Beyond Analytics : l'influence de l'intelligence artificielle sur votre entreprise

Beyond analytics:
how A.I. can impact YOUR business
Dr. Sébastien Foucaud
sebastien@sbsf-consultancy.com
http://sbsf-consultancy.com
DIGITAL ANALYTICS FORUM 2016

S. Foucaud - ATi Digital Analytics Forum - 2016/10/25
(Prof.) Dr. Sébastien Foucaud
2
๏
PhD in Astrophysics
๏
15-year long career in Astronomy (6 as Professor)
๏
Scientiﬁc expertise in Cosmology (Universe and
Galaxy evolution)
๏
Technical expertise in Data Analytics, Statistics,
Data Mining, Machine learning, Simulations,
Data Centres, product development, Big Data
Technology
>10 years
>1 year
>1 month
CrossLend | Head of Data Science
Feb 2015 - July 2015
FinTech, Risk management, Compliance
OLX | Head of Data Innovation
Aug 2015 - Sep 2016
Classiﬁeds, User segmentation, Moderation,
Data strategy, Business Intelligence

Dr. Sébastien Foucaud
3
Scout24 | Head of Data Science
since Oct 2016
Classiﬁeds/Marketplace, Data Strategy, Personalisation,
Recommendation, Lead generation, UX/UI
certace | Member of Advisory Board
since Oct 2016
Data Science, Data Strategy
SBSF Consultancy | Data Strategy Consultant
since Oct 2016
Data & Business Strategy
Ron Leishman

Artiﬁcial Intelligence is no SciFi…
4

4
It is here and now!

4
It is here and now!
…and we are rather late!

Daily Artiﬁcial Intelligence
5

Daily Artiﬁcial Intelligence
5
“One recurring theme throughout the history of AI / machine learning
research is that we are terrible at determining exactly what aspect of
human intelligence is remarkable.”
Zachary C. Lipton, UCSD

Artiﬁcial Intelligence invades all spaces…
6

… even where we were not expecting it!
7

Artiﬁcial Intelligence, when the giants join forces!
8

But innovation is still fostered by startups …
9

Embracing the data
10

Embracing the data: call a data scientist
11
Business
Insights
Analyses /
Modeling
Data
Collection

How we see the world
12

How scientists see the world
13

Data Scientists not the most business-savvy people
14

Practical (and real) use cases
15
• Moderation and quality content
How machine learning can help prevent fraud and spam?
How it can ensure global quality content and enhance user
experience?
•Personalisation
How AI can help provide the best user experience?
And deliver the right content, to the right user, at the right moment!

Moderation and quality content
16
‣ 2,000,000 ads a day
‣ 30 sec. on avg. for classifying (CS: 500 people/24h)

Moderation and quality content
17
‣70% automatically accepted or rejected
+ categorisation for free
+ reliability at 95%
+ 180 sec. for classifying (CS)
Classiﬁer
Customer
Support
Model
New Ad
Accepted
Rejected
Accepted
Rejected
30%
70%
10%

User experience
18

Personalisation
19
User
Segment
A
User
Segment
B
Item
Segment
1
Item
Segment
2
User
Segment
B
Item
Segment
3
‣ Mobile devices transformed radically the
user experience
‣ Know your customer better!
‣ Delivering the right content, to the right
person, at the right moment
+ Customer Lifecycle Management
+ Content Lifecycle Management
‣ Recommendation > Search
‣ User segmentation
+ unsupervised & supervised ML
+ dynamic lifecycle segments
+ dynamic behavioural segments
‣ Dynamic pricing

Innovating…
20

Innovating = Formulating problems properly
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Innovating = Formulating problems properly
21
Machine learning problems can be diﬃcult for an often overlooked reason. For
many settings in which we might want to introduce an AI agent, the problems
are not well-formed. That is, it's not at all obvious what objective should be
optimized.

Business & Data Strategies begins with Smart Data
22
Aligning Business & Data Strategies
‣ Abundance is not wealth:
+ not all Data is useful (Big vs Smart)
+ choose your battle (limit storage)
+ avoid data gluttony
‣ Predeﬁne use cases
‣ Develop Data Wisdom
‣ Deﬁne success (KPIs)
‣ Data acquisition
‣ Data governance
Right strategy from inception:

Data Mining Strategy
23
Data
Pre-
processing
• Distance metrics
• Sampling
• Dim. reduction (PCA, SVD)
ValidationTesting
Model
Learning
Supervised
• kNN
• Decision trees
• Bayesian Classiﬁers
• Logistic regression
• SVM
• ANN
Unsupervised
• k-means
• Density-based
• LDA
• Bayesian non-parametric
• Test samples
• Metrics
• A/B testing
• Metrics

Data governance: solid base to build from
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‣ Right data & right meta-data
+ getting what you need and only that
+ knowing what you get when you get it!
+ clean and safe data
+ right infrastructure
‣ Essential step (or everything else collapse!), requires right partnership!

SBSF Consultancy
25
info@sbsf-consultancy.com
http://sbsf-consultancy.com
Work with you to:
‣ Identify and formulate the business problem
‣ Review all available data to understand type, depth, expanse and quality
‣ Align Business strategy with Data strategy
‣ Build successful use cases
‣ Driving bespoke, cost-eﬀective product development that makes practical sense
‣ Consolidate data governance (through established relation with AT Internet)

certace
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info@certace.com
http://www.certace.com
The digital expert marketplace for data science projects:
‣ independent “ace” data science experts at the forefront of their ﬁelds
‣ solving your toughest data challenges
‣ save long-term costs associated with permanent hires
‣ immediate impact on your business
‣ SBSF + certace: winning combination for designing right strategy,
appropriate use cases, and implementing them!

Thanks!
27

Beyond Analytics : l'influence de l'intelligence artificielle sur votre entreprise

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Beyond Analytics : l'influence de l'intelligence artificielle sur votre entreprise