Feranmi Muraina on AI in Consumer Insights & Foresight

2026 Future List Honoree Feranmi Muraina joins Karen Lynch to explore what it really means to lead AI transformation inside a global brand. With a background in engineering and brand management, Feranmi brings a scientific mindset to insights, demanding evidence, challenging assumptions, and teaching teams how to work with AI rather than blindly accepting its outputs.

From building AI protocols and cultivating curiosity across organizations to understanding digital communities and amplifying fringe voices, Feranmi shares practical strategies for embedding AI responsibly and effectively. He also discusses the future of foresight, scenario planning, and how AI can surface early signals that shape tomorrow’s markets.

This episode is essential listening for insights leaders navigating AI adoption while staying people-centered and future-focused.

Key Discussion Points:

• What it means to be a 2026 Future List Honoree and why client-side representation matters
• Transitioning from engineering and brand management into insights leadership
• How to create AI standards and protocols inside organizations
• Teaching teams to be naturally curious and challenge AI outputs
• Community-first brand positioning and decoding digital cultural signals
• AI’s role in foresight, early signal detection, and scenario planning

Resources & Links:

• Register for **IIEX Europe** (where Feranmi will be on stage)

You can reach out to Feranmi Muraina on LinkedIn.

Many thanks to Feranmi Muraina for being our guest. Thanks also to our production team and our editor at Big Bad Audio.

Transcript

Karen: Hello everybody. Welcome to another episode of the Greenbook Podcast. I’m your host, Karen Lynch. I am so excited to be talking to one of our Future List Honorees today. If you’ve been paying attention to our podcasts at all for some time, you’ll know that these are my favorite episodes to record because I’m talking to a generation and a cohort each year of really stellar thinkers, people who are working hard to elevate the industry, and today’s guest is no exception to that rule. I’m talking to Feranmi Muraina—he will correct me on that pronunciation if I’ve gotten it wrong—but he’s from the Magnum Ice Cream Company, Global Manager, Digital & Communities Insights, AI Transformation. It’s a big title, but he’s a brand to insights leader, pioneering AI transformation in global CPG, a human-centered advocate for ethically-grounded, digitally-enabled insights work. So, before I you know, even get into the topics we’ll be discussing, I want to welcome you to the Greenbook Podcast.

Feranmi: Thank you so much, Karen, this has been such a huge honor, and I’m so excited to be on the podcast.

Karen: Well, we will talk more about that, but before we get too into it, tell people a little bit more about your role so that they can kind of get a taste for the type of work that you’re doing and where you sit today.

Feranmi: Yeah, absolutely. So, I’m Feranmi Muraina. I’m Nigerian and I work at the Magnum Ice Cream Company. I currently work as the global lead for digital and communities insights and AI transformation, and that’s essentially a merging of two roles. So first, I’m in charge of digital insights, that’s getting understanding from digital signals like social listening, search listening, ratings and reviews, whatever you can get from the internet. And by virtue of that position, I am also leading the AI transformation for the company within the insights community. And that’s essentially changing how we do insights, how we understand our consumers, how we support the business with decision-making, trying to take technology and see how that can change the way we do all of these things to make it, you know, more qualitative insights for better decisions, can we do it more efficiently that’s faster and cheaper, you know? So, that’s the scope of what I do at the Magnum Ice Cream Company.

Karen: And for our listeners, if you don’t know the Magnum Ice Cream Company, let me tell you—and I even wrote this in the brief because it’s very important to my family—my mother is a Breyer’s ice cream loyalist. She always has Breyer’s ice cream in the refrigerator—I mean, in the freezer—and it is the only brand that she will buy, with the exception she does like Ben and Jerry’s Cherry Garcia, which is also a Magnum ice cream brand, which I did not know. And Klondike bars are almost always in my refrigerator because my husband loves them. So, I was very excited to see your name on the list, and I was glad that the judges ended up seeing what they like to see in the applications, which is just really great leadership and innovative thinking. So, what a fun brand. And, you know, it makes me think sometimes we have, you know, brand stars on the list of Future List Honorees, and we have a lot of brand partners in the industry as well. But it’s not always that we get to talk to them live, those who are on the brand side. So, I want to know for you on the brand side, what did it feel like being named as an honoree? You said it was an exciting honor. Tell me more.

Feranmi: Yeah, so I did go through the list of previous honorees, and I noticed that, you know, majority of them come from the agency side, and so it was much more of an honor for me, especially coming from the client side. And I think it’s also—I mean, this was my musing because I thought it was also indicative of the convergence between, you know, the agency side and the client side, and how some of the capabilities that used to be the exclusive remit of the agencies are now becoming something that, say artificial intelligence is able to make generally available, and then anyone can just leverage those tools and have those insights at their fingertips. And it’s just one of the ways that the industry is changing right in front of us.

Karen: And I think what’s interesting is also this is an honor for you that’s… you represent somebody who kind of has been out there before, but you’ve only really been doing insights work for about two years. Your journey has been very interesting. So, why don’t you tell our audience a little bit about your shift because, kind of, working on a brand, versus now working on insights which informs a brand is really switching into a supplier role from being on the client side for real. So, talk to us about that transition.

Feranmi: It’s funny because when I think about it, my first degree was actually in engineering, and then right out of school, I switched careers, I switched career paths as a way because we had this business competition on campus, and then I got in, and then I was successful, and then I decided to go into business full time. And I chose marketing, and of course, that was brand management. But then because of my engineering training, I think it kind of changed the way I thought because I was always looking for more information, more data. Like, the story, the narrative needed to fit, right? It wasn’t me taking a narrative and then looking for the data to back that up. Everything had to fit for me. And so, I was the bane of the existence of my insights person because I was always going to her—that’s because I was always going to her, “How did this number come about?” “How did we get this percentage?” Right? And so eventually, just to get me off her back, she had to, you know, teach me the methodology, teach me how to use the tools, and everything. And so, you know, I became, you know, an insights person, but not a name. And essentially, I would run these analysis, I would do these studies, and then I would go to her to just kind of vet it, to see, you know, did I do this right? Did I do this correctly? And so, right from the scratch, I was the brand manager that was also very, you know, deeply understanding of what went behind the scene with respect to the insights. And so, it was very easy for me to then transition from marketing and brand management into insights because, you know, I saw that that was the area that got me really excited, you know, learning about people, understanding what made them tick, you know, what keeps them up at night. And, you know, can there be a win-win situation where the consumer wins but also the business wins? You know, those were the things that really excited me, and so it was just a natural progression from there.

Karen: I think that sharing that experience is very helpful. I wonder what differentiates you from your work as an insights professional now, that you learned from that experience as who you were as a brand professional, and how you approach insights. Is it still the same? Are you still with that engineering, you know, show-me-the-evidence type of background, or have you evolved a little?

Feranmi: Oh, it’s even worse now, I would say, because if you think about it, I work a lot with artificial intelligence, and artificial intelligence does have the capacity to hallucinate a lot. So, you should see my conversations with the AI. It’s like, you know, show me, where did you get this from? Where did you get that from? How did you arrive at this conclusion, you know? You want to get down to ensure that, okay, this is actually backed by real data, right? And so, it’s the same logic guiding me, guiding the way I, kind of, got up to speed on insights and the way I do my transformation work right now.

Karen: I love that. And I can relate. I am also—it’s interesting, I am also very hard on the AI tools that I use where I’m like, “Tell me where you got that. See this sentence here? Tell me where you got that from because that seems out of place.” And we do a lot of talking these days about the need for human judgment over how we’re working with AI and certainly how it shows up in its work. So, that’s a very relatable statement when you say you’re hard on it [laugh]. Are others in your organization sort of following your lead when it comes to digital transformation? Like, are you teaching? Are you training? Are you mentoring? How is your role internally, just in that space, operating right now?

Feranmi: Well, like I said, it’s part of my job to drive this transformation agenda, and so one thing that I am finding that I have to work on is how to codify and create standards, create protocols with how people work with AI because the reality with any organization, any body of people is you have people on different spectrums of their capabilities working with AI, and so you kind of have to create this protocol such that people can follow and the least standard is ensured, such that, you know, people are not just taking AI at face value and taking the first response that comes from the AI. You get the skills that allow you to probe further, and you can kind of take on a position to what this AI is saying and force it to kind of, you know, double-check what it’s providing for you, right, just to ensure that the quality is there. We’re not just, you know, AI zombies in the organization. So, it is part of my job to also teach people, and it’s something I do actively.

Karen: Yeah, I’m glad they have you in that role there. And I imagine there are other brands doing the same thing, having somebody on the team, who is adept and has the background to kind of, you know, upskill others and set those standards of conduct or standards of work.

Feranmi: Yeah, absolutely. I think it is important, especially as we go into an age where AI begins to permeate every level of the organization. You kind of need someone just, you know, kind of watching the back of the organization to ensure that we’re doing this the right way and we’re taking the right approach to embedding AI in our processes. I think it’s absolutely critical.

Karen: Yeah, certainly we’ve come a long way in a very short period of time with AI, haven’t we? It seems that we were disrupted, and here it is, and now it’s a part of our work world. Are there any pro tips that you have right now, just kind of before I start talking about something else, just for others who might be on the brand side looking to set these standards or create some guidelines internally. Any pro tips you can offer people for how you’ve done it there?

Feranmi: Yeah, I think you always need the people. I think they’re a crucial aspect. You can have the best AI platforms in the world, you can have the best AI tools in the world, but if the people do not change the way they approach work, it’s not going to work. And I’ve been very fortunate because the people I work for, they’re very curious. They’re amongst the smartest people I’ve ever met in the world, and so, you know, they’re naturally curious. When there’s something to learn about AI, you know, you can see their eyes pick up, and then they’re already thinking of the implications to how they do certain things, and that’s really made my job easier. Because you need people to be able to envision how this could help them. Without that, it all falls apart. So, it’s absolutely important. But it is also teachable, right? You can teach people to be naturally curious. And so, even if you see that people are not having the reaction you need for your agenda to be successful, it’s something you can start with. Start with the people before you introduce the tools and the processes. This is what I always say.

Karen: Yeah. Now, of course, how do you do that? How would you teach somebody to be naturally curious? I’m actually very curious about that. Is there something that you say or that you kind of prompt people when you’re working with them?

Feranmi: I think the way to judge where someone is in that journey is to, you know, give them a problem and kind of watch how they approach it, right? You watch how they break that problem down into its composite parts, and how they then kind of solve each element of it because that speaks directly to their ability to kind of break problems that AI solves for them, right? And so, what you do is you teach them problem solving, essentially. What are the steps to problem solving? How do you go about taking a problem that you know absolutely nothing about, and how do you go about getting information to tackle every stage of solving that problem? Because only when you know how to break down a problem can you understand the chain of thoughts that the AI goes through in solving that particular problem. So, it’s one of the things I see that is very useful for me to gauge where a person is at in their ability to work with AI effectively. If you’re someone who just, you know, you just popped a question in the ChatGP, and you take the first answer that comes to you, then I already know that you have a lot to learn about how to work with AI because that is not going to serve you well at all, right? You need to be able to say, “Okay, this part of the problem, you got it up until this part. This is where you started to miss it.” And so, by giving feedback to the AI, you’re able to improve the quality of the AI, but also you yourself, you’re taking a step back and you can see the big picture and you’re able to guide the AI, and that’s already building your skills, your future fit skills. Because first, it shows me, you know, you’re thinking creatively, you’re thinking about the problem creatively, but it also shows me that you have, kind of like, a generalist skill. You’re able to see the big picture; I can see the part that’s missing, the part that doesn’t fit, and you’re able to give the feedback to AI, and it’s able to kind of correct itself, right? That is how you work with AI as opposed to, you know, taking what you want, like, hook, line, and sinker. If you do that, then the list of biases that will be in your work is endless, to be honest.

Karen: I love this. Thank you so much. And it just points out to me one of the values when people do make a kind of a bold career pivot—and I again, I keep thinking about you with an engineering background—and how somebody with that type of background who has this, you know, very heavy scientific method background is really skilled then in a career like insights. I think that serves you well. I was having a conversation with—my daughter is a science-minded young lady, and we were having a conversation, and she said, “Mom, where’s the evidence for that statement?” And I was like, “What are you even—‘Where’s the evidence for that statement?’” But she [laugh]—I was like, “I am not AI. Do not ask that of me again.” But it just shows you that the scientific method is alive and well when it comes to insights work.

Feranmi: Yes.

Karen: It’s very interesting.

Feranmi: That is so true. I think in this… okay, so I was going to say in the science world, your thoughts to think in troubleshooting mode, and troubleshooting, it requires you to, like I said, break things down into the different parts, look at the nodes and how they connect, and immediately you can see what’s wrong, and you can just fix something in the middle and the whole machine kind of starts to work well again. And bringing that same logic into insights, you know, I think has served me pretty well.

Karen: Well, for sure. And I think what I love about this conversation is, we have a lot of conversations on the Greenbook Podcast about AI, and here it is, and what you need to do, but this is actually very applicable. Like, here is how you practice what we preach about leaning into AI. It’s much more—it’s more—it’s less about just ‘lean into AI and get used to it,’ and more about ‘here’s how.’ So, thank you so much for this conversation. I’m sure there are people listening who are recognizing that there’s a mindset shift that you’re bringing to the table here about how to execute against this adoption of AI internally. So, thank you for sharing all of that.

Feranmi: No, it’s my pleasure. Always my pleasure.

Karen: I also want to understand, kind of, the aspect of your job that’s not just about kind of data, it’s about communities. So, talk to me about the community work you’re doing. How are you defining it there? What does that part of your role entail?

Feranmi: So essentially, it’s a level higher than digital signals, right? The way brands are approaching consumers right now, they’re doing that at the community level, right? We’re moving from speaking to individual consumers and we’re moving to speaking to communities because we see people merge around certain ideologies, they merge around certain parts of culture. And you have communities permeating every level of our society. And you have marketing campaigns now that definitely came out of an idea that was gotten from, you know, trying to understand the community and the way they speak to each other, the way they interact. And so, a brand that is able to kind of position itself within a certain community and kind of get recognized as part of that community is going to have huge success interacting with the consumers within that community. And you see this with a lot of brands, for example, you know, brands like Duolingo, for example, they’ve been able to tap into a specific community, right, and the idiosyncrasies there permeate that community, and they’re able to speak like those people. It’s essentially what brands must aspire to do in today’s world. And so, my job, part of my job, is understanding the digital signals of how people within certain communities that we’ve identified as where we want to play, how they are able to interact with each other, how they speak, how they show up because that’s going to influence how the brand shows up in the conversation. If everyone is wearing a black tie and you show up to that event wearing jeans and a t-shirt, you’re out of place. And it’s not just out of place where no one knows; everyone sees that you’re obviously out of place, and so you leave people with a negative sentiment, as opposed to a world where you don’t show up at all, right, and nobody knows you, you’re worse off than if you hadn’t showed up at all. And this is the power that communities hold nowadays. And it’s every level of society you see communities there.

Karen: Well, it’s interesting to think about this. I imagine it’s not lost on you that a brand has its own identity, and you might say, you know, the brand would show up the way the brand is because the brand has a strong identity, and yet what you’re talking about is kind of adapting and morphing on some levels, showing up at the way the community is. So, how do you translate, kind of, what you’re learning within a community that helps inform brand decision-making when there is a strong—your brands have strong identities?

Feranmi: Yeah.

Karen: So, tell me how you do that, how you help the teams balance what the digital signal is and who they are and staying true to who they are while still matching the consumer signal. Does that make sense as a question [laugh]?

Feranmi: Brands definitely have identities. They have things that they stand for. They have, you know, their core values, how they show up, and communities also have that. The sweet spot is when you can find a space where the identity of the brand intersects with the identity of a particular community, right? That automatically tells, you know, where you should be showing up. Because what you say you stand for, others are looking for brands who stand for that, right? And so, when you show up, it is a perfect fit. It’s a natural fit. It’s amazing. And the thing with brands is, when you look at the identity of a brand, the way you—perspective matters. The way you frame it, you can look at a brand, you can look at a community and say, “Oh, these guys have absolutely nothing in common.” But then when you frame the identity of the brand in a different way, you can already see a way, or multiple ways that this brand could show up in this society or in this community. I’ll give you a good example, the Magnum Ice Cream Company as it were, we like to think of ourselves as, you know, making life taste better with ice cream, like, you know, sharing happiness, that kind of positioning. And you can see that with some of our brands, the Wall’s brand, for example. And then when you look at a certain community, say, the gaming community, you can see that, okay, ice cream, gaming, you know, it’s a force fit. You can push it and it could work, we don’t know. But then, when you frame the core truth, core human truth, of what gaming speaks to, gaming speaks to a sense of escapism. You want to leave the current world you’re in. You want to play in a different world. You want to, you know, hang out with your friends. But underlying all of that is the core idea of happiness. You want to be happy within your space, within your room, right? And then you can already see if it was a Venn diagram, you can see an overlap of happiness there. And so, it then becomes a way where Wall’s could actually show up for the gaming community in a way that stays true to its identity but also meets the need of the people in the community. And all you need to do is, you know, you speak like them, you think like them, all you need to do is show up like them, and you’re part of the community. And that’s it.

Karen: Yeah, yeah. It’s a great example. Thank you. I—yeah. I have a son who, you know, ends his work days and games as part of that escapism. And I can tell you, after a couple of hours of gaming, he’s, you know, in the kitchen looking for some ice cream, so that makes sense to me [laugh]. We are an ice cream family. So, let me ask you this. I want to make sure we talk a little bit about something you’ve said you—and this came across in your applications, also for the honoree—you’ve described your work as people first, technology second. So, we’ve spent a lot of time talking about the technology and a little bit about, kind of, understanding communities, but in practical terms, what does a people-centered approach look like today, especially when it comes to AI? What is a people-centered approach?

Feranmi: So, when I say people-centered approach, this is what I mean. AI helps people understand people better. That’s always been my, kind of, positioning. And this is how it happens. Previously, before we had AI permeate society the way it does today, the industry worked on averages, right? When we spoke about a demographic or ideas for the demographic, we would always tend towards the average. You know, who is your ideal consumer? Who is the average consumer? What is the average psychographic of people who shop? But now with what AI brings to the table, we’re able to understand the range of people who we interact with. And what AI does is it amplifies the voices of people on the fringes. And if you look at how trends form, how trends, you know, grow in society, it’s usually people in the fringes that are the first signals of where the future is going to. And so, with AI, we are able to amplify their voices and understand, you know, what they’re telling us, what they’re saying so that we are prepared for the future better, as opposed to in the past, where, oh, there’s a trend and everyone’s running to catch it. Right now with AI, you can understand people who would not show up in the average, but you can understand the whole range, and you can tailor solutions for them. You can tailor brands for them, and in so doing, you position yourself for the future because the people on the fringes usually drive the future agenda, and that’s something I found that in my work. And so, this is how I say that, you know, AI helps people understand people better.

Karen: Yeah, I have a question about that, actually. Last week, I was at work—two weeks ago? Time is blurred at the moment—was that the annual Qualitative Research Consultants Association conference, and we were talking about, at one of the sessions, how AI—and we’re talking about in the context of, like, AI moderation—how sometimes the results and the synthesis AI flattens kind of what might be normally interpreted by a human being. So, you might get kind of, you know, less emotive and less of a focus on outliers. So, this flattening of intelligence, if you will, or the flattening of the voices into kind of the patterns and a synthesis rather than understanding outliers. And what you were just describing was, sort of, sometimes those outliers are really important, and we really need to learn from people who do not fit into the patterns, or, you know, individual users who don’t fit into a specific community, but they’re still equally important. So, what is your take on that? Have you noticed, kind of, flattening of information in the work that you’re doing? Or are you able to pull out those outliers in the tools you’re using or the processes?

Feranmi: The way I would answer the question is to kind of split the context because I think context is important here. There are two ways we can aim to understand consumers in today’s world. One is through what you’ve just mentioned, where you know a human being is speaking to a human being. Nothing can take away the importance of having, you know, within a core setting, of having human moderation and understanding the nuance, right? Additionally, when it comes to the context of digital signals, I think this is where the value really, really, really shows. Because the problem with digital signals is, it’s a lot. If you’re moderating a panel, for example, you could have 8, 10 people, you know, around the table, maximum, 15, 20. You know, we can handle that. But when you’re talking of 200,000 mentions, 1 million mentions, you’re always, when you do the analysis, especially within the digital space, when you do the analysis, you’re always going to average out, you’re always going to cut out some of the people on the fringes. But with AI, you really do not need to because the capability to kind of analyze the full data set, we now have it, right? And so, when you hear—and this is why this is important. People on the fringes, they do not really get a platform to share their ideas, but what social media has done is it’s giving everyone a platform to share their ideas. Everyone is a speaker, everyone has an idea, everyone goes online and tweets, you know, or shares this idea with people within their communities. And so, what you see is you’re able to actually get people who are on the fringes, they speak within their spaces. And once you can get all of that and kind of analyze it, you’re able to identify underlying patterns. And so, the answer to your question is, there’s a split. There will always be space for human-to-human ethnography and study and interaction. That will always have a space in insights. That is my take. But when it comes to digital insights, digital analytics, which is becoming increasingly important in today’s world, then AI is what definitely is helping us, you know, take value out of that data set.

Karen: That’s great. Thank you. And I love hearing the hope for those people that love that, even the idea of ethnography around ice cream has me, you know, feeling nostalgic for the days when I was executing research because that’s some research I would love to be involved in. So, before we wrap, I do want to ask you, you’re ahead of the curve, even on the brand side, ahead of the curve here. What are you still wishing for? What do you think there’s room for in terms of innovation in the insights industry? New methods, new tools, anything kind of on your wish list that you’d like to see?

Feranmi: I think I’d like to see what foresights looks like in a world with AI increasingly embedded within processes because it’s like I said, AI helps you to kind of augment and amplify some of these early signals that are usually discounted or usually kind of filtered out. Additionally, patterns, right, something could happen in an absolutely different category and it could have an impact on your category, but because the category is so distinct, so distant, you really do not see the link. And this is one of the places AI shows up well: identifying patterns. And so, as we embed AI more into our processes, I think that one of the major benefits we’ll see with AI is in foresights, where we’re able to, kind of, detect these patterns, or detect the importance of these early signals and how they have implications for where we go as an industry or where we go as a society and how businesses should, kind of, prepare for these different scenarios. I think it’s going to be absolutely amazing. I think what comes to mind is, in my master’s, this was the first time I interacted with a scenario 7 simulation, a business simulation, before. And, you know, it felt very academic and I kept thinking to myself, why can’t we have this within the business space where we, kind of, you know, run this scenario models, If I do this, how is my competitor likely to, you know, respond? How will consumers respond? You know, it makes business a lot more about the decision, about the trade-offs, and it makes you stress test your assumptions more strongly, right? And I think it’s going to be amazing for businesses to get to that point where, you know, decisions becomes about, you know, this is, these are the trade-offs I need to make, these are my assumptions, and less about, you know, gut feeling. And there’s always going to be a space for that. There’s always going to be a space for creativity, but I think we also need to kind of strengthen the evidence of businesses because that’s where real value lies.

Karen: Yeah. I will share that probably one of my favorite sessions at an IIEX event was an IIEX Europe. I’ve talked about this on the podcast before. The [Kerry Group 00:32:12] shared some scenario planning for what happens to coffee consumption when climate change has affected the world’s ability to produce the, you know, the coffee bean. And as a coffee consumer, I was riveted with the different scenarios and what it might mean. And of course, they were like, “Don’t worry, you know, we’ve got the coffee drinker covered.” But that scenario testing and planning, I think, to make it more accessible through some new tools and innovative methods, I agree with you, could be very valuable, especially when there are brands that are beloved like yours. So, I’m so glad we’ve had this chance to talk. Is there anything that you wish I had asked you that we didn’t get to on our time together today?

Feranmi: Maybe something what I do outside of work, you know? Because I’m not all you know, in the server rooms with the AI models, you know, trying to get insights and holding a gun to their head to tell me the right answer. No, that’s not what I do. I think, outside of work, I quite like to learn. I like to listen to stories, and I like to learn. And the reason why I say I like to listen to stories is because they take so many forms. It could be a book today, it could be a movie tomorrow, you know? And I think a joy of mine is also kind of, you know, teaching people. I like to, you know, understand really difficult things and see how I can present them in the simplest way possible and once I have that, I like to share them. Like, I’m not fulfilled until I’ve shared that knowledge, and this applies, you know, to all of my societies that play in my professional society, my friends, you know, people from church, people from work. You know, it permeates my life. I love to share knowledge, so I think those are the two things that really get my energy up. Can I learn and can I share it? I think that’s what sums me up in a nutshell.

Karen: I’m always touched when a Future List Honoree shares something like that very authentically. And I think that is what the judges saw in you and why you are at the top of the industry at this moment. Being able to kind of get inspiration from your life and bring it into your work and then influence others and make a difference, that is really what makes you a standout. So, thank you so much for joining me on this episode of the Greenbook Podcast. I’m so very grateful, and I can’t wait to meet you in person [laugh].

Feranmi: It’s been an absolute pleasure, Karen, and I really have to thank you and the judges for choosing me to be a Future Honoree. And I look forward to meeting you in person at IIEX Europe.

Karen: Absolutely. It’s going to be great. So yes, and we can share in the show notes a link to register to IIEX Europe, where you’ll be on stage. I can’t wait to be there. That’s one of our favorite events. So, thank you. To all of our listeners, thank you so much for tuning in. We are just so pleased to be able to bring you some insights and knowledge from some of the leaders in our industry. Thank you to our editor Big Bad Audio for doing what you do. You might have had your work cut out for you today, but I am just so very grateful. And again to you, Feranmi, thank you so very much for joining us. See you next time on the Greenbook Podcast, everyone.