March 20th 2017 08:55 am

Wise Practitioner – Predictive Analytics Interview Series: Angel Evan at Angel Evan, Inc.

By: Eric Siegel, Founder, Predictive Analytics World

In anticipation of his upcoming conference co-presentation, Identifying Unique Gamer Angel Evan PAW BLOGTypes Using Predictive Analytics at Predictive Analytics World San Francisco, May 14-18, 2017, we asked Angel Evan, Founder of Angel Evan, Inc., a few questions about his work in predictive analytics.

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

A: I work in marketing, so typically we are trying to predict a customer behavior or outcome. For example, whether or not a customer is likely to cancel a subscription or the probability they will respond to an ad. 

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

A: If I were to cite just one thing, I would say that it helps us (and our clients) figure out where to focus, i.e., which customers are most at risk of leaving, or which customers represent the most potential revenue. 

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

A: While I cannot share actual figures due to NDA, I can say that we recently finished creating a predictive model for a large wine brand to determine which customers were most likely to cancel their wine club memberships. Wine clubs are a vital revenue stream for most wineries, as they represent the single highest percentage of profitability. As a result of our analysis and predictive model, the company saw a decrease in customer churn in just 60 days. 

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

A: Which predictive variables cause individual customer segments to act the way that they do.

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

A: The old data attributes of media planning, especially household income, don’t necessarily influence customer spending the way people think. Traditionally media and strategy planners would target people with high household incomes based on the perception that they have more disposable income. What we’re seeing is that user behavior is a better predictor of outcomes. 

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Don't miss Angel’s conference co-presentation, Identifying Unique Gamer Types Using Predictive Analytics on Tuesday, May 16, 2017 at 11:45 am to 12:05 pm at Predictive Analytics World San Francisco. Click here to register to attend

By: Eric Siegel, Founder, Predictive Analytics World

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