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Leah Pope is a featured contributor to Predictive Analytics Deconstructed: A Super-Simple Recipe for Marketing Success report.

Here's the complete contribution:

Predictive analytics has come a long way from a handful of years ago, both in terms of functionality and how accessible it is. This only stands to gain momentum, which is a good thing, as businesses move from a business intelligence (BI) perspective that allowed them to analyze data in the rearview mirror to forecasting — with accuracy — what’s around the corner.

Although predictive analytics has been around for quite a bit of time, in reality it required multi-million dollar services engagements and, in addition, long lead times — 12-18 months if you were lucky — to code and train models that would work some of the time. Now we’re getting to a place where predictive analytics is becoming more democratized and the specialty is filtering down to the analyst/admin level.

Don’t get me wrong, we still have a long way to go but the progress in only five years has been immense. Where things get really exciting is how the space has been moving away from services engagements to fully productized and packaged solutions that empower teams to apply predictive analytics to their respective work. And the quality/reliability of the predictive models is getting better. This is particularly nascent right now but expect this to be the way forward over the next five years.

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