AI + Culture + Strategy

Guy: [: 00:00:00

And if you haven't already done so, please visit pro relevant.com and sign up for all of these episodes and podcasts. As you know, I am the author of the up and coming new book, the AI Marketing Machine, and if you'd like more information on that.

Please go to marketing machine.pro relevant.com. Today I'm interviewing Omar Johnson. He's with Opus Intelligence and let me tell you a little bit more about him. So he's the founder and CEO of Opus and uh, which is an AI powered marketing platform built to empower marketers with culturally aware insights and enable more authentic and effective campaigns.

and Vice President at Apple. [: 00:01:00

That's great. So background wise, my marketing career has all been very traditional marketing, right? So traditional, and I learned it from some of the best, um, the CPG space, right? Consumer packaged goods. Coca-Cola craft. Campbell's, I always have admired the way they take a random product and you build a brand out of it, right?

So if you think about the commoditized things that those companies make, the magic is really the brand you put on top of it. So I learned pretty authentically how do you take almost anything and build a brand around it. Next chapter was Nike. And what was interesting with Nike is Nike is amazing at storytelling.

air means for basketball or [: 00:02:00

Um, when I left and I got thrust into a CMO role, and for me it was, could I bring it all together? Could I bring together the background on consumer packaged goods storytelling at Nike into a new category? And, um, that new category was beats. Now, from a context perspective, beats was. Like the whole category was $700 million when I got there.

Right. And I left, it was $10 billion. So we grew the pie, if you will. And then Apple, I'd say I started, technology started to become more important to me at Nike with the whole shift towards social media communication and earned media. Um, so I was always in these bleeding edge groups and Nike was the first company that introduced me to technology.

ats, which was technically a [: 00:03:00

That was a great sort of learning ground. But the pinnacle experience for me was, um, when I was on the board of a company called Qualtrics, and they're an enterprise software company. I learned so much between them. And at the time, um, one of their investors sat, um. SAP. So between those two companies, they created a pretty insatiable appetite to, as a marketer, I can keep making more money per, per hour or I can deploy my marketing knowledge at a scale of enterprise software.

and it's so interesting when [: 00:04:00

And then I like your point about, you know, it's not only you know how to market, but then how to tell, tell a story. And, uh, I like your. You're thinking about, you know, what you learned at MIC, at Nike, to be able to tell that story in a, in a way that really makes sense for your, for your products and your brands.

Yeah, and back to the point on McKinsey, I think when you become really good at it, whether it's the CPG marketing or Nike, as much as everything feels very new, and the idea is always innovation and marketing innovation. You start to see the patterns, right? You start to like the matrix, see the numbers come down the screen where it's not all different things, right?

ce. 'cause then you start to [: 00:05:00

Mm-hmm. Why would you not use technology to aid in a bet? Yeah. Right. Your speed, your precision, and your ability to scale. Yeah. Well, you know, to your point about McKinsey, uh, I was, uh, I worked for one of their competitors at Kearney for a a while. And, um, their process, uh, is not only to get to the answer, 'cause you're absolutely right.

The senior guys on our team, I was a, you know, I was a low level guy and, and the senior marketers. Or the senior consultants, they knew what the answer was within like 10 seconds. You know, they'd been, been done it, they'd done it before and they'd been there before and, and they knew where it was going and okay, there might have been some, you know, polish around the edges.

mpany. 'cause there's always [: 00:06:00

Agreed, agreed. But this is what you just spoke of is also is what shapes the AI adoption challenge, right? So when you think about big. Right. You know, it's, you can't go on your boss and say, Claude told me. Right. That's probably not gonna do well for you because your boss is gonna say, well, I got Claude too.

oint, the socialization side.[: 00:07:00

Because you're able to walk people along your journey. Yep. So, uh, you've got an incredible background, but now you're at Opus Intelligence. Tell us about that. Great. Um, so Opus Intelligence is a generative AI tool, which is built to solve marketing. Now, when I say solve marketing, and that sounds like a big surface area, right?

Marketing for me has two major components. One, which is what I know about my consumer. And who they are and how I target them. And the opposite side is then what do I create right? To get them engaged with my product or service, whatever it may be. Our system works to do both, to understand your consumer, your product, your product category, macro trends that live around it, and then helps you think about how do you smash those things into a brief to then whether you're driving a human, creative or generative machine.

opposite side, right? When I [: 00:08:00

So Opus Intelligence is a series of tools that takes you from what's your marketing problem. To hear some viable outputs that not only have what the traditional LMS would give you from a, I read the internet, here's how other people have done it. But then what's Omar Johnson's special sauce? I'll give you some versions of it.

Like for me, I typically start with our media. Our recommendations typically start with our media. Now when I say it, it sounds obvious, right? But most people start with paid media, as you know, right? Um, because, well, the first question is like, what's my budget? You put that in, it gives you an output. Well, you're probably not gonna get a breakthrough answer if you start with What's my budget?

we've taken our knowledge of [: 00:09:00

Yeah. Yeah. Makes a lot of sense. And to some extent, uh, you know, when we were talking before, uh, as you were talking, I was also thinking that, you know, the, the intuitive or the intuitive general intelligence, whatever, however you wanna define that, I think you're right, is, you know, it's a long way off. But, um, one of the things though that's interesting though, is, uh.

Um, is AI from an agent perspective, so agentic ai, you know, there's gonna be a lot of agents and some of them are gonna be more comprehensive than others. And it sounds like that's kind of where you're at, is putting together the agentic AI so that I can make the right decisions in, in marketing, uh, you know, across all of the marketing functions.

full rag marketing operating [: 00:10:00

You know, for me it's always been about these small jobs and its interface of help, so they're much smaller versions of the bigger system that we've built, and there's obviously a combination of it. I, as a storyteller who's also building this, so much of how the system works is very much how the human system works, right?

There's no person in the company outside of the CEO that knows everything, and even A CEO, he typically knows everything. At a summarized level, I leverage different subject matter experts. With unique training to come together and bring answers. And as we think about agent design and its operating system, we think about it almost through the lens of those roles.

opywriting, right? So giving [: 00:11:00

You get a little less consistency in answers with these tools. But when you can give them really tightly defined jobs, they're actually, I. At, at least ours do. They perform really consistently. Yeah. Yeah. And that makes sense. And it's, and it is the consistency and it's also the, you know, the lack of, uh, hallucinations and making sure that it, that the AI stays on track, uh, you know, for what you want, as opposed to, you know, what it kind of hallucinates.

ers. I. Yeah. So let's start [: 00:12:00

Right. So job wise, as marketers, we're always, this is what I, I try and remind marketers is we're doing the work, the correlated work to AI today. We just don't always see ourselves doing it, right? So there's all these inputs that we look at as marketers. We look at consumer inputs, we look at category information, we look at past things that have happened in the past or research.

We typically wanna understand like macro trends, so we have a series of inputs that we always want to look at when thinking about marketing with culture, relevant marketing. You really have to understand consumers and consumer behavior and what's happening to them, not just through the lens demographics.

ht? You think about people's [: 00:13:00

Mm-hmm. It's dynamic and it's hard for a marketer to keep on top of those changes every day. AI can be amazing for that, right? A lot of the way our system works is it's always keeping a beat on our customer's client and the changes so that client can see changes. And to have a human do that, I would need an army and we can use machines to do that.

So from a consumer perspective, that's one interesting dimension. The other one is around trends. Macro trends and macro trends happen fast. There's a speed and like there's, they're so temporal. That you've gotta have sort of ongoing curated tracking. And again, our machines do that really well. So from a consumer intelligence perspective, from a macro economic trends perspective, the machines do a great job.

l the decks a client has put [: 00:14:00

You also get to index and organize that information. Typically, we do it mentally or through file systems and folders. Well, you can do that a lot more. Um. In a way more scalable way using some of these tools. I'm a, my training has taught me the most important part. Important part of marketing aren't the ideas, it's all the inputs.

Mm-hmm. How you organize them, how you create, absolutely. Yeah. So for I am, I've always been a bit of a nerd and I spend way more time on the research side of a customer than I spend on the ideation side. I spend way more time understanding behavior, behavior patterns. So these machines, um, can be immensely helpful in those tasks.

you fact find it, fact find [: 00:15:00

We're seeing our ability to do, um, those bodies of work. The cost to do it's cut by about 75%, which means we've been able to cut 75% at a time out of it, which is huge. I think we can get those into the upper eighties or nineties. As we get more control of prompts, so that input part of the process for how do you get to a great marketing answer, AI can be extremely valuable and to me it is the biggest value dimension on the creative side, the generative side, obviously, you know, being able to say, I want to build a mood board with low camera angle shots to create this mood.

nk when most marketing ideas [: 00:16:00

And when you think about knowing all the inputs and then being able to convince a client that this is what they should do, and being able to visualize that. That's a big chunk of the creative process, right? It only leaves execution after that, which the machines can't do yet, right outside of programmatic, but that's a huge.

When I think about the, you know, plus trillion dollar TAM of advertising, a lot of that time is spent in those first phases where I think AI can wipe out about 75% of it. So those are the benefits of not only a system like ours, but also ai, where it gets tough. Um, I mean, where are you gonna have challenges or what?

You said there's gonna be [: 00:17:00

But that's all in a marketer, and I think those can be solved. And, and then I think the last dimension is, this is weird positioning where the world positions agents as assistants to people. I think over time there's a bit of an inversion where you can have a lot more agents running in the world where you as a human can assist.

ougher part is the, the work [: 00:18:00

Hallucinations will always be a part of these systems, which is why you still need humans involved in a process to quality control. So, you know, in our business we've made sure they're still humans to help other humans. Um, because again, I go back to like, there's not many people I can walk to their boss and say.

Opus told me, or Marco West told me, or Claude told me that human side won't dis as long as Wall Street demands that there's a human CEO, that human CEO is gonna need other humans to sort of give them trust and, and sort of confidence. Yeah. You know, it's interesting, uh, as you're saying that because the, uh, uh, I mean first there, there has to be humans, although.

er that was. Uh, what was it,: 2001

It doesn't, the, where the AI just doesn't know what the answer is. And so it's, it has to make it up. It makes, it makes sense. You've told it to give me an answer, so it's gonna make it up and, and, you know, and or there isn't any data there, so it says, well, I can make up an answer that might be, might be right.

And let them figure it out. Let them kind of, you know, figure that out. Um, yeah. Very, very fascinating. Okay. That, that won't change. That won't change. I think, you know, long as these machines are. Told they must have. They will at some points make them up. And that's where I think humans have to continue to be involved.

And again, I just think it's a bit of reorientation. I probably spent a lot more of my time looking for hallucinations now than doing desk research, but that I think makes them work. Yeah. Well, and, and maybe, uh, you know, what you could do is, uh, and I don't know, I haven't tried that from, you know, a prompting perspective is kind of like give, you know, just give me answers to the 80% level.

ric, you know, at the one or [: 00:20:00

Have you seen that as well? And, uh, how do you, uh. How do you, how do you look at it as ai, you know, in terms of being able to, you know, take that strategy and then e even build out the strategy, but also then to define the, uh, the campaigns and, and things like that. Great question. So I'll give you two again.

an answer, right, to lead me [: 00:21:00

So from a strategy perspective, that it can play a huge role in being able to see tons of information, not only from, you know, your client. But also you can bring your knowledge to a problem. You can also bring outside knowledge. So I think from a strategy perspective, we're seeing it give us huge scale and advantages.

Mm. It also, you know, our outputs speak in multiple languages, so we're able to deploy strategy in multiple languages, which is, that was, that is easy before on the tactic, creative side, making sure there's an integrity of all those inputs. Into some of the outputs and what I was called giving you a springboard.

me a question to, here's all [: 00:22:00

I can get to those things a lot faster on the tactic side and what we tell our clients is it's going to get you about 75% of the way there. Now, if you think about the time savings. It's 90% cheaper than what you pay an advertising agency. So I take a 75% probability to cut out 90% of the cost. And then that's where I think us as humans.

ency fees, but if I get that [: 00:23:00

And so, you know, I don't know if I would agree with how you, you did the math there. Mm-hmm. And, and I, of course, I'm a marketer. No, no, I get it. So my marketing stuff is incredibly valuable. I get it. I get it. And look, here's what I'd say. We've, we've got business cases, right? So we've done campaigns, a huge discount to others.

Again, it's the jobs, right? So when you look across all the jobs, I as a marketer, pride myself and this company on desk, on research, on really understanding our consumers. A lot of our costs were driven by us understanding consumers. Trends, what's happening in market, what's happening in culture. I've now trained products that can go out and grab that information for me and bring it back to me.

tterns to it, the better the [: 00:24:00

So again, for every company it may be different, right? We tend to spend our time assessing about consumer and return on investment. And while I think a lot of other marketers would say they spend a lot of time on return on investment, they just, in my past career as a CMO. Watching a lot of advertising agencies and paying a lot of money to advertising agencies.

There's a lot of ideation work that happens. And they make it my job to tell 'em if it strategically lines up with my business problems. I always wanted to focus on the opposite side. What are the business problems consumer? And again, these machines have been immense at understanding that. Yeah, that's where our speed comes from.

what's guided, that model's [: 00:25:00

So again, I think for our marketing process, which is consumer obsessed. And culture obsessed. We've been able to have huge at speed advantages driven by not having humans keep on top of what's happening in hip hop music and what's happening in sports, and what's happening in the conversion, the two, what's happening in fashion.

All those spaces that require someone to be reading every day, every moment. Mm-hmm. Um, get really expensive. Yeah. Yeah. So, um, uh, I, I mean, I exactly, uh, let me just change the, to the topic just a tad. So do you see that there's maybe, uh, some different industries where AI is maybe more applicable or less applicable?

to mind there? Look, I think [: 00:26:00

A lot of information lost by human information transfer. Um, so knowledge work and a lot of industries I think can be impacted by these tools. Yeah, definitely. But, uh, but what about an industry, you know, in marketing? Now just let's focus on marketing. Uh, do you see any specific industries? 'cause a couple come to mind for me.

ted industry like banking or [: 00:27:00

Right. And moves and moves on you. Yeah. In a big way. Yeah. Again, so his, I'll give you a couple. I think it's going to disrupt a lot of how marketing works. I believe that, right? Not everybody does, but I think almost everything up until I have a camera shooting a person. So when I have another human to manage, I think machines will struggle with that.

But the process of problem solving, bringing in con, bringing in inputs, synthesizing those inputs, building a strategy around it, directly driving where creative should go from a scripting perspective, output perspective, spec perspective. I think you're going to see huge time advantages driven by ai. So I tend to look at the big.

problem that needs to get to [: 00:28:00

Person stand here, here's light shoot camera. But it shifted that entire, that whole workflow. Um, social media had a huge impact, right? SaaS has been the next big dimension of, of. Speed and, and change or more efficiency in work. And I think AI is the next big dimension of, like I said, speed, change, precision, and scale.

our organization. Um, how do [: 00:29:00

And, um, how can the, you know, the. The, the top level executives in marketing and even maybe the CMO, the CEO, and maybe some of the other C-suite, how can they really say, you know, I trust this answer. I'm about to, uh, build a plant to produce that product that you said that AI helped you with. And we're gonna invest, you know, $50 million in, in doing that.

How do you build trust, uh, you know, for them to say, yep, I'm ready to, I'm ready to, you know, to pull the plug on, or I'm ready to, you know, to plug that in right now. Right. Great question. So again, I think there's a parallel to how the human experience works and, um, it's less about is the AI right or wrong?

ploy my trust. So it's not a [: 00:30:00

Because once I know that, I then have the breadcrumbs of the decision making, and I can define what a hallucination is. Or what's a stretch of like, you know, a good stretch of thought, but it all goes back to me as a marketer to know. But again, I go back to when I say the human vector of this is I don't just walk up to anybody in the organization and say, Hey, can you help me solve an engineering problem?

I go and I ask the person from Stanford or Georgia Tech or MIT, the engineering problem because what I know how I was trained, I know when they were trained, and I know they're pretty good when they get trained. I think these are questions that executives have to start to ask. So again, I, I think that the part that I've been trying to teach marketers is the work is on us to do this work.

ary. Right? But if we do the [: 00:31:00

And, and you know, as I learned, and I think you did too, is that that process is about building trust and selling the solution into the organization. And, uh, in a similar way. That's exactly what you're saying is that once I know what the data was, I know what the theory was and the concepts behind the training, and I know who, you know, did the uh, you know, the development of the model, you know, then that.

essful out there, especially [: 00:32:00

If you don't know the answer is going to work. Yeah. Right. No, that's true point. The methodology, the past success. Yep. The trophies, the awards, you're betting on that, right? Yep. You don't always know, as you know, so you're still making a bit of a bet. And, um, I love what you said because it is about, the trust to me comes from the understanding of what the inputs were and how those inputs are representing themselves in the answer.

relevant marketing is worked [: 00:33:00

However, um, the one thing I can tell you is that it's consistent based on how I think. And as we add more thought leaders, I can say yes, it's consistent to the way that person thinks, but that's essentially what the trust factor comes from. I. Omar Johnson's success or guy's success in the past? Not the machine, if you will.

Yeah, yeah. I hate to say it. Uh, we've gotta cut this a little bit short. I think we're gonna have to do another second, maybe a third or a fourth session. I. Uh, this has been absolutely phenomenal and, uh, you know, I've been writing notes down here on what you've been saying and thoughts are just going like crazy.

ready. I don't care what you [: 00:34:00

I think that's the only way we move forward. Right? Yeah. It's like you need a little bit of friction in these topics. Yep, yep. Um, to move this industry forward. So, and I think any industry, right? And they never move forward through just consensus, right? Yeah. We're watching that happen. Some countries, so for me, I.

Find some things you disagree on, let's go have some fun. And, uh, absolutely. We're sad about it. Yeah. Well, I do have one last question for you, um, and that is, uh, I used to ask, uh, you know, what advice would you give an up and coming new marketer? Yes. But, uh, what advice would you give a new market or a younger marketer spinning maybe the market for a, you know, been working for a little bit and to help them manage their boss?

know, experience or they're, [: 00:35:00

And I'm thinking, you want me to snap this around our conversation around AI more? Yeah. Yeah. Right? Yeah. Yeah. It's. Look, I, I think it's very similar to the last answer I just gave you, which is all too often I've been, I've been a problem here also. 'cause Omar Johnson goes, we have ai, I. That means nothing.

Okay. If you're managing up, hey, say you're my boss guy. I am presenting a campaign to you. Here's all the data I looked at. Here's all the inputs I use. Here's the sort of time period I focused on. Um, guy, here are some strategic, um, documents that I use from our business to drive this idea that I'm gonna give you.

uts are a result of all that [: 00:36:00

You just hit it. You just hit it. All right. Before we just set up the answer. But 'cause the boss and and us, we had to do the same work to kind of get there. There's just assumption that they did the work. You assume that they read the books, they read the research, they did the, they did the work. Right? Now, if I show up with that answer with, in a day versus a week how to get it done, and obviously we're using machines to do it, but I think the explaining.

y, I never said the word ai. [: 00:37:00

So if you wanna look at it from an AI perspective, that's the AI definition of what I said. But I said it to you in a very simple, understandable, digestible way where you can say, Omar, why don't you include last year's report, Omar, did you include this research? You can then engage me in that conversation.

Yeah. And I teach, you know, I'm, I'm even having these conversations with people that work for me now. It's like you're gonna do a lot of the same job, but you now have different tools to do it. So you shouldn't be thinking about the, you know, manual for how to work with me. You can load that and that can be what you used to get answers, so you don't have to read it every week to understand what to do.

I think as we focus on that, [: 00:38:00

'cause then the conversation becomes about data sources and what you included versus what you didn't include tone and temperature and how far you let the machines go. You also pretty, you both at the same moment. Have a pretty clear understanding of what hallucinations look like because you have an expectation of the output because you fed it things.

So, you know, a young marketer, I'd advise you to, um, not walk into your office and boss's office and talk about ai, but talk about what you use AI to do. Yeah, yeah. And having. If you don't understand it, go understand it. Because the only way to understand hallucination from not hallucination is to understand what it's processing, how it's processing it.

me an anime commercial. You [: 00:39:00

Right? We went to someone else for that, and we took advantage of that curated knowledge that that person has. So marketers have been playing in ai. I. Before ai, they just don't. They haven't made the mental switchover to, like, I have these curated knowledge groups that I can tap into to answer questions and also bring them all together to give me creative outputs.

I think we have a lot less of an intellectual leap to make than some of us may perceive. It's just scary because you know, you now have a new machine that's doing a lot of what you did as a human. Yeah. No, I like that. That's great. Um, wow. I, uh, really appreciate it. You know, my mind is just going like crazy right now.

ll remember 'em all and I'll [: 00:40:00

So, funny enough, we've been in stealth for a while. We're now starting to merge outta stealth, so stay tuned for opus intelligence.com and our link. I'm updating my LinkedIn page weekly. So we're doing more things with big car brands, big sports brands. Um, so we're now starting to get into a public, um, momentum.

Look, I think we, some people build things in. The vacuum of like knowing the right thing to do. I've always been a fan of like building things with customers. So we've been building with some big multinational brands and exposing 'em to Opus intelligence before we bring it to the world. So, um, I just advise everybody to stay tuned for Opus intelligence, opus intelligence.com, our website.

Johnson And I'm on LinkedIn. [: 00:41:00

Omar, again, thank you so much. Looking forward to it. Looking forward to the book. Yeah. Yeah, me too. Cheers. Talk soon.