Michael Kaminsky argues that great marketing teams run a continuous loop of forecasting, testing, and measuring results. He uses linear TV as an example: a team predicts revenue lift, invests, measures actual results against the forecast, then doubles down or pulls back based on what happened. This cycle of prediction and validation builds a culture of rapid experimentation.
Repeatedly forecasting and checking predictive accuracy is exactly the cycle that you want to be in when you're a marketing team, because this is what gets you into the realm of following the scientific method of saying, hey, we have a hypothesis that linear TV is going to be a really good channel for us. Okay, next month or next quarter, we're going to invest a lot more into linear TV. And then here's how we're going to evaluate if that worked. We're going to see if revenue went up by a certain amount or not. And then once we get to the end of the quarter, we're going to check, we're gonna say, were we right? Did the revenue go up by at least that much? Maybe it It went up more, maybe it went up less. Okay, what have we learned? We've learned that Linear TV was even better than we expected. Okay, great. Next quarter we're gonna double down even more. We're gonna go hard. Or maybe it's worse and we're gonna pull back and we're gonna switch. The key here again is to get into this world of we're gonna make hypotheses about what we think is actually working. Then we're gonna go test them in the world and then we're gonna go adjust and we're gonna keep doing that process forever. That is what makes really strong marketing teams that are really able to take advantage of what's working for them, the current climate, and then continue to take advantage as things change because they have built in this idea of continuous testing, continuous validation into the way that they work. And so we highly recommend that marketers start to think this way. And that's where having a system where you're continuously forecasting, continuously checking the forecast is really important because it allows you to continuously optimize.
