Nir Weingarten

And you let them learn by experience what rewards them and whatnot, what's tasty and what's not.

And to complete the analogy, we can say that we can train an AI model

to try out different creative concepts or different content or different messaging, different creative intents, and learn by how actually people click on that or buy from that what's engaging for these audiences.

So we are replacing the baby with a neural net that generates content, and we're replacing the taste buds with counting clicks and revenue.

And so that's the concept.

I think it's pretty, pretty intuitive.

And, and I think that a lot of marketers, you know, the first thing we ask and we, we, we talk with really hundreds of marketers and we ask them if they AB test.

Did you ever AB test something, Brian?

Absolutely.

And how did that work for you?

Great.

And would you say you A-B tested enough or did you want to do more A-B testing?

That's the answer we keep hearing across the board.

I never, never heard otherwise.

And when you ask people why, they tell you, well, we don't, we just don't have the time.

It doesn't scale.

And it was very effective when we did that.

And you remember the sale two years ago and we try, but we never do enough like we want to.

And then we say, okay, so this is a very big problem.

Now we're going to create scalable A-B testing.