Manos: Once you create that piece of content, then the machines, artificial intelligence machine learning have a role to play in optimizing that content. How can you make sure that the content you’re creating is, uh, visually impactful is memorable. And it’s going to have the effect that you’re looking for
Lauren: From LS international. This is the career success podcast. I’m Lauren Stiebing. And on today’s show, we will discuss how marketing has changed with AI concepts, like machine learning, which help to anticipate your customer’s next move and improve the customer journey. Manos Spanos will be joining me today to share his experience and how even with more data it’s important to still listen to your gut. So Manos, thank you for joining me today. Really wanted to discuss with you about the role of AI and machine learning when storytelling in relation to marketing. But yeah, if you could start off and give me a bit of your background and introduction, that would be helpful.
Manos: Of course. So background, Greek, making his way through corporate America, born and raised in Greece and have spent most of my career in the us with three fabulous companies, Johnson and Johnson in the beginning for nine years across various roles in Greece, in the us, and then Pepsi for 10 years, very big part of my life, a brand and a company that I adore, Danone in north America came afterwards for two years and I was the CMO for the yogurt business in the us. And then since September, my, uh, L-Nutra stole my heart and my mind. And I joined L-Nutra to be the president of the consumer side of the business globally. And L-Nutra is a company that’s, uh, in a nutrition technology. It’s a nutrition technology company with a clear mission to improve human longevity through the power of nutrition and food. Several solutions deployed on how to do that with big brands like prolon, which is our fasting mimicking technology nutrition program or fast bar. That is our, um, intermittent fasting bars, as well as nutrition for longevity, which is our everyday medically tailored meals and other solutions that are coming on the way. So being with L-Nutra since September and trying to, to bring to the team what we’re gonna talk a lot about, which is, I guess, the fusion of AI with marketing that.
Lauren: Sure. Well, I know that let’s say AI and machine learning have been buzzwords that have been you a lot in the past years, but yeah, I wanted to hear from your side. So what role does AI machine learning play in today’s world of marketing?
Manos: Absolutely. You’re absolutely right. They’ve been overused overplayed to an extent that is dangerous. Look at the end of the day, machines are never going to replace humans, right? There is, but machines can work to get other with humans in my philosophy and what we’re trying to implement now in L-Nutra, there is a place for human intelligence and there is a place for artificial intelligence throughout the, the brand creation, content creation and brand storytelling process. They have different roles to play in a different balance. For example, when in the early stages of the process of brand storytelling, when you are gathering insights from the consumers, trying to understand who’s the right people that you need to talk to, what are they interested in? What are they talking about? What is their profiles? What are the common elements, how your brand should approach it? There is a lot of role for AI there.
Manos: So using AI technology and machine learning to gather insights in a very quick way, based on real actions of people, not what five people will say in a room, in a focus group. I think there’s tremendous value there. So there’s a lot of that that we’re using in the upfront piece of the process that informs a very, very clear brief towards the creative team, but the brief is made by humans. And then the actual storytelling, the actual creative ideas are made by humans and machine will never replace that. That’s where the humans come in. That’s where the marketing gap, the marketing creativity, that’s where that piece comes in. However, once you create that piece of content, then the machines, artificial intelligence machine learning have a role to play in optimizing that content. How can you make sure that the content you’re creating is, uh, visually impactful is memorable, and it’s going to have the effect that you’re looking for.
Manos: There’s very good work that has happened in algorithms and, and AI learning in order to analyze these pieces of content we work with, uh, for example, with a company called explain from, from Europe that does that very good. We look at the pieces of content and we make sure that we optimize them visually for impact and memorability this way. You know, that a storytelling that was created by humans is actually gonna have a very impactful outcome when it’s positioned. And you go into the next cycle of how do you handle brand storytelling, which is the deployment of it. And that’s where I think both humans and machines can work together. Media strategy is, is a very important thing. And a lot of the media strategy is done from people utilizing their experience, their gut feeling. But then there is the optimization and the optimization that comes with programmatic buying that comes with if tracking, analyzing, measuring the effectiveness of your campaigns.
Manos: And there obviously machine learning and AI has a very big role to play because they look at that, they analyze the performance. You make the changes live on the go 24×7 machines never sleep. So I think there’s a big role there. And then at the tail end of the process, which is looking the data analyzing and utilizing the learnings that you have to re brief and continue the creative, uh, direction, utilize the AB testing that you’ve done, understanding what worked, what didn’t work, and then feeding back into the loop. That’s again, where a lot of human analysis comes in. You’re looking at the data that are punched out by machines. You understand what went right, what wrong, and you feed back the process. So as again, as you see that whole process, I think there is a role for machines in the early part, in the middle part, in the tail end. But there’s also a role for, for human instinct and marketing guts to get into the system. When you get the two working together in a very good way, that’s when you get great results in broad storytelling.
Lauren: When would you say, if let’s say from the data that you have, you think that the data may be wrong, or you have a gut feeling that something is wrong? How much should we still use or still trust our gut
Manos: <laugh> we should absolutely trust our gut. There’s been times in my career that I did not follow my gut and I so much regretted it. Machines are improving the odds, right? They’re not faultless. And people like us that have the experience. You’ve done it multiple times. You see you get the feel, you get the touch, you gotta listen to your gut. There’s a fine balance. And that one does not have a magic recipe that really, really with each individual, there will be times when the data will say one thing, you’re gonna go and you’re gonna take a risk and, and do something different and that’s gonna work. So I listen to my guts just as I listen to consumers, I don’t always believe them. And I don’t always believe my gut, but I definitely listen to it. So it has a big role.
Lauren: And yeah, I mean, if humans are gonna be working a alongside with machines and let’s say, that’s how we’re gonna [00:07:00] generate the best results, what skillsets or behaviors do you think marketers will need in the future to really Excel in the function? Yeah.
Manos: Very, very, very important. Thank you for bringing this up. I have the pleasure of being at the board of the university of Miami business school, and we help guide the curriculum at that business school of, um, uh, for students. And I think it all starts there. It starts from education. It starts from what do both undergrads and MBA students. What is included in the curriculum that we’re going through? How are they getting better prepared for their real world? I think it is absolutely mandatory. Critical. Tell that there is data and analytics are part of the marketing curriculum in both schools in a very concrete way, not take an elective here and there, but make it part of the curriculum. I think business analytics is super important. Data analytics is, is super important and they have to go through that. The second thing that I think they need go through is understanding of how do you take this data and apply them in marketing, planning, and marketing creations of courses, around marketing, planning, media mix modeling and things like that are super important for, for them to do.
Manos: And obviously, as we do in the business school, we always encourage real life experience. So start working with startups, start working with companies that need help in this. As you’re crafting, you’re learning through the university, go and apply it in real world and, and see how it works. So I think it all starts there when you’re already in the game. When you’ve been a few years in, you’re going through your career, continuous learning is super important. There is fantastic organizations across the world that provide continuous learning opportunities. Either industry forums like here in the us, we have the Ana the association of national advertisers that does a phenomenal work in continuous education in conferences. Be curious. Curiosity is a very, very important trait in the marketing world. Go to conferences, read, look at podcasts, read articles, try to find what’s the new technology, but be also careful that it doesn’t mean that because a new technology exists.
Manos: It means we always have to adopt it, but be curious, inquisitive, ask about it, read about it. Perhaps try it in a soft way. I think that’s a skillset that is absolutely required. So start early, start from education. Once you are in your career, continues learning, have that passion to learn and find new things. Have an inquisitive character, ask questions, try the new technology, see how it works, but also be very critical to make sure that it’s not done for the sake of technology it’s done for the sake of driving business results. So measure, understand, and then implement. And if it works scale it, if it doesn’t work, move to the next.
Lauren: All right, manos. Well, thank you so much for your insight. Very appreciated. And um, yeah, we’ll keep connected.
Manos: Absolutely. Thank you, Lauren.
Lauren: Thanks.