users implement these
tools in order to monitor their own
development, MedHelp collects all
of the data.
General
Electric

34
Nike is another brand that charged
headfirst into the year with a new product/
service that expands the possibilities
of its successful ecosystem Nike+: the
Nike FuelBand. This system allows users
to track their daily activity and see their
progress.
Nike+ FuelBand has an LED screen where
you can see the information gathered
about the activities in your day, sensed
and collected via wrist movements. The
user sets a goal for how active he/she
wants to be during the day and his/her
movements are recorded and measured
by the bracelet with 20 LED lights, which
change from red to green as the user
nears his/her goal. There’s a website
where all of your NikeFuel points are
accumulated, so you can compare your
performance based on the time, day,
week, month, or year using different
types of graphics. You can also compare
your data to that of your friends in the
Nike+ community. This device can also
be synchronized with the iPhone and
the data can be viewed using a free
application.
Nike
Fuelband
Although similar devices like Fitbit
and Jawbone UP have existed since
2009, Nike waited for the trend to go
mainstream, in order to execute a major
launch that would position the brand
as the leader of its category and as the
reference brand for this type of gadget—
in short, becoming the company that
democratized the measurement of
sports performance and well-being for
all users. Ultimately, Nike has been a
true game-changer, offering relevant
services to its consumers thanks to
data mining. If all of this information
is analyzed on a large scale, the
opportunities for the brand are infinite.
“Nike is becoming a company that
isn’t just focused on products, but on
products and services. It used to be
that when you bought a product, that
was the end of the relationship. It’s
classic marketing. Great, you bought
the product. See you in a year, when
the next campaign comes along. That
thinking has flipped on its head. Now,
the purchase of any Nike product needs
to be the beginning of the relationship
we have with the consumer.”
–Stefan Olander, VP Digital Sport

35

The system allows users to track their daily
exercise and see their progress. As the claim states,
“Make it count.”

36
The real estate website Trulia (New York
housing sales and rentals), has launched
an interactive “commute map” that
allows users to view their route to work
in a dynamic format. This is especially
useful for those who plan to move to a
new neighborhood, since they can easily
see on the heat map how long it will take
to get to work or to other places. When
users specify a starting point, the duration
of the trip will immediately be shown in
real time on the heat map. Using the slider,
users can see the sites they can reach
quickly, as well as those that will take
longer. Trulia helps its potential customers
make better decisions, and positions
their site as a more useful space, thus
generating traffic and sales. The commute
map is a useful tool for communicating
a large quantity of information in an
easy-to-understand format. It uses the
traffic information and the OpenStreetMap
data to create a visual image with a
range of colors that represent the different
travel times.
Trulia

38
The Eatery is an application developed by
Massive Help (USA), which lets users take
pictures of their food and rate other users’
food photos based on their perception of
whether or not what they see is healthy.
Since its launch last year, this platform
has acquired a vast quantity of data from
hundreds of thousands of users. Massive
Health has used the photo ratings to
analyze how our friends influence what
we eat. If you are obese and you have a
partner, there is a 34.5% chance that he
or she is also predisposed to obesity.
This percentage increases to 57% when
it’s your friends who have weight issues.
With this information, Massive Health
hopes to help people improve their food
habits. They’ve found out that people
who eat healthier food tend to stick
together, and therefore the application
seeks to facilitate contact between people
with healthy and not-so-healthy habits
in order to promote better attention to
food choices.
The Eatery

40
Walmart gained Big Data experience
with its purchase of Kosmix in April of
2011, with which it created WalmartLabs.
Kosmix’s expertise was in analyzing
enormous sequences of data from social
networks in order to help companies
understand what consumers are saying
about products and brands. Wal-Mart is
also trying to use social network trends
to influence the marketing and inventory
decisions on their website and in their
stores. Their technology, called Social
Genome, uses the aforementioned
Hadoop and other open-source tools to
capture and analyze in real time the flow
of comments made on Facebook, Twitter,
and other social networks that reveal
what people think about certain products,
brands, places, and events. Walmart has
even developed its own technology to
rapidly analyze the data.
WalmartLabs’ first innovation with this
technology was Shopycat, launched
in December of 2011. Shopycat is an
application that recommends gifts to
friends and family members based on
your tastes and likes on Facebook. Its
Wal-Mart
objective is to turn insights about
the consumer, extracted from social
networks, into practical shopping
advice. Shopycat is capable of
interpreting unstructured data like the
feelings behind a Facebook status
update, which are difficult for traditional
databases to analyze. Shopycat also
identifies which items are “better gifts”
than others, using an algorithm that
analyzes multiple aspects such as how
recently the product was launched, its
uniqueness, and the user’s purchasing
behavior on Walmart.com. Walmart is
taking an unconventional approach to
offering gift recommendations. If the
company does not find the best product
in line with a recommendation online
or in a local store, it will send the
user to another retailer who does have
that product.

Privacy
42
As the relationship between marketing
and Big Data evolves, brands need
to examine how to obtain information
while not only protecting the privacy
of their customers or users, but also
demonstrating that they are making the
effort to do so.
In a world where we increasingly
capture more and more information,
and where information comes
from the daily use of all types of
devices, we have to be ever more
responsible about the use of data.
What’s more, consumers and users
are also becoming more aware. They
are informed about how companies
use information and they demand
suitable data protection policies that
are perhaps not always compatible
with maximizing marketing
opportunities, even when those
opportunities would benefit
the users.
In this context, the public response
is unpredictable and variable.
BlackBerry has been severely
criticized in public for leaking
certain data, and Twitter has been
praised for protecting it. Google
became the center of attention
when The Wall Street Journal
revealed that the US government
had obtained a secret court order
to force Google and the Internet
service provider Sonic.net to
give up all of the email account
information of the famous hacker
and WikiLeaks volunteer, Jacob

43
Appelbaum, who had not been accused
of a single crime. The Wall Street Journal
disclosed how the ISP secretly fought
to avoid providing the information until it
was forced to do so. Google, in turn, did
not comment on the WSJ exclusive, thus
creating discontent amongst online users.
These types of cases generate a great
deal of controversy.
On the other hand, we often lose sight
of the idea that certain data is personal
and must be protected. For example, the
Ritz-Carlton chain has taken big steps
forward in the hotel industry, improving
its hospitality by collecting a lot of data
from its customers, with the sole goal of
improving customer service.
For now, this seems valid and no
one has complained. That said,
it can also be counterproductive
for a service to become “too
good” as a result of data analysis:
the customer who notices how
proposals or content are always
personalized may feel “watched”
or frightened about the company’s
data-gathering methods.
Balance appears to lie in a
combination of strict
data-protection policies that
allow information to be used to
improve services, but are always
transparent with regard to what
information is being used and why.

44
The marketing benefits of Big Data are not
just related to the possibility of offering
improved content or better applications
for consumers. Rather, Big Data can also
be used to improve the products and
services offered by brands, or to facilitate
marketing decision-making beyond
conventional market research.
Wal-Mart itself has had positive
experiences with this. This is because its
efforts to make the most of opportunities
that lie within data analysis went
beyond just personalized product
recommendations. An example of this
was when Walmart detected an increase
in demand for juicers which correlated
with the premiere of a Netflix movie that
examined the health benefits of juices. As
a result, the company promoted its juices
with this theme.
Big Data can
improve
decision-making
and promote
innovation

46
Netflix, a company that streams television
series and movies online, recently
purchased the license for a television
series, surpassing the bid proposed by
the cable TV channels HBO and AMC,
in order to guarantee their rights to the
series House of Cards. This is the first
time that Netflix has invested in original
content. Netflix, since its founding, has
distributed television content using a
subscription model (physical shipment
of DVDs through the mail), and now has
broadened its business to provide
on-demand video streaming. The content
is transmitted online to consoles like the
Xbox 360, Nintendo Wii, the PS3, and
other devices like Blu-ray players and
Smart TVs connected to the Internet, in
addition to smartphones, tablets and
computers.
The series the company purchased is a
remake of a BBC political thriller. It will
be directed by David Fincher and will star
Kevin Spacey. What Netflix did was collect
large quantities of data from all of its
subscribers in order to determine if they
would want to watch this combination
Netflix
of political thriller, director, and actors.
The answer was yes. And not just that,
but the same data that helped Netflix
decide which series to purchase will
now help the company promote it
effectively among their subscribers
through their recommendation system,
which suggests 75% of what users end
up watching, according to the company.
To understand the context, it helps to
keep in mind that in the month of June,
Netflix streamed more than one billion
hours of online video to its subscribers.
Well-managed data collected on its
viewers can help the company find
a new series in the future or movies
that will be in line with what Netflix
customers want to watch.

48
Another interesting case is that of the
startup Bluefin from the MIT Media Lab.
Bluefin associates the conversations held
on social networks with television in order
to help brands. This allows producers,
television channels and brands to see
which content generates the most interest
and connections among the viewers,
which is an interesting step forward
in measuring audience sentiment and
engagement.
Founded by professors Deb Roy and
Michael Fleischman in 2008, Bluefin scans
more than three billion mentions on social
networks per month and crosses them
with an archive of “visual signatures” of
more than 200,000 television programs
from more than 50 channels. This data is
used to provide retrospective information
MIT
Media Lab
on what viewers were saying about the
program when it aired.
This can help brands reach a higher
level of understanding, with a deeper
and more precise grasp of how
viewers see the program and its
advertising. It allows them to check how
advertisements work in different time
intervals, and on different channels or
programs, as well as how they stand up
to their competitors.

50
6 Key Points
50
BIG DATA IS ALSO FOR MARKETING:
The term Big Data refers to infrastructures and systems so broad and powerful
that they can seem unrelated to marketing. But Big Data in fact represents a real
opportunity to develop strategies, campaigns, customer experience models, and
CRM based on access to and use of never-before-seen levels of data, even when
it doesn’t quite reach the volume truly required.
BIG DATA IS A MEANS, NOT AN END:
Like any procedure for obtaining knowledge, Big Data is an instrument in the
hands of marketers, which can have powerful implications for their businesses,
but it should not be a claim or goal in itself.
REQUIRES A CROSSCUTTING APPROACH:
Big Data involves the capacity to extract and transform data in a powerful way
that would not necessarily be possible with conventional methods. This requires
a cross-cutting approach to integrate data-capturing devices, systems, different
types of data, and, above all, an open-minded way of thinking to discover new
opportunities.

5151
VALUE FOR CONSUMERS:
Strategies based on Big Data have proven to be capable of creating value for
consumers in many fields by helping to develop new tools, applications and
products that benefit the consumer, while always defending and protecting
consumer privacy.
VALUE FOR BRANDS:
The ability to connect enormous amounts of data from diverse sources
constitutes, at a minimum, a powerful tool for researching nonmanipulated
markets. Big Data represents an opportunity for brands to better understand their
consumers, even providing answers to questions that consumers may not even
be asking yet. Big Data is also a tool that can have profound effects on loyalty
programs and CRM customer-service strategies, creating ever more accurate and
relevant personalized communications.
BIG DATA HAS IMPLICATIONS:
With Big Data, infrastructure, resource, and work-style needs are not trivial, but
they are not unrealistic either. The application of Big Data to marketing is a
proposal for the long term.

52
Big Data is starting to enter inaccessible
realms. It is always possible to collect
more and more pieces of data and ask
ourselves ever more complex questions.
The European Organization for Nuclear
Research’s Large Hadron Collider atom
smasher generates so much data that
most of it is ignored and deleted, in the
confidence that nothing of importance
is being discarded—unlike, for example,
in the healthcare world, where clinical
histories, or all of the medical images,
such as X-rays and MRIs, could be
important. There will always be a doctor
who wants to cross-reference data from,
for example, all of the X-rays of tumor
patients still alive after five years, who
have families and no alcohol drinking in
their background. Or perhaps we might
want to analyze power-consumption data
An emerging
issue
from all power meters to the minute, in
order to make appropriate consumption
decisions. Why not have meters in
every outlet and in every appliance to
customize electricity charges as much
as possible? Or perhaps someone might
want to collect all of the tweets that
mention a specific subject and correlate
them with news items; or follow the
movement of every vehicle on the
road; or study the influence of rumors
propagated on social media about stock
exchanges and financial products, or
about recently premiered movies or new
products. And what about a system
that links a buyer’s personal data from
his NFC-enabled payment device (NFC
is soon to be implemented in cellular
phones) with every item purchased
in the supermarket, through the NFC

target incorporated into each product
unit? This will soon revolutionize the
way we pay for our groceries. The list of
questions that industries, sectors and
companies can ask themselves is never
ending. So is the list of answers, although
the majority of them start from a shared
premise: concern for the consumer and a
push to unveil all the hidden potential of
this knowledge.
In order to apply marketing strategies
based on Big Data principles, first we
must invest in infrastructure, and systems,
and resources with which to analyze all
the data in the spirit of a search that does
not rule out deep connections between
data and events that on the surface seem
completely unrelated. And of course, we
must have the will and the resources to
53
activate that knowledge in specific
strategies and actions, whether it be
the launch of a new product or the
creation of a cell-phone application that
distributes new brand content in a new
or more effective way.
The reward, in the form of value added
for the consumers and growth and
loyalty for the brands, is waiting for you.
It is Big Data.

54
El Blog de Enrique Dans
ALT1040
The Wall Street Journal
Public Technology
Harvard Business Review
Fast Company
VentureBeat
lnformation Management
Statista eMarketer Forrester Gartner
Sources
ZDNet
Robert Kirkpatrick: How The
United Nations ls Using Social
Data To Spot Disasters
TED talk: Kevin Slavin: How
algorithms shape our world
McKinsey & Co.
TheNextWeb
The Guardian
Forbes
Business lnsider

5555
About the Authors
This document was written by Juan
Manuel Ramírez, Director of Strategy
and Development, and Daniel Camprubí,
Planner, at Proximity.
Proximity is a digital agency that offers
integrated marketing and advertising
solutions. By bringing together knowledge,
creativity, and technology, we develop
innovative ideas and measures able to
solve business problems.
www.cpproximity.es
www.youtube.com/cpproximity
twitter: @cpproximity

56
WWW.BBDO.COM
WWW.PROXIMITYWORLD.COM
WWW.DIGITALLABBLOG.COM
WRITTEN BY
JUAN MANUEL RAMÍREZ
DANIEL CAMPRUBÍ
EDITED BY
GRACE CHANG
DESIGNED BY
KATHLEEN HANNA

Big Data

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