Los datos, la nueva materia prima del
marketing
Too many
Vs for Big
Data
Batch of new technologies that allow
us to extract value out of a dataset
which, due to it’s volume, variety or
velocity, was not previously exploited
“Set of new technologies, able to extract additional
value of all the available data of a company”
Petabytes: Google 300 PB, facebook: 45 PB, Yahoo! 180 PB
Exabytes: U.S. healthcare
Zetabytes: 2011, 1.8 ZB created. World Information 9.57 ZB
YottaByte, Brontobyte, GeopByte to be reached
I don’t have so much data…
A big European company = Terabytes
Why does it apply to marketing?
Marketing has all that data….
and more
M2M not a trend, your future
MARKET TRENDS
DATA = VALUE
DATA = COMPANY VALUE
Gran parte del valor de las
empresas se mide por sus datos
Startups
Data Loyalty
1
467.142 Mill
$
Grandes empresas
3
20
373.608 Mill
$
150.211 Mill
$
21
148.210 Mill
$
DowJones
Facebook
PER2014 = 13
PER2014 = 48
Diferencia 35
PER + = PER + PDR
PER + = 13 + 35 = 48
UNIVERSAL DATA VALUE
BUSINESS INTELLIGENCE
10
PDR
UDV=
DATA DRIVEN DECISIONS
10
BIG DATA STORED
20
BIG DATA INTERACTIVE
BIG DATA REAL TIME DATA
STREAMING
BIG DATA INTELLIGENCE
100
=
35
100
= 0,35
35
20
20
PDR
20
10
100
10
20
20
20
20
UDV DE TU EMPRESA
BUSINESS INTELLIGENCE
5
X
PDR (tú) = UDVX 10 = 0,35
DATA DRIVEN DECISIONS
5
BIG DATA STORED
0
BIG DATA INTERACTIVE
BIG DATA REAL TIME DATA
STREAMING
BIG DATA INTELLIGENCE
10 = 3,5
35
0
0
0
PDR
3,5(tú)
10
10
10
20
20
20
20
Opportunities/possibilities
Threats/risk for marketing
The Bubble filter
You must enter in the user bubble
83% of the surveyed companies were
able to do things with Big Data that
seemed impossible to achieve before
“The art of possible”
“Impossible is not a fact, it’s an opinion”
Visualizations
And Analysis
Social networks tracking (Tag Clouds)
Social networks tracking and flow of data
Social networks tracking and geolocation
Marketing with Sentiment analysis and semantic engines
Social networks tracking Application
Description:
Search the social network comments and
mentions of interest of a particular issue or event
for further evaluation, influencers detection and
graphical display of the conversation to facilitate
analysis.
Advantages:
Show real-time event (symposium, forum,
seminar, etc..) with visual information.
 Get opinions and feelings about a topic in social
networks in real time
Identify the influencers of a hot topic
 Risk detection and prevention
 Emotional mining: Know the term that is most
popular for some people, brand, event, etc.and
this way you can know about the generated
feelings by the most important terms.
Web Content Crawling and Scraping
Description:
Search the network content and publications on
specific subjects of our interest, to detect, filter,
collect and process relevant information in semireal time or batch.
Associated with the semantic analysis this allows
the detection and classification of the contents
effectively.
Advantages:
Allows the generating of sites in a dynamic way
without any intervention or exhaustive searches,
with the contents collected and categorized.
Unifies in a single web all the tasks that users have
to do manually, so it saves them money and
generates loyalty.
EXAMPLES
Marketing online: Customizing Web Sites (Behavioral
Customization)
Description:
Customizing homepages based on user navigation
Analysis and customization of the homepage and site in
real time for each user based on their browsing
Modification of contents, highlights, ads, in real time
based on user history
Advantages:
Over 300% increase in clickthrough
Creating millions of web pages in real time
Increasing Conversions
Increase in sales
Cost ten times lower than other solutions
Recommended links
News Interests
Top Searches
+79% clicks +160% clicks +43% clicks
vs. randomly selected
vs. one size fits all
vs. editor selected
Marketing offline: Personalized Marketing with Big Data
Description:
Newsletter development, email-marketing or any
other sent material segmented by individual
preferences
Analyzes and takes into account:
• Financial information and user data
• Navigation and usage information from previous
marketing shipments
• Mobile app data (GPS, payments, browsing of
offers…)
• Users’ information from the social networks
Advantages:
Increased clickthrough
Increase in conversions and sales
Natural language processing – semantics and
sentiments
Combines private and public data
Marketing through private structured data with unstructured
public data
NH Quality Focus:
Complementing the internal data of a company by
combining the structured and the unstructured
data, with the data generated by the web and
social networks, allows us to determine the validity
of the data of our brand, product or company.
The comparison and analysis of internal and
external data (web) increases the value of our data
and allows us to gain a competitive advantage over
our competitors.
Advantages:
 It allows sales improvement.
Improves loyalty.
Increases Conversions.
Detects errors or data manipulation.
 SEO improvement with regards to the users and
the public data.
Improves marketing and product boosting with
regards to trends.
Massive information tagging
Description:
Allows you to label and categorize automatically and
massively, any type of content or information.
Advantages:
Allows searching, categorization, clustering, and be
able to extract value out of information otherwise
hardly findable and usable.
Utilizes state of the art tools to identify entities, NED
systems, NERD. These tools combined with the use of
disambiguation of entities using a Big Data system
containing the Wikipedia and other sources of
information.
Speed ​processing capabilities and data volume
superior to that of other systems.
TECHNOLOGY AND THE FUTURE OF BIG
DATA
COMBINATION AND SPEED
Combine all type of data and past, present and future
“Cross Data Spark” main mission is:
• To facilitate the use of data stored in different noSQL databases and data
containers
• To allow combining stored data (past), real-time data (present), and future data
(predictive).
COUCHDB
MACHINE LEARNING AND ALGORITHMS
USING ONLY SPARK FOR ALL PROCESSING:
BATCH, INTERACTIVE AND STREAMING
CROSSDATA SPARK:
Stratio is able to
combine, in one query,
stored data with
streaming data entering
in the system
Polyglots: Spark
integrated with the main
noSQL databases, starting
with Cassandra & Mongo
DB.
SIMPLE AND EASY
Lean = Easier deployment, management,
and use of the system
Stratio Platform
Former Hadoop or
Hybrid Hadoop-Spark Platforms
SIMPLIFICATION
Simplify Building
Process
No te puedes quedar mirando
Arriesga, innova,
reinventate
Hazlo ahora,
si no puede ser tarde
No hay nada mas
arriesgado
que no arriesgarse
Enjoy with “Big Data”
Q&A
THANKS
“the best way to predict the future is to create it”
Óscar Méndez, CEO de Stratio, omendez@stratio.com, @omendezsoto