Today’s topic is Predictive Analytics and this is the second in a series of audio podcast interviews on this topic. Dr. Eric Siegel is a former computer science professor at Columbia University and the President of Prediction Impact.
Q: How do companies benefit?
A: Well, the business case for a predictive analytics initiative is clear because having a predictive score for each customer is so clearly actionable. For example, knowing which customers are worth targeting for an offer is about as actionable as business intelligence can get.
To be more specific, let’s say we generate scores to predict the risk each customer has of canceling or defecting from a subscription-base service. Targeted customer retention has impact on such businesses — such as ISPs, magazine subscriptions, online dating, you-name-it.
Retention offers – say a discount – are usually expensive. You can’t extend the offer to all subscribers. The only way to target a retention campaign precisely where it’s needed is with predictive scores that earmark which customers are most likely to leave. When you follow these predictions, you don’t expend the cost of the offer on customers that don’t need it. So, the campaign ROI is much better, growth rates improve and bottom-line profit increases.
So, in general with predictive analytics, each customer’s predictive score informs actions to be taken with that customer. You just can’t get more actionable than that.
To listen to the entire interview visit: http://predictiveanalytics.org/?p=7
