By: Eric Siegel, Founder, Predictive Analytics World
In anticipation of his upcoming conference presentation, Using Predictive Analytics to Improve Customer Retention, at Predictive Analytics World San Francisco, May 14-18, 2017, we asked Craig Soules, CEO & Founder at Natero, 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: Natero helps its customers by predicting two kinds of potential customer behaviors. The first is customers who are likely to churn or stop using a given service. The second is customers who are likely to upsell or purchase more of a given service.
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 is a key way in which our customers decide which customers to reach out to and work with. By focusing on the customers who are likely to change their use of the service (either churn or upsell), they can have the most positive effect on the health of their business.
Q: Can you describe a quantitative result, such as the predictive lift of your model or the ROI of an analytics initiative?
A: Customers using Natero have been able to reduce their customer churn by as much as 24% month-over-month. Although churn reduction is ultimately achieved through the efforts of the customer success team and their engagement with the customer's needs, knowing which accounts to spend time with is a critical factor in spending those efforts wisely. Predictive analytics play a key role in driving their attention and efforts in the right ways.
Q: What surprising discovery or insight have you unearthed in your data?
A: One surprising discovery is the role that individual user data plays in understanding account churn. A lot of customer success teams today rely on high-level metrics such as DAU and MAU to understand account health, but those are almost never enough to be truly predictive. In the end, the behaviors of individual users and the changes in those individual behaviors are often required to build accurate models of churn outcomes.
Q: Sneak preview: Please tell us a take-away that you will provide during your talk at Predictive Analytics World.
A: Predictive models really need to be tuned not just to the use case, but to the individual scenario. As such it's critical to gather feedback from the users of the model results on an ongoing basis to continue to tune those results toward the specifics of their use case.
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Don't miss Craig’s conference presentation, Using Predictive Analytics to Improve Customer Retention, on Tuesday, May 16, 2017 from 10:55 to 11:15 am at Predictive Analytics World San Francisco. Click here to register to attend.
By: Eric Siegel, Founder, Predictive Analytics World