Big Data is a formidable opportunity for the Telecommunications industry. The abundance of data must be leveraged thanks to Data Science to improve the management of customer relationships, operational analyses, network optimization and monetization. Skylads, a startup specialized in R&D on Artificial Intelligence and Big Data offers products and services to make of the most of your data.

1. Big
Data
for
Telcos
Use
cases
Skylads
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2. Skylads
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Skylads:
who are
we?
Skylads
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• Skylads
is
a
startup
founded
in
2015
and
specialized
in
R&D
on
Artificial
Intelligence
and
Big
Data
• Successful
design
and
deployment
of
products
for
the
management
of
real-­‐time
programmatic
advertising
platforms
in
the
US
and
Europe.
• R&D
extended
to
other
industrial
applications:
telcos,
banking,
finance

3. Skylads
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The
consulting
team
Skylads
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• Omar Maes graduated from l’Ecole Polytechnique Paris, France, and l’ENSAE
and is an expert in data processing, machine learning and big data, data
science.
• He has worked on various subjects involving an intensive use of artificial
intelligence, the advanced analysis of data and the production of analyses
based on the exploitation of massive amounts of data.
• He is currently an expert consultant acting globally on innovating projects
(artificial intelligence, programmatic marketplaces, data science).
• Soufian Aboulfaouz graduated from l’Ecole Spéciale des TP et de l’Industrie, Paris,
France and founded several companies in the digital industries in 2006 after
having led for 7 years a software engineering company, a subsidiary of the
Moroccan group Finance.com.
• He is an expert in digital technologies with a pioneering vision on the technologies
of the Internet.
• He is currently an expert consultant acting globally on innovating projects (artificial
intelligence, programmatic marketplaces, data science).

4. Skylads
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What is Big Data?
Skylads
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• Everything
that
can’t
fit
in
a
single
hard
drive
falls
into
the
category
of
Big
Data.
• It’s
a
way
to
think
about
and
predict
the
future,
that
assumes
that
the
more
data,
the
better.
• Describe
and
predict
the
world
around
us:
• Descriptive
progress,
influential
progress
• Feed
back
loop
• Models,
pattern
matching
to
a
definition
of
success
• Historical
data,
training,
historical
patterns,
definition
of
success

5. Skylads
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Telcos:
areas
of
application
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Customer
experience
management
-­‐ Targeted
and
personalized
marketing
-­‐ Predictive
analysis
of
the
churn
rate
-­‐ Analysis
of
online
and
offline
interactions
-­‐ Proactive
management
of
the
customer
relationship
Operational
analyses
-­‐ Profit
and
loss
analyses
-­‐ Fraud
detection
-­‐ Onboarding
optimization
-­‐ Customer
relationship
optimization
Network
optimization
-­‐ Capacity
planning
and
optimization
-­‐ Investments
planning
-­‐ Real
time
analyses
Monetization
-­‐ DAaaS (Data
Analytics
as
a
Service)

6. Skylads
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Architecture
Skylads
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Internal:
business
process
optimization External:
monetization
Marketing Experience
et
Retention
Network
Planning
and
Optimization
Data
Structuration
and
commercialization
Connectors
Business Network
Structuration
and
Mining
Data
Integration
/
ETL
/
Pre-­‐processing
Spark? Hadoop?
BSS OSS
Big
Data
Platform

7. Skylads
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A.
Customer
experience
Management
• Improve
and
optimize
the
customer
experience
to:
• Maintain
the
competitive
advantage
• Reduce
the
churn
rate
• Building
of
a
360° view
on
the
client
through
his
journey
through
all
online
and
offline
interaction
channels:
• Intelligent
and
dynamic
segmentation
• Behavior
analysis
and
insights
• Multi-­‐channel
ultra-­‐targeted
marketing
• Hyper-­‐personalized
offers
• Predictive
analysis
of
un-­‐subscriptions
and
switches
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8. Skylads
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B.
Network
optimization
• Ensure
the
network
coherence:
• Service
capacity
and
quality
management
• Investments
planning
• Introduction
of
real-­‐time
and
predictive
analyses
in
the
data
logs:
• Real-­‐time
network
surveillance
• Capacity
optimization
• Predictive
analysis
of
the
usage
• Usage
mapping
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9. Skylads
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C.
Operational
Analyses
• Increase
of
processes
efficiency:
• Reduction
of
revenue
losses
• Reduction
of
non-­‐quality
costs
• Preventive
analysis
of
behavioral
patterns
of
qualitative
analysis
of
data:
• Fraud
detection
• Anomalies
detection
• Data
correction
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10. Skylads
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D.
Monetization
• Generate
additional
revenue
sources:
• Revenues
diversification
• Transforming
data
repositories
into
revenue
generators
• Packaging
and
commercialization
of
the
asset
“data”:
• Geo-­‐marketing
• Customer
Business
Intelligence
• Digital
Advertising
Segments
(dmp)
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11. Skylads
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Visualizations – Analyses
of
calls
by
type,
origine,
daytime

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Visualizations – Geographical analysis of
the
network
for
failure detection
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13. Skylads
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Visualizations – Geographical analysis of
penetration rate
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14. Skylads
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Approach– « Release
Early,
Release
often »
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START
Audit
of
existing
systems
Data
collection
1
month
POCS
POCs propositions
Validation
Specifications
GO
Execution
Adjustments
Deployment
Evaluation
Learnings
2
months
3
months

15. Skylads
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Some figures
to
illustrate
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Orange
– Livebox – customer
relationship
2014:
Results
of
the
predictive
analysis
approach
:
92
%
of
satisfied
customers
;
35,000
saved
Livebox and
8,000
exchanged,
producting a
gain
of
2.8
million
euros.
2015
:
20
%
additional
saved
Livebox and
3,6
millions
of
gains.
Source
:
http://www.relationclientmag.fr/Thematique/techno-­‐solutions-­‐it-­‐1016/Breves/Big-­‐Data-­‐2016-­‐Comment-­‐Orange-­‐utilise-­‐machine-­‐learning-­‐
service-­‐experience-­‐client-­‐302764.htm
SFR
– Churn
rate
81%
of
potential
un-­‐subscibers identified
and
75%
of
clients
contacted
before
the
un-­‐subscription
stayed
with
SFR
Source
:
http://www.zdnet.fr/actualites/comment-­‐sfr-­‐repere-­‐ses-­‐clients-­‐voulant-­‐le-­‐quitter-­‐grace-­‐au-­‐big-­‐data-­‐39815340.htm
FYI
:
http://www.asprom.com/big/gras.pdf -­‐>
graph
a
recuperer pour
le
geomarketing sur
la
france
FYI
:
http://www.journaldunet.com/solutions/dsi/projet-­‐de-­‐big-­‐data-­‐en-­‐france/
biensur que
l’architecture est faite sur
hadoop
T-­‐Mobile
– Churn
rate
Cut
by
half
churn
rate
in
the
USA
with
big
data
Source:
https://datafloq.com/read/t-­‐mobile-­‐usa-­‐cuts-­‐downs-­‐churn-­‐rate-­‐with-­‐big-­‐data/512
FYI
:
https://www2.deloitte.com/content/dam/Deloitte/us/Documents/deloitte-­‐analytics/us-­‐da-­‐telecom-­‐case-­‐study-­‐final-­‐03232015.pdf
(paper
without
any
figures
but
interesting
to
see
deloitte in
it)
T-­‐Mobile
– Acquisition
cost
The
company
added
2.1
million
customers
in
the
second
quarter
of
2015,
in
its
ninth
consecutive
quarter
where
it
added
more
than 1
million
customers.
This
summer
T-­‐Mobile
bumped
Sprint
out
of
its
spot
as
third
largest
telecomm
company,
and
now
thanks
to
T-­‐Mobile's
clever
use
of
big
data
AT&T
might
just
be
the
next
giant
to
fall
Source:
http://www.smartdatacollective.com/jessoaks11/351284/t-­‐mobile-­‐mines-­‐big-­‐data-­‐continues-­‐progress
Bouygues
– Optimisation reseau
Utilisation d’hadoop sur
le
reseau – gain
de
client
entreprise (Pas
de
chiffre)
Source
:
http://www.lemagit.fr/etude/Bouygues-­‐Telecom-­‐deploie-­‐Cloudera-­‐pour-­‐reduire-­‐les-­‐incidents-­‐de-­‐la-­‐4G