The death of prediction

Prediction has always been a tricky business. Weather forecasts, airline schedules and stock tips are often the butts of jokes for the very simple reason that predicting the future is not only difficult, but most valued when the future is hardest to see.

Reliable, trustworthy predictions depend on having the right data inputs. The real trick is knowing if and when you have a blind spot in that data — which is tough, because not knowing about it is exactly what makes it a blind spot.

The same holds true for predictive analytics and their use in marketing. Our ability to predict something — like a revenue outcome or the performance of a sponsorship — improves exponentially when we’re already familiar with all of the factors surrounding it. But in most of those cases, gut instinct and personal experience will already lead us to the right answer.

The value of prediction — and forward-looking analytics, in general — increases exponentially when we’re operating in unfamiliar territory, without the benefit of an intuition informed by experience.

Human assumptions are some of the biggest impediments when working with marketing analytics — we think we know what matters, even when we don’t. What we need is a way for the data to talk to us when we’re operating in new situations, to let the data itself tell us what variables we ought to be considering.

Ultimately, this is what helps illuminate our unknown unknowns. More importantly, this is the necessary first step toward discovering game-changing strategies. Because in the end, analytics isn’t about predicting outcomes. Analytics is about informing the human decisions that change outcomes.

[Read the full article on MarTech Today.]

Some opinions expressed in this article may be those of a guest author and not necessarily Marketing Land. Staff authors are listed here.

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