Tobias "Tobi" Konitzer

But what do you do with descriptive ML?

How do you turn that into revenue growth, right?

And it was a very hard question to answer.

This is all about closing the loop, right?

If you know this future, remember, this is the future based on your status quo.

The whole idea of marketing is you want to do something different for customers.

You want to change something.

Otherwise, you don't need to be there.

And it turned out that sort of translating these predictive scores or predictive models into this outcomes-based thinking was really hard.

I lost a company over that because I saw that too late.

We cracked it at Acure, by the way.

We cracked it by piping these predictions back into the ad auctions, the ad bidding systems on Google Ads.

And you can see that was the only way to turn this descriptive machine learning model into an end-to-end pipeline that generated measurable returns.

But so one thing I've learned the hard way is don't put too much stock into accuracy of machine learning.

It's the wrong question to ask.

The right question to ask is how much business impact does technology or AI generate and how easily is it provable and how early is it provable?

Future for the industry certainly will look like machines making more and more decisions.

And by the way, I think that's a good thing.

Machines making more and more decisions of traditional marketing workflows are the traditional job to be done that marketers right now own.

And that's, by the way, that's not unique to marketing.