By: Eric Siegel, Founder, Predictive Analytics World

In anticipation of his upcoming conference presentation, Data Driven Selling: Enabling a Direct Salesforce with Tools that Re-Enforce Predictive Selling Methods at Predictive Analytics World Chicago, June 20-23, 2016, we asked Lawrence Cowan, Partner at Cicero Lawrence_Cowan imageGroup, 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: A good portion of the advanced analytics work we do at Cicero deals with consumer behavior across all stages of the customer lifecycle.  So this would span from acquisition through the development of “typing” tools for targeting and segmentation, to response and uplift modeling for existing customers, to attrition modeling and customized intervention strategies.

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

A: Predictive analytics defines our organization.  With it, we would not have an offering.  As a full service data-driven strategy consulting firm, it is our job to provide the technical and analytical expertise to help our clients leverage data to make smarter decisions.  And in all engagements involving predictive analytics, our ultimate objectives are results and implementation – if our clients cannot actively use the models and insights to make decisions, we have failed.

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

A: In a recent effort to help a financial institution optimize its marketing campaigns, we developed a model that identified customers who were more likely to respond to a CD campaign, and who were more likely to bring “new money” to the CD (opposed to simply shifting money from another account at the financial institution).  The results were very impressive, including the following metrics: 14x higher response rate, 4x increase in average deposits, 60% in “new money” compared to just 3% “new money” in the control group.

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

A: I’m always surprised at the opportunities unearthed with predictive analytics – things that you would never expect if it were not for efforts in data mining.  For example, for a large grocery retailer, we were able to identify two critical customer behavior trends (made possible through loyalty data) that were significant predictors of customer profitability.  These two trends were counter to heuristic judgment at the executive level (executives have since changed their perception of the event after seeing the compelling evidence.

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

A: How to leverage secondary data (household level data) to drive more business value from your predictive models.


Don't miss Lawrence’s conference presentation, Data Driven Selling: Enabling a Direct Salesforce with Tools that Re-Enforce Predictive Selling Methods on Tuesday, June 21, 2016 from 10:30 to 11:15 am at Predictive Analytics World Chicago. Click here to register to attend.

By: Eric Siegel, Founder, Predictive Analytics World