webinar: analytics as your business edge
TRANSCRIPT
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Analytics as Your Business Edge
Srinath Perera, Ph.D VP Research, WSO2
Member, Apache Foundation @srinath_perera
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A Day in Your Life
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Success Stories • Money Ball ( Baseball drafting) • Nate Silver predicted outcomes in 49 of
the 50 states in the 2008 U.S. Presidential election
• Cancer detection from Biopsy cells ( Big Data find 12 patterns while we only knew 9), http://go.ted.com/CseS
• Bristol-Myers Squibb reduced the time it takes to run clinical trial simulations by 98%
• Xerox used big data to reduce the attrition rate in its call centers by 20%.
• Kroger Loyalty programs ( growth in 45 consecutive quarters)
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If you collect data about your business, and feed it to a Big Data system, you will find useful insights that will provide competitive
advantage – (e.g. Analysis of data sets can find new correlations to "spot business
trends, prevent diseases, combat crime and so on”. [Wikipedia])
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Putting Analytics to Work
§ What happened? And Why? ( Hindsight)
§ What is Happening right now? ( oversight)
§ What will happen? (Foresight)
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Value Preposition
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Let the Analytics Lead the Charge
§ Keep Your Customers
§ Get New Customers § Improve Operations § Monetize your data
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Keep Your Customers§ Churn Prediction
§ Telco (E.g. Is account in use)
§ Customer Context § In Branch Interactions ( use Bacons to
know when customer is in the branch, tell him waiting time proactively)
§ Customer’s Own Statistics ( Can you help him plan his life?) § E.g. Bank, Grocery
§ Customer Segmentation ( not all customers are created equal, do special treatment for who really matters)
GeorgeCalebBingham,1846
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Customer Context with BLE
• Track people through BLE via triangulation
• Higher level logic via Complex
Event Processing
• Traffic Monitoring
• Smart retail
• Airport management
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Get New Customers§ Brand Awareness
§ Who mention my brand § What are their sentiments § What affects my brand?
§ Marketing Campaigns § Does marketing $$ spent efficiently? § Where are outcomes? § Ask hard questions?
§ Who are non Customers in the site?
§ What new services existing customers looking at?
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Predict Promising Customers
• Typical website can get millions of users
• Only very small fraction coverts
• Each user, we know what he access, where is works, country, what browser, OS, etc.
• Problem is to predict what users will covert
• Used Logistic regression, Random Forest, Survival Modeling etc.
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Improve Operations§ Understand cost center and
ROI § Day to day Operations
§ Where is most friction? § Ask what if ? § Alternative modes of interactions: Can
customer make an appointment via his phone, and give feedback also via phone?
§ Predictive Maintenance § Employee Hiring and Churn
Prediction § Fraud and Risk Analysis
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Predict Wait-time in the Airport
• Predicting the time to go through airport
• Real-time updates and events to passengers
• Let airport manage by allocate resources
• Implemented using linear regression
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Fight the Fraud§ Fraud are cause for major
risk and friction § Often done via human
authored rules (e.g. more than 10k at midnight)
§ Machine Learning can learn those rules and adept
See White Paper,
Fraud Detection and Prevention: A Data Analytics
Approach
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Data is the New Oil • Best example is Google, Facebook
( most valued companies) • Some operations can be justified just
to get the data • Monetize your data
• Retailers could be paying major US banks $1.7 billion a year by 2015 to send targeted discount offers to customers (Aite Group)
• Telcos send targeted advertisements
h5p://dupress.com/ar>cles/data-as-the-new-currency/
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Challenges: Causality• Correlation does not imply Causality!! ( send a
book home example [1]) • Causality
– do repeat experiment with identical test – If CAN’T do a randomized test (A/B test)
– With Big data we cannot do either
• Option 1: We can act on correlation if we can verify the guess or if correctness is not critical (Start Investigation, Check for a disease, Marketing )
• Option 2: We verify correlations using A/B testing or propensity analysis
[1] http://www.freakonomics.com/2008/12/10/the-blagojevich-upside/[2] https://hbr.org/2014/03/when-to-act-on-a-correlation-and-when-not-to/
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Curious Case of Missing Data
http://www.fastcodesign.com/1671172/how-a-story-from-world-war-ii-shapes-facebook-today, Pic from http://www.phibetaiota.net/2011/09/defdog-the-importance-of-selection-bias-in-statistics/
• WW II, Returned Aircrafts and data on where they were hit?
• How would you add Armour?
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Actionable Insights are the Key!!
• Significant event that warrant attention ( e.g. more than two technical issues would lead customer to churn)
• Can identify the context associated with the insight ( e.g. operators can see though history of customers who qualify)
• Decision makers can do something about the insight ( e.g. can work with customers to reassures and fix)
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Summary • Role of Big Data and Impact • Keep Your Customers • Get New Customers • Improve Operations • Monetize your data • Use your common sense