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Speaker 1: What's up. I'm Laura Currency and I'm Alexa Kristen. Welcome

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Speaker 1: back everyone. We've got two great guests on the show.

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Speaker 1: Kern Shearson, chairman and CEO of Known, and Ross Martin,

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Speaker 1: President and Chief Experience Officer of Known. So, Laura, we've

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Speaker 1: never actually talked to, and I don't know if there

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Speaker 1: is an agency or a modern marketing company that exists

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Speaker 1: today that is truly equal parts data, strategy, and creative.

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Speaker 1: We've had holding companies by data companies, We've had data

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Speaker 1: analytics companies by creative agencies, and they've become kind of

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Speaker 1: tacked on in parts of a whole. But really what

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Speaker 1: Known is doing is they've taken those three components that

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Speaker 1: are equal experts and truly created one agency that works

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Speaker 1: together on equal parts to create and bring the best

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Speaker 1: creative work and the best kind of need based marketing

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Speaker 1: to their clients and their consumers. Yeah, Alex, I think

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Speaker 1: it's an interesting business model that Ross and Kerner after

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Speaker 1: in bringing data and creativity to the center together. And

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Speaker 1: I think coming into the conversation with Ross and Kern

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Speaker 1: was really kind of posing a question or or had

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Speaker 1: a question of well, who wins in a tiebreaker and

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Speaker 1: you're actually going to hear this in the show. Does

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Speaker 1: does data lead or does creativity lead? And even as

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Speaker 1: I think over the last few episodes, we've had this

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Speaker 1: sort of tension of well, is it numbers or is

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Speaker 1: it gut? I think it's interesting to think about this

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Speaker 1: as you listen to the conversation is this an ant

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Speaker 1: or is this an oor situation? And I think this converse,

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Speaker 1: Asian has been one that the industry has been having

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Speaker 1: for years now, and we've been having on this show

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Speaker 1: for for three seasons, yeah, and the last ten fifteen years.

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Speaker 1: And I think that Ross and Kern are onto something

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Speaker 1: that is different, the details of which and the nuance

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Speaker 1: of which comes through in this conversation. So with that,

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Speaker 1: we'll be right back. We are back at Landia with

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Speaker 1: exciting partners from yield Mo. We are here with Lisa

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Speaker 1: Bradner GM of Analytics and Teddy John d E, head

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Speaker 1: of Product. So we're here to talk with Lisa and

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Speaker 1: Teddy about making attention actionable over the next four episodes

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Speaker 1: of Atlantia. Let's start from the top. What is yield Mo.

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Speaker 1: Yield Mo is a next generation marketplace powered by attention

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Speaker 1: analytics superior formats and real time data. So Lisa would

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Speaker 1: love for you to expand on what yield mo does

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Speaker 1: and share with our listeners how yield mo thinks about

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Speaker 1: and approaches the market. Well, I think you have to

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Speaker 1: start with you know the vision everybody has for advertising, right,

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Speaker 1: we have this perfect vision. We're advertising flows like water.

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Speaker 1: The right people see your ad, they get the right creative,

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Speaker 1: they're inspired, they go by your product. Every impression is

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Speaker 1: valuable and it just flows right. Doesn't quite work like that,

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Speaker 1: never has, But I think you know Programmatic. When that launched,

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Speaker 1: we were really trying to say, how do we connect

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Speaker 1: this ecosystem and make everything flow? With programmatic, We've spent

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Speaker 1: all the time talking about the pipes, like it's so cool.

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Speaker 1: We can deliver a lot more impressions, a lot faster,

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Speaker 1: we can reach your entire audience. But you know what,

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Speaker 1: if you're put in sewage in those pipes, you've just

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Speaker 1: wasted a whole lot of money really really quickly. So

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Speaker 1: I like to step back and say, all right, great,

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Speaker 1: we've built the infrastructure, we're great blumber, but let's talk

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Speaker 1: about what we're putting through those pipes. Let's make sure

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Speaker 1: it's quality. Let's make sure it's clean, let's make sure

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Speaker 1: everybody knows that it's fraud free and can be trusted,

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Speaker 1: and let's make sure we're not poisoning our own ecosystem.

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Speaker 1: What do you when you talk about quality? I think

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Speaker 1: that's such an interesting part of the conversation. Quality is

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Speaker 1: a great question. Right. As an industry, we've been sort

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Speaker 1: of stuck in lowest common denominator. Right, we talked about viewability,

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Speaker 1: and we talk about fraud free or you were seen

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Speaker 1: by a human not a box. But if you even

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Speaker 1: look into the definition of view ability, it is a really,

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Speaker 1: really really split second of moment where it's on the page.

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Speaker 1: It's not exactly something I think that any brand person

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Speaker 1: would say, Yeah, my brand showed up great. But it's

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Speaker 1: a place to start, and it was a common denominator

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Speaker 1: we could all rally around. But the reason we look

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Speaker 1: at attention at yield mode in addition to those signals

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Speaker 1: is we want to go a layer deeper to say,

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Speaker 1: all right, we know it was seen by a human being,

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Speaker 1: we know it was on the screen, and how long

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Speaker 1: did they care, were they interested? Did they signal that

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Speaker 1: to them it was a quality? Add experience and something

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Speaker 1: they wanted to engage further in. And the better job

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Speaker 1: we can do of matching the person, the device, the impression,

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Speaker 1: the time, and the creative the higher quality that add

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Speaker 1: experience is going to be for everybody. So how is

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Speaker 1: yield MO helping the industry navigate the pipes? We have

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Speaker 1: a marketplace with highly curated, high quality inventory, but it's

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Speaker 1: not a walled garden, right, anybody can play and the

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Speaker 1: data goes in, the data goes out. We are working

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Speaker 1: across the ecosystem to find the highest quality inventory, bring

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Speaker 1: our formats and our data to that and create a

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Speaker 1: really really great brand experience that's good for the user

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Speaker 1: tou that's in the context of what they're looking at,

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Speaker 1: and bring all that together to make sure that we're

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Speaker 1: delivering quality experiences and that the money we're spending is

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Speaker 1: going to quality publishers. Teddy, what are your thoughts on

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Speaker 1: AD experiences? Those two words actually don't typically go together,

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Speaker 1: but the meaning when you put those words together around

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Speaker 1: actually creating an AD experience that someone wants and potentially

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Speaker 1: even anticipated right or needed, I think actually does create

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Speaker 1: an experience. How are you guys thinking about that? Well,

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Speaker 1: that's the idea behind quality advertising is can you deliver

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Speaker 1: an ad experience to a user that actually influences and

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Speaker 1: allows them to make a brand decision. And that's what

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Speaker 1: we try to do it. You'll most we try to

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Speaker 1: You know, there's a great technology out there. You can

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Speaker 1: buy ads and serve them anywhere, but what is actually

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Speaker 1: making an impact? And we focus on trying to allow

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Speaker 1: marketers to seed at with with our investment and attention

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Speaker 1: and so they can quickly decide, well, this is working

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Speaker 1: and this isn't You do you both talk about the

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Speaker 1: kind of green spaces, what i'll call green shoots. Are

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Speaker 1: you working with brands do you identify through these different

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Speaker 1: ad experiences new white spaces and green shoot areas for

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Speaker 1: their products for audience development? And if so, how are

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Speaker 1: you thinking about that? I love this notion of green shoots. Right.

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Speaker 1: I've always said when you work in marketing, you're always dating,

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Speaker 1: You're never married. Right. Every time you show up it's

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Speaker 1: a chance to impress your customer and you never get

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Speaker 1: to hang out in the catch and sweatpants. Right, It's

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Speaker 1: like you've got to prove yourself every day. But you know,

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Speaker 1: I think that if you think about those fast moving

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Speaker 1: media metrics. If you can be really agile with the

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Speaker 1: ad experience and when with the data, you can recognize

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Speaker 1: when a green shoot is happening. And I think as marketers,

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Speaker 1: we've always gone top down, right, here are my segments,

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Speaker 1: here are the people I'm talking to. But you know,

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Speaker 1: we saw this in the pandemic. People who hadn't bought

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Speaker 1: certain brands in twenty years all of a sudden ripped

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Speaker 1: them off the shelf. So as a brand person, you've

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Speaker 1: always have to be listening for that surprise signal that

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Speaker 1: signals an opportunity you may not be thinking about. And

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Speaker 1: our agile data structure allows our brands to work with

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Speaker 1: us to do just that. Lisa Bradner, Teddy Jwadi from

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Speaker 1: yield Mo, thank you for being our partners, Thank you

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Speaker 1: for coming on at Landia, Thank you for having us,

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Speaker 1: and we are back at Landia. Welcoming back to guests.

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Speaker 1: Curren Jeerson, Chairman and CEO of Known, and Ross Martin,

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Speaker 1: president and Chief Experience Officer of Known, Welcome, guys, welcome,

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Speaker 1: thank you great to be here, so good. So the

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Speaker 1: first question everyone wants to know is what is known?

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Speaker 1: Known came together out of three? Really? Uh, leaving companies.

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Speaker 1: Company I found it almost twenty years ago is a

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Speaker 1: data science and advanced analytics company me UM. It's called

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Speaker 1: it was called Cheerson Associates, which is my last name.

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Speaker 1: So you can see I was not on the creative side.

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Speaker 1: You don't you don't want to hire me for naming.

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Speaker 1: I think I added the associates so people would think

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Speaker 1: I had associates. But that was about his That was

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Speaker 1: about as creative as a god. But this was a

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Speaker 1: company that was doing data science before it was called

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Speaker 1: data science. For a lot of the big tech companies

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Speaker 1: are our clients for twenty years, like Google and Microsoft

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Speaker 1: and Amazon. UM. So tons of PhDs and just number

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Speaker 1: crunctures and the other components come out of the brilliant

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Speaker 1: creative mind and strategic mind of Ross Martin, who ran

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Speaker 1: a company called Blackbird that I think somehow he must

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Speaker 1: have been strategic because he got you guys to talk

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Speaker 1: about it well two years ago. He was with us

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Speaker 1: two years ago talking about Blackbird. Let him back in.

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Speaker 1: I want him back in. I want current to continue

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Speaker 1: talking about knowing. But I will just stop for one

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Speaker 1: second for an ad for Atlanta to say when I

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Speaker 1: was originally on your podcast. I think I got seventeen calls,

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Speaker 1: so I think I owe you a chunk of cash.

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Speaker 1: And anybody ever, anybody who ever shows up on this podcast,

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Speaker 1: if you make it this far, you're good. Like Malcolm Gladwell, congratulations,

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Speaker 1: you have now made it and you have a chance

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Speaker 1: at the same kind of career that I have had

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Speaker 1: over the last few years. Because I was on this

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Speaker 1: and they add, you were the first guest to do

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Speaker 1: live poetry on Atlantia. So Kern, I hear that you

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Speaker 1: may try to want I may, I may so fastinuing

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Speaker 1: with known U, the third component of this, the third heat,

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Speaker 1: if you will, came out of a group called Stunt Creative,

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Speaker 1: which is really a best in class creative and production

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Speaker 1: studio at l A. Again you know, twenty years in

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Speaker 1: the business, won every award on the planet, and the

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Speaker 1: unifying belief that brought us together was this idea that

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Speaker 1: art and science needed to live together in a real way,

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Speaker 1: not in a big box consultancy buys global creative agency way,

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Speaker 1: and um, you know, we felt like there was a

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Speaker 1: place for these capabilities to sit around the table as equals,

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Speaker 1: as friends, as partners, um, where everybody had a superpower,

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Speaker 1: but we all wanted to work together to create the

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Speaker 1: right outcome for our clients. So kar and put that

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Speaker 1: into practice, right because you're doing a tremendous amount of

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Speaker 1: work with TikTok right now seeing some of the work

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Speaker 1: you're doing with the A n A around see her.

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Speaker 1: So if you look at the spectrum of work that

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Speaker 1: you have, the body of work that's out in the market,

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Speaker 1: when you bring together those three pillars data, strategy, creativity,

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Speaker 1: how is that manifesting? It's a great question, um So,

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Speaker 1: So I think the the process. You know, what you

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Speaker 1: see is creative, and what you see is creative that

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Speaker 1: you hopefully remember, um And that really is evocative, and

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Speaker 1: that is hitting you in a place and at a

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Speaker 1: time that makes sense, right, and that that those other

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Speaker 1: aspects are not what people remember, but they're part of

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Speaker 1: our process. So the place we like to start is

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Speaker 1: with the fundamental questions. And this goes back to the name.

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Speaker 1: You know, like we wouldn't be in the marketing and

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Speaker 1: advertising industry if we hadn't a long and hired about

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Speaker 1: the seven different meanings of our name. But that you know,

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Speaker 1: the first question is like what know yourself as a brand? Right, Well,

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Speaker 1: what do you stand for? What do you mean in

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Speaker 1: the world? Know your customers? Uh, why do they care

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Speaker 1: about you? What do they think, feel and believe about you?

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Speaker 1: And what do they need to know to understand whether

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Speaker 1: or not you fit into their life? And then how

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Speaker 1: do you make that know? How do you bring that

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Speaker 1: to life insights out, emotion and in a way that

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Speaker 1: it creates a real emotional fonts and though that that

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Speaker 1: is the process. So like when we sit down, whether

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Speaker 1: it's with a client, TikTok or see her or vivent

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Speaker 1: or any of these or memorial sunkettering, right, it's those

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Speaker 1: questions in that order. Um, what is this brand, what's

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Speaker 1: happening to it? How does it exist in the world,

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Speaker 1: How do we find the right audiences, how do we

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Speaker 1: connect with them in the times and places and ways

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Speaker 1: that makes sense? How do we bring that into being

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Speaker 1: in a way that's beautiful and evocative and and it's

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Speaker 1: great you know that people see our creative on the

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Speaker 1: world and remember it. But the process that gets it

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Speaker 1: there is really what we think drives a lot of

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Speaker 1: the impact for our clients because we're not wasting impressions,

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Speaker 1: we're not wasting the audience's time. So that's that's sort

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Speaker 1: of the science side that's harder to see and touch,

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Speaker 1: but is really part of why we think this stuff

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Speaker 1: works so hard for our clients. So ross last time

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Speaker 1: you were on the show, UM, we were talking all

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Speaker 1: things Blackbird. How did Blackbird come to work with Current?

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Speaker 1: So Blackbird came to work with Kern and also with

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Speaker 1: Jeff Kingsley, who is the chief operating officer of Sheerson

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Speaker 1: came to work with Brad Roth and Mark Feldstein from

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Speaker 1: Stun because back in the day by Coom, when I

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Speaker 1: was running marketing, UM, I was their clients. Sheerson Associates

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Speaker 1: and Stun were like my secret weapons, and so I

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Speaker 1: knew very well what those two companies were capable of

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Speaker 1: and how fantastic they were they you know, even if

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Speaker 1: other people didn't know that yet. UM, and I was

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Speaker 1: making a living on the work they were doing. Um.

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Speaker 1: The truth is Blackbirds, as you know, it was going well.

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Speaker 1: It was two two and a half years old, and

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Speaker 1: I loved it. But every once in a while, or

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Speaker 1: like once in your lifetime, there's a generational opportunity to

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Speaker 1: do something really unique. And special, not just disruptive, but

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Speaker 1: game changing. So the hypothesis of known represented a generational opportunity.

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Speaker 1: If what we believe to be true UM and possible

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Speaker 1: could actually be achieved, then this this wouldn't be sort

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Speaker 1: of just a good business opportunity, but it would be

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Speaker 1: a game changing UM I guess inflection point for how

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Speaker 1: marketing gets done in the twenty one century. And I

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Speaker 1: know it sounds like I'm vastly overstating that, and maybe

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Speaker 1: I'm a couple of years ahead of other people getting

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Speaker 1: what we're trying to do, and it probably sounds a

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Speaker 1: little arrogant, But in the beginning, we weren't sure, right,

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Speaker 1: So we put these companies together and we started to

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Speaker 1: try to go to market together as a unified set

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Speaker 1: of capabilities. And think of it almost like as a

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Speaker 1: moment of Pangaea where the continents come back together on Earth,

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Speaker 1: when the marketing capabilities and advertising capabilities that never should

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Speaker 1: have been separated are actually unified and there's no fidelity

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Speaker 1: loss between them. When that happens, you actually returned to

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Speaker 1: being UM. Not is efficient and effective and transparent, but

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Speaker 1: you can actually align the goals of your company with

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Speaker 1: the business interests of your clients. And when you can

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Speaker 1: do that, then you provide the first meaningful alternative to

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Speaker 1: the holding company model in a long long time. That's

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Speaker 1: the opportunity that I saw. That's the opportunity that we saw,

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Speaker 1: And more importantly, it's it's the opportunity that dozens of

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Speaker 1: clients saw and and and really pulled us together um

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Speaker 1: to provide a comprehensive set of marketing services for them.

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Speaker 1: So a lot of holding companies would say the same thing,

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Speaker 1: what is setting known apart? What I think is setting

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Speaker 1: us apart is truly best in class in every discipline.

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Speaker 1: Right In some cases, and I was kind of joking

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Speaker 1: about it before, you've got companies that are pretty good

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Speaker 1: at data and analytics and process and technology trying to

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Speaker 1: glue on creative capability. And now you know exactly how

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Speaker 1: that relationship works. You know who is the step child

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Speaker 1: of who, and who drives? You know who's got the

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Speaker 1: bigger revenue line and what bread is butter were right,

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Speaker 1: like we all know, um. And in other cases, you've

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Speaker 1: got a creative shop or a traditional media buying company

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Speaker 1: hiring a couple of people who maybe have an undergrad

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Speaker 1: degree in math or economics and no a little are

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Speaker 1: or sequel and they're like, no, we have data capabilities,

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Speaker 1: or even buying a data company, which by the way,

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Speaker 1: is like the most ridiculous thing for supposedly impartial agency

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Speaker 1: to be doing. But leaving that to the side for

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Speaker 1: a second, what we thought was exciting about this in

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Speaker 1: kind of the cultural synergy that led up to this

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Speaker 1: combination was not just the thesis, not just the business opportunity,

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Speaker 1: but the cultural synergies and the fact that currently the

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Speaker 1: top creative director at Known Studios won't stop calling our

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Speaker 1: chief technology officer to talk about you know, non stochastic

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Speaker 1: modeling and like creative optimization. It's like, that's happening, that's

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Speaker 1: actually happening because the creative team is totally gigging out

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Speaker 1: on the data. The data scientists, and you know, this

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Speaker 1: is also a real, a real different thing. We've got

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Speaker 1: like postdoctoral PhD data scientists, like actual data scientists who

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Speaker 1: extend the analytics capability of clients like Amazon and Microsoft

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Speaker 1: and Google when they're not working on our advertising clients.

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Speaker 1: And that's that's not that's not even in the realm

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Speaker 1: of firepower at these other agencies and our creatives who

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Speaker 1: are making these moments that break culture are also best

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Speaker 1: in class and they love each other. And our strategists

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Speaker 1: are sitting there in the middle of it saying, I

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Speaker 1: cannot believe like the weapons that we get to deploy

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Speaker 1: both on the inbound customer insight and the creation of

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Speaker 1: breakthrough storytelling. So who gets the tiebreaker in data versus gut? Well,

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Speaker 1: there there isn't one. That's not a that's not like

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Speaker 1: it's that's just not the process that we run. The

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Speaker 1: like they're not at odds with each other. What happens

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Speaker 1: is are creative and strategy teams have brilliant ideas, and

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Speaker 1: as often happens in creative ideation and all the sort

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Speaker 1: of like work that leads up to an incredible campaign

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Speaker 1: is there are a bunch of things that people love.

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Speaker 1: And then there's like that final round of tweaking and

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Speaker 1: tuning of like do we alpha this up or down?

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Speaker 1: Like what's the color mix? How big is the like

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Speaker 1: how much do we pull into the foreground background? Like

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Speaker 1: what you know where? Like how tight is the focus

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Speaker 1: those things? It turns out you don't have to guess,

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Speaker 1: So the gut is all there like that you see

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Speaker 1: the heart I would think in our TikTok campaigns, you

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Speaker 1: see the heart and see her. You see the heart

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Speaker 1: in what everything our studios turns out, and like the

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Speaker 1: creative minds at work there, like that's real, that wasn't

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Speaker 1: computer generated. And then the question is of all the

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Speaker 1: thousands of different perspectives and backgrounds and sort of the

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Speaker 1: constellation of audience out there. Each person is a little

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Speaker 1: bit different, each platform is a little bit different. So

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Speaker 1: how do I match the absolute best version of the

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Speaker 1: creative to the right individual audience member based on everything

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Speaker 1: I can into it about them in the right place,

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Speaker 1: at the right time, in the right format, on the

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Speaker 1: right platform. That's where data takes creative and like beautiful creative, evocative,

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Speaker 1: creative and supercharges it. And that's where we see the

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Speaker 1: results going absolutely crazy. I want to go back to

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Speaker 1: something that you said that I think is probably if

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Speaker 1: we don't go back to his probably passed over pretty easily.

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Speaker 1: You have twenty five pH d data scientists and analytics

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Speaker 1: folks working with Amazon, Google, Microsoft, not on marketing creative.

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Speaker 1: We have about seventy analytics people working outside of the

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Speaker 1: marketing space. I'm just talking about like the what I

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Speaker 1: was trying to say, is of the of the advanced

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Speaker 1: degrees working in advertising? These are not people when we like,

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Speaker 1: you see listings out there and tors when we're not

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Speaker 1: trying to you see listings out there for you know,

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Speaker 1: data scientists or advertising analysts, and they'll say things like,

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Speaker 1: you know, Excel skills are a must. Excel skills are

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Speaker 1: not a must, right like they're there there. There are

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Speaker 1: profoundly more powerful tools. And so when we when when

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Speaker 1: we list a position for a data scientists, that's a

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Speaker 1: person who's coming out of uh typically like a postdoctoral

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Speaker 1: fellowship up at a leading academic institution, and you know,

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Speaker 1: the folks on that team talk about sort of rehabilitating

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Speaker 1: academics and and helping them find these new careers, you know,

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Speaker 1: from physics finding looking searching for the ghost particle in

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Speaker 1: in mild cubic mild blocks of Arctic ice, to trying

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Speaker 1: to identify audience signals in social and and digital environments.

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Speaker 1: And our strategy and our analytics and data science teams

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Speaker 1: are beating out their pure play competitors with clients like

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Speaker 1: Google and Amazon and Facebook. Can you double down on

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Speaker 1: the seamlessness of your data scientists talking to your creative leads.

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Speaker 1: Is that appairing that we need to see more of

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Speaker 1: in the market. I think it's the thing that UM, I,

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Speaker 1: at the end of the day get most excited about

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Speaker 1: in our business. And in this sort of crazy concoction

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Speaker 1: that that we're delivering, that's what really he got us there,

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Speaker 1: That's what got us to the point of saying, we

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Speaker 1: all have great businesses. Can you give us an example

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Speaker 1: where like you were in a creative pitch and you

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Speaker 1: you brought out data scientists and it was like, at

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Speaker 1: that point, completely unexpected for the narrative of what I'm

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Speaker 1: assuming brand marketers typically here in a creative pitch. Yeah, look,

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Speaker 1: it happens all the time. We were I don't want

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Speaker 1: to name the client, but we were working on a

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Speaker 1: pretty important campaign that started with a deep dive into

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Speaker 1: some micro segmentation, and um what we found in the

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Speaker 1: micro segmentation and the attributes and you've got a data

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Speaker 1: scientists sort of walking through like these are the drive

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Speaker 1: this is the driver model of you know, who is

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Speaker 1: likely to be persuadable of outcome air B or c

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Speaker 1: um and And what we realized in that was that

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Speaker 1: the the creative that the client wanted was something that

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Speaker 1: was really sort of edgy and sharp and fresh, and

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Speaker 1: what and what the audience wanted was to be spoken

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Speaker 1: to an authentic way about values, right like, and you

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Speaker 1: could see it and it just like it spun the

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Speaker 1: creative ideation around, not because that not because it's not

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Speaker 1: like not because they were being lectured by the data scientists,

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Speaker 1: but because they were discovering it together, because the data

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Speaker 1: scientist was surfacing a constellation of attributes and the creatives

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Speaker 1: were saying, hold on, that's not what was That's not

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Speaker 1: what was in the brief at all, Like what you're

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Speaker 1: telling me? And am I understanding this? Right? Like if

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Speaker 1: you're saying that it's suburban zip codes and it's you know,

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Speaker 1: non Apple devices and it's you know, these kinds of demos,

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Speaker 1: like that's not what they're asking for. Why are we

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Speaker 1: doing that? And like you could just feel this this

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Speaker 1: momentum building and jelling around a different vision of the

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Speaker 1: opportunity and and the arc of the story that needed

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Speaker 1: to be told for this brand that wasn't gonna get

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Speaker 1: told But wasn't. It wasn't a research report that was

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Speaker 1: plopped down on a desk, right it was it was

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Speaker 1: a live collaboration and and by the way, that goes

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Speaker 1: in both directions, you know, and I've seen creative teams

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Speaker 1: working through a pitch and coming back to the scientists

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Speaker 1: and saying like, can we test this? Does this feel right? Like?

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Speaker 1: How would we start to focus into signals and social

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Speaker 1: media to understand if I've got the right phrasing here,

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Speaker 1: the right meme, the right kind of moment and culture

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Speaker 1: like is this what it needs to be? Or should

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Speaker 1: I look over here? Because I can't. I'm weighing these

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Speaker 1: two options. And so sometimes it's the refinement. Sometimes it's

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Speaker 1: a kind of a revelation. And then I think what

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Speaker 1: happens after the fact. We look at the performance of

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Speaker 1: all these campaigns, even if their brand campaigns. We're running

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Speaker 1: five seconds snapshots of every exposure that happened in every

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Speaker 1: five seconds, and what are all of the what's all

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Speaker 1: the metadata around that? How do we understand that atomic

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Speaker 1: intersection of creative an audience and every day the path

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Speaker 1: and matching that happens, which is a collaborative process between

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Speaker 1: the creatives and the data scientists together reviewing these five

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Speaker 1: second snapshots and reviewing these sort of patterns and trends

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Speaker 1: that are coming out leads to a re racking of

431
00:26:14,920 --> 00:26:19,720
Speaker 1: some of the really hyper specific nuances of the creative

432
00:26:19,760 --> 00:26:22,199
Speaker 1: as it's happening in each platform and each subsegment. So

433
00:26:22,200 --> 00:26:24,399
Speaker 1: they're like, okay, all right, we gotta swap out that

434
00:26:24,520 --> 00:26:26,800
Speaker 1: art because like it's definitely like that stuff is not

435
00:26:26,920 --> 00:26:31,560
Speaker 1: working on Facebook. It's working great on you know, on

436
00:26:31,600 --> 00:26:34,479
Speaker 1: digital display, but we got like and for search, I

437
00:26:34,520 --> 00:26:36,920
Speaker 1: feel like this copy right here, let's change that one

438
00:26:37,359 --> 00:26:40,120
Speaker 1: word like And then the brainstorming happening with the data

439
00:26:40,160 --> 00:26:42,680
Speaker 1: scientists and the creatives at once, saying why that word,

440
00:26:42,720 --> 00:26:44,000
Speaker 1: what do we think it could be? What do we

441
00:26:44,000 --> 00:26:46,919
Speaker 1: think like what is working in other parallel platforms, and

442
00:26:46,960 --> 00:26:49,200
Speaker 1: you know what, like we literally had a moment. We're

443
00:26:49,240 --> 00:26:53,199
Speaker 1: swapping out a single word in digital display, drove the

444
00:26:53,240 --> 00:26:59,480
Speaker 1: results of that ad by one word. What you're seeing

445
00:27:00,680 --> 00:27:04,440
Speaker 1: is really exciting to me, and it's actually very different.

446
00:27:05,400 --> 00:27:11,000
Speaker 1: So what people aren't doing. People aren't actually going off

447
00:27:11,119 --> 00:27:16,080
Speaker 1: of their web metrics or their basic campaign metrics, or

448
00:27:16,280 --> 00:27:21,440
Speaker 1: they've got isolated first party data and analytics. What you're

449
00:27:21,480 --> 00:27:24,879
Speaker 1: doing because you're talking about the whole thing and the

450
00:27:25,040 --> 00:27:28,520
Speaker 1: right stuff at the right time and that's easy to say,

451
00:27:28,600 --> 00:27:31,439
Speaker 1: but lots of folks when they're talking about data and analytics,

452
00:27:31,720 --> 00:27:35,280
Speaker 1: they're talking about campaign metrics. And something we talked about

453
00:27:35,640 --> 00:27:41,480
Speaker 1: was the hypothesis that more brands, more companies, more marketers

454
00:27:42,080 --> 00:27:48,400
Speaker 1: need to build a multi layer hypothesis hypotheses and run them.

455
00:27:48,680 --> 00:27:52,400
Speaker 1: That's exactly right. The campaign is the beginning right day.

456
00:27:52,440 --> 00:27:55,120
Speaker 1: What if you were to ask me, uh, the night

457
00:27:55,160 --> 00:27:59,360
Speaker 1: before a big campaign launches, like, is this gonna work tomorrow?

458
00:28:00,000 --> 00:28:02,080
Speaker 1: I'll say, I don't know if it's going to work

459
00:28:02,080 --> 00:28:04,440
Speaker 1: tomorrow morning, but I think it has a better chance

460
00:28:04,480 --> 00:28:07,160
Speaker 1: of working by mid day or later in the day

461
00:28:07,240 --> 00:28:09,439
Speaker 1: because of what we learned in the morning, right Like,

462
00:28:09,680 --> 00:28:13,439
Speaker 1: the very beginning of a persistent optimization loop is the

463
00:28:13,480 --> 00:28:16,400
Speaker 1: most exciting time because what you're doing is treating everything

464
00:28:16,440 --> 00:28:18,920
Speaker 1: that's going out in the world as a social experiment

465
00:28:19,320 --> 00:28:22,040
Speaker 1: that you get to learn from. And the more quickly

466
00:28:22,080 --> 00:28:25,760
Speaker 1: you can metabolize that information and act on those insights

467
00:28:26,320 --> 00:28:29,800
Speaker 1: with the help of machine learning and an AI, the

468
00:28:29,840 --> 00:28:33,600
Speaker 1: more quickly you can optimize. Whether it's the creative, the channel,

469
00:28:33,720 --> 00:28:38,160
Speaker 1: the time, the messaging, the copy itself, the beating algorithm,

470
00:28:38,240 --> 00:28:42,120
Speaker 1: it's all of those. That's why we say, for a

471
00:28:42,160 --> 00:28:45,200
Speaker 1: campaign like the one we are about the launch on Sunday,

472
00:28:45,280 --> 00:28:48,080
Speaker 1: if you were looking from our control room, you'd see

473
00:28:48,120 --> 00:28:51,240
Speaker 1: ten to twenty permutations going out at the same time,

474
00:28:51,920 --> 00:28:53,520
Speaker 1: and we're gonna learn a lot from each one of

475
00:28:53,560 --> 00:28:55,200
Speaker 1: them in real time. Can you tell us about the

476
00:28:55,200 --> 00:28:58,600
Speaker 1: campaign that's going out Sunday. Yeah, So we took on

477
00:28:58,640 --> 00:29:01,080
Speaker 1: a new client where the Agency of Credit's Vivint, the

478
00:29:01,200 --> 00:29:05,760
Speaker 1: I V I n T Home security UH company, and

479
00:29:05,760 --> 00:29:08,600
Speaker 1: and it's a smart home company essentially, and you know

480
00:29:08,680 --> 00:29:12,120
Speaker 1: it's it's it's becoming a loud, noisy competitive space, especially

481
00:29:12,200 --> 00:29:15,040
Speaker 1: during the pandemic. This is a company that is hot

482
00:29:15,080 --> 00:29:18,760
Speaker 1: as hell, like they are performing incredibly well. It's a

483
00:29:18,800 --> 00:29:24,800
Speaker 1: publicly traded company, but current multi multibillion dollar company four

484
00:29:24,880 --> 00:29:27,640
Speaker 1: percent on aided awareness, right like just you just haven't

485
00:29:27,680 --> 00:29:29,520
Speaker 1: heard of it because it is loud, it's noisy out there.

486
00:29:29,560 --> 00:29:32,760
Speaker 1: But but that's about to change. And um, we've got

487
00:29:32,760 --> 00:29:36,400
Speaker 1: a really fun campaign or as Ross would say, campaigns

488
00:29:37,080 --> 00:29:39,600
Speaker 1: um that that's going to support them out there in

489
00:29:39,640 --> 00:29:41,240
Speaker 1: the world coming up with and there's gonna be some

490
00:29:41,320 --> 00:29:43,280
Speaker 1: time pole placements and I want to come back to

491
00:29:43,320 --> 00:29:45,960
Speaker 1: also like the art of this is not lost. The

492
00:29:46,000 --> 00:29:49,600
Speaker 1: core creative is super funny, you're gonna see it. And

493
00:29:49,640 --> 00:29:52,600
Speaker 1: what's the right sequencing of creative and how do you

494
00:29:52,720 --> 00:29:59,520
Speaker 1: move people from awareness to advocacy to intent? Right like that,

495
00:29:59,600 --> 00:30:02,800
Speaker 1: those things, like they're massive differences based on what they

496
00:30:02,800 --> 00:30:04,880
Speaker 1: see in what order, even if all the creatives great,

497
00:30:05,040 --> 00:30:07,880
Speaker 1: what what's what's really really interesting about this moment in

498
00:30:07,920 --> 00:30:11,760
Speaker 1: time for Adlandia fans, right because the marketing and advertising

499
00:30:11,800 --> 00:30:15,880
Speaker 1: community listens to this podcast religiously. Here's the thing, like

500
00:30:16,680 --> 00:30:21,200
Speaker 1: there we're sort of seeing a bifurcation in the CMO land, right,

501
00:30:21,480 --> 00:30:24,239
Speaker 1: Like there are cmos who are you know, are just

502
00:30:24,480 --> 00:30:27,320
Speaker 1: not ready for this stuff, Like they don't really need

503
00:30:27,400 --> 00:30:29,920
Speaker 1: to care that much and they're just sort of managing

504
00:30:30,960 --> 00:30:33,600
Speaker 1: as they did before. But there's a new breed of

505
00:30:33,640 --> 00:30:38,400
Speaker 1: cmos and marketing leadership. For example, you mentioned TikTok. We

506
00:30:38,520 --> 00:30:40,880
Speaker 1: couldn't do what we do if if they didn't have

507
00:30:41,040 --> 00:30:44,200
Speaker 1: Nick Trent in that seat leading that team, if they

508
00:30:44,240 --> 00:30:47,240
Speaker 1: didn't have a team that was just excited about the

509
00:30:47,240 --> 00:30:49,880
Speaker 1: marriage of art and science as we are. We couldn't

510
00:30:49,920 --> 00:30:53,160
Speaker 1: do it with just any client. And what's fantastic about

511
00:30:53,160 --> 00:30:55,040
Speaker 1: the clients that we've been able to assemble. It's not

512
00:30:55,120 --> 00:30:57,600
Speaker 1: that they're all big brand, awesome names, which many of

513
00:30:57,640 --> 00:31:01,360
Speaker 1: them are, but they are all of sort of the

514
00:31:01,400 --> 00:31:05,240
Speaker 1: future economy of marketing. These are all human beings who

515
00:31:05,360 --> 00:31:08,880
Speaker 1: understand everything we are talking about on this podcast right now,

516
00:31:09,320 --> 00:31:11,880
Speaker 1: and they do it. That's why the marketing flywheel can

517
00:31:11,920 --> 00:31:14,720
Speaker 1: actually happen. TikTok's a unique example because it's such a

518
00:31:14,720 --> 00:31:17,880
Speaker 1: gigantic global platform and there's so much happening to create

519
00:31:17,920 --> 00:31:20,840
Speaker 1: culture every minute, but the same can be sort of

520
00:31:21,040 --> 00:31:24,280
Speaker 1: done for so many brands and so many categories, and

521
00:31:24,400 --> 00:31:27,360
Speaker 1: one by one we're proving that. So talk a little

522
00:31:27,360 --> 00:31:30,720
Speaker 1: bit about data as it relates to strategy, because so

523
00:31:30,800 --> 00:31:32,680
Speaker 1: much of what we've seen in the headlines in our

524
00:31:32,720 --> 00:31:35,480
Speaker 1: industry is thinking about your tech stack, your data stack

525
00:31:35,760 --> 00:31:38,600
Speaker 1: as being means to find an audience, right when I

526
00:31:38,600 --> 00:31:41,680
Speaker 1: think about the world of programmatic and addressable, But very

527
00:31:41,800 --> 00:31:45,600
Speaker 1: rarely in this industry are we privy to the conversation

528
00:31:45,960 --> 00:31:49,680
Speaker 1: of data science as it relates to creative optimization in

529
00:31:49,840 --> 00:31:53,280
Speaker 1: the work, not the delivery of it in the work.

530
00:31:53,640 --> 00:31:55,800
Speaker 1: So it's a it's a great question because I think

531
00:31:55,840 --> 00:31:58,320
Speaker 1: the thing that's so often missed on the kind of

532
00:31:59,640 --> 00:32:05,160
Speaker 1: Apple location of data to advertising is this reality that

533
00:32:05,800 --> 00:32:10,959
Speaker 1: bad advertising and badly targeted advertising is paid for by

534
00:32:10,960 --> 00:32:14,160
Speaker 1: the audience. Right, that's just a tax that you had

535
00:32:14,200 --> 00:32:17,840
Speaker 1: to pay when they showed like Ross's kids are, you know,

536
00:32:18,440 --> 00:32:21,240
Speaker 1: junior high school in high school, when somebody shows him

537
00:32:21,240 --> 00:32:25,200
Speaker 1: a Pamper's ad that he pays for, that it didn't

538
00:32:25,240 --> 00:32:28,760
Speaker 1: fund the content he was watching and they wasted his time.

539
00:32:29,040 --> 00:32:32,479
Speaker 1: And so not showing Ross that Pampers at his service, um,

540
00:32:33,120 --> 00:32:35,800
Speaker 1: showing Ross an ad for a product that I thinks

541
00:32:35,960 --> 00:32:39,080
Speaker 1: unless you tell me otherwise, Showing Ross an ad for

542
00:32:39,120 --> 00:32:41,880
Speaker 1: a product that he's genuinely interested in in a category

543
00:32:41,960 --> 00:32:44,560
Speaker 1: that he's exploring. I'm not talking about retargeting, but like

544
00:32:44,600 --> 00:32:49,000
Speaker 1: that's intuitively applicable to Ross's life. That is informative, that

545
00:32:49,120 --> 00:32:53,120
Speaker 1: is funny, that is joyful, that's that's not a tax

546
00:32:53,200 --> 00:32:56,040
Speaker 1: on Ross's attention, that's additive to the experience. And so

547
00:32:56,440 --> 00:32:59,560
Speaker 1: what we try and do is stay in that zone.

548
00:32:59,600 --> 00:33:02,360
Speaker 1: And like I sometimes I do get excited as like

549
00:33:02,400 --> 00:33:06,000
Speaker 1: a nerd about you know, all the things we can

550
00:33:06,080 --> 00:33:08,280
Speaker 1: learn from all of the signal that's coming out of

551
00:33:08,280 --> 00:33:12,160
Speaker 1: our lives. I also I want to be really measured

552
00:33:12,800 --> 00:33:16,960
Speaker 1: as a human being about the question of how would

553
00:33:16,960 --> 00:33:20,360
Speaker 1: I feel about that the application of that whether or

554
00:33:20,400 --> 00:33:23,840
Speaker 1: not it's legally obtained, whether or not it's gdp R compliant, Like,

555
00:33:24,040 --> 00:33:26,720
Speaker 1: how would I feel about the application of that data

556
00:33:26,760 --> 00:33:31,000
Speaker 1: point to what's happening in my media consumption experience right now?

557
00:33:31,520 --> 00:33:33,520
Speaker 1: I hear you. I think that's awesome. I think you

558
00:33:33,520 --> 00:33:36,560
Speaker 1: guys are setting up for a post cookie world, which

559
00:33:36,640 --> 00:33:40,520
Speaker 1: I don't actually think a lot of companies, at least

560
00:33:40,600 --> 00:33:43,920
Speaker 1: a lot of cmos are not thinking about yet. Unquestionably,

561
00:33:43,960 --> 00:33:46,480
Speaker 1: we actually just did a project in the publishers side

562
00:33:46,480 --> 00:33:49,360
Speaker 1: of our business for one of the largest publishers on

563
00:33:49,360 --> 00:33:51,320
Speaker 1: the planet that I want that I'm on name here.

564
00:33:51,880 --> 00:33:55,239
Speaker 1: That was Cookieless World. That was basically, how do you

565
00:33:55,320 --> 00:33:59,560
Speaker 1: build a smart and virtuous ad business um and how

566
00:33:59,560 --> 00:34:03,600
Speaker 1: do you part anticipate as a platform of scale in

567
00:34:03,600 --> 00:34:06,400
Speaker 1: a cookuous world. So the people on that side are

568
00:34:06,400 --> 00:34:08,600
Speaker 1: starting to think about it, But I agree that wave

569
00:34:08,680 --> 00:34:11,839
Speaker 1: hasn't really hit the cmos yet. They're like, they're gonna

570
00:34:11,840 --> 00:34:13,480
Speaker 1: get pulled into it, and I'm glad we're on the

571
00:34:13,480 --> 00:34:16,200
Speaker 1: forefront of it, but it's not sort of broadly out

572
00:34:16,239 --> 00:34:19,400
Speaker 1: there yet. So what is known want to be known for? Like,

573
00:34:19,440 --> 00:34:23,600
Speaker 1: what is the influence you want to have on this

574
00:34:23,680 --> 00:34:28,040
Speaker 1: industry short term? Long term? I'll tell you there are

575
00:34:28,040 --> 00:34:33,680
Speaker 1: two things. UM. So they're like there's the part of

576
00:34:33,719 --> 00:34:40,040
Speaker 1: me that's just excited about seeing the alchemy of you know,

577
00:34:40,280 --> 00:34:44,400
Speaker 1: ardent science in like a real partnership of equals UM

578
00:34:44,440 --> 00:34:49,480
Speaker 1: in doing this stuff and breaking down some of the

579
00:34:49,560 --> 00:34:53,440
Speaker 1: barriers in the way that people when professionals talk to

580
00:34:53,480 --> 00:34:55,400
Speaker 1: each other like it's a real thing and we shouldn't,

581
00:34:55,440 --> 00:34:57,520
Speaker 1: you know, Like people are bigger than those boxes of

582
00:34:57,600 --> 00:35:01,120
Speaker 1: data scientists and creative director and that's that's just an

583
00:35:01,160 --> 00:35:04,640
Speaker 1: amazing thing to watch and to watch happen in the

584
00:35:04,680 --> 00:35:07,239
Speaker 1: world of modern marketing as people get more fluent and

585
00:35:08,440 --> 00:35:12,040
Speaker 1: more dynamic in how they use this stuff. There's also

586
00:35:12,920 --> 00:35:20,680
Speaker 1: the competitive oppositional like grumpy business person in UM and

587
00:35:21,719 --> 00:35:28,400
Speaker 1: I get incredibly frustrated when I see structures in place

588
00:35:29,400 --> 00:35:33,799
Speaker 1: that are self serving and designed to impede the intellectual

589
00:35:33,920 --> 00:35:40,560
Speaker 1: metabolism of an environment like this. And I think unintentionally,

590
00:35:41,200 --> 00:35:45,640
Speaker 1: but over many, many decades, we've created a structure in

591
00:35:45,840 --> 00:35:54,400
Speaker 1: the traditional media planning and buying environment that deliberately holds

592
00:35:54,600 --> 00:35:59,440
Speaker 1: back the evolution of the industry and and the passion

593
00:36:00,120 --> 00:36:03,120
Speaker 1: that I had for like going all in, Like guess what, like,

594
00:36:03,239 --> 00:36:07,680
Speaker 1: you own a data science and analytics company in you

595
00:36:07,719 --> 00:36:09,920
Speaker 1: don't need like nobody said you should really merge with

596
00:36:09,960 --> 00:36:13,640
Speaker 1: a creative agency, right, Like That's like that's everybody wants

597
00:36:13,640 --> 00:36:15,880
Speaker 1: to be a data science and analytics company in for

598
00:36:15,920 --> 00:36:18,399
Speaker 1: all the wrong reasons. But that's that's like a good

599
00:36:18,440 --> 00:36:21,080
Speaker 1: place to be. And the thing that I think made

600
00:36:21,080 --> 00:36:24,279
Speaker 1: me and all the other partners in that company want

601
00:36:24,280 --> 00:36:27,200
Speaker 1: to go all in on this was having the deep

602
00:36:27,200 --> 00:36:30,239
Speaker 1: experience we had on the publisher side seeing all the

603
00:36:30,280 --> 00:36:34,239
Speaker 1: amazing investments publishers and platforms are making to expose their

604
00:36:34,280 --> 00:36:37,799
Speaker 1: inventory and novel ways, and then also on the on

605
00:36:37,840 --> 00:36:42,080
Speaker 1: the client side seeing next generation marketers like Ross talked

606
00:36:42,080 --> 00:36:46,840
Speaker 1: about making massive strides to do things differently and in

607
00:36:46,880 --> 00:36:49,480
Speaker 1: a smarter way, in a more efficient way, and then

608
00:36:49,480 --> 00:36:54,000
Speaker 1: watching this thing just get stuck because the economic models

609
00:36:54,920 --> 00:36:59,680
Speaker 1: for how these transactions get handled and processed are broken.

610
00:37:00,120 --> 00:37:03,319
Speaker 1: Look like when I was working at Viacom with an

611
00:37:03,360 --> 00:37:06,680
Speaker 1: incredible group of people who are trying to do things

612
00:37:06,719 --> 00:37:10,520
Speaker 1: a different way and trying to bring media out into

613
00:37:10,520 --> 00:37:14,799
Speaker 1: the marketplace in a different way. And and the whole problem, though,

614
00:37:14,960 --> 00:37:17,880
Speaker 1: is if they go transparent, If the platforms and publishers

615
00:37:17,880 --> 00:37:22,719
Speaker 1: are transparent and advanced and integrated, and they expose their

616
00:37:22,760 --> 00:37:27,200
Speaker 1: inventory brank banks with real time discoverable pricing, which even

617
00:37:27,320 --> 00:37:32,440
Speaker 1: TV companies do now for television, and you've got data savvy,

618
00:37:32,560 --> 00:37:35,239
Speaker 1: aggressive marketers on the other side, like, how do I

619
00:37:35,320 --> 00:37:38,440
Speaker 1: make money as a media buying platform? Like I'll tell

620
00:37:38,440 --> 00:37:40,560
Speaker 1: you how we make money. We say, oh, that's cool,

621
00:37:40,560 --> 00:37:43,279
Speaker 1: Like we have incredible data scientists. We're happy to have

622
00:37:43,360 --> 00:37:47,120
Speaker 1: them support your team, work with our creative folks. Optimize

623
00:37:47,160 --> 00:37:51,400
Speaker 1: the ship out of this not by not by telling

624
00:37:51,440 --> 00:37:53,640
Speaker 1: you you can't buy it on your own, not by

625
00:37:53,680 --> 00:37:57,160
Speaker 1: telling the upfront scary. The upfront is so scary you

626
00:37:57,200 --> 00:38:01,399
Speaker 1: can't go in there. We have to value and so

627
00:38:01,560 --> 00:38:06,239
Speaker 1: like that passion for adding actual, real hard value to

628
00:38:06,360 --> 00:38:10,279
Speaker 1: this ecosystem made us realize that, like, you have to

629
00:38:10,280 --> 00:38:12,279
Speaker 1: have all these things together, You've got to really do

630
00:38:12,320 --> 00:38:14,759
Speaker 1: it right and and it's all or an nothing. We

631
00:38:14,840 --> 00:38:17,239
Speaker 1: need to be the place where the best people on

632
00:38:17,280 --> 00:38:20,280
Speaker 1: the planet come to do the best work of their lives.

633
00:38:20,920 --> 00:38:23,719
Speaker 1: How are you training talent? How are you training future marketers?

634
00:38:24,760 --> 00:38:26,719
Speaker 1: That's hard. In fact, I think it's one of our

635
00:38:26,719 --> 00:38:29,560
Speaker 1: greatest challenges because it's really difficult for us to recruit

636
00:38:29,600 --> 00:38:32,120
Speaker 1: as you can imagine the kind of talent that's required

637
00:38:32,120 --> 00:38:34,799
Speaker 1: as at this level from other agencies. We do a

638
00:38:34,840 --> 00:38:38,560
Speaker 1: lot of recruiting out of the top colleges and universities

639
00:38:38,680 --> 00:38:42,920
Speaker 1: and you know post doc programs in the world. Um.

640
00:38:43,040 --> 00:38:45,279
Speaker 1: Many of the people who come and work and known

641
00:38:46,280 --> 00:38:48,920
Speaker 1: just aren't from this industry, and the perspective and the

642
00:38:48,960 --> 00:38:53,720
Speaker 1: brilliance that they bring is what's sort of rejuvenating everything. UM.

643
00:38:53,760 --> 00:38:57,120
Speaker 1: And then you know, world class creative talent and strategic

644
00:38:57,160 --> 00:39:02,759
Speaker 1: talent like hard to find and incredibly in demand. UM.

645
00:39:02,800 --> 00:39:05,600
Speaker 1: But but we we've been lucky so far in that

646
00:39:05,640 --> 00:39:07,719
Speaker 1: we've built a culture that people want to be part of.

647
00:39:08,040 --> 00:39:10,600
Speaker 1: So if you think about every new person that joins

648
00:39:11,560 --> 00:39:13,800
Speaker 1: our company, they're sort of recoding the d N a

649
00:39:13,840 --> 00:39:16,799
Speaker 1: person by person that's Adam by Adam right, and they're

650
00:39:16,840 --> 00:39:21,160
Speaker 1: adding us their own apps to this operating system and

651
00:39:21,200 --> 00:39:23,680
Speaker 1: they're making it better. And that's sort of happening now

652
00:39:23,719 --> 00:39:25,719
Speaker 1: at a pace that I don't know that we could

653
00:39:25,760 --> 00:39:30,040
Speaker 1: have imagined a year ago, especially given you know, how

654
00:39:30,320 --> 00:39:32,359
Speaker 1: is gone. But We've been very fortunate, and I think

655
00:39:32,360 --> 00:39:34,680
Speaker 1: now the most important thing is healthy growth. What do

656
00:39:34,760 --> 00:39:37,759
Speaker 1: you both think it takes to break through going into

657
00:39:39,360 --> 00:39:42,520
Speaker 1: I think Ross and I and and Mark and Brad

658
00:39:42,320 --> 00:39:46,080
Speaker 1: and all the you know, creatives and scientists at talk

659
00:39:46,160 --> 00:39:48,600
Speaker 1: about this a lot, and we talk about it in

660
00:39:48,600 --> 00:39:52,399
Speaker 1: the context of some of our values right around sort

661
00:39:52,440 --> 00:39:57,200
Speaker 1: of authenticity, UM and honesty. There's no doubt and we

662
00:39:57,200 --> 00:40:01,040
Speaker 1: we recently you know, you talked about we feel like

663
00:40:01,239 --> 00:40:05,120
Speaker 1: I felt like there was a real UM has been

664
00:40:05,120 --> 00:40:08,640
Speaker 1: a real hard reset in the culture and and there

665
00:40:08,640 --> 00:40:11,640
Speaker 1: are a lot like a lot of things have changed,

666
00:40:11,760 --> 00:40:15,520
Speaker 1: need to change, will change UM coming out of this experience,

667
00:40:15,520 --> 00:40:17,640
Speaker 1: and I'm an optimist about where it all ends. But

668
00:40:17,680 --> 00:40:21,000
Speaker 1: we also felt like we needed to reset and put

669
00:40:21,000 --> 00:40:23,520
Speaker 1: our finger back on the pulse of what was happening

670
00:40:23,520 --> 00:40:27,040
Speaker 1: in the world. So we ran this huge self funded

671
00:40:27,040 --> 00:40:30,960
Speaker 1: study of the human condition in UM that we just recently.

672
00:40:31,120 --> 00:40:34,120
Speaker 1: What did it say? It said that in a in

673
00:40:34,160 --> 00:40:39,200
Speaker 1: a sort of a universal experience and phenomenon, it's hitting

674
00:40:39,200 --> 00:40:45,279
Speaker 1: different people very differently. UM and UH. The kinds of

675
00:40:45,680 --> 00:40:50,120
Speaker 1: things that are UH, that are allowing some people to

676
00:40:50,760 --> 00:40:53,960
Speaker 1: survive and thrive are not the things you think, it's

677
00:40:54,000 --> 00:40:58,920
Speaker 1: not your economics standing. Um, it's not even necessarily your

678
00:40:58,960 --> 00:41:05,759
Speaker 1: career um or your position. Um. It looked to us

679
00:41:05,800 --> 00:41:08,920
Speaker 1: through this sort of qualitative and quantitative segmentation that it

680
00:41:08,960 --> 00:41:12,880
Speaker 1: had to do with your relationships, your strong ties, your

681
00:41:12,880 --> 00:41:16,160
Speaker 1: relationships with people in your life, your sense of purpose,

682
00:41:17,160 --> 00:41:20,520
Speaker 1: and your sense of place and connection to your community.

683
00:41:21,600 --> 00:41:24,640
Speaker 1: And that all makes sense, right when you break it

684
00:41:24,640 --> 00:41:26,240
Speaker 1: out like that, that that all makes sense. But it wasn't

685
00:41:26,239 --> 00:41:28,160
Speaker 1: necessarily how we were lensing, and it wasn't how our

686
00:41:28,200 --> 00:41:31,279
Speaker 1: clients we're seeing it. It wasn't about the tropes of

687
00:41:31,400 --> 00:41:34,920
Speaker 1: in extraordinary times, right, And there's a lot of deeper

688
00:41:35,040 --> 00:41:37,560
Speaker 1: data there too, But but those things all struck us

689
00:41:37,600 --> 00:41:44,640
Speaker 1: as like foundational human authentic building blocks of who you

690
00:41:44,680 --> 00:41:47,960
Speaker 1: are and why you are and so first and foremost

691
00:41:48,120 --> 00:41:51,439
Speaker 1: who we're trying to ask ourselves those questions for any

692
00:41:51,480 --> 00:41:53,840
Speaker 1: creative it's like, does this is this real? Does this

693
00:41:53,880 --> 00:41:56,960
Speaker 1: speak to anyone? I think you know you always want

694
00:41:56,960 --> 00:41:58,239
Speaker 1: to do that in the process, but I think it's

695
00:41:58,239 --> 00:42:00,880
Speaker 1: like it's twice as important right now to get back

696
00:42:00,920 --> 00:42:03,600
Speaker 1: to for any given brand, like what is your purpose?

697
00:42:04,000 --> 00:42:07,880
Speaker 1: What is your place in the lives of your audience,

698
00:42:07,920 --> 00:42:11,600
Speaker 1: your consumers, your constituency um and how do you want

699
00:42:11,640 --> 00:42:15,200
Speaker 1: to talk to those people. Alexa hit this home in

700
00:42:15,200 --> 00:42:20,160
Speaker 1: our Malcolm Gladwell episode and referencing David versus Goliath scenario

701
00:42:20,239 --> 00:42:24,640
Speaker 1: of not losing sight of those relationships with our consumer

702
00:42:25,040 --> 00:42:27,600
Speaker 1: and what matters to them. And I'm gonna throw this

703
00:42:27,760 --> 00:42:32,280
Speaker 1: back to your partner, Ross, because I've had the really

704
00:42:32,640 --> 00:42:35,400
Speaker 1: great honor of getting to know Ross a few years

705
00:42:35,400 --> 00:42:39,239
Speaker 1: ago and talking to him and understanding when he was

706
00:42:39,280 --> 00:42:42,880
Speaker 1: building Blackbird that and Ross, you correct me if I'm wrong,

707
00:42:43,840 --> 00:42:48,600
Speaker 1: but you were always in the pursuit of truth, and

708
00:42:49,000 --> 00:42:52,640
Speaker 1: as a marketer, I think maybe that's the that's the

709
00:42:52,680 --> 00:42:55,600
Speaker 1: whole point. You bring up a great point, and it's

710
00:42:55,640 --> 00:42:57,360
Speaker 1: it's sort of an extension of what Kerment was just

711
00:42:57,400 --> 00:43:00,279
Speaker 1: saying that, like that that is sort of the the

712
00:43:00,400 --> 00:43:04,120
Speaker 1: dark side of what we're learning about ourselves as a society,

713
00:43:04,280 --> 00:43:07,560
Speaker 1: especially here in America, is that like, there is no

714
00:43:09,360 --> 00:43:15,680
Speaker 1: Laura and Alexa. Right, there's Laura and there's Alexa, and

715
00:43:15,760 --> 00:43:18,360
Speaker 1: you happen to do this show together, but the truth

716
00:43:18,480 --> 00:43:21,200
Speaker 1: is so different, or maybe just a little different, but

717
00:43:21,239 --> 00:43:23,520
Speaker 1: it's different for each of you. And so if I

718
00:43:23,560 --> 00:43:27,120
Speaker 1: want to reach your heart and make a connection. If

719
00:43:27,160 --> 00:43:29,680
Speaker 1: I want to change what you think, if I want

720
00:43:29,719 --> 00:43:32,000
Speaker 1: to get you to turn right when you're normally going

721
00:43:32,040 --> 00:43:35,160
Speaker 1: to turn left, I actually have to find the central

722
00:43:35,239 --> 00:43:39,400
Speaker 1: human truth of you. And I can't rely, as I

723
00:43:39,440 --> 00:43:43,960
Speaker 1: did before, on my own bias on shallow punditry, on

724
00:43:44,160 --> 00:43:47,080
Speaker 1: assumptions about who you are. Because you're two white women

725
00:43:47,120 --> 00:43:48,960
Speaker 1: of a certain age who live in the East Coasts,

726
00:43:49,640 --> 00:43:52,200
Speaker 1: and that's what we used to do. We actually did

727
00:43:52,239 --> 00:43:57,440
Speaker 1: that for decades. We cannot afford to waste the marketing

728
00:43:57,480 --> 00:44:01,120
Speaker 1: dollars on that kind of carelessness and waste the time

729
00:44:01,120 --> 00:44:03,440
Speaker 1: and attention of that audience, of that audience, when the

730
00:44:03,480 --> 00:44:07,360
Speaker 1: tools are all available to us. They are now at

731
00:44:07,440 --> 00:44:11,080
Speaker 1: our finger trips. There is no more excuse for not

732
00:44:11,360 --> 00:44:20,719
Speaker 1: knowing that. I think we mic drop that. So we'll

733
00:44:20,719 --> 00:44:22,720
Speaker 1: start with current. Because Karrent has never played the game.

734
00:44:23,160 --> 00:44:26,080
Speaker 1: Kerrent killed by d I Y. I think you've heard

735
00:44:26,080 --> 00:44:27,480
Speaker 1: it from me a few times, Like I would get

736
00:44:27,560 --> 00:44:33,040
Speaker 1: rid of anybody out there who has gotten themselves boxed

737
00:44:33,080 --> 00:44:36,719
Speaker 1: into a corner where they're where they're fighting against progress

738
00:44:37,120 --> 00:44:40,960
Speaker 1: in this industry, where they're pushing back on efficiency and

739
00:44:41,040 --> 00:44:46,000
Speaker 1: opportunity in in progress UM and that that's not that's

740
00:44:46,000 --> 00:44:48,520
Speaker 1: not one company, and that's not one category. But like

741
00:44:49,040 --> 00:44:51,799
Speaker 1: in any category, there's a bunch of UM. So let's

742
00:44:51,800 --> 00:44:53,640
Speaker 1: get rid of them because like that, we don't have

743
00:44:53,719 --> 00:44:57,359
Speaker 1: time and and and the clients deserve better. I'll tell

744
00:44:57,400 --> 00:45:00,799
Speaker 1: you what I think we've talked about. We feel like

745
00:45:00,960 --> 00:45:04,520
Speaker 1: we can and should buy doesn't sound like the right word,

746
00:45:04,560 --> 00:45:06,560
Speaker 1: but but but who we want to go find and

747
00:45:06,640 --> 00:45:11,360
Speaker 1: partner with and bring in. We think that there's outside

748
00:45:11,360 --> 00:45:16,279
Speaker 1: of the US, there's a bunch of tremendous creative assets,

749
00:45:16,360 --> 00:45:21,280
Speaker 1: creative companies out there who are doing beautiful, amazing work

750
00:45:21,960 --> 00:45:25,239
Speaker 1: in each of their regions and countries, and who are

751
00:45:25,280 --> 00:45:29,239
Speaker 1: also increasingly trying to scratch the data action Like who

752
00:45:29,400 --> 00:45:34,000
Speaker 1: could be incredible additions to our team, incredible extensions of

753
00:45:34,000 --> 00:45:37,160
Speaker 1: our DNA as Ross said UM as we serve more

754
00:45:37,160 --> 00:45:41,280
Speaker 1: and more global clients, right, so getting into local markets

755
00:45:41,440 --> 00:45:45,600
Speaker 1: with best in class creative for those markets I think

756
00:45:45,640 --> 00:45:48,120
Speaker 1: makes sense for us. And what I want to keep

757
00:45:48,200 --> 00:45:53,240
Speaker 1: d I y NG is the process and the culture

758
00:45:53,719 --> 00:45:57,799
Speaker 1: that connects this thing together. And you know, we talk

759
00:45:57,880 --> 00:45:59,560
Speaker 1: a lot about the operating system of our clients, but

760
00:45:59,600 --> 00:46:02,360
Speaker 1: also they an operating system and a belief system for ourselves.

761
00:46:03,280 --> 00:46:06,640
Speaker 1: And that's the thing we need to never stop building it.

762
00:46:07,000 --> 00:46:11,120
Speaker 1: Ross killed by d I y I'm gonna kill hate.

763
00:46:13,400 --> 00:46:19,480
Speaker 1: I'm gonna buy time. I'm gonna build empathy, Ross Kern,

764
00:46:19,680 --> 00:46:22,040
Speaker 1: known dot is. If people want to get in touch

765
00:46:22,120 --> 00:46:26,480
Speaker 1: with you to remix data, science and creativity, how do

766
00:46:26,560 --> 00:46:29,359
Speaker 1: they get in touch with you? Hello at known dot

767
00:46:29,480 --> 00:46:33,760
Speaker 1: is and we will say hello back, Ross Kern. Poets

768
00:46:33,920 --> 00:46:37,280
Speaker 1: of progress? Did you know that I have been for

769
00:46:37,280 --> 00:46:40,400
Speaker 1: for years since I first met Ross, I've been calling

770
00:46:40,480 --> 00:46:44,000
Speaker 1: him a business poet. Here is a business poet. I mean, Ross,

771
00:46:44,040 --> 00:46:46,440
Speaker 1: come on, give us something, Ross, just something to close

772
00:46:46,480 --> 00:46:49,160
Speaker 1: the episode with something from your book. Let's put it

773
00:46:49,200 --> 00:46:51,759
Speaker 1: a little plug here. Ross is a published poet. The

774
00:46:51,840 --> 00:46:55,880
Speaker 1: cop who rides alone, Ross Martin. It started to thunder.

775
00:46:55,960 --> 00:46:58,600
Speaker 1: I began to wonder why do we mow our lawns?

776
00:46:59,160 --> 00:47:01,160
Speaker 1: Then it hit me. The nice lines are pretty when

777
00:47:01,160 --> 00:47:04,120
Speaker 1: they wake up freshly cut it dawn. Maybe they want

778
00:47:04,120 --> 00:47:06,640
Speaker 1: to keep growing, but man's too ignorant to stop mowing,

779
00:47:06,680 --> 00:47:09,839
Speaker 1: So lawns are cut each day because man doesn't care

780
00:47:09,880 --> 00:47:13,000
Speaker 1: about cutting nature's hair, even if nature doesn't want it

781
00:47:13,040 --> 00:47:15,200
Speaker 1: that way. I love it Did you write that when

782
00:47:15,200 --> 00:47:17,319
Speaker 1: you were fifteen? Yeah? Did I do that in the

783
00:47:17,360 --> 00:47:21,919
Speaker 1: last episode? No, but I remember you talking and he's

784
00:47:21,920 --> 00:47:24,120
Speaker 1: always triing that out. I only got one poem and

785
00:47:24,200 --> 00:47:32,520
Speaker 1: I was fifteen. Can and order, Yes, this opportunity less

786
00:47:32,560 --> 00:47:35,040
Speaker 1: opportunity Our data side just five out of six. Data

787
00:47:35,080 --> 00:47:37,600
Speaker 1: Side just will tell you that that is the best title.

788
00:47:39,520 --> 00:47:45,160
Speaker 1: Can we just say congratulations on this season and this

789
00:47:45,239 --> 00:47:47,799
Speaker 1: is the podcast. So we're just so grateful to be

790
00:47:47,840 --> 00:47:50,279
Speaker 1: part of you your world here on a small part,

791
00:47:50,320 --> 00:47:52,279
Speaker 1: but thank you so much. You will be coming back.

792
00:47:52,400 --> 00:48:02,399
Speaker 1: Thank you guys, to Laura coming out of this conversation.

793
00:48:03,000 --> 00:48:07,960
Speaker 1: The things that shine through for me one, we as

794
00:48:08,160 --> 00:48:12,400
Speaker 1: marketers and especially cmos, tend to continue to look at

795
00:48:12,480 --> 00:48:16,680
Speaker 1: the vanity as you call them, vanity metrics. Right, So,

796
00:48:16,840 --> 00:48:19,920
Speaker 1: what's happening on your website, what's happening in your purchase funnel,

797
00:48:19,960 --> 00:48:23,080
Speaker 1: what's happening da da da da. But those are surface metrics,

798
00:48:24,239 --> 00:48:29,719
Speaker 1: that's surface data and analytics, rather than having creatives and

799
00:48:29,840 --> 00:48:35,960
Speaker 1: data scientists briefed together, starting together and going to find

800
00:48:36,000 --> 00:48:40,160
Speaker 1: out what could be known. It's interesting in how Ross

801
00:48:40,160 --> 00:48:44,160
Speaker 1: and currenter positioning their value prop right, and that it's

802
00:48:44,239 --> 00:48:46,839
Speaker 1: less so about um one or the other, but how

803
00:48:46,880 --> 00:48:50,759
Speaker 1: these two things work together, the ability to understand patterns

804
00:48:51,560 --> 00:48:55,080
Speaker 1: using data and breakdown at the individual levels. What I

805
00:48:55,080 --> 00:48:59,840
Speaker 1: took away down to the individual level what creative serves

806
00:49:00,000 --> 00:49:04,280
Speaker 1: Alexa versus what creative serves Laura and I think marrying

807
00:49:04,360 --> 00:49:06,160
Speaker 1: that you know this idea of we think so much

808
00:49:06,160 --> 00:49:09,520
Speaker 1: in the creative spaces art director meets copywriter, but is

809
00:49:09,560 --> 00:49:14,480
Speaker 1: the new critical pairing data scientists and creative director. Yeah,

810
00:49:14,520 --> 00:49:18,919
Speaker 1: I love that. And when you think about designing, designing

811
00:49:19,200 --> 00:49:27,080
Speaker 1: both product designing, designing both products and campaign or message

812
00:49:27,520 --> 00:49:33,000
Speaker 1: right against triggers that are about the needs that are

813
00:49:33,040 --> 00:49:37,080
Speaker 1: filling the needs and understanding the triggers of the consumer first,

814
00:49:37,320 --> 00:49:40,680
Speaker 1: designing that upfront that should be your brief with a

815
00:49:40,760 --> 00:49:46,160
Speaker 1: bunch of hypotheses, a bunch of opportunities right to test.

816
00:49:46,200 --> 00:49:49,560
Speaker 1: And too often I think, you know and Ross kind

817
00:49:49,560 --> 00:49:51,239
Speaker 1: of hit on this too often. I think we talk

818
00:49:51,280 --> 00:49:55,360
Speaker 1: about campaigns and there that that alone is something that

819
00:49:55,640 --> 00:49:59,160
Speaker 1: starts and ends. And what Ross and Kurn were saying

820
00:49:59,280 --> 00:50:03,520
Speaker 1: is that this just keeps going, This just keeps learning.

821
00:50:03,880 --> 00:50:05,879
Speaker 1: And in order to do that, you have to get

822
00:50:05,880 --> 00:50:08,480
Speaker 1: out in the market. You have to actually have a

823
00:50:08,520 --> 00:50:12,120
Speaker 1: hook to start reeling in. If you don't have that

824
00:50:12,200 --> 00:50:15,399
Speaker 1: hook out there and you're not testing multiple iterations, I'm

825
00:50:15,400 --> 00:50:18,600
Speaker 1: not just talking about messaging and creative, I'm talking about ideas.

826
00:50:19,360 --> 00:50:23,839
Speaker 1: I'm talking about products. And so is the question that

827
00:50:24,040 --> 00:50:26,360
Speaker 1: the CMO becomes more of a growth marketer or is

828
00:50:26,400 --> 00:50:29,840
Speaker 1: the question that the CMO becomes more of a product person.

829
00:50:30,880 --> 00:50:33,640
Speaker 1: Is that where we're headed. Yeah, it's interesting when you

830
00:50:33,640 --> 00:50:37,640
Speaker 1: think about the word programmatic. So much of the emphasis

831
00:50:37,960 --> 00:50:41,360
Speaker 1: has been on the automatic part of that word. But

832
00:50:41,520 --> 00:50:46,120
Speaker 1: really what I heard is using data science to really unpack,

833
00:50:46,400 --> 00:50:50,319
Speaker 1: unbundle the journey, really think about the message that's going

834
00:50:50,360 --> 00:50:55,040
Speaker 1: to resonate in that journey, and really thinking about programming

835
00:50:55,360 --> 00:51:01,120
Speaker 1: the automation versus automating the programming all of that, you know.

836
00:51:01,160 --> 00:51:03,479
Speaker 1: And on that note, one of the things that Kern said,

837
00:51:03,520 --> 00:51:05,440
Speaker 1: and he kind of said it quietly, right, it was

838
00:51:05,480 --> 00:51:09,840
Speaker 1: like a point was about sequencing. We don't actually think

839
00:51:09,880 --> 00:51:16,240
Speaker 1: about sequencing enough. This is about design up front. Designing

840
00:51:16,440 --> 00:51:19,520
Speaker 1: up front the path you're going to take someone, and

841
00:51:19,560 --> 00:51:23,280
Speaker 1: it has multiple iterations, and it has multiple turning points.

842
00:51:23,719 --> 00:51:26,680
Speaker 1: They could take someone down depending on their behavior, depending

843
00:51:26,719 --> 00:51:30,400
Speaker 1: on where they are in their interesting consideration, and I

844
00:51:30,440 --> 00:51:37,000
Speaker 1: think that you know, the industry is separated the tools, right,

845
00:51:37,200 --> 00:51:40,440
Speaker 1: the data science and the analytics and the metrics and

846
00:51:40,760 --> 00:51:43,759
Speaker 1: point KPIs and those types of things with good creative

847
00:51:44,040 --> 00:51:47,279
Speaker 1: but those things, as Ross and Kern said, they go

848
00:51:47,360 --> 00:51:49,520
Speaker 1: hand in hand. Well yeah, I mean so much of

849
00:51:49,680 --> 00:51:53,280
Speaker 1: what I've experienced throughout my career is the creative leading

850
00:51:54,360 --> 00:52:00,520
Speaker 1: that messaging and then using the data science to target

851
00:52:00,560 --> 00:52:03,840
Speaker 1: audiences right, to go out and find the audience to

852
00:52:03,920 --> 00:52:06,680
Speaker 1: deliver that message. But by pairing those two things together

853
00:52:06,760 --> 00:52:10,320
Speaker 1: from the onset, you start thinking less like a planner

854
00:52:10,360 --> 00:52:15,080
Speaker 1: and more like a programmer designing the journey versus planning it.

855
00:52:15,440 --> 00:52:17,200
Speaker 1: Kern really got to that when he was talking about

856
00:52:17,600 --> 00:52:22,960
Speaker 1: bad advertising is like attacks on the consumer. They thought

857
00:52:22,960 --> 00:52:25,319
Speaker 1: that was a fascinating That was a great way of

858
00:52:25,360 --> 00:52:27,359
Speaker 1: saying it. It was a great way of saying it.

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Speaker 1: And I think, so it's less of people been paying

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00:52:30,320 --> 00:52:32,440
Speaker 1: with their time. People are paying with their time, And

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00:52:32,480 --> 00:52:35,319
Speaker 1: I think it's less about what you want to sell

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00:52:35,440 --> 00:52:41,239
Speaker 1: someone and more about how are you reaching someone and

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00:52:41,320 --> 00:52:45,440
Speaker 1: making sure that there's value and what you are selling them.

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Speaker 1: There's like this this thing going off in my brain,

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Speaker 1: going wait a minute. If you look at a standard

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Speaker 1: reporting dashboard in media, one of the metrics you will

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00:52:54,640 --> 00:52:58,160
Speaker 1: often find is time spent. But we don't measure the

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Speaker 1: sentiment of the time in so I may capture somebody's

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00:53:01,960 --> 00:53:06,520
Speaker 1: attention for thirty sixty seconds, but was that a good experience?

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00:53:07,000 --> 00:53:11,480
Speaker 1: What was that time well spent? Right? So central question,

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Speaker 1: what do you want to be known for? That is

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00:53:14,800 --> 00:53:18,120
Speaker 1: the question? And speaking of questions, Alexa, We're going to

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Speaker 1: be introducing a new segment on Atlantia called The Burning

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00:53:22,200 --> 00:53:25,960
Speaker 1: Question with Kindred CEO Ian Schaefer so Atlanta. Each week

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00:53:26,000 --> 00:53:27,920
Speaker 1: we're gonna be teaming up with Kindred to pose a

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00:53:27,920 --> 00:53:31,320
Speaker 1: provocative question to our listeners that explores how popular culture

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00:53:31,400 --> 00:53:34,920
Speaker 1: movements affect brand decisions. And we're gonna be asking those

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00:53:35,040 --> 00:53:37,680
Speaker 1: questions on Twitter and then some of the responses from

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00:53:37,719 --> 00:53:40,640
Speaker 1: the Atlantia community will be read on air and discussed

880
00:53:40,680 --> 00:53:43,279
Speaker 1: in the podcast in addition to having I and share

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00:53:43,320 --> 00:53:47,759
Speaker 1: his perspective. So week one question has the fear of

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00:53:47,880 --> 00:53:51,120
Speaker 1: cancel culture lad brands and the people behind them to

883
00:53:51,280 --> 00:53:56,000
Speaker 1: develop faux food. Fear of fffing up is the appeal

884
00:53:56,080 --> 00:54:01,040
Speaker 1: to everyone, the new appeal to no one. This popular culture,

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00:54:01,160 --> 00:54:06,080
Speaker 1: Eat Corporate Culture for breakfast, tweet at Atlantia Podcasts and

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00:54:06,320 --> 00:54:10,359
Speaker 1: see c I Shaefer Ian Shaeffer to get into the conversation,

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00:54:10,840 --> 00:54:13,560
Speaker 1: and we may have you on one of our next

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00:54:13,560 --> 00:54:17,040
Speaker 1: episodes to discuss Laura hit it with the list of

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00:54:17,080 --> 00:54:18,799
Speaker 1: all of our friends and family at I Heart who

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Speaker 1: have been so good to us and helped us get

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00:54:21,080 --> 00:54:24,840
Speaker 1: back on air. Big thank you to Bob Connal, Carter, Andy,

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00:54:25,160 --> 00:54:28,600
Speaker 1: Eric Gayle Val, Michael Jen. We appreciate you. Thank you

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00:54:28,640 --> 00:54:31,480
Speaker 1: so much for this opportunity. We'll see you in two weeks.