Data Correlation. Behavioral Predictions.

Something early on, when we first started, before we joined, we were kind of talking, and I forget what the exact thing was, but it was something about a Prius and avocados.

I remember

that.

And it was

like all avocado lovers don't necessarily like Priuses, but all Prius drivers love avocados.

It was like something like...

And it got me kind of thinking as far as like, that is... that is a means to circumventing the reliance on on behavioral data right and everything we get is behavior or behavioral data in platform in crms in web analytics it's all like what happened right but it's not necessarily the cause right or or understanding why something didn't happen Um, so like that, that initial unlock and the use of AI, when Chris started to talk about, it doesn't, we don't need to know it was Michael, right? We can look at Michael and how he speaks and how he reviews things and and understand a profile and then match similar profiles.

And that was kind of the unlock for me as far as it goes to put it, how can we get it into a tool was because so much of our effort is on the 3%, right? The 3% of people that click, the 3% of people that open, the 3% of people that transact, right? And the 97% is still a black box.

And it's a lot easier for us to say, oh, they just weren't interested or they weren't the right customer or whatever it may be.

But they may

be, right? And there's a lot more opportunity there while the world is only focused on getting a better ROAS from that 3%, right? Optimizing against that 3%, recreating lookalikes from that 3%.

So the tool was essentially built to be able to look at a lot of data at once, right? A broader population, a broader audience size, and basically recreate who an audience should be based off of their personality traits, not just their sort of demographic patterns.

And that's been sort of the seed, right, which then allows us to message differently, engage with, you know, segments differently, come up with messaging and things that are more personalized.

You guys have obviously had access to the tool.

You guys have seen some of the work that the general have been doing.

I guess from your perspective, how does a tool like this impact some of the work that you've been doing traditionally? And what is the benefit that you see in understanding the data at a deeper level, understanding any gaps that there might be? And how does that kind of change your focus moving forward, I guess?

Something early on, when we first started, before we joined, we were kind of talking, and I forget what the exact thing was, but it was something about a Prius and avocados.

I remember

that.

And it was

like all avocado lovers don't necessarily like Priuses, but all Prius drivers love avocados.

It was like something like...

And it got me kind of thinking as far as like, that is... that is a means to circumventing the reliance on on behavioral data right and everything we get is behavior or behavioral data in platform in crms in web analytics it's all like what happened right but it's not necessarily the cause right or or understanding why something didn't happen Um, so like that, that initial unlock and the use of AI, when Chris started to talk about, it doesn't, we don't need to know it was Michael, right? We can look at Michael and how he speaks and how he reviews things and and understand a profile and then match similar profiles.

And that was kind of the unlock for me as far as it goes to put it, how can we get it into a tool was because so much of our effort is on the 3%, right? The 3% of people that click, the 3% of people that open, the 3% of people that transact, right? And the 97% is still a black box.

And it's a lot easier for us to say, oh, they just weren't interested or they weren't the right customer or whatever it may be.

But they may

be, right? And there's a lot more opportunity there while the world is only focused on getting a better ROAS from that 3%, right? Optimizing against that 3%, recreating lookalikes from that 3%.

So the tool was essentially built to be able to look at a lot of data at once, right? A broader population, a broader audience size, and basically recreate who an audience should be based off of their personality traits, not just their sort of demographic patterns.

And that's been sort of the seed, right, which then allows us to message differently, engage with, you know, segments differently, come up with messaging and things that are more personalized.

You guys have obviously had access to the tool.

You guys have seen some of the work that the general have been doing.

I guess from your perspective, how does a tool like this impact some of the work that you've been doing traditionally? And what is the benefit that you see in understanding the data at a deeper level, understanding any gaps that there might be? And how does that kind of change your focus moving forward, I guess?