Predictive response modeling isn’t new. By statistically analyzing the demographic and behavioral characteristics of responders to direct marketing campaigns, it is possible to predict the likelihood of response to a future effort at an individual prospect level. This allows the marketer to select prospects with the highest likelihood to respond and vastly increase campaign response rates, while cutting costs.

But what is surprising, is that while predictive response modeling usually does improve response rates, in many cases it actually increases customer acquisition cost per account – or worse, directs companies away from their most profitable customers and significantly reduces ROI.

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