Slide di Presentazione del Dott. Mangiavacchi del gruppo Telecom Italia Digital Solution per il PKMF 2015. Milano 15 maggio 2015

1. Leonardo Mangiavacchi – Telecom Italia Digital Solutions

2. The power of Big Data to support digital
marketing

3. Volum eVelocity Variety
► The rate of change in
the data and how
quickly it m ust be used
to create real value
► Capacity to elaborate data
both in real time or near real
time mode
► One key elem ent in
defining Big Data, and
it is arguably the least
im portant of three
elem ents
► Capacity to acquire, store
and access big amount of
data
► Many different data and
file types that are
im portant to m anage
and analyze m ore
thoroughly
► Different typologies of data,
coming from structured and
unstructured sources such
as systems, social media,
audio, video, networks, etc.
Big data is data that exceeds the processing capacity of conventional
database systems. The data is too big, moves too fast, or doesn’t fit the
structures of your database architectures. To gain value from this data,
you must choose an alternative way to process it
(O’ Really)
Big Data from different points of view

4. Big Data is projeted to grow into a
$53,4 billion market
by 2017, up from
$20,2 billion in 2013
Between 2005 and 2010 digital data
grew from 130 to 1227 exabytes
844%
90% of data has been created in
the last 2 years
19 30,4 39,8 56,1
78,4
102,6
16,3
21,8
27,1
35,8
51,8
72,6
3,2
4,4
7
10,7
15
19,4
17,9
28,5
41,8
54,6
11,8
14,9
19,5
26
2010 2011 2012 2013 2014 2015
Services Software Networking Storage Servers
Italian Big Data
Tech Market
(M€)
51,0
103,6
75,4
146,0
206,5
275,2
+ 47,8%
+ 37,4%
+ 40,9%
+ 41,4%
+ 33,3%

5. Big Data: from BI to Prescriptive Analytics
Business
Intelligence
Descriptive
Analytics
Predictive
Analytics
Prescriptive
Analytics
Analytic
CapabilityUnderstand the trends
in the business
Make different offers to
groups of customers
Target each decision to
a customer’s future
behaviour
Automatically take the
Ideal action on each
individual
Decision
Value
Summarize Past and Current
Behaviour
Predict Future
Behaviour and Adapt
Multiplicity of Data Sources
Real Time Analysis
Data
&
Analysis Data
...Analyzing data in a different way…

6. Analytics and Marketing: a history of joint evolution
The era of Business
Intelligence
Analytics 1.0
The era of Big Data
Analytics 2.0
The era of Fast
Business Im pact
Analytics 3.0
The era of Product
Centric Marketing
Marketing 1.0
The era of Consum er
Oriented Marketing
Marketing 2.0
The era of Values-driven
Marketing
Marketing 3.0

7. ►They can then proactively push a
personalized offer via SM S or em ail, and
live care agents can use Customer data
profiles to recom m end the next best offer
(NBO)
►The monitoring of Customers allows operators
to quicky respond to their needs by proposing
specif offers in order to reduce churn and
improve loyalty
►It enables media operators to send
automatically advertising
cam paigns to clusterized target
Clients
►The Data Monetization field enable
companies to exploit the potential of the
ow ned Custom er’s insights by selling
them to third party (e.g. data provider for
targeted display advertising)
*Source: OVUM
Custom er-centric
Marketing
opportunities
Personalized
services
Cam paign
m anagem ent
Up-and
cross-sell
Sell to third
party
Precision
m arketing
Next best
offer

8. Com plex, large, m ulti-
source data
Develop infrastructures to
manage this large amount
of data
Im prove internal
organization and analytical
capabilities
Creation of data-based
products and services
Big Data as em erged in the Analytics 3.0 era
Issues
People & Organization
► Changing leadership skills
► Real tim e analysis drives to faster
decision m aking
► organizational structure (introduction of
Chief Analytics Officers?)
Technology
► Multiple types of data
► Provided not only from static DB but from
every kind of firm in every industry
► Data available at a faster rate
► Analytics on an industrial scale
► Needs of a new tech approach (Big Data
Lake)

9. The Business Data Lake

10. Analytics 3.0
ivr web mobile tv
social
media
sms
MultiChannel Operations
CARING SALESMARKETING
PEOPLE

11. Integrate, Analyze and Visualize Data
► The integration of data acquired from different
and heterogeneous sources is a prerequisite to
enable analytics tools to process the dataset
► In this era of "Analytics 3.0" data
visualization is a very fast growing field
and a critical BI component for enabling
users to see trends, patterns, and other
relationships in a user-friendly and
integrated approach
► It can provide actionable intelligence and
insights to improve businesses across
different sectors
► Advanced analytics return insights
exploiting the potential of online and real-
time analysis that enable:
−A reliable decision making support at
different levels, from strategy to operations
−Direct contact with Clients in order to
improve the Customer experience and
comprehension
−Innovative digital services especially in
the marketing field (e.g. proximity
marketing, Customer profiling, etc.)

12. Telecom Italia Digital Solutions: innovative data-driven services
►Management and
optimization of the
awareness and
reputation of Clients’
brand
►Feedback from social
networks and web
W EB-
Social-
Sentim ent
►Customer base
analysis to profile
target Clients’
segments
►Clients’ DB integration
and delivery of
targeted ADV
cam paigns
Profiling &
Cam paign
►Delivery of push
notifications to geo-
localized target Clients
on Mobile
►A TIDS or branded
App is a prerequisite to
run the service
Proxim ity
m arketing
►Analysis of the Clients’
behaviour within a
defined space
►Optimization of
Clients’ Custom er
experience
In store
analytics
►A service (W cards)
that allows Clients to
issue a special card to
deliver promotional
offers increasing their
Clients’ loyalty
Digital
Loyalty
TIDS innovative digital services

13. Grazie