Sunday, August 21, 2011

BIG’s Blog: Predictive Analytics – Part 2

Today’s blog is written especially for my subscribers who have large direct mail fund raising programs.

Many nonprofit direct marketing fund raisers have never heard of predictive analytics. Or, if they have heard the term, they are not clear as to what it means. In Part 1 of this series on Predictive Analytics, I described how fund raisers need to think about mitigating risk through predictive analytic methods the way insurance companies mitigate risk through actuarial methods. Both are data-driven and mathematical.

Nonprofit direct marketing fund raisers that do not integrate predictive model scores into their targeting methodologies will incur unnecessary risk. But, using predictive analytics, they are incorporating a data-driven system of risk management.

In the commercial world, predictive analytics is an established, pervasive business practice. Eric Siegel, PhD., in a recent IBM paper shared the history of proven analytical technology.

“Born of research labs and built upon mathematics, probability, statistics, and database technologies, predictive modeling capabilities, known as machine learning in the academic arena, are scientifically proven and have benefited from decades of advancements.”

As nonprofit direct mail fund raisers are soon to face significant postal increases through the outright loss of the nonprofit postal discount, or, if they are lucky, a phase out of the postal discount over several years, it is imperative nonprofit direct marketers incorporate predictive analytic methodologies that will help them optimize mail quantities and maximize profitability.


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