In this episode of the Greenbook Podcast, host Lenny Murphy chats with industry legend Stan Sthanunathan, renowned for his impactful roles at Coca-Cola and Unilever. Stan shares pivotal moments that shaped his career, emphasizing actionable insights and what that truly means in a world of abundant data. He discusses his transition to founding iGenie.AI, which leverages AI to enhance human intelligence in market research. Together, Lenny and Stan explore the future of the insights industry, the balance between technology and human expertise, and the importance of empathy and understanding consumer behavior. Tune in for an enlightening discussion on driving innovation and staying relevant in a rapidly evolving field.

You can reach out to Stan on LinkedIn.

Many thanks to Stan for being our guest. Thanks also to our producer, Natalie Pusch; and our editor, Big Bad Audio.

Hello, everybody. It’s Lenny Murphy with another edition of the Greenbook Podcast. Thank you so much for taking time out of your day to spend it with us. And every podcast is special. Every guest is special. But it is rare that we have anybody who is known like Bono. Right? They’re just a single name, a singular entity that defines their entire brand. And today, that is the case. We have the man, the myth, the legend, Stan. And you may think of Stan from Unilever, Stan from Coke. But whenever you say Stan, everybody knows Stan. Stan, welcome.

Thank you. Thank you, Lenny. Thanks for the rather generous introduction. I probably don’t deserve most of that, but that’s okay. I’ll take it. In my old age, I’ll take it.

[laugh] Well, I think you should. And for—you may not say it. You can give your bio in a second, but I want to give our audience a little bit of kind of insider knowledge. So for many years, for almost the course of my entire career in the insight space, Stan has been kind of part of the Illuminati of the market research industry, right? There was a group that he led, kind of the gang of five, right? If you could see us, we’re like woo-hoo—major influencers, right, on helping to look at the future and actually using your resources as a client-side leader, a brand-side leader to help support new companies, to invest, to give them open doors, to drive business growth through the companies that you’ve been with. So you have played a huge role in creating, well, what was the future of research. Now [laugh] it’s the present state of research, and many companies owe you a massive debt of gratitude. And, you know, remember our dinner at Pittypat’s Porch in Atlanta—

Yep.

—when you kind of kicked me in the butt and said, you guys should probably start an event series and should do some other stuff. And even the term “insight innovation”—

Yep.

—came from that conversation with you—Pittypat’s Porch in Atlanta. So there’s my shout-out on things, but why don’t you tell, tell the audience a little more about your background, your take, so they have a little more context than just my gushing and hero worship.

My simple introduction to myself would be that I’m a one-trick pony. I [laugh], I’ve spent 40 years in the insights industry, and let me put that in context. The insights industry is a hundred years old, and I spent 40 percent of the time. So that kind of gives you the one-trick pony-ness of me as an individual. Bulk of my time, I have been on two very large global CPG companies: 18 years with Coke, 8 years with Unilever, and two really iconic companies. And these two companies, I owe them everything for shaping me into who I am today. And within that, you know, like all good things in life, there are always individuals who shape who you become. And there have always been some legendary marketers in Coke and some regional operators in Coke, who shaped me into who I am today. And at Unilever, there were some really high-end intellectuals who have shaped my thinking in terms of what I could do, what—or, you know, and so that’s—I owe it to them. I owe it to them. And I am who I am today thanks to those kind of people.

Yeah. I get that. And I would put you in that category for me as well, right, folks that have helped shape that. But you also had a very clear vision about where things were going, and you were never afraid to experiment. And I think that that’s hugely important. And something that talked about as much, not just you overall, but how brands influence the innovation cycle in the industry in very substantive way. Let’s talk about that for a little bit. Kind of just talk about your perspective through your roles at Coke and Unilever, how you helped do that—and for tips for the audience, maybe other leaders out there that are looking for ways to help drive innovation themselves.

I still distinctly remember, back in the days when I was in Hong Kong and I was reporting to the group president of Coca-Cola, and I thought I was very good with the trade of research. So I went to him with a report which I thought was really insightful. I went to him and said, “I would like to walk you through this because there’s some interesting nuggets in there that you might want to be aware of and you might want to action.” He looked at me. He didn’t even open one page of that report. He just gave it back to me as it is. And he said, “I don’t care about this research report, Stan. You tell me what are the three actions that I should be taking. Let me decide which one of the three I need to—which one of the three routes I need to take, but you give me three alternatives.” And that kind of was a paradigm-shifting moment for me because that’s when, you know, I coined the phrase of ‘the what to the so what to the now what.’ But all that he was interested in knowing was “now what do I do?” And that was undoubtedly the career defining moment for me Because since then, I’ve never, you know, gone to people saying that, look at, you know, 30 percent said this, 40 percent of the people said this, and here are the interesting, significant difference and so on and so forth. I never ever tell that story that way. I always tell them, this is what you need to do. And if they have a—well, a disagreement, we can have a disagreement. The disagreement is always between their gut feel and my facts. And guess what wins? Your facts always win. So keep facts as a backup. Fact should never be the hero of your presentation. The hero of the presentation should be “what do I do now?” And the same thing happened at Unilever too. You cannot do a presentation just telling to—what people should do without having done the due diligence. I’m expecting that, you know, you know your trade and you know exactly what you need to do. But telling them that you’ve done a whole lot of hard work doesn’t get you glory. What gets you the glory is what you should do. And that, as long as—you know, I kept that front and center of everything I did, and that helped me in what, 26 years and two big client entities.

So famously, when—I think when Zappi emerged, you made a statement that roughly was the point of, what, so I can only spend 20 percent of my budget and get 80 percent of the answer and get that 80 percent faster. Where do I sign up? I think that if that was roughly, you know, the point.

That is correct. Yeah. Data is commodity, Lenny.

Right.

In today’s world data is commodity. Don’t over intellectualize or don’t over intellectualize. So what and the now what is what you need to be focusing on.

And that’s why, when I think about the idea it’s, yes. And especially now in era of AI—and we’ll get to that in just a minute—but I just think, knowing you and the role that you’ve played in the industry as a whole and that progression of moving—look, let’s just do this as fast and effectively and efficiently as we can because that’s not the value-driver. The value-driver is the answer to the business decision and then the implications on here’s what we do as a result of that, where the “platformification” of research, the technology advancements—you know, I know you placed bets to help support companies, to accelerate things, to get to the now what and—you know, the so what and the now what. Is that a pretty fair assessment?

Absolutely. I think you got to be brave. You got to go where no man or woman has gone before. Sometimes you might fail, but people will cut you slack as long as, you know, you’re maniacally razor focused on the so what and the now what. They will cut you some slack. But if you make mistakes again and again, then, you know, you got to ask yourself a question, do you have judgment or not? But I’m assuming that most people who are in the insights industry have above average IQ and are good enough to, you know, make the right decisions. That’s what we need to just experiment, experiment, experiment. You know, you lose nothing by experiment. Today, experimentations don’t cost as much money. And honestly, you’re not going to bring a company down based on some research experimentation work that you’ve done. This is not like, you know, you’re taking a controversial stance in your advertising, which could cause problem for your brand. This is research. You can’t bring a company down. So please, be brave.

Be brave and be bold, I would assume.

Absolutely, absolutely. Think big. Thing big.

All right. So let’s transition from that, right? So you—that was your motto. You lived by that. You defined—

Yep.

—you know, the—in these organizations, and then you retired.

Yep.

But I know you better than—to think that you actually retired.

[laugh].

So what are you doing now? How are you taking all that learning and that philosophy and applying it now?

First of all, a small correction. I didn’t choose retirement. I chose “rewirement.”

[laugh] Okay. Okay.

I think, you know, as I said, I owe everything that I have today to the two big companies I worked for. So I learned a lot. But at the same time, there was something that was—I always had a bit of an itchy sensation. My—and I was sitting there and thinking, is there a way in which we can reimagine the research world? But you look at it, honestly, Lenny, the industry hasn’t changed at all. Yeah? You might think that, you know, I’m being stupid and my head is stuck under the ground, and I’m not. My head is not stuck there. I’ll tell you, good old days, it used to be paper and pencil, door to door. Then it became telephone. Still the same questionnaire. Then after that, it became Internet. Still the questionnaire. Then it became mobile. Still the questionnaire. Then you do DIY, still the questionnaire. You know, good old days, you did focus group in somebody’s house. Then it became a centralized venue. It became a one-way mirror. The way in which you did research evolved slowly, slowly, slowly. But if you look at it over a hundred-year time frame, you know, what P&G did in the US and what Unilever did in Europe, literally 100 years ago, in terms of creating the insight industry, the fundamental nature of the industry has not changed. And I genuinely believe that that needs to change. If that doesn’t change, then we can sit here and have a long conversation about, oh, we are losing relevance. Oh, we are not getting seats at the table. You can have the conversation. And I genuinely felt that that is the change that need to be brought about. Maybe I’m a dreamer. Yeah? Maybe I’m being foolish, but then I said, okay, let’s give it a shot. And, you know, I had the benefit. And that’s, that’s the genesis of the company that I’ve set up called IGD dot AI. And, well, you know, as my luck would have it, I also have a bunch of, you know, data scientists, and I always jokingly tell my team members that take any two people’s age, add it up, and I’m older than that.

[laugh].

So I really have some phenomenal, phenomenal people who will never say, no, not possible. Everything is possible. And I always have to say, you know, the only difference between impossible and I am possible is an apostrophe. Just put an apostrophe after I. It becomes “I am possible.” I didn’t say that. I think Dolly Parton or somebody else said that. Yeah?

[laugh].

It’s not my quote. But then I—that was a notch star for me. You know, I am possible, and that’s what my team is. You tell them, yeah, possible. Now, whether they get it right the first time or not, it doesn’t matter. We get it right. And as long as—you know, and I’m fortunate enough to have a bunch of clients early on who took the risk with us, who took the risk with us. And do we make mistakes? Of course we do. Are they patient? Probably more patient than I would have been. But they have been extraordinarily nice to us. And together we have created things that I think will be, you know, shaping the future.

Well, can you tell us a little bit more? Because you and I, we have not spoken. I mean, I know you launched IGD AI—

Yeah.

—but we have never really gotten into it. So what can you tell us about that reshaping of the future?

The reshaping of the future is, you know, I think, asking questions, getting answers from consumers will be there for quite some time. It’s not going to go away.

Yeah.

But I also believe that that is not going to be the only way in which you get insights.

Yeah, agreed.

I also strongly believe that people talk about us but do not talk to us because of various factors. They have other things to do in life. They have more interesting events happening in life. So it’s not that they always have all the time to talk to you about brands. The other clear thing that one also needs to keep in mind is that—or just looking at the elections in India that happened recently and the results came out—on the day of the exit polls, you know, they were all, “Oh, my God, this—you know, is going to be a gangbuster victory for the ruling party.” When the actual votes were counted, it was far from a gangbuster victory. Yeah? The question you have to ask yourself is the exit poll sample table were 800,000. 800,000. Yeah? How did they get it wrong? The question is if you ask a question, people will give you an answer because you’re challenging their intellect. They can’t say that “I don’t know.” They’ll give you an answer. How often they’re telling you the truth, have you ever calibrated that? No, it’s, we do it through core relationships and so on and so forth with other variables. But that particular response per se, is that a reflection of truth at that micro level? We have never calibrated it. Yeah? At least it was not done at—done at scale. And that’s the issue. And that is an issue that will become bigger and bigger and bigger, particularly in a polarized world in which we are living in. It is going to become very challenging. Because if you come and ask me who are you going to vote in the presidential election, I’m going to look at you and say, are you pro-Trump or anti-Trump? What do I tell you? Yeah? And depending on that, I will—you know, I’m not going to ask you, but I’m looking at you and I’m forming my own judgment. And depending on that, I might give an answer which you would like to hear as opposed to what I want to tell you. And that is becoming—it’s more pronounced for polling, but it is less so for consumer products and so on and so forth. But still, you know, the ability to speak the truth is being increasingly challenged, especially when people are turning around and saying there are other forums where I can actually speak my mind out and get away with it. Thats what we do. What we’ve done is we help you create products. We’ve got six products which basically do things that traditional research used to do. And we always tell our clients, you know, we’re not saying that this is the next best thing after sliced bread, but it certainly is something that will give you a more accurate assessment of what people are actually thinking rather than what people are telling you.

So you’re synthesis, if I can paraphrase—tell me if I got this right—you are synthesizing data, likely, my guess is behavioral, social...

Social is one part of the data. I also genuinely believe that in a polarized world, just leveraging social could lead to erroneous conclusions.

I would agree. There’s a lot of trolls, a lot of BS out there. So...

There’s a lot of BS. There’s a lot of trolls. There are a lot of people who are posturing. You look at, you know, platforms of people, “oh, look at my wonderful meal that I had. Oh, look at the wonderful vacation I went to.” Your life is not full of just those wonderful moments. You have a lot of events that happen between those wonderful moments, and that’s where the opportunity is. So do you know what happens? Nobody posts saying that, you know, I’m feeling really down today, and I feel down today because of this reason. We don’t see those kind of posts very often.

Increasingly to your point too, there’s—you know, we think of this—you and I lived through the explosion of social, and I’m sure, like me, that there was a part of you like what? And then, okay, well this is kind of cool, and then eventually got burned out.

Yeah.

You know, like, I don’t have time on social media anymore.

I don’t have time either. But tell me, you know, if you and I are on the two ends of the spectrum, is there a hope in life of me trying to convince you to join my end of the spectrum? And therefore, I already believe, you know, what happens in the world of politics is usually a good precursor of what happens in the real world of consumer product marketing or any other marketing. Therefore, you know, don’t waste your time just mining socially. Okay? It is important to understand, but it is not the only thing to understand. Because when people have genuine problems, they go to search. When I say search, I’m using GPT and everything in the broader context of search. Yeah? And that—

Okay, so you’re leveraging search data—

Yes.

—as well to inform.

Yeah. How do [audio break 00:17:41].

Got it.

How do you think we should do it? And then the other thing is, you know, people say, oh yeah, I analyze TikTok data. They analyze hashtags and comments below it. Important. But is that the only thing that you want to analyze, or do you want to analyze the video and the audio? That’s what makes a difference because go to the source. You know, Lenny, you remember long back, you know, when, when we were at Coke, we tried to set up neural labs in multiple locations. That, we were going to the source where the actual thinking happens. And that, we learned a lot. We learned a lot from that. But then, you know, the learnings became predictable learnings, so you didn’t have to do the same thing again and again. Then we said, okay, why do we need the lab anymore? Yeah? But new stimulus, you want responses, you can use that. But it is—you know, somebody came up with eye tracking, somebody came with facial coding. Those are all brilliant technologies. I’m not saying that, you know. But they are nonverbal responses, you know, that are passively measured. That gives you deep insights into why people are doing what they are doing. Behavioral data is a real thing. It’s a real thing. People can say what they want, but what they do, they go to their wallet, and how well they vote is all that matters. And then backtracking is always a good thing to. Why did you do what you did? Yeah? So sometimes research in the reverse is what one probably needs to do.

So I have a hypothesis that I’ve been working on, I’ve talked about before, but I’m going to get your take on it. In the era of AI, right, and we said the same thing when big-data was the topic, right, that there would come a time when the streams of information would enable us to, with great certainty, understand the who, what, when, where and how. Not necessarily the why. Right? And the why would be the, the purview of research to fill in that information. Now, since the—I don’t think—well, you may have seen the advent of generative-AI. I did not, not the way it manifested, and certainly didn’t see the skyrocket of adoption and innovation from that standpoint. So where my thinking has gone now is, yes, AI will—it unlocks that promise of big data to synthesize all the information and get to the who, what, where and how. Great. But increasingly, there will be gaps of information not present. And I think of it as last-mile data. Right? And so the role of researchers will be to get that last-mile data to fill in the gaps of information. Part of that will be why. It may not only be why, though. There will be other aspects, and that will feed into the system, increasing the intelligence, increasing the predictive value, et cetera, et cetera. But so, so here’s that vision of the tech component. And then to your point, the ‘so what’ in the—the ‘now what’ and the ‘so what.’ What I do not envision today, unless, you know, unless OpenAI, you know, is much closer to AGI than I think they are. Maybe they are. It will not replace—and this will be the role of researchers from a consultative standpoint—intuition, creativity, depth of knowledge and experience. And those will be the things that we will need to know which questions to ask that we don’t have the information for, how to ask the right question, and then what the hell does it mean and what do we do with it. And those would be the four pillars of insights as we progressed, while leveraging this massive data set of information available to us. What do you think?

I completely agree with you. You know, we have to always, always, always remember that technology is means to an end. Yeah? So when we started this company called IGD dot AI, the “dot AI”, in my own mind, it stands for augmenting intelligence. While it is, the company is powered by artificial intelligence and machine learning, but in my own mind—we even talked about that with our clients. Our goal is not to create a set of tools that will replace human thinking. You know? Because at the end of the day, if you choose to allow AI to replace human thinking, it will replace human thinking. But to your point, there is creativity that human brain has got, which is kind of kept scuttling because you are too bogged on looking at morass of data, right, and you’re tired at the end of the day. And when you say, when I ask you to spell creativity, at the end of the day, you’ll ask me, what is that? But all that, you know, AI and machine learning would do if you’re really smart is to unleash your superpower to think differently, so that the concentrated skills that you’re talking about, you can be the best that you’re capable of. I don’t think there is any machine that can replace that, at least not in the near future. But people look at it and say, you know what? Look at the gen-AI. It has created an idea. Now, if you’re lazy, you’ll take that idea and say, yeah, let’s run with this idea. But then, if you’re smart, then you’ll ask questions. How is this idea relevant? How did it create the idea in the first place? And when you start asking intelligent questions, that’s when you realize that it is actually an incredibly well-packaged stuff. If you don’t know how to challenge it, you can get conned, but it—you have to use it to actually boost your productivity, boost your creative power, and ask all the right questions, provide the consultative support, and have the time to do that. And that’s what is the goal of, you know, whatever we have created. Create time for people to provide the internal consultative support. Remember, you know, the goal of an insight person is to not just get a seat at the table but be at the center of the table, where the big decisions are being taken, people are looking at you and asking what do you think. Yeah? They ask that question because you—they know you come up with a really wise, well thought-out answer. And to be able to do that, you need the bandwidth. Leverage technology to create the bandwidth. Don’t assume that it is going to give you the answer. It will make your answers a lot smarter. That’s what I do.

I love that. Thank you. We may be drinking the same Kool-Aid, but I’m honored when it’s someone like you that’s [laugh] taking along the same lines. And it has—now, let’s broaden that scope, right, because we are in an industry. And the industry—my take is that the demand for information is only going to continue to increase. The buyers of that demand is increasing. It’s fragmenting across the—across the enterprise. It’s no longer necessarily centralized. And the insights function, there’s other functions where it’s been democratized, and that’s all good

All good.

But systemically, how our industry has been structured is continuing to change very rapidly. Where fundamentally it is your tech or your consulting. There is a little bit of gray area in between, and it’s vital. Field services enabling. There is still need for sensory testing and those things to connect with people and enable that process to happen. That’s not going to go away. It’s actually probably become more important in many ways. But the era of the large full-service companies—I mean, it’s already coming to an end. I would argue that the only one left standing that truly has that definition of we think of as a full-service company, a large full service company, at this point is Ipsos. You know, everyone else is kind of going in their own kind of fragmented—or, you know, they’re vertically focused, or they’re business-issue focused. The big, big companies are shifting away. So you’ve always supported entrepreneurs. You are an entrepreneur yourself. So in that world where you’re either a consultant, which is based on expertise and all those things we just talked about, or your tech. And tech is continually being accelerated by AI and may not be the differentiator that it is—that we thought it was going to be. What do you do? What’s the direction? What do you—what’s your crystal ball say?

My crystal ball says that it seems like a corporate answer, but I think the healthy medium is where the future lies. If you’re pure tech, up to a point, people will get impressed with your jargons that you use as a tech person. After that, they’re going to sit there and think so what do I do with it? But if you’re only a consultant who is talking about, you know, let me tell you what you need to do, and so on, then they’ll say, do you even understand the new world? So in the vantage point at which I am in right now, you know, where we are offering a tech based solution set to our clients, they always come and tell us, okay, listen, great tech, but can you also do the interpretative skill—apply your interpretative skill and tell us what needs to be done? And that is where I think—you know, most of my employees are, people who have worked on the client side of the fence. So, therefore, we know what keeps typical clients awake at night. And that turns out to be our unique selling proposition because people say, oh, you know our pain point. And that we do. It might come in slightly different flavors, but we do understand the pain point on the client side of the fence. We are not the—you know, who will come and tell you, you know, that I will use this extract, and I will use this container to do the analysis, and I use that algorithm. People don’t care. Yeah? They say, okay, if you know what you’re doing, great. Thank you so much. But tell me what do I do. And we know what we’re doing, and we can tell what they need to do. That is the sweet spot is where the industry will evolve. If you’re only tech, could be in trouble. If you’re only consulting, you could be in trouble in a slightly different way. But tech, you know, things change. Things change so dramatically. You know, did you think about Gen-AI seven years ago? No. And it came and it has, you know, changed the world. Who knows what’s coming next, right? So the tech will evolve. But thinking, human thinking, human creativity, human intelligence, human ability to, you know, connect with others will not go away. Machines are not going to be talking to each other to do marketing. You know, eventually, some, some human will be involved in the marketing process.

I don’t know. I don’t, Stan. I mean, I’ve seen this—I saw, [laugh]—for our audience, I know we have to look this up. I saw a video today of Reid Hoffman interviewing himself, his digital avatar, and it was flawless. It was weird. It was like, oh, I don’t know if I like this. But the implications are—and it was kind of gimmicky, right? But it was—it was a full deepfake, AI-powered other Reid Hoffman. And they’re talking back and forth, and it was very seamless and scary. But that indicated, from a marketing standpoint, well, are we going to get there where we have digital avatars that are handling, you know, some things for us, talking to another digital avatar, from a marketing perspective?

Who is paying the money to buy it? The [audio break 00:28:46] Right? Who is earning the money to pay for it? As long as that human is paying the money to buy it, that person will always ask a question as to is this the right thing for which I’m paying the money?

Okay, fair point. Fair point. Follow the money.

Yeah. So let’s not lose track of it. Let’s not lose track. You can have avatars talking to you. You can have—you know, you could have a digital persona online, and another digital persona could talk to you. But at the end of the day, you know, it might even order something for you, your digital persona, one time, two times. And then later on you look at your credit card bill and say, “What the hell? What did I buy?”

[laugh] Right? Did I really need ten, you know, of these things?

Well, I think there is a—I think it will automate but not replace. You know, I think the—that’s why get—I go back to the whole notion of it will eliminate grunt work with intelligence. Think of the days when outsourcing happened, you know, the call centers and stuff like that. They got outsourced. It got outsourced because we eliminated grunt work with lower-cost people who can do grunt work. AI is going to eliminate grunt work led by technology, and it will also be plus, plus. It will do something better than what a lower-cost human resource could do. It will do better job. I’m not disappointed. It’ll learn. It’ll get better. It’ll work 24 hours. It won’t get tired. I get all that. But at some point of time, there has to be somebody who’s going to look at it and say, okay, out of the 5,000 pieces of content this AI has created, does it pass my sniff test? And you would have time to look at it and say, yes, it does pass my sniff test. Because all that it takes is—you know, imagine, you know, Google had a small mishap when some great profiling was not done right. Yeah? It created a huge controversy. Imagine if your marketing is going to be entirely that. Who takes responsibility? Who takes? You can’t say, oh, my machine made a mistake. I’m sorry. You have to take responsibility. Right? So, therefore, there will be a human in the loop always. What are the role that human and the group going to perform is what we have to wait, watch, and see. You can let it run wild, or you just take charge of it.

So that’s—and I want to be conscious of your time and the time of audience, but there’s a really interesting point here that I think—let’s dive into real quick. I know you’re passionate about the idea of algorithmic bias, right? And fundamentally, that’s the old issue of garbage in, garbage out. And we see in our studies a bad sample and those type of things. But now you’re point on Google. We see it now happen at scale, right? So there’s two issues: one, bad data that can contaminate and taint the entire data stream, and bad decisions are made. And AI doesn’t judge that. You don’t have to determine whether the quality of the data, it’s simply there. And then there’s built-in biases, which we recently saw that in Google with their infamous, you know, launch of their video or their image generator, that they put some social models in there that didn’t really go as they planned. So [laugh]... So the role of the human, and particularly the researcher, is that also then that we need to lean into being the sniff testers, being like, you know what, this doesn’t pass my test. And how do you determine that in the world where there’s so much data flown in? Let’s say the India election example, all right, the data seemed to indicate that Modi was going to have, you know, a blowout. Not what happened. What is the role of the human and the researcher in ensuring the quality of inputs are there so we can get better outputs?

Yeah. I would always use one word: intimacy.

Okay.

People intimacy. If you do not have—you know, numbers can tell you so much about people. It doesn’t tell you the entire story. Being intimate with people is incredibly important, more so today than, let’s say, when I started my career in research. Right? Because I always keep saying that not just marketers but also insights professionals who are in the business today do not necessarily represent the consumers who they are trying to market to. They tend to come from slightly upper-income group. They tend to come from better educational background. Therefore, they—well, they look at a number, and what they end up having is sympathy for the consumers but not empathy. Because they all—they have—they’ve made only so much money. You feel sorry for them. No, you don’t need to feel sorry for them. They are quite happy, probably happier than you and me with much more money. But how they live, what keeps them awake at night, you know, what is the one that makes them tick? You can understand that only if you have intimate knowledge, if you actually live them. You know, I remember, you know, reading an article about 3G Capital, you know, where they talked about how they hire PhDs into their organization. The PhD doesn’t stand for what you and I normally understand. It is poor, hungry, driven people.

[laugh].

Yeah. I thought that was an incredibly profound concept. So that automatically systemically drives people in with you. You ask yourself a question. I don’t know your childhood background, you know. Where you coming from an affluent background, from which your children are today.

Yeah, I did not, I did not.

I did not too.

I grew, I grew up poor and struggling and... yes.

Therefore, you have your—you know, that DNA will never be gone. But, you know, you might not—you know, and no offense attended here. You know, my children, your children, they did not grow in that kind of environment.

Yes. Mine did not.

Therefore, but they—they need to train that muscle. And that’s my main point. And that, you know, with all the data that is coming at you, people will think, oh, I understand my consumers, and I have a fabulous story, but I don’t have time to tell you the story. But that—when I read that—when I experienced that story, I had, you know, moisture eyes. I really had moist eyes and I felt a lot more responsible towards the consumer. And I said that, you know, as a company, we should be doing something very different than what we would have otherwise done.

I love that. And I, you know, we start off talking about the, you know—my, everybody, my listeners know we moved to a farm. And, I mean, the things that I learned from living in a rural area surrounded primarily by Amish and Mennonite folks, right?

Yeah.

They have been disengaged from technology. And how inspiring in many ways they are?

Yeah. You bet.

And I’m grateful that it—I feel like I missed out for a big chunk of my life.

And very often, very often people become condescending. Oh, really? You don’t have the latest iPhone? No, I don’t need. I’m happy. Thank you so much. Yeah? Don’t judge—

I see happy, healthy people.

At the end of the day, you know, empathy. Empathy and intimacy.

Empathy.

And—

No, that’s, that’s fantastic. Thank you, Stan. It’s been too long, and it’s probably not entirely fair to our—to the listeners for us to kind of catch up this way as well. But it is what it is. We really should chat again, both privately and publicly, because you have so much to share, and I really appreciate all that you have done for the industry, for me, for Greenbook and all the success that you’re experiencing now. Just glad that you’re here, my friend.

Thank you so much, Lenny. And it’s always a pleasure talking to you.

Where can people find you?

Best way to find me is stan@i-genie.ai. Simple email address: stan@i-genie.ai.

Awesome. Well, thank you so much. Big shout out to our producer, Natalie. Thank you. We couldn’t do this without you. To our editor, Big Bad Audio, couldn’t do without you. To our sponsors, and especially to you, our listeners, because you are why—you’re what gave the excuse for Stan and I to catch up, and I’m really glad that we had the opportunity. So that’s it for this edition of the Greenbook Podcast. We’ll be here again soon with another one. Bye-bye.