Speaker 1: (00:22)
Hey friends. Welcome back to the MarTech Show. Now, what if I told you that principles from rock and roll can transform AI and revolutionize digital marketing? Digital marketing often struggles to truly captivate and engage audiences leading to wasted resources. And low ROI Creating content that resonates emotionally with consumers remains a significant challenge for a lot of brands like ours and yours. Despite using various tools and strategies, many marketers might find that their campaigns are falling flat, and that frustration grows as they realize their content lacks the emotional depth needed to make a lasting impact leading to disconnected audiences and ineffective marketing efforts. Enter Kate Bradley Cherniss, who brings a unique perspective to the digital marketing world. As a former rock and roll DJ broadcasting to 20 million listeners a day, Kate has an unparalleled understanding of audience engagement. Now, as the co-founder and CEO of lately, she leverages the neuroscience of music to drive revolutionary AI technology. And Kate's innovative approach is transforming content creation and digital marketing offering afresh and effective way to connect with audiences on a deeper level. Hey, Kate, welcome to the show.
Speaker 2: (01:30)
Mike, I love you. That's my best intro yet ever, ever, ever, ever. So thank you so much. And like, you know, from one radio person to another here, like, good job on the read. Like you're, that was so . I mean, a lot of that stuff is hard to say. So like, it's amazing. And I have mic, I have microphone envy. Uh, also by the way, my mics are like literally in a box over here. I've never, I don't know why. I've never hooked them up to my situation. Um, 'cause you know, when I'm doing voice work, it's usually like in the closet now. So not, not the computer. But anyways, I love seeing you. Thank you so much for having me here today.
Speaker 1: (02:09)
I love having you here, but I, I gotta say, yeah, I think every single time that we've been on camera like this, you're always just using the headset. I didn't even know you owned other microphones.
Speaker 2: (02:20)
Yeah, well, so once in a while, I don't get asked to do voiceovers too much anymore. Um, because, you know, I have this other job, but it's great money and it's super easy to do, you know? Um, but that, like, I like to put a lot of reverb on my voice. I have a Sennheiser, I also have the, the, um, Michael Jackson microphone. I forget what it's called, but Chris bro sold it to me. You know, my friend Chris. Um, yeah. And my, you know, my radio voice is a little bit of a different voice. , right? There you go. Yeah,
Speaker 1: (02:49)
We're gonna need to hear more of that. But I'd like for you to talk about that other job. Tell us about lately, what lately does what you do there?
Speaker 2: (02:58)
Mm. So at lately, we are really in the business of giving people the words to make others do what they want them to do. It's that simple. That's the whole business of not only marketing, but communication. Right? But our sort of jump on that is not only that, but we want them to then become your fans and evangelize the product after the sale, right? And in order to do that, you have to have a lot of trust in play. And we, we can talk sort of about the nitty gritty of how it works, but that's the, the headline we focus specifically on social media. The reason we do that is because there's so much data there. So we can always have a continuous performance learning loop so that the content we're generating is always a hundred percent resonating your voice and then also relevant, um, to your, your audience. Um, so that's sort of a, the high level nutshell. you wanna go deeper, ?
Speaker 1: (03:53)
Yeah, I do. And I love that concept of a feedback loop. 'cause it's something we're talking about more and more, you know, at Agorapulse by just simply looking at the content that you're putting out and making sure that you're paying attention. How does it perform? How are we using that information to leverage and change what we do? But yes, go deeper.
Speaker 2: (04:11)
. You know, one thing that's pretty funny to me, which is, I forget if it was Hootsuite who did this poll, but, um, the least looked at section of any social media management platform happens to be the analytics page, which is shocking. . Yeah. And it's why, um, this stat is true, which is 99% of all social media posts see zero engagement. Okay? Zero. So this idea of getting people to do what you want them to do and having the right tools and messaging to do it is obviously a real problem for so many. Um, I'll back up for a little bit to sort of discuss lately and like, you know, you know why we are sort of a different kind of generative AI you might say, but as you had mentioned, I was in the radio business, my uber power Mike is turning listeners into fans or customers into evangelists, right? And this is the sort of gift of being able to read a room of 20 million people you've never met before. You can't even see them, right? That's what you learn. And I'm old. So radio, radio was a thing. back in the day. It
Speaker 1: (05:18)
Still is. You're not that old
Speaker 2: (05:19)
. I still listen to the radio, but I have a high tolerance for like terrible radio. Um, and I yell at the DJ the whole time, like, shut up already. Um, but anyways, so back then you couldn't Google us. Really, you couldn't, there weren't websites happening, you know, there was no social media. And so we were taught to lean into this thing called the Theater of the Mind. I don't know if you've ever heard of that concept before. Um, but the theater of the mind happens when your imagination kicks in and fills in the blanks. Like when you read a book or when you're listening to a podcast like this, for example, right? And you can't see the images, right? And when the theater of the mind is, and your, your brain is engaging in that, it's tapping into obviously imagination, but nostalgia and memory and emotion to kinda kick, kick in this other, other, um, other character I guess you might say.
Speaker 2: (06:19)
So, you know, when you read a book, you go to the movie theater and then you're, you're mad 'cause the movie was not as good as the book, right? Mm-Hmm. That's how powerful Mm-hmm. That imagination is. And if you're imagine this, the author has to know this is gonna happen. So they have to allow for this unknown, I'm gonna call it a character, the human, the reader making up parts of the story that they can't control. Now they can guide it awfully well, and that's what your job is, you know? But the reason you're so mad at the movie not being like the book is because you have ownership in the story. Now, it's not a one-way street, it's a two-way street. And listening to someone on the air is the same idea. So your imagination kicks in and you're playing this role. And our customers, our listeners were saying they thought I was talking 20 million people.
Speaker 2: (07:06)
They think I'm talking to them specifically, right? That's crazy. What is that phenomenon? That's what I was really interested in, you know? Um, so then I, I had this funky experience where I, I went to my format, Matt, where, uh, Mike, where do you live again? What, what city? St. Louis. St. Louis. I can't remember the stations in St. Louis, but the format we worked in was called Triple A or Adult Album Alternative. There's like a hundred of them in the country. Not very much. It might be, if you've heard some cool rock and roll on NPR, it's basically that kind of music. Originally these channels broke, you know, the police and, and David Bowie and, um, talking heads back in the day. Um, but wouldn't be, wouldn't be like, you know, foreigner . That'd be classic rock. Um, ,
Speaker 1: (07:53)
You gotta be careful today. Classic rock is not what I grew up with
Speaker 2: (07:57)
As classic rock. No, it's not. I mean, because I don't consider, um, I love Eddie Vet's new single.
Speaker 1: (08:03)
That's exactly what I was thinking. Pearl Jam is classic rock. Classic rock today. And that
Speaker 2: (08:07)
Hurts me. No, I that hurts Me too. I mean, I'm sorry, but we're so, we're friends. So anyways, the formats, that format is usually like 20th in the market, whereas like country or rock, that would be number one, right? Stuff everybody listens to. And I was number one on, on the show in Carolina, and my boss called me after I left. And when the Arbitron ratings book came out and was like, what the hell did you do? How were you number one? And I said, well, I threw your playlist out the window, . Which is true . And I was crafting things in a way where I was designing, you know, new and old together. 'cause that's part of what the for is about, but also the segues and the way things sounded together. Like, I really love it when someone says to me, I hated that song until you played it.
Speaker 2: (08:56)
'cause you're surrounding it with other familiar touchpoint that are like, you know, it's like making mm-Hmm. , I dunno. Um, Brussels sprouts taste good. You just add a little maple syrup, right? You know? Right. Um, and so I was also the production director. This is a long story, but I think it's worth it. Um, and the production director is in charge of making all the commercials and then all of the IDs, all the station IDs that land between the songs, like, and so it was the me show for the whole four hours, but I also wanted to learn more about it. So I read, um, Daniel Leviton's book called, this Is Your Brain on Music. That was like a big, big deal book and very thick. I got through like half of it. Um, but this one part talked a lot about , the, the act of listening to new music.
Speaker 2: (09:43)
And what happens, Mike, is that your brain instantly accesses every other song you've ever heard over your entire life when it hears a new song and it's trying to index this new song Mm-Hmm, and find, find familiar touchpoint. So it knows where to index it in the library of the memory of your brain. Okay? And guess what, when it does that, it pulls on nostalgia and memory and emotion. The same things as theater of the mind. Also all the things that have to be in place for trust to happen. And when trust is happening and you've made the buying decision, that's when you get the evangelism. Okay? So one more part to this, which is, I was a fiction writing major and I'd written hundreds of commercials and radio, and I saw these parallels between reading and, and, and listening. And it occurred to me that when I write, or when you write me an email or a text or a Katie writes me a slack message, I'm gonna hear your voice in my head.
Speaker 2: (10:45)
And so if you're clever, you're figuring out, well, how do I pull on nostalgia and memory and emotion to get Kate to do what I want her to do and then love me for it? , right? . So that is a big component of what we pull into how lately works. So understanding what are the behavioral tendencies of people when they're reading social media messages? Like how do you, not only the words, and that's another topic we, we could discuss, but like, what's the motivation behind the words that'll make you do what I want you to do?
Speaker 1: (11:21)
And to your point, those words are important. Like I've studied NLP and you're, you know, you're talking about, you know, theater of the Mind. It's one of the reasons why one of the most powerful worlds in English language is to start a sentence with Imagine.
Speaker 2: (11:32)
Imagine.
Speaker 1: (11:33)
Right? You're commanding them to do exactly what you wanna do. 'cause you can't help but not to imagine whatever it is that I'm going to say next. You know? Right? It's, it's like, yeah. You know, don't think about a blue elephant. Well, everybody listens, just thought about a blue elephant, right? And if I, if I tell you, you know, imagine you're walking into the bedroom you grew up in as a child, you're all doing it. Absolutely. You're doing it. So connect the dots for us. You know, you're talking about the neuroscience and, and, and how you've ingrained that into lately in, in content. How does AI fit into that?
Speaker 2: (12:06)
By the way, I used to save my, um, bubble gum on the back of the headboard of my bed .
Speaker 1: (12:14)
It's disgusting. Fun fact
Speaker 2: (12:15)
In that room. Yeah. In that, in that room, .
Speaker 1: (12:18)
Um, and I just made you recall that, didn't you?
Speaker 2: (12:20)
Yeah, you did. Yeah.
Speaker 1: (12:21)
And that nostalgia,
Speaker 2: (12:22)
Bubble, Bubba Yba, was that it? No. Hubba Bubba. Hubba. Bubba, Bubba, Bubba. I like to grapee. Um, . So the way lately works is we have been studying social posts for about a decade and what, what specifically makes them stick. Like, you know, what makes you click, like, comment, and share. And what we do is when we use that information to kind help us understand what will make anybody tick, right? But first thing we do is we study your social media analytics. So you would log in and, and connect us to your Facebook or Instagram or Twitter or x or whatever accounts, wherever they are. And we are gonna jump back to the last 12 months of what you've been publishing there. And we start by creating a baseline and we'll rank what's performing well versus what's not so much. And then we're studying the patterns to patterns specifically within, so I can see of the content that does work well for you.
Speaker 2: (13:20)
What's it like, what's, what's it made of? What are the characteristics? What is the tone of voice? What's the phrases, the grammar, the sentence structure? Um, is it the link in a message? Is it a video in a message? So I can see all these patterns. And then the second thing I can do is I can understand from there what makes your unique target audience click, like common and share specifically what makes them take that action. So we call this a voice model. Um, that's my v and the voice model. Um, it's a living and breathing thing. It learns over time by understanding what's happening algorithmically on different social platforms. Understanding what, you know, Mike specifically is like, so if Mike is constantly publishing about, um, you know, sexy bowling shirts, then l Lately's gonna like, and it gets a lot of likes. Lately's gonna understand that this is a topic that does well for you, right?
Speaker 2: (14:17)
Um, but it also then can pull on the information that we've gathered over a decade of all of our other customers. We never share anybody's information, but we do look at patterns and we look at those patterns to help us, um, provide better recommendations, right? So we can understand that. Um, and then my special sauce too. So when I, um, post messages on LinkedIn, I get 86,000 views. Like I'm good at that. So we taught lately a couple hundred sets of basic rules that can really help anybody, you know, cut through that noise. So that's part one there. The second part is the human, as, as you and I know Mike of all people, the human capacity to outperform AI is still very, very high. In fact, um, AI is reliant on humans to succeed and do well still to this day, and will be for some time.
Speaker 2: (15:07)
And lately is no different. Um, what we've found is that AI alone fine, but when humans jump in and analyze and course correct it, you'll see a seven x in ROI. So that's why we've woven this fabric into the, the, the platform. And so what happens is if you get a result that you don't like in any way, if there's any edit that you make, if there's, if you trash it all together, the brain goes, oh my God, we didn't do a good job here. We gotta do something else. Um, or if you're constantly deleting a, a certain word or replacing that word with something else, you're just training it to learning it smarter, um, over time. And, and you end up being able to essentially thumbs down and thumbs up what it's surfacing for you to help keep it on, on the rails. Like when you go bowling, like those extra, what do they call those extra car rails there? The bumpers. The bumpers, yeah. . I don't use the bumpers. Sometimes I should .
Speaker 1: (16:03)
So I imagine that there are like key aspects or principles to, to music and neuroscience that you've kind of baked into this algorithm. Am I, am I correct in saying that? And and could you share what those are? 'cause I think that might help us understand why a lot of this works the way it does.
Speaker 2: (16:25)
Yeah. I mean, I'll give you an example. Um, so I, I worked for, I worked for Walmart for a few years and, um, in the Walmart project it was, there were 20,000 marketers all all collaborating on this big idea. And they were from Bank of America and at and t and United Way worldwide and National Disability Institute. So it was libraries and colleges and um, you know, little mom and pop shops. Like everybody was participating in trying to help lift the poor out of poverty through income tax credits and, and, uh, financial education. That was the, the thing. So, you know, a lot of an acronyms not very sexy. Um, and I studied what they were doing and I saw all these similar patterns, right? The largest retailer in the world had a really similar problem to the library down the street. And that they didn't understand what worked for them.
Speaker 2: (17:25)
And when they did understand, they didn't understand why, right? Generally as far as like words go. And so I was doing things like, okay, well in the zip code that we put this advertisement in Salt Lake City, it performed really well. So why don't we take the words there and try them on, uh, Twitter posts, , right? This idea of like just taking what works and trying it in different places. And then also how can you take a national message and then localize it so that the voices of the individuals who want to talk about the same project in a way that would reach their audience, work for them and not make them sound like super stiff as, you know, Walmart corporate might sound for example. So that's what we were kind of focused on, and those are the principles that sort of built those couple hundred rules that we have.
Speaker 2: (18:14)
So I'll give you an example of one. And they're pretty universal, right? Um, don't undercut your authority with what I call weak words and mm-hmm, , there are exceptions, but like, these are the words. Probably think just, um, maybe, right? I, I think versus, I know I just wanted to , I just wanna say, right? Yeah. Do you, we all do it. You know, like customer service should always do that. 'cause the customer service, you're taking the backseat, you know, . Yeah. But sales should not do that. And, and when you undermine your own authority, guess what? You kill trust mike. And trust is why we buy and evangelize. So it's, there's all connected, you know, types of things there. Um, so that's kind of one. And these patterns, like lately knows to not do them or if it sees you continually do them, it'll actually suggest recommendations and then help you try to help you understand, you know, why you shouldn't do that. Um, and let me share the proof in the pudding, right? So people are like, okay, I mean that all sounds nice, but this is social media and like who gives a hoot about it? So the difference between doing it the lately way and not doing the lately way is a 12000% increased engagement. 245% more clicks, 200% more leads, 40% more sales, and 80% less cost, right? So it's not that this is just nice fluffy stuff. We are giving you these suggestions. We are generating this content for you 'cause we know it works.
Speaker 1: (19:54)
So it's engendering more trust. What would you say some of the other things that this is doing and, and like, because we engender more trust that leads to more engagement, uh, it resonates more emotionally. But what, what else are you doing to the content besides gendering? More trust
Speaker 2: (20:13)
The action. So we're compelling people to take the action and in social that's clicks, likes, comments, and shares, right? Um, really I like to break it down to two, which is just simply clicks and shares. So, um, shares are pretty easy to get in general because what you have to do is appeal to the ego of the person who might be sharing your contact. People share content. 'cause it makes them look smart, right? Mm-Hmm. . And so that's why Gary v's one-liners go viral. 'cause everybody wants to say something like, you know, just smile and get up another day or whatever the positive message is, you know, nonsense. Um, but nonsense sell. Sorry, Gary. Yeah, sorry. Gary could be anybody. He's a er. Yeah. Is he, is he there? Hi Gary. Um, gv. So, um, that with, with the shares, I like to think of it back to music as you know, when someone in college came and played you a record and you're like, oh my God, this is life changing.
Speaker 2: (21:14)
And then you played it for somebody else and now you get the credit for it, you're the tastemaker. So same idea. So if you're backing into these objectives on social share or click and thinking in this way, like what will, so for example, check out my next episode of my show with Kate Bradley Cherice. Nobody gives a about that because nobody knows who I am. Probably checkout is the laziest, most vapid call to action one could use because it doesn't tell you anything about what you get from checking out. There's no, it's, it's, in fact it's spammy because it's sort of mis there's too much mystery there. Um, and then you, well, let's talk about clicks in a second. So you're not gonna get a share out of that. You gotta like pull out some kind of nugget of wisdom or yeah, whatever. That kind of thing isn't, that's is what lately does, by the way.
Speaker 2: (22:02)
Um, so because it's, it's, it's literally running down everything you said, looking for the most shareable content basically, and the content that will get people to take the action. So that's the clicks. Now clicks is harder because you have to really trust somebody to click. You have to know what you're gonna get if you're gonna click, or there's gonna be enough mystery there that you wanna resolve the answer. So for example, um, this is another one of the rules of the journalistic questions. Who, what, where, how, why, when did I miss any? I don't know. Um, why is the best one? Because y is always followed by because always, always, yeah. And so if you ask, you know, why, um, Kate likes grape purple, Hubba, Bubba, and then you put a, who knows a link there, who knows , people are compelled to click the link if they think that's interesting.
Speaker 2: (23:03)
Um, because the answer will be there, right? And you get double benefits because there's a question mark. And so all questions beg to be answered. People can't stand not having the answer. It makes you uncomfortable. Um, so you were gonna, so, so you're gonna wanna click that to find out what it is and, and you know, maybe afterwards you'll be like, Ugh, what a waste of my time. . It doesn't matter. You know? Um, so there's little tricks like that that you can use, um, inside the writing that are, that generally apply, um, that we do apply to what, what we generate for our customers, but we do it in your voice. And that's really important. Um, because I can see, for example, I would write go, I would write go. I'm gonna go, versus I'm going to go and lately knows that and it'll make those corrections for me, right? Or you know, me, Mike, I, I think I swear it already today, but I, I swear like a sailor I am, I try not to online so much. Um, so I make up hyperbole to get my frustrations out. And I'll say things like, holy hot, pickled jalapeno peppers, whatever lately knows that. And it will insert that content into my yammering.
Speaker 1: (24:15)
It's fascinating. And you even made another subtle point 'cause you talked about why followed by because, and because is yet another one of those magic words, if I say because and follow it with a sentence, most people are going to automatically assume that that's true and correct.
Speaker 2: (24:31)
That's right. That's right. Right. You get authority
Speaker 1: (24:34)
At it. There's a very famous Harvard, Harvard study where, you know, there was a big line to use the Xerox machine. This was a long time ago, folks . And, you know, people could cut in front of the line and as long as they said, because people would allow them to step in front of them to do their copies. And the what followed because could be the absolute most ridiculous thing. Because I'm in a hurry . 'cause I need to make copies. Well, of course you do. We're all in line to make copies . But because you said because we're we're just trained psychologically that neuroscience again allows us to just take that next action and assume that that's true. So I appreciate you sharing that. One quick clarification. I'd love for you to just explain a little bit more about the logistics of how lately works, because I know it's more than just me typing in, here's what I'd like to share on social media. I can share blog posts. What, what else, what else will lately read and help me turn into great social content?
Speaker 2: (25:29)
Yeah, so we work in a couple of ways. We love it when you ingest long form content, like you said, like it could be any kind of text, like a blog, um, or a press release, or excuse me, a newsletter. And it could be content that you created for your co, excuse me, company. This is my organic coconut water is giving me burps. Sorry, . Great. Um, so it could be something that you made like own media, but it could also be earned media, people writing articles about you. 'cause that's such gold out there Mm-Hmm. , you know, that people don't know how to market. So you can ingest that content into lately and it will actually read it with your model in mind. And it's trying to pull out the sexy tidbits that don't give too much information, but just enough to wanna click or share it, right?
Speaker 2: (26:19)
Um, and it will, it can give you quotes itself, but it will also rewrite that and take the quote and optimize it for you. Which those are the posts that really get the most engagement, obviously, which is, which is really great. And it does this with video and audio too. So like this show lately, we'll transcribe the show, give you the transcript if you want. Okay? It's gonna take the model, read the transcript, clip out what's, you know, it thinks is gonna get the best for you, and clip up the video. So the highlight of Mike talking about because, and the power of, because for example, and now you have 40 movie trailers all designed to promote your show. Um, and we can also prompt content too. So if you don't, like any con you don't have content or you don't like what you have, you can prompt lately to create something for you. You can prompt it to create video for you, like, you know, whatever you want. But the, the loop is analyze social, learn from long form, um, then optimize it and then predict what will continue to work. Like that's the flywheel of learning. And, and we, we integrate with anyone. I want an integrate integration with you guys. I know.
Speaker 1: (27:32)
Hint, hint. Yeah. Right?
Speaker 2: (27:34)
Hint, hint. Yeah. Yeah. But even if, even if you, if you are a massive Agora puls plan, you, you can still play with lately and just download everything we create for you in a spreadsheet and upload it into Agora Pul. So it's, we love everybody.
Speaker 1: (27:47)
That's right. That's right. Folks, we're talking, if you're just tuning in with Kate Bradley, turn us about the neuroscience behind effectively using AI and social media marketing. In a moment, we're gonna get into some specific examples to help illustrate the point. But first, a quick message about how important it is to measure the success of your social media messaging.
Speaker 3: (28:06)
Actually can't say enough great things about the reporting with Agora Pulse. I feel like that is my job security every month. My clients aren't that active on social media, which is why they have me manage their profiles for them. And when they get that report, it verifies that they're making a good investment.
Speaker 4: (28:21)
The metrics, um, downloads are so simple and easy to read and it really helps me show where we are doing things right on social and where we need to improve. So
Speaker 5: (28:31)
I think one of the main reasons why we decided to move to Agora Pulse, um, is because it's a more comprehensive, integrated tool for all of our marketing needs. So rather than what we have had to do historically with Sprout, which is use certain parts of that fe that that platform that work really well, and then supplement it with other outside tools, by moving to Agora Pulse, we were able to keep all of that into one, you know, into one technology platform, which is not only a time saver, but it also makes sure that our analytics and all of our reporting's on point because we're pulling all from the same source.
Speaker 6: (29:06)
It's a really great platform for agencies. It makes it really easy to manage. Um, but gives me really, really, really robust information that actually helps me, um, develop better strategies for my clients and better plans of action.
Speaker 1: (29:27)
So Kate, let's get into some examples. Could you share a specific case study or example where Lately's AI informed by, by music and, and neuroscience actually helped improve someone's, uh, engagement? Or ROI even?
Speaker 2: (29:43)
Yeah, thanks for asking. So, um, my good friend Jonathan Winehart, he's over at, um, Phillips Electric or signify, which is Phillips Electric, um, com owned company. You know, they, they sell light bulbs among other things. Um, so Jonathan had a really good idea. He wanted to do kind of a runoff of lately and figure out like, is our old way good is the new way better ? Like what's the deal here? Right? Um, and so what the, the plan was like, let's do a test. Let's have 16 posts written the old way and then 16 written the lately way and do a little runoff and see, you know, what happened. So the first win for them was kind of interesting. So they were using an agency and they had in-house content creation, and they were really frustrated because the agency was always getting the key messaging wrong.
Speaker 2: (30:37)
And so then they were having to go rewrite what they were, what the agency was delivering. And that was really frustrating. And then even the in-house content, people were having a hard time, you know, getting the voices right. They were creating content for both the brand and then also the individuals that worked there who were doing thought leadership. And between legal and everything, there was just like this whole long product of, uh, process of writing drafts and, you know, edits and review and blah, blah blah. So we cut that workflow in half and then the, the second win was what you guys all know, AI does so well, we saved them 85% of their time in actual copy creation. Yeah. Which is crazy. So the average human takes 12 minutes to write a social post, a single one. They were spending 60 minutes on one be again because of all of the approvals and, you know, legal processes.
Speaker 2: (31:29)
Um, and then with lately, you know, not just nine seconds for one, but here's where lately really starts to separate itself from generative ai, um, as you know it, and certainly chat GPT. So the third win for Jonathan was saving 80% in the cost of their copy creation. So they were, uh, spending 40 grand on 200 posts, and now they can spend about $7,000 on the same 200. But the best part of course is, is the results, right Mike? So for lately, we saw an average reach increase of 115% average impressions, 279%, and average engagement's 152%.
Speaker 1: (32:15)
That is huge. It's absolutely huge. Love seeing those numbers 'cause that just underscores the, the whole point and the value of it. But as you know, I've got a whole nother podcast all about AI markets. I'm talking to folks every single day about this and it's interesting how people come on, what I would consider different sides of the fence when it comes to using generative AI for copy, for blog posts, for articles, for newsletters, and for social media. What are some of the misconceptions that you might wanna push back on, uh, when it comes to using AI for content creation and and how does lately differentiate itself in that space?
Speaker 2: (32:53)
Yeah, I mean, it's so interesting. Like we're lazy. Marketers are lazy. They don't wanna do their job. Number one, everybody just wants contents for content's sake. And their bosses though don't want that. Their bosses wanna make money and see results. And when you're using generative ai, it doesn't matter how good at a prompt you are, it can't possibly know anything about your target audience and know what will serve them because there's no analytics that I can reference to understand that. And it can't actually get to your voice either, right? It, I mean, it's impossible. It's not tied, again, not tied to anything. So that's one thing I think to, to really think about. Um, and I guess the answer is in that proof of the pudding, right? So if the content you're generating from chat GBT is getting you 12000% more engagement than it was before, then great.
Speaker 2: (33:42)
But I mean, I know it's not , I know it's not. Yeah. Um, I think like the misconception around AI is that it'll be a magic saver. And like, like I said, zero 99% of all social media posts, even those created by chat JBT 'cause chat, JBT doesn't know it will land either get zero engagement, right? Still the human is smarter than the ai the human is not faster than the ai. That's a different story. Yeah, you can get garbage quickly all day long, but great. What are you gonna do? Put more and more noise out into the world. Like that doesn't help you or your brand. So I think the, the biggest thing is for the people who care about making more money, you have to police your employees because they don't give a about that. They don't. They just wanna get their job done and go to lunch.
Speaker 1: (34:35)
That is a hundred percent right. There's just too many people who are, to your point, thinking about AI as a magic wand or magic button and just say, yeah, I'll put me this, I'll put me that. I do think if you spent enough time, you can train Claude or chat GT or one of these large language models to speak in your voice and do all the things. But I love, this is why I love tools like, like lately because you, you've decided this is where we're going to help marketers and this is how we're gonna do it. This is how we're gonna leverage AI and we're gonna build in all the things that you should be doing yourself if you were going to use a large language model natively. But most people don't. Most people aren't crafting, you know, massive custom gpt and loading up personas and analytics and and draft documents and examples of blog posts for writing to get their tone and everything so that they could have all that and then ask a simple prompt and get an amazing response. But you've got all that built in.
Speaker 2: (35:31)
Yeah, it would take too long. I mean, so lately can learn the voice of every single employee in your country, uh, country, in your country, in any country, but in your company in about 30 seconds, right? So you can't possibly ingest enough content for chacha b to do that for every employee 'cause it's just impossible. Um, 'cause that would be super human, you know, heavy. One of the other things that I think is really important to, to think about is that human contribution we talked about with the theater of the mind. Remember how powerful that is. When, when you play a role in the process, that ownership that you feel is what drives home the engagement, the the connection, the sale, right? And the evangelism. And that's, so that's another thing is like, you know, thinking beyond the sale, how valuable is that evangelism on top of it?
Speaker 2: (36:20)
That's what longevity is in, in any company. You know, um, Netflix got it really right, by the way. So they used automation to learn the patterns of what we all wanted to watch, remember those little origami envelopes that we all had to put together and they were recommending some stuff based on what we watched, but then they got real smart because they could see the patterns were so clear. So they're like, let's spend $10 million on every show of the Crown. 'cause now we know we can make it. Right. So that's, that's the difference of when you're actually using AI in a way where it's getting you that gangbuster results. Not just doing the sort of the automated, um, you know, kind of nonsense. The other story I like to tell Mike is the Betty Crocker story. I don't know if I told you this before, but, um, it's a good one.
Speaker 2: (37:12)
So you like Cake in a Box, I assume? , yes. Doesn't everybody, I, I hope so. I mean, did you know you can freeze it by the way? You can. You can like make half the cake and freeze the batter and then make it again later. Um, I do that because I don't eat, I don't eat cake, but my husband likes cake on his birthday, so I make him half a cake every year. Um, so when Betty Crocker was coming out and with their cake in a box in the fifties or sixties, whatever it was, they were selling to Housewives of course. And the pitch was like, you know, boom, this is cake. And the housewives thought it was so weird 'cause they didn't feel any ownership 'cause they didn't feel like they were making anything. And so Betty Crocker took the powdered egg out and then the slogan became just add an egg and the sales skyrocketed because now the housewives felt like they actually did some baking here, right?
Speaker 2: (38:05)
So this idea of the human collaboration with the results, right, that come out. So whether you're using lately or chat GBT, it doesn't really matter. Like you have to take the results that come out, you have to course correct and analyze them. Lately we'll learn from what you're doing. Chat GBT will not by the way 'cause you can't feed it back into a continuous performing performance learning loop. Um, but anyways, even that step of doing that is so, so important because the results that you'll see of the readership or engagement or whatever it is, you're, you're, you know, you're looking for will be seven x, right? That's Harvard Business Review. Did this study, not me,
Speaker 1: (38:42)
Right? Yeah. In fact, it is funny 'cause this is why Ethan Molik, the Wharton professor has, has said, jet GT's naming model is absurd. It doesn't mean anything. The most, you know, we're recording this on September 18th, they just released Che GPT-4 oh dash preview. What does that mean to anybody outside of that organization? A one oh preview, you know, whereas you look at Microsoft and what is Microsoft's AI solution called? Co-Pilot.
Speaker 2: (39:15)
Co-pilot. Yeah, exactly.
Speaker 1: (39:18)
Brilliant, brilliant marketing there. Because it, it sets the expectation right from the start, oh, this is not taking over, it's not taking my job, it's here to help me. It's here to sit in the seat next to me and allow me to do my work. 'cause I'm still the pilot, I'm still flying this plane. At least that's what we tell ourselves, right? . Yeah. So how do you see all this playing out? Oh, how do you see the future of generative AI evolving? And I know that's a really hard question with a technology that's evolving so quickly, but what do you think marketers should be aware of today?
Speaker 2: (39:49)
Yeah, I mean, no one, well, in, in our world, in the writing world, people can pretty much still smell AI and sniff it out quickly. They can tell, I mean, God, LinkedIn kill me now. Every suggestion it makes me is so bad, right? Yeah. Like, has nothing to do with me or my voice or anything. Any, it's so like they, they're just got Emily Post stuck up their. I'm like, guys, this is so stiff, really. You know? Um, but so that said though, like I've said this before, is the, the like, like on a food, you know, the label, like we're gonna have something that says like, X percentage of this was written by ai, by ai. I, I imagine that, um, hopefully we won't go too crazy with that. Like I just noticed on, on TV now with the ratings that it says stuff like may contain smoking.
Speaker 2: (40:38)
Like, oh people, oh, may contain kissing. Kissing is too much for someone to watch Jesus Christ, we're overs sensitized. Um, but anyways, so, um, that I'm, I'm curious of when that's gonna happen and what kind of regulations will be there with the, okay. Again, we're sticking to jet to text here. Not, I don't even wanna talk about video and deep fakes and all that kind stuff 'cause that's that's too crazy. Yeah. Um, you know, the storage, by the way, my husband is in this field, which is really interesting. The, the storage mines, the, the data housing for AI is actually suddenly exploding because people are starting to ask it smarter questions than before. So it has to, and bigger questions. So it needs more, it's taking up more energy. So it's gonna be driving one of the, one of the biggest sort of energy sucks on the planet pretty quickly.
Speaker 2: (41:29)
Um, so that's just an interesting thing to, to know and, and consider, you know, for me, we're always trying to think about h how can we get humans to want to do the work that it takes to get the optimal results? Because this is our achilles heel. As humans, we're so lazy and we, we've even trained ourselves to be this lazy mike. So like the number one, um, skills lack across the globe when people are hiring is analysts, any kind of analyst. And it's because for so long, the last three decades or so we've pushed this phrase bring me solutions, not problems. And so as humans we're, we can't identify problems. So it's like, um, I was talking to my, my friend has two 13-year-old daughters. They're very intelligent. They know they can Google or ask chat GPT or whatever, but they don't know what to ask.
Speaker 2: (42:27)
They don't know what to Google, right? So they're the, the opposite of deductive reasoning, whatever that is. They're, they don't know how to back into the solution I guess you might say. So I find that really fascinating and especially because of what we talked about before. Right now, AI and humans are a hundred percent reliant on each other. It's a symbiotic union for one to exist and, and, and serve us well for both, both to serve us well. Right? The AI needs the humans to analyze and course correct what it puts out yet we suck at it. .
Speaker 1: (43:01)
Yeah. Right. Well and that actually brings us all the way back to one of the first things you said, which is that most social media managers are not looking at their analytics 'cause they don't know what questions to ask. So why bothered looking at a report that's filled with all kinds of numbers and graphs and things going in directions? I don't understand, I dunno what to ask of that.
Speaker 2: (43:19)
Yeah, that's,
Speaker 1: (43:20)
But this is where AI is gonna help us gonna be able to read that we're, you know, have a conversation then with the reports rather than just look at a graph and try to figure it out.
Speaker 2: (43:31)
Yeah. It's so funny. Like , so the number one question we get asked by my customers is like, so we surface word clouds that will show you like that, that words that are generating the most engagement for you. And so to me, this is so obvious. Look at the word clouds, the big ones go use those more. Right? Very easy . Oh, and guess what? You could take this information and do other stuff with it too. So if you wanna know the topic for your next podcast, go look here, there it is. It's in black and white. I can tell you what your customers care about, but people don't. So like I still will be running through their analytics with them, my, my human self and telling them this information. It's like a shock to them. And, and this is a shock. And this is Mike. This is like the top agencies in the world, some of the largest companies in the world.
Speaker 2: (44:18)
So it, it doesn't have anything to do with money or whatever. It's like people, either they don't want to understand it or they're too impatient. I mean, granted, this morning one of my sales team members shot me a big page full of numbers and I was like, dude, what does this mean, ? I didn't, I don't have time to read the numbers. I'm like, just gimme the bottom line here, you know? Mm-Hmm. so guilty. You know? Totally, totally get that. But um, and we're working on automating this by the way now because we know we, we have, we have to, um, although it is, you asked, you've asked a lot of questions that proves this point today. People do wanna know how the sausage is made.
Speaker 1: (44:59)
Yeah.
Speaker 2: (45:00)
They're curious about it for sure. Um, and for us, like that's been a very interesting thing to talk about because you know, we're not a large language model. We are an algorithm that sits on your language model, which is your social media analytics, right? That's it combined with other people's. And that education has been really difficult because now people have expectations of what generative AI is and I'm something else. You know? So those are my problems. Um,
Speaker 1: (45:33)
That's what we're working towards. But yeah, to your point, I mean one of the things that we added to Agora Pulse on the mobile app was you can go to reports and you can get an AI generated summary of those reports. 'cause people don't want to spend a whole lot of time in the numbers if that's not their job. So I totally get that. Folks, we are pretty much out of time, which is a shame. 'cause I know Kate, you and I can talk about these kinds of things for hours, but for folks who do wanna know more, they wanna learn more about either your incredible career or they just wanna know more about lately, where can they go to connect with you?
Speaker 2: (46:04)
Oh, thanks Mike. So, uh, I'm Kate Lee lately in a million places, so you can find me. Hey Brad, how's it going? ? Um, but lately is, lately ai that's really easy. And if you, if you find me on social, definitely tell me that you met me with Mike, so I can high five Mike in the background. And, and, um, you know, if you, if you have any questions about ai, best practices, anything like that, you know, let me know. And thanks so much, Mike. I love you, man.
Speaker 1: (46:31)
Awesome. Thank you, Kate. Thank you all of you for watching and listening. We appreciate you. Don't forget to find the MarTech show on Apple, your favorite podcast platform, and leave us for review. We'd love to know what you think. Take care. Thank you for listening to another episode of the MarTech Show, hosted by Robin Diamond and Mike Alton, powered by Agorapulse, the number one rated social media management solution, which you can learn more about@agorapulse.com. If you wanna make sure you're part of our audience during live weekly broadcasts, take a look at our calendar@agorapulse.com slash calendar, or click the subscribe button in your email once you register for any of these events. Is there a particular tool or topic you'd like to see us talk about, or perhaps you think your solution should be featured? Email me@mikeatagorapulse.com.
