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3 years ago
Wise Practitioner – Predictive Analytics Interview Series: Madhusudan Raman at Verizon

 

In anticipation of his upcoming conference presentation, Predicting Behavioral Influence in Madhusudan_Ramanreal-time for Dynamic Offers at Predictive Analytics World Boston, Sept 27-Oct 1, 2015, we asked Madhusudan Raman, Innovation Incubator at Verizon, a few questions about his work in predictive analytics.

Q:  In your work with predictive analytics, what behavior do your models predict?

A:  Some examples are Contextual Intent, Contextual Mood, Internet Advertising Bureau (IAB) Context, Interestingness, Propensity to Buy/Act.

Q:  How does predictive analytics deliver value at your organization? What is one specific way in which it actively drives decisions?

A:  Knowing what vertical incubations to pursue and which ones to put on hold is a valuable insight. Predictive Analytics – specifically scoring ‘Propensity to Succeed’ has been a helpful operational support measure for prioritization of resource constrained pursuit of ideations.

Q:  Can you describe a successful result, such as the predictive lift of your model or the ROI of an analytics initiative?

A:  Context specific lift of 21-32% based on an adaptive model that learned from dynamic offer reactions in a reinforcement learning framework has been an eye opener in terms of understanding the potential.

Q:  What surprising discovery have you unearthed in your data?

A:  One surprising discovery was that archetype (‘think extreme’) analysis seems to always be more effective than standard statistical (‘think average’) measures and analysis when we try to unearth insight from real-time data streams.

Q:  Sneak preview: Please tell us a take-away that you will provide during your talk at Predictive Analytics World.

A:  Real-time prediction and attribution of behavioral influence on fine-grained choice can be calibrated and tuned by cloud-based prediction engines economically across a wide swath of Internet Advertising Bureau categories. Both cost and benefit measures seem to favor machine driven bucket of models versus human optimized predictive techniques.

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Don’t miss Madhusudan’s conference presentation, Predicting Behavioral Influence in real-time for Dynamic Offers, on Monday, September 28, 2015 at 3:55 to 4:40 pm at Predictive Analytics World Boston. Click here to register to attend.

By: Eric Siegel, Founder, Predictive Analytics World

Eric Siegel is the founder of Predictive Analytics World (www.pawcon.com) — the leading cross-vendor conference series consisting of 10 annual events in Boston, Chicago, San Francisco, Toronto, Washington D.C., London, and Berlin — and the author of the bestselling, award-winning book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die.

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