Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Coursera’s “Machine Learning for Everyone” Fulfills Unmet Training Requirements
  My new course series on Coursera, Machine Learning...
Segmentation and RFM Analysis in the World of Wine and Spirits
 Segmentation is a hot word these days, and it...
How Machine Learning Works – in 20 Seconds
  This transcript comes from Coursera’s online course series,...
4 IoT Devices in Healthcare Making An Impact Now
SHARE THIS:

5 years ago
White Paper – Immediate Access

 

Uplift Modeling: Predictive Analytics Can’t Optimize Marketing Decisions Without It written by PAW Founder Eric Siegel, Ph.D., and sponsored by Pitney Bowes Business Insight
Thank you for your interest in the white paper, “Uplift Modeling: Predictive Analytics Can’t Optimize Marketing Decisions Without It,” written by PAW Founder Eric Siegel, Ph.D., and sponsored by Pitney Bowes Business Insight.
 

PDF Download is restricted to site members.
Log in on the right OR subscribe for free

WHITE PAPER DESCRIPTION:

To drive business decisions for maximal impact, analytical models must predict the marketing influence of each decision on customer buying behavior. Uplift modeling provides the means to do this, improving upon conventional response and churn models that introduce significant risk by optimizing for the wrong thing. This shift is fundamental to empirically driven decision making. This convention-altering white paper reveals the why and how, and delivers case study results that multiply the ROI of predictive analytics by factors up to 11.

For upcoming presentations on uplift modeling at Predictive Analytics World, and other additional related resources, see this article.

For a broader introduction to uplift modeling, see also the final chapter of Eric Siegel’s book, Predictive Analytics.

Leave a Reply

Pin It on Pinterest

Share This