Machine Learning Times
Machine Learning Times

2 years ago
Wise Practitioner – Predictive Analytics Interview Series: Bob Nisbet at University of California, Irvine


By: Eric Siegel, Founder, Predictive Analytics World for Business

In anticipation of his upcoming conference presentation at Predictive Analytics World for Business Las Vegas, June 16-20, 2019, we asked Bob Nisbet, Instructor at University of California, Irvine, a few questions about their deployment of predictive analytics. Catch a glimpse of his presentation, Effective Data Preparation, and see what’s in store at the PAW Business conference in Las Vegas.

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

A: Customer/student retention, cross-sell, credit risk, customer value, customer acquisition probability.

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

A:  Currently, I am retired, but I still work on contract. In my recent contract with Western Seminary, I developed a student retention model, in which I combined structured and unstructured data to predict the probability that a student will remain in the school and graduate with a degree. In my former jobs, my results helped to drive relationship management operations to reduce churn, predict the probability of acquisition of commercial banking customers, and to model credit risk.

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

A: One cross-sell marketing project led to a $1.5 million new revenue stream for Bell South Telecommunications.  A recent student churn model helped Western Seminary to reduce student churn from 83% to 65% over a 4-year period.

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

A: Demographic data can enhance the quality of model predictions significantly.

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

A: Many of the most predictive variables of my models were those that I derived myself from available data elements, using various data preparation operations.


Don’t miss Bob’s presentation, Effective Data Preparation, at PAW Business on Wednesday, June 19, 2019 from 11:20 AM to 12:05 PM. Click here to register for attendance.

By: Eric Siegel, Founder, Predictive Analytics World for Business

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