Jon Janice (3:07)

Well. Or, like a lot of people, I love to listen to baseball as opposed to watch it, because baseball announcers are so much better at describing what's going on because they have to.

Kate Bradley Chernis (3:16)

They have to. And they're so crafty. I mean, they're just. It's. That's a real sport in itself, you know? Exactly. Great point. So I was. And when I was in radio, I'm old enough so that there wasn't social media when I first started and. Or the Internet, and you couldn't look people up. And so we would kind of mess around and play tricks on the listeners and, you know, make up these scenarios. Right. It was fun. And I had written hundreds of commercials because I learned quickly that was how you made money in radio. And I was a fiction writing major, and I saw these parallels between wielding the mic and wielding the pen and listening and reading and what I, My, My boss, I was number one in. In our format, which was very rare because it was called AAA or adult album Alternative. There's only a handful of stations in the country, but we were.

Jon Janice (4:05)

And even fewer women.

Kate Bradley Chernis (4:06)

And even fewer women. Yeah. Yeah. It was this, like, totally random thing I fell into. But like country and rock, those stations are number one, you know. And so my bosses were like, what are you doing? And I'm like, well, I did know what I was doing. I threw out their playlists and I was. I was running the whole show because all the content was produced by me, all the commercials, all the drops, everything during my time. But I looked into it more. This is a long story. I hope it's interesting. And I read this book called this is your brain on music. You guys remember? I think Daniel Levitan did that. Hard read. It's a thick read, but it's about the neuroscience of music and music listening. And I learned something interesting about the parallel of music listening and theater of the mind. All of this relates to lately somehow, but I'll share. So when you. When your brain listens to a new song, John, what. What songs do you like, by the way? Are you classic rock guy like. I am, yeah.

Jon Janice (5:00)

I mean, I, you know, I listen to the Loft and occasionally jump over and listen to Earl Bailey.

Kate Bradley Chernis (5:05)

That was my station. So yeah, I love Earl. He's so great. Yeah. So great. Oh my go. You're making me reminisce. So great quality music, you know, rock and roll, that's for, I think I'd say intelligent rock and roll, let's say.

Jon Janice (5:20)

Yeah, yeah.

Kate Bradley Chernis (5:20)

What I was learning from Daniel was that when your brain listens to a new song, it must instantly access every other song you've ever heard before. And it's trying to index that new song in the library of the memory of your brain. This is happening like in a moment. Right.

Jon Janice (5:34)

Makes sense.

Kate Bradley Chernis (5:34)

And of course, in order to access all that memory, it's pulling on nostalgia and emotion, obviously memory, all those things that create trust. And trust is why we buy now. Guess what? When the theater of the mind kicks in, same thing happens. Nostalgia, memory, emotion, trust. And when you're doing a good job on the mic, John, you actually make your listeners feel as though they're talking, you're talking to them directly.

Jon Janice (6:01)

Yeah.

Kate Bradley Chernis (6:02)

That this one way street is a two way street and they have ownership in the conversation. And writing is the same thing. And it's a complicated feat to do it well because you know, you're talking to nobody but also somebody specific. That's the, the magic. So I took these ideas to a little company, you know, called Walmart and I got them 130% ROI year over year for three years with what became the prototype for lately.

Jon Janice (6:31)

Screw it. We're not going to talk about lately. Let's just talk about the Jayhawks latest album.

Kate Bradley Chernis (6:36)

Yeah, I'm sorry. Oh my God, you're so funny. I. I took out their last. Well, I don't if it was their last record, but the one with Cloud something Cloud, it was their last like really poppy record from the 90s and I was, I had that in my. I still have a CD player in my car and I was rocking to that record because I love it so much. Any other Jayhawks fans listening to us, I wonder.

Jon Janice (6:59)

Of a certain age.

Kate Bradley Chernis (7:00)

Of a certain age, yeah, for sure. But I love that record and it got panned for being too poppy, but I think it's a real lot of gold in there.

Jon Janice (7:08)

Absolutely. So let's talk about content marketing. AI seems like daily is changing. I mean, content marketing's changed dramatically over the last decade or so, but certainly AI seems to be changing it every day. What's your take on, you know, how it's changing really the whole landscape of content marketing?

Kate Bradley Chernis (7:25)

Well, I mean, Thanks a lot, ChatGPT. Because now everybody can make more garbage than ever before. It's no way they made our jobs, you know, a lot harder. The. The task for marketers, the challenge has always been how do we cut through the noise. Right. And now there's just, you know, so that certainly has changed the landscape. One thing that I'm seeing, and I wonder if you are, which is astonishing to me, what's the laziness is not changing. Right. So it's specifically with generative AI and text. Generative AI, which is where I live, like, people still hate writing. They don't want to do it, but also their value behind it is save time as opposed to be more effective. Yeah, yeah, that's shocking. Like, and honestly, I'll ask our own clients this customer this question all the time, and like the CEO or the CRO, they want to make more money, but the actual users are thinking of save time and getting them to be aligned is a challenge.

Jon Janice (8:23)

You know, my take on is a little bit. I agree with you. At least we're in this phase right now of more noise. But I think eventually, like old things, people are going to go. It's pretty easy to separate noise from signal, you know, maybe even more so now. Right. Because, you know, writing quality content still takes strategic thinking. And I think that, I think it makes people who do strategic thinking even more valued. Even though right now there are a lot of them are feeling sort of underwrite.

Kate Bradley Chernis (8:50)

Yeah. So on parallel with that. And so. So there's this symbiotic relationship between AI and humans who can think strategically and analytically.

Jon Janice (9:00)

Absolutely.

Kate Bradley Chernis (9:00)

And they rely upon each other. Right. And it's called collaborative AI that this is the year of collaborative AI, in my opinion. We built collaborative AI into lately from the beginning, which, you know. But it's the idea of a human analyzing and course correcting what the AI generates so that it can, you know, boost the learning. Here's what's fascinating about what we're. What you said, which is the number one vacuum of skills across the globe, is, guess what? The ability to analyze. And the reason that is is because we have. This is back to laziness, too. We've become a culture unable to identify problems because for so long, especially in corporate life, it was like, don't bring me a problem, bring me a solution. Right. So even when, like, I have a friend who has some teenage daughters and when they need to go, they know they can Google the answer to anything, but they don't know what to type in.

Jon Janice (10:00)

Yeah, right. Well, and that's so many things brought up there. The, you know what I tell people all the time is what we're left to provide is context. That context cannot be provided by ChatGPT. And so that's to your point of the search. I mean, a lot of it is the right context produces the right answer. But these machines are basically just going into a database and saying, here's what I think the answer is. Whereas we are saying, well now here's what, here's the real problems the customer is telling us they're struggling with. And you know why? Our solution or whatever it is we're selling is, you know, the answer for them. And I think short of having that understanding, you know, you who know, it's a crapshoot what you're going to get back.

Kate Bradley Chernis (10:41)

Yeah, I mean that. Thank you. I'm going to steal that, the context, because it is so true. Someone was just asking me the other day, well, should I second guess everything that late lately generates for me? And I said, yes, you're still the king the humans. We are still the king of the food chains, of course, you know, and he's like, well, won't AI know better than me? And I'm like, never. No, like all AI is good at doing is now is synthesizing scale. Really.

Jon Janice (11:08)

Right. Yeah. In fact, I've been for a long time, you know, because I don't really think it's AI yet, to be truthful.

Kate Bradley Chernis (11:14)

Right.

Jon Janice (11:14)

It's not really artificial intelligence. Turn it around. It's more informed assistance is kind of how I, you know, talk about it. Do you ever feel like TV ads are just for the big guys? Well, not anymore. Ad Critter makes it easy and affordable for small business owners to run targeted connected TV ads that drive real results. Their full funnel approach combines high impact connected TV ads with precise digital retargeting. So you can easily reach your audience across platforms and keep your business top of mind. And the best part, AdCritter takes care of the tricky stuff. Just upload your customer data and they handle the rest. And try it out for yourself. Right now, Duct Tape marketing listeners get a dollar for dollar match on any TV campaign up to to $5,000. That means if you spend $5,000 on TV ads, you'll get an additional $5,000 to spend. Head on over to AdCritter.com that's AdCritter.com and get started. All right, so I'm going to ask you a really hard lately question. You and I started talking about lately Three or four years ago at least. And at that point, three or four years ago, what lately was doing was very cutting edge. People didn't necessarily understand it, but it definitely produced a result that was very cutting edge. Fast forward to today. You know, everything you buy now has AI in it, supposedly like your detergent now has AI in it, I think if you buy it. So you know, what's, what's the differentiator or what's your stay ahead, you know, cutting edge play?

Kate Bradley Chernis (12:47)

Yeah, yeah. So, well, a couple of things. Yeah, it's a hard one and there's like functional answers and then there's kind of aesthetic answers I'm going to call them. But so functionally we're the only generative AI that, that I know of where we have a continuous performance learning loop plugged in so that the results that we generate for you are always tied to your personal analytics or the analytics of your company, which is to say it's never out of thin air. So all other generative AI doesn't know you in any way and can never give you results that are essentially really meaningful. The other component there is the collaborative AI. So because we built that into the product, the whole product originally, we have kind of pole vaulted over everybody else. Harvard Business Review just released an article about collaborative AI citing lately as a leader. And one of the studies they did showed that collaborative AI outperforms AI alone 2 to 7x every time. But the, on the sort of aesthetic side, what's again, what's really interesting to me is that save time piece. Right? So of course we save time like everywhere else, but that is not our cutting edge leg up. The leg up is we show you why. Right? Why it's effective. What, what's the DNA of the messaging that will get you the highest response? And I think what we've done a poor job of is actually leveraging how well we do that and what that value is. So I've called upon my engineering team for this year to actually do a better job of getting people to understand this information and how to use it. That's what's fascinating to me is like, I can show you these words, John. I can show you the ideas, ascendance structures, all the things that will get you the most engagement. But people then don't know what to do with it, which is like, to me, duh. But that is the crux, right? The last answer to your question is going even deeper here. So I'm planning an integration with my friend David Allison, who owns the Value Graphics database And value graphics are identifying how to group people by what they care about as opposed to demographics, which is more insightful. Radically more insightful. And they consult the United Nations. Yeah. And so like some characteristics would be like, if I care about the environment and you're selling me lipstick, you want to sell me lipstick that talks about how great it is to. For the environment. Right. Or if you're selling me lipstick and I care about family, you want to mention that the family company has been around for a hundred years, passed on by daughter, whatever. And so we're working on a way of integrating these values inside lately so you can get more of that why. And understand who your target audience is and why are they responding to the content we're generating for you. Kind of nerdy. I don't know. I'm excited about this.

Jon Janice (15:50)

No, I. But I think you're absolutely right. I mean, I've been saying for years I'd rather, I mean, my target market is based on behavior, not on, you know, how old somebody is. It's what they value. It's. Do they invest in the community? I mean, do they invest in their industry? Those are how we actually identified some of those behaviors. And I feel like that's a way to actually niche down is to focus on behavior. So having, obviously tools that. And I'm guessing that you're going to go into personalization, you know, at some point with that level of segmentation as well. Let me ask you, I said in the intro in your bio, I mentioned the idea of data privacy. I know, you know, it's a big deal. How much does the market perceive this idea of public data sets versus privacy versus. I don't know what you're talking about.

Kate Bradley Chernis (16:34)

Yeah, pretty huge. And it's another arena of AI where everybody thinks they know all about it, but they don't, which is kind of the whole trend of the last year. So some companies come to us with like an AI task force, and that has to be part of one of the initial calls where they're. We're checking the boxes for them, you know, the safety boxes with their legal and IT teams, which we check a lot of those boxes. You know, the. Then there's other companies like PwC who've gone full on into AI and they don't seem to really care, you know, which is. And then there's a lot of companies where they know people are using it, even though there's a, maybe a ban on ChatGPT throughout the company, but people are using it anyways.

Jon Janice (17:20)

Yeah.

Kate Bradley Chernis (17:20)

So there, there's nothing consistent for sure. My husband actually just bought ChatGPT for his phone because he didn't want to put on in his work computer. But he wants to be able to use it for work to help him do things faster, smarter, better. You know, of course, I think there's a lot of that going on.

Jon Janice (17:38)

Yeah, yeah.

Kate Bradley Chernis (17:39)

What I understand, you know, I mean, it's stupid.

Jon Janice (17:42)

It's stupid. I mean, I. It's like I can write a formula in Excel or I can just dump all this in to say, give me the answer, you know, so I use it all the time for stuff like that. Right. But maybe we better back up just a minute because I asked that question assuming a lot and assuming that people knew what that really meant. So when I go to ChatGPT, everything that's being put in there is helping teach the entire language model and everything from my customer statistics to my Google Analytics that I'm getting analyzed. I mean, that's all just being fed. Right. And theoretically, in some fashion, anybody has access to it that, I mean, not specifically to it, but it's feeding the machine that then is going to produce something, whereas the private data set, you know, that is, if I come to lately and I put that same kind of information in there, it's only going to be used to build my personal model. Is that the way to sort of explain it?

Kate Bradley Chernis (18:34)

That's right. That's correct. Yeah. We don't take any of your information and muddy it with anybody else's. And like, the one thing we can see is the patterns that if things are working well for you and they're working well for another customer, we can see those patterns, but we don't share them with you individually. We would take the knowledge and share it at large. And so that's been a real win for us, by the way, is because, I mean, I've been asked, I've been asked to actually give courses on AI to educate companies on why that exact thing matters.

Jon Janice (19:04)

Yeah.

Kate Bradley Chernis (19:04)

I think David Allison, not David Allison, David Meerman Scott, who was investor and friend, he put it succinctly where to help people understand, you know, he was like, Listen, there's only two questions that matter. Whose data and who's math with ChatGPT, it's the world's. It's your data. It's, you know, the world's data, everybody's data, and general math, like a general generic math with lately, it's your private data and then our math on top of it, you know.

Jon Janice (19:38)

So I need two more questions. I'M going to ask you the first one. Sure. Just because we haven't, you know, you and I have talked enough for Times. It's like, you know that idea of like, oh yeah, we have listeners too. If somebody came to you and said lately, I kind of heard of that. What does lately do? How would you describe what lately does?

Kate Bradley Chernis (19:53)

Oh, I'm so bad at this. It's like the shoemaker has no shoes. But I'm evolving. So lately learns the patterns of when you write well, what helps you do that. And it also learns the patterns of what your unique audience will actually reply to on social media. And then we help you evolve that model by repurposing long form content and identifying what part of that content will actually get you the highest possible engagement on social.

Jon Janice (20:21)

Awesome.

Kate Bradley Chernis (20:22)

How did that go?

Jon Janice (20:23)

So that was great. So the output could be a blog post. No, that was very good. It was still maybe a little off until I know. So the output, the end output is a blog post or is a LinkedIn post or is a X post, right?

Kate Bradley Chernis (20:37)

Yeah, the output is a social media post, but. And so much more. I mean it's really the insights to know this is why we have investors like you and David Merman, Scott and others is like there's so much potential in what we've identified. How can we evolve the product to really give you more, you know, so.

Jon Janice (20:57)

An entrepreneurial question to send us out does do you think, because I know you haven't done this a hundred times, do you think that working in an industry that is evolving so quickly is make it makes it even harder to evolve a business?

Kate Bradley Chernis (21:12)

Oh, I mean there I. The challenges are yes, for sure. But there's so many other smaller challenges that I didn't expect that seem to me to eclipse that. Some of it's being a female entrepreneur, let's be honest.

Jon Janice (21:28)

Yeah.

Kate Bradley Chernis (21:29)

Some of it's working through a pandemic. You know, I think the way that we come at this from radio, from this totally unfathomable background gives us a huge insight as a company, not just me, at how we go at AI. And we go at it very humanly because that's just how we, we did it from the beginning. So I love that what we're able to see about the benefits of it are often inside out of what everybody else is seeing. And I feel really proud about that.

Jon Janice (21:58)

Yeah, that's really interesting because I do think a lot of people approach this as what can the machine do? And I think that you're actually saying our point of view is, you know, how do we get the output that's going to have the most impact from a neuroscience point of view? And I think that's. I think that's a harder one to explain probably, but it's certainly more impactful than a machine view, for sure.

Kate Bradley Chernis (22:22)

I just got a Kennedy chill. So, like, not what can machine do for you, but what can you do for your machine?

Jon Janice (22:28)

I like it. I like it. Okay, T shirts. Let's start printing T shirts right now. We have to.

Unknown Speaker (22:34)

All right.

Jon Janice (22:34)

Katie, it was great catching up with you. You want to obviously we've mentioned lately AI numerous times. Is there anywhere else somebod should connect with you?

Kate Bradley Chernis (22:43)

They can find me in all the places. LinkedIn. I'm just playing Kate Bradley and tell me that you met me with John and that we can be friends.

Jon Janice (22:51)

Okay. Awesome. Well, it's great catch up with you again. Hopefully we'll run into you soon out there on the road.

Unknown Speaker (23:01)

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