Predictive Analytics Times
Predictive Analytics Times

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


In anticipation of his upcoming conference presentation, Best Practices Enhancing Contextual Experience with Predictive Analytics, at Predictive Analytics World New York, October 23-27, 2016, we asked Madhusudan Madhusudan_Raman IMAGERaman, 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: As in the past, Contextual Intent, Contextual Mood, Internet Advertising Bureau (IAB) Context, Contextual Interestingness, and Propensity to Buy/Act continue to be strong prediction targets.

Q: What emerging needs are you seeing related to the behaviors your models predict?

A: Recently the prediction of Thing behaviors to identify Contextual Interestingness has gained in importance due to the recent push to extend the embedded device boundaries to include cloud activity; in other areas, there seems to be increased interest in Propensity for Attrition where a body of best practices are emerging.

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

A: Knowing which market 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: Applying Context (Information) Gain to constrain datasets increases the resulting lift from the model deployment from 2X-9X when applied to a range of Consumer Experience enhancement scenarios.

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

A: One interesting discovery was that archetype (‘think extreme’) analysis seems to always be more effective than standard statistical (‘think average’) measures and analysis for predictive segmentation incorporating near-real-time sensor streams from Things.

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

A: Contextual understanding enhances Consumer Experience. We will share a systematic Predictive Analytic technique for dealing with context, its quantification within a dataset, and how channels and touchpoints can use this derived “context” in near-real-time across Industry verticals especially with Thing Sensor data.


Don’t miss Madhusudan’s conference presentation, Best Practices Enhancing Contextual Experience with Predictive Analytics, at Predictive Analytics World New York on Wednesday, October 26, 2016 from 4:20 to 5:05 pm.  Click here to register for attendanceUSE CODE PATIMES16 for 15% off current prices (excludes workshops).

By: Eric Siegel, Founder, Predictive Analytics World

Eric Siegel is the founder of Predictive Analytics World ( — the leading cross-vendor conference series consisting of 10 annual events in New York, Chicago, San Francisco, Washington DC, London, and Berlin — and the author of the award-winning book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die – Revised and Updated Edition, (Wiley, 2016).

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