But then if you want to actually... have like designed the structure of the experimentation and like closely adjust each variable then weevie is like a good way to like have a lot more control with the workflow that's that's a good tip you have some interesting frameworks here

my version of this would be a little bit more granular which is kind of message plus media plus content type times funnel equals audience yes creative does your targeting but i think it's worth thinking about kind of the top level variables that go into that so one it's message because message will determine your kind of psychographics and kind of the the audience you're targeting from a messaging perspective so if we talk about anxious attachment or we talk about overthinking or we talk about Any other pain point that people identify with and feel like, okay, I'm experiencing this, that's going to end up targeting completely different audiences and purely based on kind of the words you say in that message.

And that's a big, big kind of way to scale.

If you find out, well, what are all these pain points we can tackle with our product? The other part is media.

So just by whether it's a static or it's a video that will determine where this ad is running because they have native placements in Facebook's ecosystem.

On that placement, there's going to be different audience.

Older people tend to use Facebook.

But of course, other way is always

Yeah

... an interesting one where, like, older or, like, newer devices and OSs tend to convert better.

Um, age, as we already said.

So you can get really smart over time, and there is, like, companies like Day30, Journey, um, those signal engineering providers that help you basically look across all of your data points and, like, find out, well, if we cut these 40%, how much higher would all track conversion be? Um, and that definitely gets very interesting as you scale because as said, AI is taking over more and more, so really creative and signal are the two main things you can be working on.

There is some work to be done with account architecture, as we just said, but then other than that, it's not like you're gonna set up 50 ad sets, some targeting male and female in different age groups as you used to back in the days.

Um, so definitely signal is one of the levers that you can still be pulling.

The algorithm knows very little about what makes your business profitable in the end because you're optimizing for that shallow event.

Can you set, um, different CPA goals per placement? Or are you saying post the fact, do your analysis, and try to break down by placement?