After months of working on a marketing campaign, nothing’s worse than realizing you aren’t seeing the results you expected.

Unfortunately, many of us have been there. We’ve put all of our creative effort, time, and numerous resources into a campaign that sounded like a great idea, but had nowhere near the expected ROI or engagement. Then, on top of watching our project fail, we’ve had to deal with the awkward scenario of sharing bad performance data with our teams.

No matter how hard you try, it’s impossible to know exactly how well a campaign will do before you run it. However, there’s a strategy that gets pretty close.

It’s called predictive marketing.

While predictive marketing sounds like some futuristic technology you’d only see on a show like Westworld, using data to estimate an outcome isn’t new.

Predictive marketing is fueled by predictive analytics, which dates back to the 1930s. It enabled mathematicians and computers to calculate and analyze the possible successes, failures, and results of various scenarios — such as health or weather conditions.

Later, in the 1990s, when analytics tools became more available to brands, marketers at companies like eBay and Amazon began to combine marketing data with similar formulas or algorithms to predict and strategize around potential consumer behaviors, purchases, and marketing campaign performance.

In the early 2000s, with the presence of “Big Data” many more brands and online advertising platforms embraced predictive analytics and marketing technology.

Now, predictive marketing is all around us. Below are just a few common instances of it, along with explanations of how brands can leverage it.


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