Predictive Marketing analytics (PMA)… is enjoying piles of VC money and lauding sophisticated new technologies.
Predictive analytics isn’t especially new; it’s been around for more than 75 years. Scientist Norbert Wiener used it during World War II to create an anti-aircraft gun that could predict where the targeted airplane would go next. Yet all the current excitement seems to suggest that predictive has reached the point where it can now, somehow, radically improve performance in B2B.
As a B2B marketer, I like new tools. But I’ve learned the hard way that while many ideas have good points I can leverage, they are far from a sure thing. I am always careful navigating trendy environments because, while a new approach may help some companies, there’s always risk involved in applying it to my own situation. I like to know how quickly I will see real, significant value. In a pilot, I like to see indications of outcome improvement very early on.
One thing is clear with respect to predictive: it is shining a light on the importance of fact-based understanding. There is real evidence that an analytical approach to improving outcomes works better than other methods.
In this month’s column, I will take a quick look at what’s new in predictive for B2B, how you might evaluate a predictive proof of concept project, and how you could get the kind of results you’re seeking simply by employing some of the same principles via more direct, easy-to-explain approaches.
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