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2 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.

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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 (www.pawcon.com) — 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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