Once you start getting into marketing analytics, and you start mastering the basics, the concept of predictive analytics will start to creep up. There's nothing that CMOs and CFOs want more than to plug some dollars into a model that tells them where they'll get the most bang for their buck. So, it's inevitable that it's going to come up.

Predictive analytics is hard though. There's a number of ways to do predictive analytics, but they mostly require a data scientist that can do things like media mix modeling, regression analytics, and other complex analytics models.

But, that doesn't mean that you can't get started. And, the starting point–or the gateway drug–is a metric called "Expected Pipeline". It's fairly easy to start calculating, and you don't need a PhD to get started.

So, let's break down what this new "Expected Pipeline" metric is, how you can use it, and how to calculate it. We're going to talk about it through the lens of marketing attribution data, because it's really compatible with marketing attribution data.