Big Data in the Retail Business.
Laurent Kinet CEO of Swan Insights
Who am I?
My goal in my professional life has always been to deliver strategic value to my customers through the potential of new technologies.
DIGITAL-INFUSED AND ENTREPREUNEUR
Who am I?
Data is not new. Big is not new.
Galileo Galilei, On Saturn.
The first and most beautiful data visualization on earth.
“The best statistical graphic ever drawn”, Edward Tufte.
The first and most beautiful data visualization on earth.
Data is not new. Big is not new.
The new in Big Data is…
A couple of figures.
$600 buys you a disk drive that can store all of the world’s music
7 billion mobile phones in use in 2012
40 billion pieces of content shared on Facebook every month
Source: McKinsey
A couple of figures.
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4
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2013 2014 2015 2016 2017 2018 2019 20
Data Growth
IT Spending
Source: McKinsey
A couple of figures.
Source: McKinsey Big Data: The next frontier for innovation, competition and
productivity
Meet the demand.
Data have swept into every industry and business function and are now an important factor of production.
Big Data creates value in several ways.
Transparency. Expose variability and Improve performance. Segment populations to customize actions. Supporting human decision making with automated algorithm. Innovate new business models and P&S.
There will be a shortage of talent necessary for organizations to take advantage of Big Data.
Source: McKinsey Big Data: The next frontier for innovation,
competition and productivity
Background observations on Big Data.
“The best statistical graphic ever drawn”, Edward Tufte.
The first and most beautiful data visualization on earth.
Use cases.
Source: SAP 2013
Big Data?
Big Data for Retail?
Big Data: the next big thing in Retail?
Fact. We entered a data-driven society.
We entered the age of information. Human information is growing three times faster than structured, corporate data. We can’t ignore them both anymore.
All decisions will soon be made out of data.
WE SWITCH FROM “GUESS” TO “KNOW”.
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Huge opportunities are missed. Companies need help to take the most of external data, delivering strategic insights as the fuel for decision-making and targeted actions.
However, tons of data are still under-exploited. Today,
companies can’t ignore those facts to ensure their business sustainability and
competitiveness.
Holistic Data-driven Business.
External Data Sources are the
KEY to sustainable performance
HOW DO WE DO THAT
HOW DO WE DO THAT
CM Tools are here
INSIDE VIEW
OUTSIDE VIEW
PAST FUTURE
Corporate Cockpits
Standard B.I.
Historical Social Data Analysis
Analytics
Machine-learning Algorithms
Prediction
Social Web Data Open Data
Machine-learning Algorithms
Corporate Data
How can we do that?
You need three things
HOW DO WE DO THAT
MULTIPLE DATA SOURCES.
POWERFUL DATA ANALYSIS.
HUMAN INTELLIGENCE.
DATA SOURCES
BIG DATA ANALYSIS METHODS
WEB DATA SOCIAL DATA OPEN DATA ACQUIRED DATA YOUR DATA
MICRO SEGMENTATION
CUSTOMER INTELLIGENCE
PREDICTIVE MODELING
PRESCRIPTIVE ANALYSIS
BEHAVIORAL OUTLOOK
WHAT-IF SCENARIOS
SENTIMENT ANALYSIS / NLP
DATA-DRIVEN OPERATIONS
DATA-DRIVEN CAMPAIGNS
ACTIVATION PROJECT MANAGEMENT
INFORMATION SYSTEMS LOOPBACK
SPECIFIC ACTIONS
STRATEGIC CONSULTING
The DataGraph in 90 seconds.
See it online on swaninsights.com/video
The DataGraph in 90 seconds.
See it online on swaninsights.com/video
The DataGraph in action.
DataGraph Data Sources Actions Needs
It delivers drastically better results than “mere” software.
Extended range of
data sources
Proprietary DataGraph
Most advanced Data Analysis Methods
Strategic Consultancy Background &
Approach
Sectorial Knowledge
The DataGraph in action.
DataGraph Data Sources Actions Needs
WEB DATA
OPEN DATA
OTHER DATA
CORPORATE DATA
SOCIAL MEDIA SEARCH ENGINES GOOGLE TRENDS BLOGS / FORUMS
GOVERNEMENTS UNIVERSITIES INSTITUTIONS
DATA SUPPLIERS PARTNERS
CRM / ERP INDUSTRIAL DATA
DATAGRAPH
Insights
DATA ANALYSIS
GRAPH DATABASES
RELATION DATABASES
PROPRIETARY ALGORITHMS
ADVANCED ANALYSIS METHODS
DATA-DRIVEN CAMPAIGNS
STRATEGIC CONSULTING
INFO SYSTEMS LOOPBACKS
DECISION-MAKING
SPECIFIC ACTIONS
IDENTIFIED NEED
From data sources to tangible results.
Types of tangible benefits.
Data Products.
SAMPLES OF BENEFITS YOU CAN DRAW FROM THE DATAGRAPH.
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Lead Generation.
YOU CAN GET A LIST OF LEADS THAT ARE MOST LIKELY TO PURCHASE YOUR PRODUCT.
Lead Ranking.
YOU CAN RANK YOUR LEADS BASED ON THEIR PROPENSITY TO CONVERT.
Client Segmentation.
YOU CAN GET NEW, UNSUSPECTED INFORMATION ON YOUR CLIENT BASE.
Churn Prevention.
YOU CAN GET A LIST OF CLIENTS THAT ARE ABOUT TO LEAVE YOUR COMPANY.
Sociography.
YOU CAN MAP AND DEFINE GROUPS AGAINST ANY GIVEN TOPIC.
Example 1: Simple Lead Ranking for Automotive.
DataGraph Data Sources Actions Needs
WEB DATA
OPEN DATA
OTHER DATA
CORPORATE DATA
SOCIAL MEDIA SEARCH ENGINES GOOGLE TRENDS BLOGS / FORUMS
GOVERNEMENTS UNIVERSITIES INSTITUTIONS
DATA SUPPLIERS PARTNERS
CRM / ERP INDUSTRIAL DATA
DATAGRAPH
Insights
DATA ANALYSIS
GRAPH DATABASES
RELATION DATABASES
PROPRIETARY ALGORITHMS
ADVANCED ANALYSIS METHODS
DATA-DRIVEN CAMPAIGNS
STRATEGIC CONSULTING
INFO SYSTEMS LOOPBACKS
DECISION-MAKING
SPECIFIC ACTIONS
L E A D R A N K I N G
INCREASE CONVERSION
RATE
LEAD RANKING
Example 2: Advanced Lead Ranking for Automotive.
DataGraph Data Sources Actions Needs
WEB DATA
OPEN DATA
OTHER DATA
CORPORATE DATA
SOCIAL MEDIA SEARCH ENGINES GOOGLE TRENDS BLOGS / FORUMS
GOVERNEMENTS UNIVERSITIES INSTITUTIONS
DATA SUPPLIERS PARTNERS
CRM / ERP INDUSTRIAL DATA
DATAGRAPH
Insights
DATA ANALYSIS
GRAPH DATABASES
RELATION DATABASES
PROPRIETARY ALGORITHMS
ADVANCED ANALYSIS METHODS
DATA-DRIVEN CAMPAIGNS
STRATEGIC CONSULTING
INFO SYSTEMS LOOPBACKS
DECISION-MAKING
SPECIFIC ACTIONS
L E A D R A N K I N G
INCREASE CONVERSION
RATE
LEAD RANKING
Example 3: Churn Prediction for Telco.
DataGraph Data Sources Actions Needs
WEB DATA
OPEN DATA
OTHER DATA
CORPORATE DATA
SOCIAL MEDIA SEARCH ENGINES GOOGLE TRENDS BLOGS / FORUMS
GOVERNEMENTS UNIVERSITIES INSTITUTIONS
DATA SUPPLIERS PARTNERS
CRM / ERP INDUSTRIAL DATA
DATAGRAPH
Insights
DATA ANALYSIS
GRAPH DATABASES
RELATION DATABASES
PROPRIETARY ALGORITHMS
ADVANCED ANALYSIS METHODS
DATA-DRIVEN CAMPAIGNS
STRATEGIC CONSULTING
INFO SYSTEMS LOOPBACKS
DECISION-MAKING
SPECIFIC ACTIONS
C H U R N P R E D I C T I O N
DECREASE CHURN RATE
IDENTIFY POTENTIAL CHURNERS
Example 4: 360 Client View for Retail.
DataGraph Data Sources Actions Needs
WEB DATA
OPEN DATA
OTHER DATA
CORPORATE DATA
SOCIAL MEDIA SEARCH ENGINES GOOGLE TRENDS BLOGS / FORUMS
GOVERNEMENTS UNIVERSITIES INSTITUTIONS
DATA SUPPLIERS PARTNERS
CRM / ERP INDUSTRIAL DATA
DATAGRAPH
Insights
DATA ANALYSIS
GRAPH DATABASES
RELATION DATABASES
PROPRIETARY ALGORITHMS
ADVANCED ANALYSIS METHODS
DATA-DRIVEN CAMPAIGNS
STRATEGIC CONSULTING
INFO SYSTEMS LOOPBACKS
DECISION-MAKING
SPECIFIC ACTIONS
S E G M E N T A T I O N & C H A R A C T E R I Z A T I O N
RECOM-MENDATIONS
CROSS-SELL
UP-SELL
KNOW CUSTOMERS
360
Example 4: 360 Client View for Retail.
DataGraph Data Sources Actions Needs
WEB DATA
OPEN DATA
TWITTER STREAM GOOGLE TRENDS
SOCIO-DEMOGRAPHICS & CARTOGRAPHY
LOYALTY CARDS CLIENTS / GOODS
1 LOYALTY CARD
PRODUCT GRAPH A- People/Product
affinity B- Cross-buying
DIRECT MARKETING
SUPPLY CHAIN
PLANNING
CRM ENRICHMENT
DECISION-MAKING
S E G M E N T A T I O N & C H A R A C T E R I Z A T I O N
RECOM-MENDATIONS
CROSS-SELL
UP-SELL
KNOW CUSTOMERS
360
2 MAPPING
SOCIAL GRAPH A- Segmentation
B- Characterization Lifestyle/Interests
Lifestage Psychology traits Professional info
3 INTEGRATION
180* VIEW WHAT, WHEN, TO WHOM
4 MATCHING WITH SOCIO-DEMO/
CARTOGRAPHY 360* VIEW
WHAT, WHEN, TO WHOM AND WHERE
CORPORATE DATA
Potential of Big Data: examples.
Swan Insights’ internal work note (December 2013).
Potential of Big Data: 10 examples.
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Data Graphization.
BY THE GRAPHIZATION OF YOUR DATA, IT IS POSSIBLE TO DERIVE AFFINITY LEVELS AND RUN PREDICTIVE MODELS
1. Increase the Average Basket Price
2. Increase the Customer Year Time Value
3. Churn Detection
4. Increase the share-of-caddy
5. Segment most valuable customers
6. Purchase prediction
7. Bundle-purchase identification
8. Smart Couponing
9. Anticipate cash desk congestion
10. Real-time pricing changes
Ethics & Privacy.
One must declare the activities to the appropriate Privacy Commissions.
It is essential to comply strictly with Privacy regulations and follow
a Code of Conduct.
Privacy Commissions
Service Contracts and NDA’s must foresee privacy clauses and confidentiality.
Master Contracts & NDA
Infrastructure must be protected against intrusion through the latest technologies, and the delivery channels must be adapted to corporate security policies. Master Service Contracts always must include a Security Appendix detailing all measures taken to ensure data integrity.
Security Policies & Delivery
Open Discussion.
What kind of Big Data initiatives has your organization started?
Let’s keep in touch.
Laurent Kinet.
CEO Swan Insights sa/nv
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Swan on LinkedIn.
company/swan-insights
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