In this episode, Lenny Murphy welcomes Stephan Gans, SVP Chief Insights Analytics Officer at PepsiCo, and Ryan Barry, President at Zappi, to discuss the launch of their new book and their transformational partnership that’s reshaping the consumer insights industry.

Together, they dive into how PepsiCo and Zappi collaborated to transform the insights process, the evolution of their partnership, and how brands can leverage technology to gain deeper, faster consumer insights. Key takeaways include their lessons learned, the potential of AI in insights, and how to navigate the cultural change that’s essential for success in today’s market.

In this episode, we’ll explore:

• The launch of the Consumer Insights Revolution book and its immediate success.
• How PepsiCo partnered with Zappi to transform insights into a strategic, tech-enabled function.
• Why owning your data is the real competitive advantage in a world of AI and digitalization.
• Insights on navigating the challenges of integrating technology into global companies.
• The future of consumer insights, and how AI will reshape data-driven decision-making.

Resources:

Consumer Insights Revolution Book on Amazon

PepsiCo’s Website

Zappi’s Website

You can reach out to Stephan on LinkedIn.

You can reach out to Ryan on LinkedIn.

Many thanks to Stephan Gans and Ryan Barry for joining the show. Thanks also to our production team and our editor at Big Bad Audio.

Hello everybody. It’s Lenny Murphy with another edition of the Greenbook Podcast. Thank you for taking time out of your day to spend it with myself and my guest. As always, we deeply, deeply appreciate it. And I guess that’s a good little segue. Today, we are talking to Stephan Gans, the SVP Chief Insights Analytics Officer at PepsiCo, and Ryan Barry, President at Zappi. So welcome, gentlemen.

Thanks, Lenny.

Thanks, Lenny.

It’s great to have you both. I know, Stephan, you did a podcast with us recently, but it was just you. And now you drag this guy, Ryan, along with you. A little context before we dive in., I will give Ryan some hell because we’ve known each other a very, very long time. And full disclosure, everybody knows I was an advisor to Zappi for many years, and so I’ve had a front row seat to watching the evolution of the company.

I will—you’ve said this publicly, so I will take credit for it. I introduced you and Steve at IIEX in Atlanta, the best recommendation I ever made for anybody. So, this is special, especially because we are talking about, really, a pretty big milestone for any company, and that is the launch of the Consumer Insights Revolution Book, number one Amazon bestseller—yeah—in one week. It’s a fantastic book. Yes, you guys, if you’re not seeing the video, everybody’s, you know, going, “Woot, woot.”

Let’s talk about that. I mean, it’s just really a hell of a week, right? You’re in New York, on the big board, in front of the New York Stock Exchange, all types of cool stuff. Let’s just talk about that for a minute. What’s this week been like of launching a book, and the success you’ve got? And then we’ll get into the book itself.

So, I have to say before we talk about this week, Lenny’s right, he introduced me to Steve, who’s not only been my business partner for ten years, but also one of my very best friends. So Lenny, thank you. I get a lot of unsolicited LinkedIn emails—as you both probably do—but the, “Lenny Murphy, are you looking for a new gig, question mark,” one couldn’t have been more well-timed, and I have zero regrets of taking that call. It was awesome. So, thank you for your friendship and everything.

I guess I’ll talk about this week, and before I do talk a little bit about the process. We started writing this book about a year-and-a-half ago, and the process of creating a book is, particularly with multiple people that have different perspectives, different expertise, is fun, but you also end up reading and writing quite a bit of time. And so, there’s been this lag of excitement. And this week was just surreal. I mean, we were in Times Square with our wives, Stephan’s son came.

We had this amazing party where we had someone gave us Sharpie markers, and we were signing books for people. And I guess we felt like geek celebrities for a few days. And it was just great to share it with our colleagues, and our families, and our friends. So, yeah, I have to say, it was a bit of a pinch-me week. And I found myself back here today on, like, a normal work call, and just being like, “Oh, right. Back to normal.” But I really enjoyed it. Steph, what’d you think?

Yeah, I share a lot of the same emotions, Ryan, but on top of that, I feel—I’m not, let’s say, by nature, somebody who assumes that what I have to say is necessarily interesting for others, [laugh] so for me to see my name on the book and to see that people are actually interested in buying it, I had to overcome some internal hurdles to fully engage with that. But then I did. And by the way, just the intimacy of the events, and the feeling of family between my team and Ryan’s team that has grown over the years, obviously helped with that a lot.

I am still thoroughly enjoying it, right? And I’m telling this to everybody on both teams. So, this is the launch week. That’s great. Let’s celebrate, but this book is news for at least a year, right? Let’s not make the mistake most marketers make, and that is that things start to feel like old news way too soon. So, this is a relevant story for a lot of different people in our space, and it’s going to remain relevant for maybe years even, I’m afraid.

Well, it’s like, it’s a labor of love of ten years of work and transformation, but as we were talking this week, there’s still hundreds of heads of insights that have a bit of a shortcut in front of them, if they take the time to read it, and maybe can avoid some of the steps we had to work through. And that was really our goal in creating the book.

Well, that’s a great segue, right, so thank you for setting it up. I mean, again, having this kind of ringside seat, I’m aware of this very interesting, almost symbiotic, transformational journey that PepsiCo and Zappi have collaborated on. When Stephan—you know, shout out to you of having that vision and finding a partner that to say, “Okay, here’s what this is going to look like, what the future is going to look like.” Not just the present, but the future, and working together. So, let’s start with that from your perspective, Stephan because you came in, obviously, with the remit, PepsiCo is a very storied company in terms of, you know, leveraging insights, but you had a different vision. And talk about your vision, and then how you aligned with Zappi as a partner to help bring that to the market? Because that’s the crux of the story in your book, is that journey and the lessons learned.

Yeah, it’s kind of the red thread through the book. And, Lenny, I think there’s a—I’m a very practical person, right, and I think this is something that Ryan and I also definitely have in common, practical, realistic. And so, the word vision in and of itself, I guess, that sounds lofty, or it sounds exciting, and it sounds commendable that somebody has a vision, but where it started is just a more of a conviction that we couldn’t continue the way—we couldn’t continue to work the way we were working. So, it started with running away from something, not necessarily, you know, with clarity about the direction to run into, right? I mean, and I think by the way, that is how most visions come to life, but for sure, this vision.

I came into the role I’m in today, seven years ago. And I, of course, as one does, if you lead a function that is spread across all these different divisions, in all these different parts of the world, in a company that is the size of PepsiCo, you go and talk to people, right? Because I didn’t come in with a vision. This is the first insights job I’ve ever had. I’ve always been a marketer and a consultant.

And that vision was really like, okay, we got a role to play in this company. I always say, you know, what consumer insights does is identify, enable, and optimize. Identify opportunities for growth, enable the company to do the world’s best marketing and/or innovation, right, and optimize our in-market presence through human-centricity. And in order to achieve that, we need a certain toolkit, but not only a certain toolkit, also a certain way of working, and a certain operating model, and a certain way of organizing ourselves. And while working with Zappi the full, let’s say, potential of what digitalization of a function really entails became more and more clear to me.

And I think I benefited a lot from the fact that I, frankly, don’t have a background in consumer insights. I sort of—

[laugh]. Right.

—I sort of very respectfully, if you’re a marketeer for most of your career, and you come into a consumer insights function, then you’re very clear about what consumer insights can be and what you would like it to be, but you’re not too hampered with this is the way things go, or you’re not too bothered by the operational limitations that’s, you know, if you make a career in a function that everybody kind of gets used to and starts to accept as given. There was nothing cast in stone for me. And that’s, yeah, just because of—credit to PepsiCo for hiring somebody with, like, I guess, a relevant background, but not too relevant of a background for the role.

And to be free from the orthodoxy and the biases. Now, Ryan, if I recall correctly, this relationship started manifesting roughly, what, kind of five years into your growth story or so for Zappi, and I suspect that there was an ‘oh, crap’ moment as a startup, still a startup, still growing, to find this relationship. Because I’ve seen other companies that, “Oh, we landed a relationship with P&G,” and they couldn’t manage it, right? That relationship dominated the entire company and brought a huge number of complications as well, so they couldn’t actually grow as a company. So, that’s a challenge on the supplier side for the partner side. So, kind of, walk us through what that looked like for you when you met Stephan and started to get a sense of what his conviction was, and what that meant for Zappi to adapt as a company to help fulfill that, and what that journey looked like for you early on. And then we get into the longer-term learnings as we go.

Yeah, that sounds g—so I think two things. It’s worth noting that Zappi had been doing business with PepsiCo before Stephan got there but, you know, like a lot of companies who landed PepsiCo, you’re doing it in pockets. But there had always been this fostered culture of innovation out of pockets of PepsiCo. I think of the early days with Gatorade and other businesses, where we were always kind of looked to PepsiCo to inspire us. And if I go back to 2014 when Zappi was really getting off the ground, Steve’s original thesis was, if I take the thinking of the agencies and the software of, say, the Survey Monkeys of the world, and deliver that, I can give brands, say, 80% of the answer quickly. And that was V1 of Zappi. It was very much an app store.

And in those early days, right, around before the time Steph got there, but just around that time, we had basically had a channel business, and some of our own products to get in the door. And it became clear we were growing too fast for the channels’ comfort, the big agencies that’s products we were using, so they were—you know, it was tense. You know, channels are good until they’re not sort of thing. But more importantly, what we kept hearing over and over and over again from brands was, we need speed, but we need tomorrow’s thinking quickly, and we want our data to be worth something, and we want to own our data. And so, it started to sort of ruminate in our brain.

And I distinctly remember the day I met Stephan. I live about three hours away from Purchase, and in the early days of Zappi, I was driving to Purchase, New York, twice, three times a month, in some cases. And I walked into his office—and I didn’t realize we were going to write a book together at that time, of course, or in many ways, change his entire department—but he had this piece—and I can vividly remember—he had a piece of paper on his wall. And I remember before we even get to talking, going, oh, we have this exact same vision for this industry, which is, how do you use technology to get answers in the right people’s hands quickly, to give brands a data asset they can learn from, but to actually enable insights people to spend their time on human-centricity. And so, we had that conversation, and it triggered everything that’s come since, but I just remember leaving Purchase that day, buzzing with energy, and calling Steve and saying, “We’re pivoting the company around this Pepsi thing.”

And we did. We ended our Kantar partnership. We bet, quite literally, the farm on this thing. And there was nowhere to go for Zappi, other than to make it work. And we spent the next five years figuring out, how can we prove that we can do this at enterprise scale? And so, Stephan and I had, I think, a kind of cool idea, but people thought was crazy at the time. Why don’t we do this together, but bring friends, and bring in other manufacturers so that we can develop tools that are going to work cross-functionally?

And you know, so we spent a lot of time just laser-focused on—and frankly, making a ton of mistakes on—you know, shit, we actually can’t pull that off, right? Oh, wow, it’s really hard to change this behavior, or maybe underestimate the matrix nature. And so, you know, it’s been an amazing ride. And Steph said this week, like, if he had had our book seven years ago, we’d probably be—his life would have been a lot easier.

And so, that’s our hope. Like we spent a lot of time and effort making mistakes, iterating, figuring things out, and I think, you know, we could help others get there faster, while we figure out the next three horizons that we want to go on, which we are doing. But honestly, it was a—I think you probably know this about me, Lenny—I really believe fortune favors the bold. And I think we both are—and our teams decided to bet on each other, and we set it up where we had to stick it out through thick and thin. And you know, it’s been an amazing partnership that’s turned into some amazing friendships and relationships.

That’s very cool. And you don’t hear that very often in, well, in any industry, but certainly not in ours of, again, this kind of deep connection that isn’t a supplier relationship, but a partner. Everybody uses the term partner, but I think you guys actually did it. And let’s talk about that. Let’s talk about the learnings from this transformational partnership because a huge through line in the book is the learnings from that, you know, behavior change, you know, working through the entrenched orthodoxy of well, but wait, this is how we do things. And so Stephan, let’s start with you. What were some of the key things that you learned along the way pushing through this transformational strategy in thinking about the insights process, and what it could do to drive impact in the organization?

Yeah, it’s a big question, but I think—and I guess this is where a little bit of vision came in, is that about the way we set up the partnership. Ryan said, “Let’s”—we decided to set it up and bring friends, right? I think it felt incredibly logical to me that, let’s say, the competitive advantage of this kind of capability that we would be building jointly would rest on the ownership of the data that the tool generates, not on the tool. For me, that’s a complete no-brainer. I have to say, though I’m in a ton of discussion since, internally here, where people say, “No, no, we need to own the algorithm.”

I don’t think that is smart because I think our algorithm, or our tools, get better by being exposed to other fantastic advertisers that Ryan and his team work with. And I want my tool to be exposed to those other great advertisers, but at the same time, I do want to own my data. And so, the reason I start with that, Lenny, is that once I realized that, the team and I, internally here at PepsiCo, talked a lot about that, we came to realize that, you know, that’s, in a way, that’s a nice thing to say theoretically, but what does it mean practically? Well practically, it means that if you test 23, say, Gatorade ads, then you’ve become 23 times smarter, right? Then, you know, in the past, we would test 23 Gatorade ads, and we would have to kind of go back on our knees and bring a big pot of money—and by the way, a ton of time—to ask the vendor to do some meta analysis for us. And now we were suddenly able to do this ourselves.

And so, once you’ve thought of that, it becomes very logical to then say, hey, let’s set up a little team of three to five people that are basically a resource for all our businesses across the world to actually drive that meta-learning, and help those people with mining the data in the best possible way. Now, at the same time, consumer insights people historically are used to partner with agencies and consultancies, right? And so, here’s a partnership with a software company that happens to work in consumer insights. I mean, Steve and Ryan could have also started the bank, [laugh] or done something else. But it’s a software company first that happens to work in insights.

That comes with a certain set of skills and a capability that I’m a huge fan of called customer success. Don’t go and look for customer success type of resources with McKinsey or Ipsos or Kantar, right, because it’s not—I would cynically say, it’s not really in their interest to make their customers very successful because—

[laugh].

—that diminishes the reliance on their brilliance, right?

Yeah.

And so, okay, so then you have a customer success function. So now, if you’re an insights person in, say, Spain, you have, of course, the global insights team—my team—that is kind of telling you, like, this is the new capability, it’s super exciting, these are all the examples, you can call us anytime, all right? But they’re in New York. They’re far away. But you have another small group of people that can help you with the interpretation of the data and leverage the data to the most, whether it’s through meta-learning or direct analysis, plus you have the customer success team of Zappi that can help you with anything around am I setting this study up in the right way? I don’t understand this function? Should I be thinking about this or not?

And so suddenly, on the one hand, you don’t have the comfort anymore of being able to hide behind the external consultant as an insights person, but what you’ve gained is better data, a better tool, that is a ton cheaper, like, seriously, significantly cheaper, that is, like, incredibly fast, ultimately, like, so much faster than what I’m used to, and that I can, as a result of all these things, use a couple of times if I want to. It’s not one and my budget is gone, right? It’s like, I can use it three times, four times if I want to test another whatever. Plus, I’ve gained these friends, you know? And so, there’s a bunch of customer success people in Zappi that should take a ton of credit for the progress we made as PepsiCo because the progress is made in the market, right?

So, Ryan, what was that—you know, early on, the vision was, we’re going to build a SaaS company, you know, and we’re going to be a unicorn, billion dollar valuation, no service because that’s how you know, the myth has been for a tech company, a SaaS companies can’t have any service, while those of us in the industry—in this industry—know that’s bullshit. There is no technology company that has ever succeeded without some level of service, for all the reasons that Stephan just laid out. What was that, like, to build out that capability and recognize that there was going to be a unique component where you’re going to have the best of technology—and early on, AI, machine learning, right? I mean, that was foundational to [unintelligible 00:20:45] you were AI before AI was cool—

Yeah, we were.

—you were, yeah—and we’ll get to the current era in a minute because I think it’s interesting from that standpoint—while also having the best of the service capability to help with this transformational journey into adapting automation and AI into organizations to unlock the potential that Stephan was laying out.

Yeah, so I think Steve and myself probably had an advantage because we had been in the insights industry for a long time, so we knew how it worked. We knew the tensions. I mean, that’s why, when you texted me that day and I went on that horrific V1 website Steve had, I was like, “I totally get what he’s trying to do. I want to be part of it.” But we always had this flywheel. Like, if we give our customers a better answer easily, they’ll adopt more, they’ll get better, they’ll get more data, their answer gets better, and so on and so forth.

So, a lot of our early decision-making lacked some of the vocabulary that I’ll probably share now, but it was, what are the things we need to do to make the flywheel spin faster so that our customers get better data, they get better answers, et cetera, et cetera. And so, a lot of our decision-making was, sort of, grounded in that. And I think the dawn of Zappi’s customer success team came right around the time of our partnership because it was like, “Oh, wow. People are coming in, inbound leads, to test an ad once. They’re not becoming customers. We’re not setting them up for success. We’re not teaching them how to fish.”

And I credit Julio Franco, our Chief Customer Officer, for this. I asked him. I said, “Hey, there’s this budding industry in SaaS called customer success. I know you’ve worked in market research your whole career, but can you start that out and figure it out?” And we went from having a really horrific churn rate to industry-leading net revenue retention within eight months of his tenure of doing that job.

And it was a lot of because of what Steph said. Like, how do we set people up, right? How do we teach them how to fish? And then that led to the next opportunity. Every business is going through some degree of transformation. We talk about this in our book, level one, two, and three insights. We actually created an insights maturity matrix to help organizations kind of guide themselves. But if your organization is using technology for the first time, forcing them to push buttons right away might not be the best thing to do.

And so, we realized we needed to offer a series of professional services to help people set their system up, to help them push the buttons, to help them present to their CMOs. And we also realized there’s a monetization angle to that, so it was a smart thing for us to do. And some businesses, like in the case of PepsiCo, are in-sourcing some of that work through Global Business Services, Diversified Services, whatever you want to call it, others aren’t. And so, I think for us, it’s like you could be a software company as long as you’re clear about the value you’re bringing with software being different from the value you’re bringing with service. And I think that’s where a lot of businesses—at least on the B2B side—get it wrong.

Because if you go back 15 years in time, the market research industry’s growth strategy was, do good work; phone rings. Do better work; phone. And I think that’s bullshit. I don’t think customer success is about saying, “Yeah, Stephan, I agree with everything you say because you’re Steph Gans, the chief insights officer at PepsiCo.” My job is actually to understand him and his problems and challenge his thinking so he can be successful. And there’s a difference.

And I think that’s one of the things in our industry, client-side and tech agency vendor-side, that we need to improve upon. We’re not servants; we’re catalysts of change, and that requires us to solve problems with a clear path, not, “Yes, ma’am. Yes, marketer, you needed an ad test done. How high should I jump?” And that’s why we spent so much time in our book, really trying to lay out a framework of an ecosystem that can run itself so that insights people can actually be strategic. But, you know, it’s equally about people, as it is about technology, as it is about process. Those three things all have to work together.

Yeah, could not agree more. Not that you need me to agree, but I… but I love—

[laugh]. I very much value your opinion, Lenny.

Thank you. Thank you, Ryan. And so, I would say you’ve been an example of—an early example—of a trend that now is just here, front and center, period. There’s no getting around it. You were the poster child, the beta test for now what is simply ubiquitous and undeniable. Because the power of AI has unlocked a lot of these same trends. You saw them coming—both of you saw them coming—you started adapting.

Now, I think a lot—that’s why I love that the book coming out now because I do think it is a guide for many organizations that are struggling with, oh, my God, AI. What do we do? Well, here you go because it’s exactly the same thing. It’s exactly the same process. You know, the journey is going to be the same. The tools may have changed a little bit, become slightly more sophisticated, a little more holy crap [laugh] in some cases, and what they can do, but there we are. So first, do you agree with that, that kind of, the journey you’ve been on now the rest of the world is suddenly forced to get on the same train?

I do agree with it. I also would say, when we started Zappi and when we started partnering with Stephan, the industry did fundamentally have a technology problem. We don’t have a technology problem. There’s so much wonderful technology. We have a utilization and integration problem, and I don’t think you can fully take advantage of the power, particularly of language models, unless you get your data systems in order. Otherwise, there’s no point. It’s not going to work.

And that is—so back to your point where you started, Lenny, asking about the vision, right, I mean, I think this is one of those examples where we kind of, from my perspective, I stumble into what’s in hindsight, may look like a great vision, but now I did know that the source of competitive advantage would be the data, not something else, right? I did know that. So, there we go. We now have complete control over our own data, and we got it sorted out, as Ryan just outlined. And hey, lo and behold, the next major opportunity that AI presents relies on having your data ducks in a row, if that is an [laugh] expression.

And we do, so the competitive advantage actually kind of becomes a self-perpetuating thing. There’s a built-in accelerator because of AI, and now I can connect even more dots, right, between the data that the Zappi tools spit out and other sets of data, right? And I can do that at scale, and I can do that as often as I want, and so on. So, that’s super exciting, and I’m sure you want to talk about that more, but what I don’t want to overlook is some of the things that we also talk a little bit about in the book. Let’s say the more practical, mundane challenges that you run into when a startup goes—basically marries [laugh] or gets engaged to a gigantic company like PepsiCo.

[laugh]. Right. Too much. Right. Yeah [laugh].

[crosstalk 00:28:36].

That’s the oh crap moment that I was referencing earlier [laugh].

Turns out that the PepsiCo systems are set up in such a way that every time you do a piece of research, you need a purchase order number, and a statement of work, and the whole shit. So, we were just not set up for this level of agility, certainly not set up for a SaaS-based way of working, right? And so, Ryan said, “You got to help me out because I’ve got all these smart people, like, filling out bloody forms now [crosstalk 00:29:05].”

[laugh].

“That cannot be why we’re—you know what we want them to do.” And so, I had to fight some battles with finance internally and the control people to drastically change processes internally. And that’s just a great example of the practical stuff you run into that absolutely don’t see coming, right? At least I didn’t, you know, prior to engaging on the journey.

That’s one of about a hundred times we’ve had one way or the other. “What the eff is going on over there?”

[laugh].

[laugh]. Well, and it brings up a great point, right? So, I mean, the—you know, wearing my Gen2 advisors hat, part of that is working in brands to innovate, you know, and help on board new suppliers that are, you know, transformative. And the biggest barrier is procurement. You know, it takes a year to get approved, it takes, you know, a hundred and twenty days to then get processed financially, yadda, yadda, yadda.

These systems—to your point—that they are—a lot of the institutional systems, outside of the insights function are not designed for optimization in this world that we now find ourselves in. So, it’s a very widespread series of, kind of, second-order consequences that have to be dealt with in order to be successful. Were there other things that you discovered besides the well, we got to pay people in an easier way, right [laugh]?. We got to execute faster. Were there other challenges that you thought, “Oh, crap, I never thought about this.”

Well, change is hard, right?

I mean, this is arguably my biggest learning of it all is that I fell for the temptation of the fallacy of thinking that if you give somebody a new tool, he or she is going to change the way he or she does their work, and that is just really naive to think that. And so, we had to—took us a little bit to figure that out. Not that much, a couple of months, right? And then we were finding that, you know, for example, that small team I had set up, that was supporting the insurance leaders all over the world, what they were doing is they were basically—you know, what they took as a benchmark to do great work was the old decks that the external consultancies would create. So, we would do a Zappi test, or a series of tests in, let’s say, 48 hours.

“So, where’s my PowerPoint?” [laugh].

Yeah, exactly.

[crosstalk 00:31:41] work for two bloody weeks, right, [crosstalk 00:31:46] by three other layers of people before it went to the marketing box. Now, that has taken me, I think, the last two years, to really change, right? Where people are like, “Hey, dude, I’ve got the data here on my laptop. Let’s look at it together.” Right? “Okay, let’s look at it together.” “I’ve got some follow-up questions.” Okay, boom.

And so, that level of, let’s call it informality, or you can call it agility, and it’s a bit of both, right? But it’s also, in large part, fueled by confidence of the insights leader. Like, I’m sufficiently confident to just take this piece of data, this stack of data, and go to Lenny, the marketing director that is trying to look at this ad launch, and just take him through it, and figure out together, you know, what is and isn’t working. That is another type of showing up altogether, right? So, handing people a tool, you know, is absolutely crucial to do, but don’t be as naive as I was. Help people develop this whole new way of working.

Yeah.

Well, if you think about it, like, the ecosystem around these businesses—PepsiCo is a good example of them—is complex. They’re naturally matrix, so the people closest to the local PNLs have power, and there’s many ecosystems in each of those silos. There’s CMOs, there’s regional presidents, there’s brand managers, there’s heads of insights, and then there’s services, and then there’s platforms, and it’s really easy to throw a piece of tech in the background, but it’s actually the interconnectivity of how that whole workflow happens. And to me, that’s, like, one of the bigger [unintelligible 00:33:26] of the Chief Insights Officer role is actually figuring out the local nuance, and building that ecosystem in a way that catches the ecosystem in stride, not just says, here’s our—I mean, you remember when you got to Pepsi—and, Lenny, you know this from all your work—there was a day where Global Heads of Insights were vetting capabilities, and then just hoping teams would use them, and then doing projects for the CEO every so often. And I think in our case, we learned a lot about the power of having CEO sponsorship, CMO sponsorship, all the regional teams in one place. And he’s right. I mean, we learned a lot about change management. We’ve learned more about change management than we did about software development, or frankly, even advertising research. That was easy. It was the change that was hard.

Yeah [laugh].

Yeah. Well, and again, for the audience, if you’ve not checked out, the book, number one Amazon bestseller [laugh] for a reason, that is the compelling component is the distillation of this conversation with far more deeper and pragmatic examples of the change management. I want to be conscious of your time as well as of the audience. So, we kind of touched on it that, you know, this was whether you want to take ownership of it or not, Stephan, this was visionary, it definitely was a change, and now—it’s kind of the old William Gibson quote, you know, “The future’s already here. It’s just not widely distributed”—and now it is.

The capabilities make this widely distributed and have unlocked more—a future that is what you’ve done on steroids, right? As far as owning the data asset, and I could not agree with you more, go on the record, everybody, if data is the new oil, you damn well better own the well. And now we have the ability to unlock value, and we’re just beginning to scratch the surface on the type of value that we can unlock with data through the power of LLMs. It’s just a force multiplier for the model that Zappi was building. And I personally envision a time in the not-too-distant future where the volume of questions that we ask goes down simply because we will be utilizing synthetic sample personas, agents, whatever, you know, interrogating the data in a far richer way, but then the questions we do ask will be far more important and meaningful in trying to drive more growth overall.

And it won’t matter whether that methodology. Questions about quant and qual, that’s going to go away. There will be some things that will be different. You know, specifically we want to dive deep in ethnographic research, or we want to ask 10,000 people, but for the most part, that’s going to change. And the world is now catching up to you. Now, that being said—well, one, do you agree? Do you think, yep, that’s kind of where we are, Lenny. That’s the vision we saw, and here we are. And then the second question—the dreaded double-barrel question—what’s next for you, since you were already there before many other companies were?

First of all, just to start in a way close in or modest, we’re actually just kicked off about a couple of weeks ago, very jointly with Zappi, a complete kind of tune-up of the tools that we’ve developed together. Because whatever the tool is, right? I mean, after, let’s say, two or so years of using it, the audience, the users, they start to understand the tool a little bit too well, right? And so, if you really want to continue to raise the floor on creative effectiveness, in our case, or of innovation effectiveness, you got to tune up the tool. And that’s a big piece of work, and so we’ve started that. That’s not sexy, but you need to do that every two or three years.

And so, working on that with Ryan and the team, I think, to your broader question, yeah, I mean, first of all, for sure, that the distinction that existed when I started my career of qual and quant is gone. That is just… that is very clear. And there’s a lot of tools now, increasingly, that can help us make sense of what’s happening in the world. However, I think if—you know, back to the good old W’s right, I think with all the data in the world, the vast, vast, vast majority of all that data does a fantastic job at describing who’s doing what, where, with whom, at what price, and in what channel, and et cetera, et cetera, but the why is not something that’s easily extracted from a set of data. And in the future, which feels still, to be honest, a little bit science fiction to me, but in the future where we can rely on whatever the language model is at the time—or whatever model [laugh] it is at the time—if we feel we can rely sufficiently on those type of models to get at that why, okay. That’s a future I—that’s not what I’m seeing today.

So, I still need fundamental insights work and there’s enough tools now that can help me build what I call empathy at scale, right? So, empathy is one thing, but I can do it at scale now, so that is a phenomenal complement to those other data sets. And bringing that together in the best possible way is absolutely what we’re focused on every day now.

Great. I love that you brought up that point on the why, and couldn’t agree more. What does that mean for you, though? So, in this—and Ryan, I know you have a point of view on this, but I’m going to draw on this with Steph for a minute, to get to the why, in my view, there’s kind of two primary ways to do it: it’s either behavioral data or observational data that fits to be more qualitative. And we can do those things at scale now. Are you looking at incorporating those things in to help enhance and get to the why? Or what does that vision look like for you?

Yeah, it’s a bit of a boring answer, but the vision that looks like is, let’s say, what we call end-to-end. So, it is… right, I think, just like you have qualitative and quantitative research and that is disappearing, what should disappear is the siloed nature of consumer insights, shopper insights, retail expertise, channel insights, and whatever, right, that we have in a company like ours. And arguably, you have that in every company. And we need to find ways to bring all those different angles, those different, let’s say, viewpoints, on the business together. We’re building a capability that we call Growth Navigator, which is really basically a toolkit that enables commercial leaders to take better commercial decisions that, importantly, are human-centric.

So, that toolkit needs to draw, not just from consumer insights, but as much from shopper insights and all those other data sets. The more those data sets are, let’s say, observational, the better it is. I mean, at the end of the day [laugh], the way I jokingly say that is seeing is the new asking. We should stop asking people questions—

[laugh]. Right.

—we should look at data, behavioral data, I mean. And that is the future, right? I mean, I think… more and more we migrate to—technology enables us to migrate to tools that are based on observational data. And I’m sure our toolkit with Zappi will migrate in that direction as well, you know.

Okay. Ryan, what do you think with this transformational period we’re in, from a technology unlocking new capabilities. What does that mean for Zappi as a technology company? What’s future look like for you?

Well, I think, first and foremost, the reason I work in insights isn’t because of technology, or methods, or market research. It’s because I believe customer-centric businesses grow and win, and we’ve proven that with the Ada setup. We’ve improved advertising by 40% we’ve sold more soda. That’s what’s more—the most important thing. And so, I look at technology as the enabler of outcomes, and I think AI is the biggest—particularly large language models—is the biggest technological revolution since the dawn of the internet, period, full stop.

However because of that, it’s a commodity. Anybody can use these models, and so it’s what you do with them, to me, that matters. And so, I look at—like, my vision for the future of the industries is something that excites me. How do we leverage what we know about people’s behaviors, attitudes, shopping history, preferences, and how they respond to brands, advertising, innovation, and use that data asset to mine what we know, so that when I call you, Lenny, I’m only asking you the two or three assumptions or the two or three things I don’t know, and because of language models, I’m engaging you in a rich way, whether that’s voice, or video, or text, and I’m getting that data to be rich. Because one of the beauties of language models is the word language is in them, and so you can cut across qual and quant in a way that is amazing.

And so, I think we have a world coming sooner than later, where we start by leveraging what we know, we ask two or three questions in a rich way, we engage the user around the companies like PepsiCo to make them smarter on a Tuesday, but we embed consumer data into the data ecosystem that every single big business is learning, so that they’re not just getting operational data. And we’re going to be spending a lot of energy driving that. And we’ll use various techniques like agents to query data or chat-based functionality to do meta-analysis on the fly. But to me, it enables such an amazing outcome that actually gets at a place where the customer is in every single room around a company. And by the way, speaking as an industry person, we have to because the data quality paradigm has never been worse than it is now. We need to find better ways to engage human beings to get their opinions. They’re not panelists, they’re people, and so I think this is a really exciting time for this industry, for a variety of reasons, but those are, I guess, would be the top of my thoughts.

Yeah. No, totally… totally agree. Preaching to the choir. Preaching to the choir, man. I will say, too, that I think this change is far faster than what anybody’s probably thinking. And if we don’t, someone else is going to because there’s certainly—you know, we have lots of big tech companies OpenAI, et cetera, et cetera, looking for business use cases for their capabilities, and I know for a fact that they are looking at insights as potentially one of those areas because I’ve had the conversations.

You know, Lenny, I want to say that, though, like, we’ve always sucked at adoption in our space. We were slow to move to the internet, we were slow to use technology. Stephan and I were at a Zappi-hosted conference this week, and I was actually pretty inspired by the experimental approach everybody in the damn room had to, like, “Yeah, we’re doing this,” and, “We’re trying this.” And it is happening faster for that reason because we’re not nay-saying; we’re actually leading in, and that’s exciting.

It is. It is, and the—well, one of the other benefits is that the risk of experimentation has gone down because of ease of implementation.

Exactly.

Right, just the barrier to entry has declined. Which creates more competitors, but that’s healthy for the ecosystem, right, because everybody’s going, “Oh, well, I got to do this now, too.” While you guys are still ahead of the curve overall. All right, we could go on and on, playing off of this stuff, but we try and keep these relatively short, and we’re already verging on an hour, which is longer than the average Greenbook Podcast.

Final thoughts. So, you had—it’s great, you know, wonderful week. You launched a book, you’ve put it out for the world, everybody to realize what you’ve learned on this journey. The world’s at a place where they’re now looking for guidance because they’re on that journey, too, whether they like it or not. What’s next? Ryan, why don’t we start with you, and Stephan, we’ll end with you. So, what’s next for you?

Personally, I’m going to be spending the next six months on the road with insights departments, helping them go from, if they’re order-takers, or if they’re doing things in one place well, but not others, helping them think through how they step-change their stat so that they can elevate their talent, and as a result, the impact they make on their business. And I’m really excited about that. I love spending time helping brands improve. So, I got a lot of that on my agenda, a lot of frequent flier miles, I guess, too. So, sorry in advance to my beautiful wife, Jill, for being gone a lot.

Yes, and the boys.

The minions. Yes.

Yes.

I’ll still be [unintelligible 00:46:06] baseball on Sunday, so I’m good.

Okay, that’s good. Do you still remember when you were at IIEX and Jill called and said, “I’m in labor.” And you’re like, “I’m out of here.”

I was on the stage with Lenny, giving away a gift, and my wife was like, “You got to get home.” And there was one total flight left [crosstalk 00:46:20] night. And I remember wind-sprinting through Hartsfield-Jackson Airport. I made it, though, by the way, everybody. I did not—

You did. You made it. That was great. I think I texted you like, “Did you make it?” You know [laugh]?

[unintelligible 00:46:33] god.

Yeah, fun times. Fun times. All right. So, Ryan, thank you. Thanks for taking the time, and congratulations on the book and everything. The—now I’m done with you, so—[laugh].

I’m not done with you, but we’ll talk again later.

[laugh]. Stephan, what’s next for you?

I think, not dissimilar to what Ryan said, but from, let’s say, my perspective, I’m in awe of the potential, the untapped potential that insights has to add value to the business, but also to the lives of people. And people, let’s say, as in the people that buy our brands or products, but also the people inside of our company. And I see that in my own company, I see that at, frankly, each and every company I talk with. I see so much potential for the insights function to have more impact, and, you know, shake off the last remnants of that conservatism that has dominated this industry for so long, which is very rooted, also, in the [traffic-like 00:47:40] nature of all those bloody tools, [laugh] right? And really change the culture of the function, also to, you know, to, you know, fully aligned with the agility and the availability of data.

That’s what we’ve just talked about for an hour. So, I’m super excited about that potential. And also, you know, for me, you know, starting in my own company that’s paying my salary, but I’m, you know, as recent as this morning, I was on the phone with another company, and somebody in my role at a different company, you know, who called me and said, like, you know, “Can we talk? I know I should read the book, but can we talk about it, also?” Because, you know, it’s hard to get that momentum of change going. So, I have a lot of energy for that, so.

That’s fantastic. And I should say, by the way, thank you for being out there. It’s hard. And before you, it was Stan at Unilever and Coke. There just weren’t many senior leaders that would come out and talk about their strategy and write a book, you know, those type of things to help others on this transformation journey. So, it is needed, absolutely, and thank you for doing that.

Great. I’m enjoying it a lot. Sure.

Good. Well, you’re probably going to get a hell of a lot more calls from other people, so [laugh]—

Or he has [Dee 00:49:19] to protect him. He’s good.

Yeah, I have a firewall around me.

All right. Gentlemen, thank you so much, really. Congratulations, thank you for the time. Any final thoughts?

No, thanks for the time, Lenny. This was a great conversation. Enjoyed it.

The future’s bright for the customer, everybody. Let’s get it.

Yeah, absolutely. All right. Well, on that, we’re going to wrap. So, thank you. Thank you guys. Thank you, Natalie, our producer, without you, this wouldn’t happen. Thank you to our editor, Big Bad Audio. Thanks to our sponsors, and most of all, thank you to our listeners because you give an excuse for great conversations like this to occur, and we really appreciate it. That’s it for this edition of the Greenbook Podcast. We will be back with another one very soon. Bye-bye.