Valtech - Big Data for marketing (EN)

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Valtech - Big Data for Marketing Aurélie Hornoy, Digital Performance Lead, Valtech aurelie.hornoy@valtech.fr The benefits of data-driven marketing Event - Big Data : de l'analytics à la créativité ... Valtech - 29/11

Technology

Big Data, the new Eldorado for marketing!

Big Data, An under-exploited opportunity!

75%
Of the CMOs believe that
this is an important topic

18% 11%
Consider investing in Big
Report to be using Big Data*
Data

Source : IDC, EMC juiy 2012
* What is the perception and what are initiatives in the field of Big Data?
160 French companies were interviewed

Big Data, a revolution for Marketing departments

“ With the data coming from social media now, it’s like running
24/7 focus groups
” Chief Marketing Officer at Kiddicare,

“
It’s all very well to have all your data in one place, but you need
to do something with it. We have hundreds of millions of rows of

”
data going back to 1998.

Martin Moll, Head of Marketing at Honda UK,

“ The question shouldn’t be about how you manage big data, but
how you are continuing to encourage imagination versus data.
”
Javier Diez-Aguirre, Ricoh’s Director of Corporate Communications

Big Data, capitalize on customer knowledge!

How to relieve What will be the
urban traffic next Gaga song?
congestion?

How does your
supermarket know
that you are
pregnant?

Big Data, beneﬁts for a more creative Marketing!

Big DATA
Ciblage fin
Personnalisation
totale
Automatisation
des actions en
temps réel

Growth and
creativity
Analyse
Identification de
nouvelles

booster
prédictive en
opportunités
capitalisant sur
invisibles à l’œil
les données
nu

Big Data shape a new marketing model!

BEFORE! AFTER!
Ò  Analysis of averages Ò  Analysis of correlations

Ò  Large segmentation Ò  Accurate customization

Ò  Standardized push Ò  Scripted automation

Ò  Declarative data Ò  Data 360° (explicit/implicit)

Ò  Traditional Marketing Ò  Agile and reactive Marketing

Big Data versus Analytics : what are the differences?!

Formulate Define the
Analytics the need need Big Data

Structured Define KPI
Collect ALL the
data from different De-structured
canals
Data Data
Extrapolate to
Collect data explore / define
new indicators

Analyze, explore,
Integration correlate and
aggregate

Re-inject indicators
Analysis of to model and
relationships
visualize data flow

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From hype to action getting what's needed from big data a

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The banking industry will benefit from adopting the latest technology advancements that include artificial intelligence and cognitive computing. These technologies provide the opportunity to mine the massive amounts of transactional data that banks have collected over the past decades to better serve their customers, automate time-consuming mundane tasks and to integrate the act of banking into the lives of consumers. Learn how: http://ibm.co/bankinganalytics

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Data science

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CRM is not a new concept, but with the emergence of Big Data, it has the ability to transform organizations more than ever. The rise of the social customer has also given rise to communities, friends, and recommendation sites having profound influence in their purchase decision. Companies have gotten too big to think about the individual customer. Companies have ignored the statistically insignificant. These days, that same customer has the ability to bring down Goliath. I always come back to United Breaks Guitars incident. The truth is that we've now come full circle and these days in order to get a customer and keep them you have to go beyond just meeting their expectations. A recent article: "The Reason So Many Brands Fail On Social Media Is That They Don't Actually Talk To Their Customers" indicated the following: The wealth of data on customer desires being generated is helping organizations work more effectively, and achieve better results. Social customer management doubles the percentage of sales leads that result in actual sales, relative to traditional CRM approaches. Corporations are starting to recognize that paying attention to customer comments, interests and preferences–once deemed "irrelevant" by brands– becomes the competitive differentiator.

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趙國仁 (Craig Chao) Vpon 行動數據科技數據科學家趙國仁是 Vpon 行動廣告科技的數據科學家，中山大學資管系、資管所畢業，並於2006年取得臺大商研所博士學位。曾創立台灣第一個中文BBS系統、發展全球第一套中文套裝搜索引擎，以及創立龍捲風科技。在加入 Vpon 之前，在國立高雄應用科技大學擔任專任助理教授，曾發表數十篇國際期刊與研討會論文，並通過20項以上的發明專利，喜歡創新、整合性資料分析與探索性研究。

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Valtech - Big Data for marketing (EN)

1. Big Data for marketing! 29/11/2012

3. Big Data, the new Eldorado for marketing!

4. Big Data, An under-exploited opportunity! 75% Of the CMOs believe that this is an important topic 18% 11% Consider investing in Big Report to be using Big Data* Data Source : IDC, EMC juiy 2012 * What is the perception and what are initiatives in the field of Big Data? 160 French companies were interviewed

5. Big Data, a revolution for Marketing departments “ With the data coming from social media now, it’s like running 24/7 focus groups ” Chief Marketing Officer at Kiddicare, “ It’s all very well to have all your data in one place, but you need to do something with it. We have hundreds of millions of rows of ” data going back to 1998. Martin Moll, Head of Marketing at Honda UK, “ The question shouldn’t be about how you manage big data, but how you are continuing to encourage imagination versus data. ” Javier Diez-Aguirre, Ricoh’s Director of Corporate Communications

7. Big Data, capitalize on customer knowledge! How to relieve What will be the urban traffic next Gaga song? congestion? How does your supermarket know that you are pregnant?

8. Big Data, beneﬁts for a more creative Marketing! Big DATA Ciblage fin Personnalisation totale Automatisation des actions en temps réel Growth and creativity Analyse Identification de nouvelles booster prédictive en opportunités capitalisant sur invisibles à l’œil les données nu

9. Big Data shape a new marketing model! BEFORE! AFTER! Ò  Analysis of averages Ò  Analysis of correlations Ò  Large segmentation Ò  Accurate customization Ò  Standardized push Ò  Scripted automation Ò  Declarative data Ò  Data 360° (explicit/implicit) Ò  Traditional Marketing Ò  Agile and reactive Marketing

10. Big Data versus Analytics : what are the differences?! Formulate Define the Analytics the need need Big Data Structured Define KPI Collect ALL the data from different De-structured canals Data Data Extrapolate to Collect data explore / define new indicators Analyze, explore, Integration correlate and aggregate Re-inject indicators Analysis of to model and relationships visualize data flow

11. AureHor aurelie.hornoy@valtech.fr

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