Data is your most valuable asset. It represents the entire history of your organization and its interactions with customers. Predictive analytics taps this rich vein of experience, learning from it to offer something completely different from standard business reporting and sales forecasting: actionable predictions for each customer. If you predict it, you own it.
Seven Reasons You Need Predictive Analytics Today
Predictive analytics has come of age as a core enterprise practice necessary to sustain competitive advantage. This definitive white paper, produced by Prediction Impact and sponsored by IBM, reveals seven strategic objectives that can be attained to their full potential only by employing predictive analytics, namely Compete, Grow, Enforce, Improve, Satisfy, Learn, and Act. By Eric Siegel, Ph.D.
Uplift Modeling: Predictive Analytics Can't Optimize Marketing Decisions Without It
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, sponsored by Pitney Bowes Software, reveals the why and how, and delivers case study results that multiply the ROI of predictive analytics by factors up to 11. By Eric Siegel, Ph.D.
Predictive Analytics Delivers Value Across Business Applications
This article summarizes the wide range of business applications of predictive analytics, each of which predicts a different type of customer behavior in order to automate operational decisions. A named case study is linked for each of eight pervasive commercial applications of predictive analytics. Originally published on BeyeNETWORK. By Eric Siegel, Ph.D.