This model has helped Tesco generate annual aggregate gross

Data Science Consulting
Monétisation des données
Big Data Paris 2015
Julien Cabot, Directeur
La Monétisation des données?
Générer un revenu,
direct et/ou indirect,
par l’exploitation des
données, comme actifs
de l’organisation
© Quantmetry 2015 | Salon Big Data Paris 2015
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Quatre Business Models clefs
de la Monétisation des données
Amélioration des processus internes…
Activité dédiée…
Performance
Marketing et
Commerciale
Performance
Opérationnelle et
Financière
Commercialisation
de Données brutes,
enrichies ou
indicateurs
Commercialisation
de Produits &
Services Intelligents
SFR, AXA, SG,
Solocal, Amazon,
Tesco, …
Bouygues Telecom,
Orange, EDF,
Toyota, Amazon,
UPS, …
Météo France,
GERS, BIEN,
Médiamétrie,
Bloomberg, Twitter,
Tesco, …
1000Mercis, AXA
Drive, Google, SFR
Geomarketing,
Equifax, Intuit, …
Revenu d’amélioration
© Quantmetry 2015 | Salon Big Data Paris 2015
Revenu de croissance
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De combien parle-t-on?
“Tesco uses a data ecosystem to monetize data
from its loyalty program, the Tesco ClubCard.
This model has helped Tesco generate annual
aggregate gross billings of US$500 million
globally.”
Source : Forbes, Janvier 2014
“For financial services firms, the opportunity to
monetize customer and transaction is new and
compelling – with revenues of US$175-300
billion per year.”
Source : Strategy& PwC, formely Booz&Company, Juin 2013
© Quantmetry 2015 | Salon Big Data Paris 2015
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Quel raffinage des données?
Niveaux de raffinage des
données
Typologies de données
Usages
5
Service
Données « intelligentes »
Processus adaptatif, règles de
gestion adaptative, …
4
Prédiction
Données prédites, probabilités
Anticipation, recommandation,
alerte préventive, …
3
Indicateur
Données agrégées, calculées
KPI, scores, alerte, dashboard,
infographie, …
2
Caractéristique
Données validées, complétées,
nettoyées
Analyse détaillée, gestion, reporting,
…
1
Brute
Données brutes de logs, capteurs,
formulaires, …
Audit, détection d’incidents, …
© Quantmetry 2015 | Salon Big Data Paris 2015
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Les constituants de la Valeur des données
Utilisabilité
Temps
Précision
Exhaustivité
Rareté
Les données sont-elles
utilisables,
compréhensibles, utiles
pour mes besoins?
La fraicheur des
données permettentelles de réagir
rapidement et/ou
efficacement?
La granularité et la
significativité des
données est-elle
adaptée à mes besoins?
L’exhaustivité et la
complétude des
données
correspondent-elles à
mes besoins?
La donnée est-elle
facilement accessible
et/ou largement
diffusée?
Structuration de
données,
Infographies
…
Remarketing en temps
réel, attrition long
terme, anticipation
d’incident, …
Ciblage
comportemental, Lutte
contre la fraude,
personnalisation de
l’expérience client, …
Benchmark, indice de
référence, …
Avantage concurrentiel,
exclusivité, …
© Quantmetry 2015 | Salon Big Data Paris 2015
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Quels prix pour les données?
Tesco Bank, +3% Market Share, +39%
Car insurance Premiums, +44% Pet
Insurance Premiums
Valeur complète
des données de
Tesco ClubCard
pour Tesco Bank
Source : Strategy&, PwC
U.K.-based supermarket giant Tesco is a
prime example of a nonfinancial company
that’s using data to compete effectively
with traditional financial players. Until
2008, the company ran Tesco Bank as a
50/50 joint venture with the Royal Bank of
Scotland. That year Tesco bought out RBS
and began developing a completely new
infrastructure for the business, built a new
team, and brought in new expertise. The
transition was not always smooth — for
instance, online customers were locked out
of accounts for several days in 2011 when
Tesco moved data from the RBS systems to
its own — but it’s now complete. To fully
exploit this treasure trove of data, the
company took a significant stake in
Dunnhumby, a U.K. data mining firm that
will help Tesco monetize the consumer data
from both the retail and banking
operations. At its core, Tesco Bank is
underpinned by the Clubcard. The insights
the bank gains from the Clubcard customer
data allow the company to understand
customer needs and make the most
relevant offers in the store and in the
bank. The Clubcard credit card rewards
customers with points whenever they use
their card — one Clubcard point for every
£4 (US$6.12) spent. Clubcard customers can
also receive preferential deals when buying
Tesco Bank products — including discounts
on car, home, pet, and travel insurance —
and can use points to buy Tesco Bank
insurance. This year, Tesco Bank gave
customers around £70 million (US$107
million) worth of points to spend in the
store or on Clubcard rewards. In terms of
systems and IT, Tesco’s new platforms
significantly improve customer service.
Instant decisions are now possible on loan
applications, and customers can open and
fund savings accounts in just 10 minutes
rather than the two weeks required in the
past. The conversion is still in its early days,
but Tesco’s efforts are paying dividends in
the form of increased market share across a
range of products. In 2009, Tesco Bank
credit cards made up 9 percent of all
MasterCard and Visa credit card
transactions in the U.K., and by 2012 that
figure had grown to 12 percent.
Meanwhile, from 2008 to 2012, the
company’s car insurance gross written
premiums increased by 39 percent and pet
insurance gross written premiums rose 44
percent.
© Quantmetry 2015 | Salon Big Data Paris 2015
Valeur
Comptable
Coût de
production des
données pour
Tesco Clubcard
Valeur
d’Usage
Revenu
incrémental
estimé
(« UpLift ») lié à
l’utilisation des
données par
Tesco Bank
Valeur de
Marché
Prix des
données
Prix auquel Tesco
ClubCard vend
ses données à
des tiers
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Quels moyens pour monétiser les données?
Types de solutions
Exemples
5
Service
Web Service
Predictive Business Process
Data Management Platform, Data
Exchange, RTB, …
4
Prédiction
Modèle prédictif
Data Science Studio, OpenScoring,
RTD engines, Model as Code, …
3
Indicateur
Data Mart, Data Visualization
SGBD, InMemory, BI, DataViz Tool, …
2
Caractéristique
Data Lab
Hadoop, Datawarehouse MPP, ETL,
BI, …
1
Brute
Data Lake
Hadoop, NoSQL, Stream Processing,
…
© Quantmetry 2015 | Salon Big Data Paris 2015
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Conclusion
5 Etapes essentielles à la
Monétisation des Données
Par Chris Twogood, Teradata
5
4
3
2
1
Start with
Questions
Look for
Data
Patterns
© Quantmetry 2015 | Salon Big Data Paris 2015
Search for
External
Data
Sharpen
Your
Analytics
Skills
Understand
Your Data
Monetization
Identity
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Merci!!!
Julien Cabot
[email protected]
06 64 45 53 73
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