[DECODED] Unblocking the Exploration–Exploitation Dilemma

[00:00:12] Phillip: If marketing once ran on the logic of the assembly line specialized, segmented, siloed, then AI? AI is the sledgehammer, and it's smashing apart that old factory floor. And what happens when we shift away from positions to roles? When belief outranks bureaucracy? And when autonomy, not authority, drives execution? Welcome back to Decoded, a Future Commerce limited series presented this season in partnership with Optimove. I'm Phillip Jackson, and today we are diving deep beneath the dashboards, behind the org charts, and into the hidden mechanics of the modern marketing organizations. Joining me and my cohost, Pini Yakuel, is Neil Hoyne, the Chief Strategist at Google and the author of the bestselling book, "Converted." Together, we're going to interrogate the rituals and the relics of business as usual, and we're gonna talk about fear and identity in the age of automation. We question whether the org chart has become the greatest obstacle to innovation. And we introduce a new idea, that of the positionless organization. Teams made up of not specialists, but of hybrids, generalists, craftsmen, A teams. And in this episode, we unpack how marketers can navigate uncertainty, not with rigid playbooks, but with experimental courage. Not with silos, but with systems of trust and creativity and shared ownership. Let's decode that together. Welcome back to Decoded, a podcast by Future Commerce brought to you in partnership with Optimove here this season, and I'm really excited today. We have a very special guest, Pini. I can't wait. We have Neil Hoyne, who's the Chief Strategist at Google and the bestselling author of my most recent read. This is "Converted: The Data Driven Way to Win Customers' Hearts." And Mr. Hoyne, you here with us today, senior fellow at the Artificial Intelligence division over at Wharton School and Board of Trustees for Purdue University Global, among many other things, also a patent holder. And you speak all over the place, publish all over the place. Can't wait to hear what you have to say and share with us. I've got a ton of questions about this book. Welcome to Decoded, Mr. Hoyne.

[00:02:34] Neil Hoyne: Thanks for having me. I appreciate it.

[00:02:35] Phillip: Yeah. I'm really pumped. And I think as we're kind of in the middle of this positionless marketer series, Pini, we've been sort of talking about how the world's changing, talking about how marketing's changing. What has changed in the world since you wrote the book? That's the big question for me.

[00:02:55] Neil Hoyne: Everything. Everything. I didn't mention this. I started writing that in March of 2020, right, as COVID...

[00:03:02] Phillip: Ugh.

[00:03:02] Neil Hoyne: That was the only time that I could actually write a full book, was when we were all stuck inside. And you kind of had these questions. What would the world look like afterwards? Would we recover? If we did, what would that recovery look like? Which companies would survive? I'd say the more interesting thing that came from the time post-book was really looking at the hypotheses that companies have with uncertainty. And so if you go back, and I think we all try to suppress those memories from our brain, because I don't have a lot of positive ones. I remember my wife baking bread and it not working for the couple of times and crying. It was a very sad experience. But on the commercial side, I remember it was mid March of 2020, right, as I started drafting the outline for this book. Patagonia comes out, and they're like, "Well, because of COVID, we're just gonna shut down our retail store for two weeks." You're like, "Huh? How's that going to work?" And then McKinsey comes in with their projections. They're like, "Latest point, December 2020, world is back to where it is."

[00:04:09] Phillip: Right.

[00:04:09] Neil Hoyne: And then you see predictions. "People are never going back to the office."

[00:04:12] Phillip: Remember that.

[00:04:13] Neil Hoyne: Are they? "People are never going to buy in stores." "Physical retail is dead," and instead it recovered. And so a lot of those dynamics were built on people making guesses. And kind of the interesting thing I take away is whenever there's periods of uncertainty, as what we face now, people will come up and say, "Which beliefs do I actually stand by?" Now I have permission. I have the proof. I have the motivation to challenge the assumptions that my business has always operated on. And if this wasn't true about what we've done for the past couple years, what would I do differently? How would I market to my consumers differently? What would I say? How would I plan the next generation of my business in an era where everything that we thought was true may not be?

[00:05:01] Phillip: I'm gonna have to prod at that a little bit later because I think that one of the questions I have coming out of this read and the first read through is something I would sort of characterize as the difference between tradition in a business or like "We always do it this way," right? Versus maybe what I would say is like intuition or a sense of belief. I don't know that we've trained people in the modern era enough to actually form a deep sense of conviction and belief around something. I think we do things because we do them. But I don't know that we've trained a lot of people to actually learn why we do them and have to develop an intuition and conviction around it. And I think that that is what I'm taking away here is that learning how to gain that for yourself is the skill to learn moving into this modern era, because we all have tools to be able to do that now, where maybe we didn't all have the tools before. And so I think that that's a really clever thing to look at. 2025 also is a year that could paralyze a lot of companies into not doing anything because of all of this uncertainty. You're a strategist. How do you, you know, give people any sort of framework? I'm sure there's not a... There's no silver bullet, but how do you keep from being paralyzed in an uncertain environment? There's so many dynamics playing right now.

[00:06:33] Neil Hoyne: I'll give you the way I approach it. Well, first of all is everybody has to figure out where they're gonna put their chips so to speak. Some companies would say, "Hey, business as usual, stay the course." Others say, "Uncertainty is ahead, pull back." And you know what? These were the same arguments, the same uncertainty that came with COVID. Right? Do we conserve cash, or do we go big into delivery and retail? And there's no right answers to it. Where I generally advise companies, as I say, it's two things. I say one is, this gives you a time to actually test new ideas based on the information that you have. It also removes a little bit of the pressure, I'd argue. Because if nobody knows what the answer is in the market, it's not like you're missing something that they have. If I were to build models around this, I kinda joke with people, when we build consumer models, there's generally that part at the end that really irritates you, which is like, we have, like, a one or 2%. We really don't know what's causing it. It's just error. It's just random. It's leftover. And now it feels like it's 40%, that we really don't know what's going on and where things are going. And as concerned as people become, I always tell them to pause and I say, guess what? I say your competitors are dealing with the same uncertainty too. And at the end of the day, your consumers are still out there, and they're still looking for the best company that can meet their needs at this moment. And since those needs are changing based on the economic conditions, maybe they're more concerned about saving money. Maybe you're more concerned about the availability of inventory for Christmas, which is a big storyline nowadays.

[00:08:09] Phillip: Yeah.

[00:08:09] Neil Hoyne: Question is, how do you meet those needs and those concerns of your consumers better and faster than your competitors? If you assume what I said to be true, where your competitors are sitting there trying to think their way through this problem before acting, then I see a solution as being, no. It's to capture more data, to run more tests, and to learn how you just get a little bit more connected with that consumer than you've been in the past.

[00:08:34] Phillip: Pini, I want to pull you in here. I feel like this is a perfect opportunity to start thinking about how organizations who were overly indexed in specialists in the past can become really hamstrung because if you're a specialist, you only know how to do one thing. You're sort of stuck in one area of expertise. I'm sure that this is something that you feel very deeply about in a shift away from deep entrenchment in specialization. What does a future organization makeup look like in being able to be more reactive and nimble in these sorts of situations?

[00:09:14] Pini: Yeah. Thanks, Phillip. And hi, Neil. Great to see you again. I think just to go back on kind of like Neil's point and what you guys just discussed, it reminded me of a famous trade off in the world of optimization and search problems, which is exploitation versus exploration. And that trade off that, you know, search algorithms, optimization algorithms do, but actually people do it as well. Babies, you can claim that they're all exploration, very little exploitation. And very old people are probably 99% exploitation, very little exploration because that hurts. So it just took me to the same place where when things are kind of like uncertain, like COVID, whether it's all right now with economic terms or new technology like GenAI, then basically probably need to up your... You're going to be on a certain dial, right? So if you're a very mature company, you probably do less exploration, but still probably up your exploration a little bit. And that's how you try to handle it. But to me, this big kind of like 2025 and the world where we live in today in this crazy shift of GenAI, what it does, it makes me challenge one of the old paradigms, which is ultimately, you know, my villain is the assembly line. And I say it as an industrial engineer by profession. So I actually took a full course on the Henry Ford T model. I've actually, I can draw up like a Kanban just in time Toyota production line for the two of you right now. Cause I actually taught that course in my university days. So I'm very well acquainted with assembly lines and ultimately assembly lines is the way we manufacture work and we assemble work, not only in traditional manufacturing, but also in tech, right? In marketing, where you want to run a campaign, you need to go through a few specialists to get it done. And obviously that's how we scale, right? So it's when a company matures, that's what you do. You start to create those kind of like small departments that do just one or two things. You have less variance. They do the same thing again and again. They don't make mistakes as much. You know, it's more standardized. You can rely on it more. Great. But it comes with a price, which we all know, right? We hate. We wait, we wait, we wait for that. You want to do something small. You got to wait for that specialist. That person's on a break or they're on vacation, or they got something else more important to do. And you don't have this joy of creation and autonomy to do things yourself. And what I claim is that today people and departments can be more positionless. And I take this from basketball, as we discussed before, and they can basically start to do on their own. And they can dabble in many fields and different types of craft to do more things in a self serve manner and be more autonomous and go to the specialist when it's a really high stakes job or you really need deep expertise.

[00:12:29] Phillip: This is the kind of thing that too, when you're thinking about... In this industry, it feels like narrative becomes reality a lot of times. If we talk a lot about positionless, it feels like we can almost manifest it to be true. I believe it to be true because it sounds correct. Neil, do you have a perspective on this? I feel like this is the kind of thing that, for whatever reason, I feel like we have a lot of self fulfilling prophecies in not just in the tech space, but specifically in commerce centered tech.

[00:13:05] Neil Hoyne: I mean, I always look at it in differentiation between companies. Right? If every company is doing the exact same thing, then the outputs are going to be equivalent and the advantages and efficiencies are there as well. I think that we have seen a move towards more and more specialization going pre COVID where things were in a steady state where you could benefit from that. If you wanted to look at optimizing a specific function, you could afford to hire, to train, and to retain people in that specific function and to capitalize on that money. Now all of a sudden, things change. Or I didn't take a course on production, but that sounds fascinating. I almost wanna bring up a whiteboard here and do it just because I wanna see what was discussed. We'll talk about that after the show. We'll put a link in the...

[00:13:49] Phillip: I love that. Yeah. For sure.

[00:13:50] Neil Hoyne: When people go through it, and all of a sudden you're saying, "Alright, we need to change, change our assembly line. We need to change our product." And you're not exactly sure what that product might look like. And there's going to be changes in the requirements in the production. And I'm going to take this metaphor way too far, but it's helpful, is that now all of a sudden you look at the labor that you have, and you say, "Wait a minute, we have all these specialist people. Can they bend to this role or this reality?" And it goes to this is actually something when I was at South by Southwest, I was joined by a professor, Stefano Puntoni from Wharton. Him and I were on stage talking even about, in these terms, how specialists identify with specific pieces of a job. And so there's bakers who look at the chemistry of bread as being their specialty and their expertise. And how do they react even if we say, "Well, you're really great at measuring the temperature and the amount of yeast and the amount of water. But now what's really in demand are cupcakes." How does that... Not only do you have the issue in terms of labor identity, you have that issue to say, "Is this going to be someone that can help you actually make these cupcakes? Do they have the skills across disciplines to say, "Now we need to apply your skills someplace else?'" And I think the argument is no, they don't. They could learn, but if you have an entire team of specialists versus these more generals, as you borrow from this term, positionless, then all of a sudden that flexibility is innate. That curiosity of working across functions is built into how they approach the job. So it's nothing new. It's just now their value goes up. And so I think companies that became too specialized are not only going to struggle in the transition, I'd probably go further to say they're actively going to fight against it. You're going to get those bakers saying, "No, no, we don't need to make cupcakes, plenty of demand for bread. We've always done bread. The business had been built on bread. Bread will come back." And then they miss those opportunities because they're forcing the world to adapt to how they see it as opposed to changing it to how their customers wanna see them. And then you end up with a problem.

[00:15:59] Phillip: That is very sort of a Luddite sort of mentality is we do have a... They are sort of in one case, it was, like, roles in society. Right? We don't wanna lose our roles in society. In another case, might be just a career based, maybe identity centered challenge. Like I don't want to lose, it's not just my job, but if my identity and the thing that I do is wrapped up in a trend based environment where the thing that I do in my talent is no longer in need or demand, it creates a problem. And it sort of reminds me of Goodhart's Law, which is to your point, when a measure becomes a target, ceases to be a good measure, which I think that happens a lot in businesses that look at a certain type of a hire and a certain sort of an organization structure as a target of a measure, that becomes a measure. And so we're trying to hire a specific performance marketer or a gross marketer, it's like a performance marketing team, or we have a specific org structure we're trying to optimize for, and then that...

[00:18:20] Neil Hoyne: And when you blow that up, what happens to your hiring pipeline? And you touch on a good point. It's not only the individual. The individual is a key part of it, but it's also how that rolls up and manifests within different groups. I'll give you a real world example. A few years ago, I was working with a retailer who primarily built their business on catalog. Their attribution model, how do they do it? If somebody received a catalog in the past two or three weeks and they bought regardless of channel, a 100% of the attribution went to catalog. Now, not surprisingly, they sent out catalogs very frequently. And it was also the largest team in the business. And the poor digital team is sitting there being like, "How do you know anybody's reading this shit? And do we really need a new catalog every two to three weeks? And we have all this data that says things are moving online." But because of the way the organization was structured, their role in digital was just a fraction of how big the catalog team was. And when you see those shifts happening, and this is one that you say, "When was the last time we really looked at a catalog and it drove our decisions?" But this was a business that said, "Look. We were built on catalog. Look at how large our catalog team is. This is what defines us as an organization." They will have a very difficult time as opposed to what I would have loved to see is a collection of marketers that say, "Catalog is a tool. Digital is a tool. Our goal is to drive revenue. Our goal is to drive growth. Which tool can we pull on?" But they became too closely tied to that identity, that specialization, that to pull away from catalog meant "I don't have a place here."

[00:19:53] Phillip: Pini, I just had this conversation last week with somebody who told me that they chose an ecommerce platform because they already had five developers in house. And so they chose a specific ecommerce platform because they had to have work for them. And I was like, that seems like the worst type of worst way to make a decision is you have to give these people work. I was like, "That was the matrix you use? I want to see the rubric you used."

[00:20:20] Neil Hoyne: Ecommerce powered by COBOL.

[00:20:26] Phillip: Exactly {laughter} But I think that those are, whether we want to admit it or not, I think that is actually how decisions are made a lot in organizations. And I think sometimes it comes out of, to be honest with you, really good motives, because I think that some people, we believe that that is people centric. Because we actually are, to some degree, maybe we're prioritizing some people in the process. Look at what we have, look who we have. We want to make sure that we are treating these people well.

[00:20:58] Pini: I can tell you that as a founder of a business, my situation is interesting because I'm Founder/CEO, so that creates a situation where often I see that the motivation function or the thing that I'm striving for in many cases is very different than even one of my executives. And it's not because they're a bad person or I'm a bad person. It's just different, right? So they strive, they try to steer to a place, you know, being people first, being... It's like, "I don't want these guys to hate me. I'm not going to do this." So a lot of things, and to me, when something isn't working, I feel like somebody is hurting my baby, you know? So I'm going to, no, I need to stop it. Right? My baby needs to get good care. So it's very, very different in the psychology and that, yeah, that drives that. I think I saw recently, was two years ago, I wrote my end of year letter to stakeholders and I read a bunch of Warren Buffet's. And then I saw he spoke of this guy. I may sound a little bit ignorant right now, at least, but now I'm not, but I used to. So he's like this guy, Charlie, Charlie, Charlie. I only knew about Warren Buffet. I didn't know about Charlie, Charlie Manger. So when I started looking at this guy, Charlie Manger, and he's got this really famous thing about this 24 rules of of human misjudgment or uncalculated decision making. And he actually mapped all of these places where we are not rational. And I think he did this the book about it, and you can look it up on YouTube. It's really interesting. He took his time because he saw so many bad investment decisions coming from bugs that we have as human beings. And he said, "I want to be aware of those and never, never hit those traps."

[00:22:56] Phillip: I mean, that actually leads straight into a point that actually had dock eared for you, Neil. And meet better people. I did a chapter here in the book, "Trust first impressions." I think that I highlighted Oscar Wilde's quote, which is "My first impressions of people are invariably right." First impressions, I think, are an important part of what, you know, I think we're trying to lead by. There's a lot of intense signals on that, too. But I think you're trying to get at a lot of things here, which is, giving people a framework for getting started, giving people a framework for motivating things like your CLV framework. But I think in first impressions, too, to Pini's point, there's a lot to be decoded in there. Give me a little bit about some of that in the context of the book and a little bit more about your perspective there.

[00:24:09] Neil Hoyne: I think it was when writing it, it's difficult, I think, to go through and to say, "These are all the right answers for marketing if such a thing exists." As I was getting a lot of the book content together, I remember having a conversation. And Ritz Carlton is featured in the book in a different example. But when I was talking to them, I was asking them about all the data they have and how they personalize. And before getting into that, one of the things a gentleman mentioned to me, that's the Ritz Carlton, they call themselves the ladies and gentlemen of the Ritz Carlton, which I think is appropriate. He said, "How do we lose a lot of our customers?" I'm like, "I don't know." He's like, "A single negative interaction with someone on staff." And they said they take that to heart where as much money as they can spend on acquiring customers and developing relationships, it was just as important for them to say, "Here's the guardrails and saying, if we don't do these things, we'll be alright." Like, just don't screw up these relationships and these customers will stay. And a lot of things, including that first impression quote, were built around the idea that there are guardrails you need to have when it comes to customers. And one of them, the first impression touches on, is we have this nearly insatiable belief that if we acquire a customer and we give them enough love and attention, they will love us back. We'll see it. And these first impressions are often ignored. Where you are looking and saying, "Hey, here's a customer that just heavy discounted products, used a coupon code, you know, loss leading products, but now we got them. Cause we added them to the CRM database. And now we'll just market the hell out of them. We'll send them every email until they buy more. And then we'll declare that as a victory, cause we saw a click and a conversion." And you think about it, and they look at it, by the way, and they celebrate that in terms of the righteousness of their actions by saying, "Look, we got them to click and buy another terrible margin product again. Look, it's a conversion." And then you'll say, "Well, how much time and how much attention and how many resources did you spend trying to bring those customers in?" And on an individual level, let's not just talk about an aggregate. If this is your customer base, how slow and sluggish is your business and the worry that it now becomes truth that our customers don't buy often, our customers don't wanna pay a lot, and then that becomes who you are. And so that first impression was actually one of the ones I wrote. It was just indicating to say, "Your first impression is right, not only to give you confidence that what you see of those customers is real, but also to create a constraint to say, "After that impression, there's not going to be a lot more that you can do to change the direction of that customer, so be mindful of it.'"

[00:26:45] Neil Hoyne: It's okay to be optimistic to say you can win customers over, but there's also a practical reality that customers are who they are. And if marketers just kind of accept that, then they put a little bit more emphasis to say, "Well, if this is true, then we have to make sure we're bringing in those right customers early on, and that we can measure this behavior." And I say, "Yes. Yes, you can." And then we have to go through the actual path of them looking at all the people they acquired and realizing how terrible they were. But that's the step of therapy that every marketer has to go through. But it's at first I think, short realizations to say, we do operate in a very human environment. Or just so truth. How you would be comfortable if you saw somebody walking down the street to be like, "I'm worried about them." That may be true. Or you start talking to someone and say, "I can see this relationship working." That is also true. And you need to be more confident with that as opposed to saying, there's always times to change the game later on. The data and personalization can fix everything. I think data and personalization can just increase and accelerate the momentum of what you already have.

[00:27:47] Pini: So Neil, that's something I say at Optimove, to my staff all the time about moves that we make in the business. And often I think people mistakenly, it's exactly that sentence of they try to solve it. So they don't distinguish between the zero to one phase where something just doesn't work at all. And then they say, "Okay, let's put PR on it. Let's use a lot of tactics that we know that work. But we know these tactics work because our friends tell us that we have a friend that works there and he's doing a lot of partnerships. We got a friend that works there and he's doing a ton of branding. And we got a friend that's works there..." All of your friends are doing it on things that already work. And those things are accelerators. If you want to get it from zero to one, if it doesn't work right now, it doesn't matter if you buy a huge billboard, right? You need to get to... So people often talk about it in terms of a product market fit and in tech, you know, for example, it happens a lot on a day to day of every department, every executive, every initiative that they do, you can separate that to, are we just kind of like, you know, we have this franchise that works. We want to make it better. We still believe in it. We're behind it. Or are we trying out something new? And now, so I think this thing, this sentence of accelerate something only works. And by the way, I took it from Jim Rohn, from Good to Great. I don't know about you, but that's where I heard about it for the time. He talked about acquisitions like M&A's that's, you know, it usually works when it accelerates something that, whatever. But yes, I think it's a really smart thing that most people don't get right.

[00:29:32] Neil Hoyne: Most people and I'll even take it a step further because you mentioned something there. Systems and tactics. When we talk about people who are becoming very specialized, it's almost like tactics are all they can see because that's their scope. And I remember one time where somebody was looking, this is a lecture that I was attending where a gentleman from a private equity firm came in, and he was waxing poetically about how beautiful Apple's products are. And he was talking about it, he's like, "This is fantastic." He's like, "The packaging is beautiful." He's like, "Only the right amount of text." Imagine how much value that creates from the firm. And a couple minutes later, without a sense of irony, he was showing off some of the products that his portfolio companies were building. And one of them was in those clear plastic clamshell packages. And so I just had to ask him from the class, I said, "Wait a minute. You just told me how beautiful that packaging is, and now you're showing us clamshells." He said, "Oh, well, margins. You have to understand, Neil. Margins. This cost us 30¢. This cost us $5-10 to do. We're gonna keep that money for ourselves." And I said, "So that's the limit of the ROI is just how much you're putting in for packaging versus those long term things?" He's like, "Yeah. I don't know how to measure how that makes somebody feel. So we're gonna go with how much we have to spend." And I said, "Okay, this is the problem. You're looking just at that immediate revenue. Here's how much we're spending to put the product in the consumer's hands, not to how it may make them feel, not to look at how that brand and the development of that brand could allow you to charge higher prices to the market or reduce your marketing expenditures because all you're seeing is a line item to say, tell me the margin of that product. Tell me how much money you spend as a percentage of revenue on marketing, and then I'll tell you whether it's good or bad and not being able to see how those pieces connect and why that investment makes sense." That's just a problem with specialization as a whole.

[00:31:27] Phillip: Such a good point, too. And I think the measurement challenge, especially it's the coming into focus where we perceive that elite organizations have this capability to set cultural standards for customers that we, at obviously much smaller size and scale, that we don't have the ability to measure up to or to live up to, and so we don't even attempt to. And I think that we also believe at some point, especially in the SMB and like lower mid market enterprise markets, that we don't have the tooling that they have as well. We don't have the budgets that they have as well. And I think that in reality, we're shifting into a world where I don't know that any of those things are true. They may have been true in sometimes in the past. I think that all of that those are actually excuses, but that's beside the point. I think it's never been less true than it is now. And it's going to be even less true in the future. So I think as we're actually looking into now, as we're actually kind of thinking about how GenAI is going to change a lot of this, how do you if let's say that you were to inform this gentleman in the future, now we have tools where you can pretty much take all of this data and plug it into some data analysis tools to create some frameworks to be able to measure that sort of ROI. I think you could probably plug in a ChatGPT deep research and find production facilities to help find other production facilities for packaging so that you could maybe spend the same amount for a higher quality packaging... How would you advise now in the future, using GenAI as the framework, to shift this mode of thinking away from "I don't know" to "I'm going to find out?" I think that's the shift of thinking is that the I don't know is no longer an excuse. Right?

[00:33:50] Neil Hoyne: Yeah.

[00:33:51] Pini: Maybe extend on that question, I think how much of a belief does the executive need to have or in a new world where we'll have more answers, can more decisions be basically decisive based on data versus... Because I know I still work with a ton of belief. {laughter} I still do.

[00:34:15] Phillip: I think that's an even better way to frame that.

[00:34:19] Neil Hoyne: I'll go even further on this. I'm going to say on the executive side, do I believe that the gap for companies transforming to customer relationships is their inability to calculate lifetime value? Do I believe that if lifetime value came out of an AI model, they'd like, "Oh, we have it." I think that I look directly at the leadership as saying it's not a question to say, I think it's a tactic to go through. We saw this with some major brand last week, Duolingo, that said, "We're now an AI-first company. Everybody use AI for all of your stuff."

[00:34:58] Phillip: Right.

[00:35:00] Neil Hoyne: That's a tactic. And it's not gonna work in the way they expect, and language is changing. But the question will be for the leadership to say, it's not just giving them these tools. It's what do you wanna prioritize based on what comes out of them? You know, I remember years ago where Square was just getting started. And I sat down with their leadership team, and I said, "Explain to me. How the hell do you have such a nice app? You have a small team, limited resources, and your app is better designed than any of your competition. In fact, it's an advantage of yours." And they said, "Well, Jack Dorsey," who was the CEO at the time, "look, Jack has a design background. So he actually put design in between every other team, which means if something's ugly on the creative side or on the UI side, design's gonna shut it down and it will not launch." That was how he did it. And that worked as a very well system to implement that advantage. And I look at that now in this era of AI, that it's not enough just to hand these tools over. But if creative still has to argue with engineering, with legal, with ops to get the output of their work into market, then the fact that they're generating beautiful creatives doesn't matter. If you're personalizing content for a consumer, but you're only measuring short term ROI, the full lift won't matter because nobody's looking at it. If you can now calculate what consumers are going to do next, but your traditional metrics and how the board looks at performance are going to be all short term ROI, then it doesn't matter. And so I look at it with AI. I think all too often companies are thinking that AI in itself is a strategy. And I get that oftentimes where people say to me and say, "Neil, help me build an AI strategy." No. I want nothing to do with that. What I wanna know is what's a strategy of your business? How are you going to win in the market? And then how AI can help accelerate to get you there? That's the only question I wanna know because then you're still retaining what makes your team, your competencies, your value distinct as opposed to saying our reason to believe that we can win this market is that we're going to use chat GPT better than our competition. I don't know how that can be assigned. I don't know how that can be measured. And I know companies that are doing that, so it's a sad reality. I don't think they're going to make it. Everybody use our AI tools more often. Let's measure how many prompts we throw in per week. And is that number going up? No. Go back to the fundamentals of what makes your business special. And then I'll believe that you can do AI well.

[00:37:27] Pini: But it's fear, right? I mean, people basically... I think we all feel that this technological transformation is big because we all find ourselves impressed on a daily basis.

[00:37:39] Phillip: Yes.

[00:37:40] Pini: We are very impressed on a personal basis. And for that reason, we deduce that something big is coming, and then every other day, you know, on LinkedIn, you see somebody saying, you know, SaaS companies, as we know them will no longer exist. Or Satya Nadella from Microsoft says...

[00:38:01] Neil Hoyne: So I'm going to vibe code. Yeah.

[00:38:06] Pini: People will build their own apps, no more SaaS or what is this latest now? MC something?

[00:38:12] Phillip: MCP. Yeah.

[00:38:13] Pini: Yeah. MCPs. So an agentic this, agentic that, the three people unicorn, right? There's a lot of that. The three people unicorn. So I can tell you myself, like I find myself as a CEO, I'm like, and typically I'm like an old soul, right? I'm not that flustered by trends and, you know, you know, when I work out, I actually write it down on paper and one of my chief of staff makes fun of me. "So why don't you use the app?" It like,

"It takes me a you know, I just write it down." What do you want? It's like, "Why don't you do it on the app? I mean, you're so on a kick." So, but still I find myself, yeah, there's definitely a level of fear, right? You're saying I want to be at it because I don't want to be completely left behind. And I don't think it'll happen to me because I'm definitely at it. But I think that's the emotion that drives those people that tell you, "Neil, help me out with an AI strategy." Of course they're wrong. And it's about how their business innovates and what's the strategy of the business, what's the mission statement, the values and where they're going and how AI can be a part of that. But it's fear, right?

[00:39:23] Neil Hoyne: It's fear. It's fear. It'd be almost similar when I was younger if I said, "Hey, Neil, what job are you going to do?" And I'm like, "I'm going go work in a factory." Someone would say, "Oh, that job's going to be replaced by robots. Why would you go into that field?" And so you pick fields that you feel are future proof, you feel that are secure, that you build an identity. And then all of a sudden, practically overnight, you realize and say, "Wait. I can't be a programmer. I can't be a writer. I can't be a creative. Where do these fields go?" And that concern is real. We're we're talking before the show, but we'll bring it up for all the listeners here. I was at Harvard Business School last week, and I was asking them how do you adjust to this AI era knowing that the case method, reading these 30 page cases and studying all the data are so laborious. People can throw them into Chat GPT or Gemini and get a full summary. In fact, before going to their class, they sent me 20 case studies, and that's exactly what I did, what most of the participants did. And they said, "We actually encourage it." They say, "Because this is the reality that we're working under." And the professors actually had an interesting, and I would consider and these are academics who are very stuck in their ways at times. They said, "We think it's easier to accept the world for what it is, not to block tools out because when you go into the real world at a job, people are going to be using it. And to say, "Let's figure out how we adjust our teaching methods to this platform.'" And so the way they actually approach is they say, look, we spent a of our time and most of the students prep on simply getting all the foundation figures. What's happening in the business today? Can you extract all that information? They said, "Now we don't need to spend thirty minutes of a class just being like, "So tell me what year did this happen and what's their market share?'" We have those answers. And they say, the challenge is if we've moved that benchmark a little bit higher, where else can we push this conversation in this lecture? Which I think is a fantastic forward looking view. Here's where the tension comes in. What do you say to a graduate of that program from last year before these AI products were adopted and say up to a of your degree was now spent on tasks that the market has determined are obsolete? It's just the reality of it. That's how they spent a third of their time. The world has become more efficient. The world can now review syntax and bugs and provide frameworks of software within seconds off those ideas.

[00:41:52] Pini: But do think it means that the grad from last year was actually penalized or got dealt with a bad deck of cards?

[00:42:02] Neil Hoyne: That's a question, and I will have to say yes. If you have two graduates where they say, "I had thirty more minutes of every class that I took talking about substantive issues, competitive behaviors, new information that you didn't have," it's hard for me to say, "but they did this without ChatGPT."

[00:42:25] Pini: Yeah. But you know, you remember the, I think it takes me to Isaac Asimov, right? So Isaac Asimov has a collection of short stories and one of the short stories is called "Profession." And it's from 1954. I've never read it by the way, but my dad used to tell me about it when I was a kid, because my dad was like really excited about technology and AI because Isaac Asimov was always talking about the future. So in this story, in this short story, the story is about this character called George and he's like 21 now and he's supposed to get his profession. And in the future you go into this room, they decide in advance that you're going to be a coder or a lawyer or an engineer. And you go into the room, you go five minutes, you walk out, you're an engineer. You have all the knowledge of an engineer embedded in your head. That's it. You're done. And George, the main character was chosen not to do that actually to go to law school for four years or something. And throughout the book, he's basically saying, "Why, was I penalized? What did I do wrong?" And then apparently kind of like the masters of society choose certain individuals to be the true creatives and they have to go through the old fashioned path to become... That's a sci fi story from Isaac Asimov. But I think it brings this question to like, is it worse or is it like, what's better to your point? You got thirty minutes more, but you didn't struggle. You create certain neural pathways in your brains because you didn't have to go through that type of a struggle. And I have another friend who's a famous film director here in Israel, very successful. I'm not going mention his name because he's afraid of technology and everything like that. And I was like, "Are you using chat when you write a script?" He's like, "Hell no." I was like, "Why not?" And he told me, "What do you mean? Like, the whole point of art..." I was like, "You can consult with it. Like, if you're stuck on the script and you don't know where it's going, you can get a great idea." So he was like, "What do you mean? The struggle. That's the art. Struggling with that and eventually coming out of it. That's art. If I do that with a machine, I'm done." You know? So I don't know.

[00:44:51] Neil Hoyne: I agree with you. And it's not to weaken the earlier position, but I will say, I think within certain disciplines, like business are an example, in that context, the user is always directed, the student is always directed to reach a particular answer through that discussion. And when you're discussing facts and figures where every conversation ends the same way, like you're going to put all the same relevant facts, there's not a lot of room in those curriculums to deviate. Those are areas the same thing where I would say in some parts of programming, if compilers can ever look at creative structure and stop yelling at me for missing a semicolon, then I love them. But they're like, "No, this is the way you must frame this situation."

[00:45:35] Pini: Right.

[00:45:35] Neil Hoyne: Those areas, I would argue, you're right, are easy to be replaced. But you're right, there's a larger question to say, how do these dots come together? And if you have access to a proprietary piece of data or a viewpoint that's not incorporated in the larger thinking, which means it's not incorporated in these AI models, it hasn't been seen, that idea of original thought will extend past it. It's very similar. I have reason to believe that my book has been used to train some of these AI models because when I ask about things that are very specific as to how I frame things, they seem to get it right.

[00:46:13] Pini: The accumulation of all the human knowledge put in this gigantic neural network.

[00:46:19] Neil Hoyne: Yes.

[00:46:20] Pini: It statistically produces similar answers to what you had in your book.

[00:46:24] Neil Hoyne: Yes. Yes. And it can build connections that I haven't seen and I would argue, oh, those are new inventions, but it can't go beyond it. It can't think about what hasn't been done before. And this is kind of where I think everything comes full circle, is that if you end up with a marketing field that's been dominated for the past twenty five years by short term interactions, by high amounts of specialization, by a lack of personalization with customers, then I would expect that the data in this larger corpus as well as those that most companies have in their own systems that they're mining also reflects only those short term relationships. People have never asked. They've never cared. And so now you get to this thing where I don't think AI will help them to solve this problem as much as it comes back to that leadership side to say, how do we do something different and how do we use these tools in service of that direction instead of deferring to them?

[00:47:21] Pini: So I'm a huge believer that all of those things that you're saying about, you know, how marketers work and they're myopic in their nature. And I agree with all of those things and work with a lot of them on a day to day basis, but I think fundamentally it comes from a problem in execution. It's really tough to do a lot of these things at scale. I'm going to go back to Henry Ford and the T model, right? His famous sentence was, "You can paint any color you want as long as it's black." Why did he say this? Because it's hard to paint it in many colors in nineteen twenty something. It's super hard. I mean, who can do that? So he made it into a fun slogan, like, all the cars are gonna be black and shut up. I mean, that's I just I mean, not going to personalize, like leave me alone. I have a car to build. So now we're saying, "Hey, personalize, but what do you mean? I got all this work, right? I need to create segments and briefs assets and visual assets. And I need to argue about this and then the copy and this and goes in. And then analytics have to measure it. Then I go into the execs and persuade them to give me more money." It's like, oh my god. I'll just do one a month. I'll just do one a month. Just leave me alone. I'll do one a month. I'll go through this whole... I don't have the mental energy to do more than one a month. What I'm saying is if teams become more similar to the A team, I don't know if, Neil, you're probably roughly... I feel like we're the same age bracket, and probably, I feel like we're the same age bracket.

[00:48:49] Neil Hoyne: I know the A Team and I also know they had that reboot into a Motion Picture.

[00:48:55] Pini: Oh, really? I'm talking about the OG show from the eighties.

[00:49:00] Neil Hoyne: Yeah. They brought it back with like Bradley Cooper... but I'm with you on it.

[00:49:06] Pini: Yeah. But the concept, it's a small team. And within that team, they can accomplish a lot, right? A ton. Because, yes, they're each one of them has their own, you know, thing, but they're all pretty kind of like diverse and they can do a lot, they're all fierce and they're all this and they share those attributes. And I think if you change the org structure and you allow each department to do more things than they do today. So my question is positionless is not a binary thing. You either that or you not that it's, can you be more positionless? Can you relax a little bit, like have that team give them autonomy to do 10% of the tasks completely on their own, soup to nuts. See what happens. They got GenAI, they can figure it out. They can figure it out, let them do it. And then the other team that's always being harassed by, they're freed up to do more creative things now, right? And then you get the speed. And then all sudden you can produce a campaign. We just published a case study on this Optimove Connect when a company took down the campaign creation time from six weeks to twenty four hours. Because it's a small team, it's not about the I mean, our tech allows for it, but ultimately it wouldn't happen without the change in the org structure. That's what I'm saying.

[00:50:28] Neil Hoyne: I think you need to have you to play more on that human angle. Risk aversion, right? If you called in and said, are you going to be a constrained marketing team? Are you going to be a limited marketing team? Are you going to be a position dependent marketing team? Everybody would say, "No, we don't want to be that." And you're like, "Do want be positionless? Do I have to do something?" "Yes." "Oh." You know, I think you got to play on that because the opposite, I think, becomes more salient with people. What you're saying is you need to be positionless. But a lot of companies now are specialized. They are overly indexed on specific positions. "I do one job. I have a small part. Everybody on our team has a small part on that assembly line. We do not have any craftsman on our line that can see a product all the way through and find opportunities. We only have people that know their role and know it very, very well. And I'd agree with you in that context to say, that's not going to be what marketing needs today. And I don't think it's gonna be what marketing needs in the future when so many things are changing.

[00:51:30] Phillip: There's a headline that's been floating around, which will sound aged by the time, you know, I don't know, a year or two from now when people listen to it. Airbnb was, you know, looking at doing an internal legacy platform migration, and they had internally estimated it was gonna take about eighteen months to do. Instead, they did it in under six weeks because they give it to an extremely small team entirely powered with GenAI tools. And I think that rather than doing it the legacy way where you have, you know, a lot of change management and a lot of... I want to argue the opposite side of this. And then maybe we can also bring it home here because I this has been such an amazing conversation. But I have to believe that someone on the other side of this conversation is listening and saying, "What are the other sides of that?" Are there wrong lessons to be to be learned? Because for every great outcome like Airbnb, which loves to talk about things like this on its engineering blog, I wonder how many people learn the wrong lessons and over index. So are there excesses? Right? I have to believe that there's people who could swing too far to the other direction as well. So I'd leave that to is there a critique of that that you could say there is a maybe a wholesale adoption of something like this that could happen too fast or risks that could be entered into the organization that can't be anticipated? What are things that, you know, are just good advice and best practice that we shouldn't be abandoning in pursuit of positionless as the world is making this big shift?

[00:53:17] Neil Hoyne: I think it's all going to be a spectrum that's defined by consumers. It's defined by the market. And I say this to say, if you go back let's go back a hundred years, where before the assembly line, before manufacturing, goods were handmade, you knew the artisans behind it. There was a lot of pride, there was a lot of durability. And people always kind of joke about things aren't made the way that they were used to.

[00:53:42] Pini: Oh, by the way, and those manufacturers were positionless, right? They did those. Yeah,

[00:53:47] Neil Hoyne: They knew the entire thing. And then you go through and then you put it into assembly line. All of a sudden it becomes more accessible, right? Because the prices can drop, your manufacturing. And then what are people commenting? Things aren't built like they were used to be.

[00:54:00] Pini: Quality.

[00:54:01] Neil Hoyne: And you notice that difference and then all of a sudden that fetches a premium. And so I look at it, on one side you have incredible amounts of specialization, on the other side you have a very generalist positionless. And I think what's happened is we've gone too much towards specialization in the areas where things were predictable and steady state. What we've talked about is over the past five years, and increasingly now with GenAI, it's the opposite of that. And so now the opportunity is to go to that other side to say, "Look, we can build things like they used to be. We can personalize, develop them as they were, and we can demand a premium from the market for them. And so that's what we're seeing is we're just seeing that momentum. It's not a right or wrong answer as much as it is understanding what the market needs today, where the balance is with other companies, and knowing that far too many companies have gone down that specialized position based path that is time to draw a little bit of attention to it and say, "Hey. See what Airbnb is doing? See what Apple's doing? It turns out these small nimble teams can take advantages of opportunities in the market that all you specialized ones can't."

[00:55:04] Pini: To me, Phillip, it's mostly about the scare or the way to do it wrong, is you completely go to the other side, to the other extreme, meaning you're saying no professions, no speciality. So I don't need to hire designers. I'll just hire a bunch of generalists that, you know, people who have right brain, left brain capabilities. I'm going to give them GenAI and that's it. I think you still want designers. So a designer now, let's say if in the past when you're a specialist, 100% of what you did was design, I'm saying it's going to go down to 80 And you'll do a little bit of writing and a little bit of analysis and a little bit of that, but you still have a strong nucleus of your profession. That's what I'm saying. I'm not saying that designers should be completely disappear because AI can design, right? Even if AI can design, I want somebody who studied at like a great school of design to walk with AI and get a really good produce. And I think if we go back to basketball, which is the world I took inspiration from when you had positions and you had the center position, now they call it a big. Now, the thing is the big can play the four position or the five position, or you no longer say a shooting guard or a small forward, you say a three and D guy. So somebody who can shoot the three and do defense on the other side or somebody who can self create. So it's like, it's not position, it's roles. They actually call them roles in basketball. Role is to be a rim protector and a big, and you need to, I don't know, do this and this on the pick and roll, right? You got to do... So it evolved to a place where the positions are much more fluid and the roles are more distinct. And a role is you can do three things really well. So now you have a role. So I think it needs to be like that. I think basketball has given me the answer at least. That's the analogy I take.

[00:57:13] Phillip: I love it, Pini. I know we're right at the end here, Neil. It's been such a pleasure. At Future Commerce, we like to say commerce is culture. I have to believe if converted, you say you might be you started this book five years ago. If you had a follow-up that was to come, is there a cultural shift that you think that would predict that could upend the CLV model? Is there like synthetic consumers, agentic purchasing, I don't know, the next internet. What's something that we haven't named yet that might make you have to come back and make the second edition of this book?

[00:57:58] Neil Hoyne: Thankfully, I've seen a few words. What do we have? We've had crypto, blockchain, NFTs, Web3 for a time. We will go through those oscillations in tech. Most of the models and the principles are selected because they've been durable for decades.

[00:58:12] Phillip: Yep.

[00:58:12] Neil Hoyne: I don't believe that there would be changes that would unseat that. Maybe if AI starts doing all of our purchases for us, we just have AI models talk to other AI models and the definition of a customer changes, then it could be different. But generally, they've proven to be fairly resilient. I think if anything, if I wrote a follow-up to it, it would really be one of those things to be like, "We have to be careful in our current world where we think about marketing that everything changes so quickly that we have to relearn everything." All the fundamental principles remain the same. Consumers want to have relationships with the businesses they work with. We need that flexibility in our roles. The market conditions change. All the technology in between, that will change faster than who consumers are. So all the skills that people are learning is that's what I say, systems, not tactics. And I think that plays very well here.

[00:59:06] Phillip: Appreciate it. It's been so, so great. Thank you so much for your time.

[00:59:10] Neil Hoyne: Pleasure's mine. Thank you for having me.

[00:59:11] Phillip: Thank you, Pini. Thank you so much for listening this episode of Decoded. If you want more from this podcast or anything from Future Commerce, go to futurecommerce.com. Of course, thank you so much to Optimove for making this series possible and stay tuned for Episodes four and five from this Decoded series.

[00:59:26] Pini: Thank you.

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