UNDERSTANDING MACHINE LEARNING IN MARKETING
GETTING THE MOST OUT OF YOUR DATA
Simon Waller and Iain Brown
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AGENDA
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•
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The Recent Buzz
How does it apply to my company?
Machine Learning in Marketing
Summary
THE RECENT BUZZ ABOUT MACHINE LEARNING
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RECENT BUZZ HIGH PROFILE EVENTS IN MACHINE LEARNING
Robots
Advances in the real world
Man vs Machine
Deep Learning
Very Large Neural Networks
(Ensemble Models
Many models combined)
Reinforcement Learning
Real time data from environment
Self Learning with experience
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RECENT BUZZ
PEOPLE INVOLVED IN MACHINE LEARNING
Demis Hassabis
Google (Deepmind)
“Artificial
intelligence
could end
mankind”
Steven Hawking
Yann Le Cun
(Facebook)
Andrew Ng
Baidu (Ex Google)
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“'Building
intelligent
machines is
like
summoning
the demon”
Elon Musk
RECENT BUZZ WHY HAS IT HAPPENED NOW?
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HOW DOES THIS APPLY TO MY COMPANY?
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MACHINE LEARNING
NEXT LEVEL OF
DETAIL
Super Advanced Machine Learning
Deep Reinforcement Learning ***
Advanced Machine Learning
Deep Learning ***
Ensemble Modelling
Reinforcement Learning
Support Vector Machines
Big
Data
Advanced Statistics
Regularized Regression (Lasso)
Naïve Bayes
Data
Size
Not
Big
Data
Basic Machine Learning – Decision Trees & Neural Nets
“Modern” Statistics (Bayesian & Classical). Regression Analysis.
1900
1950
2000
Date
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2015
2016
MACHINE LEARNING
IN YOUR COMPANY
Super Advanced Machine Learning
Deep Reinforcement Learning ***
A few niche
applications
Advanced Machine Learning
Deep Learning ***
Ensemble Modelling
Reinforcement Learning
Support Vector Machines
Sweet Spot Today
Big Data Analysis
Big
Data
For non-big data
analysis
Data
Size
Not
Big
Data
Advanced Statistics
Regularized Regression (Lasso)
Naïve Bayes
Basic Machine Learning – Decision Trees & Neural Nets
“Modern” Statistics (Bayesian & Classical). Regression Analysis.
1900
1950
2000
Date
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2015
2016
SAS MARKETING
THERE ARE OTHER CONSIDERATIONS!!
ANALYTICS
 Marketing manager
 Marketing analyst
 Cloud (private, SAS, public) deployment,
Hosted (SAS or partner), On-premise
(desktop, department, enterprise)
People
 Marketing scientist
 IT manager & staff
 SAS analytics and SAS high-performance
analytics (grid computing, in-database,
in-Hadoop, in-memory)
 Integrate & prepare data
 Explore data & develop models
 Explain results & share insights
 Deploy & monitor models
Process
Infrastructure
 Analytics by programming, point &
click GUI, or embedded in
marketing task GUI
 Structured, semi-structured,
unstructured, & streaming data
 From manually crafted, artisan
to automated factory analytics
 SAS and open source analytics
SAS
Marketing
Analytics
 Descriptive and inferential statistics
Methods
Paradigms
 Approachable
& actionable
analytics
 Workbenches and
business solutions
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 Exploration, visualization, reporting,
dashboards, and alerts
 Econometrics and time series
forecasting, incl. scenario analysis
 Data mining and machine learning
for predictive modeling and pattern
discovery
Applications
 Text mining and contextual analysis
 Optimization and operations research,
incl. network analysis and simulation
MACHINE LEARNING
EXAMPLE 1 - ADVANCED MARKETING ATTRIBUTION
IN MARKETING
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SUMMARY
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MACHINE LEARNING
ADVANCED MARKETING ATTRIBUTION
IN MARKETING
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SUMMARY 5 MAIN TAKEAWAYS
http://www.sas.com/en_us/insights/analytics/machine-learning.html
http://www.sas.com/en_us/insights/articles/marketing/customer-decision-hub.html
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Thank you very much!
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More information
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RAISING A TRACK
SAS Technical
Support
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SAS USER GROUPS
•
www.sas.com/uk/usergroups
• Webinars – Visual Analytics and Enterprise Guide
• Face to Face – Data Management, Platform Admin,
Enterprise Miner
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SAS FORUM UK
– 16 June 2016
• Birmingham
• Speakers needed!
• Watch your inboxes for further
information
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THANK YOU!
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