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#303: Funnels Assume Progress. Barriers Recognize Reality.

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#303: Funnels Assume Progress. Barriers Recognize Reality.

Rusty Ramer’s book *Working as Designed* critiques the stagnation in modern analytics and marketing organizations, where decades of investment in tools and teams have led to inefficiency and poor customer outcomes. The core issue lies in siloed operations focused on reach and volume, rather than solving real customer problems with timely, relevant engagement. Ramer argues that companies have reached market saturation and now must shift from "lazy marketing" to deep customer understanding. This requires a fundamental rethinking of how teams operate—moving beyond isolated functions to cross-functional, agile teams that test, learn, and iterate rapidly. These teams focus on identifying customer problems, not just demographics, and deliver measurable outcomes through value exchanges. The book champions a hybrid model: preserving centers of excellence for standards and discipline, while empowering agile, mission-focused teams to solve customer problems. Crucially, success is measured not by activity or tool usage, but by actual customer impact. Ramer also highlights the flaw in traditional customer journey diagrams, which are unrealistic and overly simplified. Instead, micro-journeys based on real-time customer needs are more effective. The transformation demands a cultural shift in reward structures—from incentivizing activity to rewarding measurable results. His insights are framed as a conversation, not a lecture, making them accessible to executives and practitioners alike. The episode concludes with a recommendation to listen to Chris Hayes’ *The AI End Game* podcast, which offers deep, thought-provoking perspectives on AI’s societal and ethical implications.

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(upbeat music) Welcome to the Analytics Power Hour. Analytics topics covered conversationally and sometimes with explicit language. Hi everybody, welcome to the Analytics Power Hour and this is episode 303. Does it ever feel like we repeat the same steps sometimes even though no one's really thinking about whether they actually apply in the scenario, that old saying the definition of insanity repeating the same activity while expecting different results? I think we've all been there. And yet as analysts, maybe we're slightly more clued in to when it's happening than others in a business. I'd like to think so, maybe not. The idea here is, are we thinking a step or two deeper as analysts or are we just sort of rolling with the same set of activities with no critical thinking applied? Well, we're going to talk about it. And now I want to introduce by two co-hosts who are definitely deep thinkers, Julie Hoyer. Welcome. - Hey there. - And Val Crowe. - Hello, hello. - How's it going? - Good. - And I'm Michael Hoblin. Well, we wanted a guest. And our guest is someone we have had on the show before, but not for a while now. Rusty Ramer is the founder and chief product officer of Star Rise AI. Prior to that, he held analytics and marketing leadership roles at GSK in Vanguard. He has a new book called Working as Designed. And today he is our guest. Welcome back to the show, Rusty. - Thank you. Thanks for having me back. I appreciate it. - And as far as bios go, you know, Val and I also worked with you on the board of the Digital and Lux Association back in the day. So we are friends going back a long way. So it's great to have you back on the show. - All right, so to kick this all off, you wrote a book. So obviously you've been thinking about this for a long time and then you decided like to get pretty serious about it. Talk about that a little bit, because I think probably something was brewing for a long time. It kind of came out in the form of the book, but like, just talk about that journey a little bit and then we'll dig into some of the content that some of the things in the book itself. - Yeah, you know, people ask me, when did you start the book? Well, I started, I feel like I started the book 20 years ago, right, it's the experience of the last 20 years that I think, you know, at Vanguard it was about building, you know, at the front end of the digital way, building out the capabilities of, you know, a user experience organization, a data and analytics and data science organization, marketing and MarTech, and then, you know, digital transformation, then going to GSK and helping them a different problem, right? They had all of these capabilities and it was about, you know, why aren't these capabilities working the way that we think that they should? Why haven't we gotten the value out of all of this? And that's a pretty common problem, I think, as I've moved on to consulting, I can see it over and over again at different companies and it felt like a problem that I had experienced solving and that I was surprised as so prevalent out there. And so I felt like I had something to say about that and I wanted to put it down in writing and my experience is what I was observing and what I think the solutions and the core of the problem and the solutions to that are. So that's really what it was. - No, I think that's great. So talk a little bit about the book contents itself, like, you know, kind of what was the driving idea behind it. - Yeah, I think there were two key observations. One was sort of, where are we now, right? Like looking around at different organizations, I see the same problems, identifying that problem and sort of describing the solutions that I've put towards that and what I think the core of the solution is. And then secondly, like, how did we get here, right? Like there's a pretty clear path that led to this place that we're in and it's both of those things that I think were what's in the book, you know, to sort of describe how we arrived, what it is that the problem is that you're feeling and then how do you solve that problem are really sort of what's underneath it. - So what are some of those symptoms of like how we got here, let's dive into it. - Yeah, okay. Well, let me start with what I think people are probably feeling today, right? So as I led each of those organizations, whether it was user experience or it was analytics or Martek in the tech side, media, I think everybody in those organizations feels like there's something wrong with the, like we could be doing so much more with what we do here. Like we're so underutilized to this problem of growth or whatever the company is trying to solve. And I think that feeling comes from very siloed organizations, I think I think I see the problem that chief marketing officers, chief growth officers, chief commercial officers have spent a lot of money over the last 10 to 20 years, buying software, buying capability, hiring teams, building teams. And largely I don't think that they're getting a large percentage of the potential value all out of all of that investment that they've made. So from the C-sweets perspective, I've put a lot of money into this on faith that this will produce value for my commercial organization. And it just doesn't seem to change the net result very much. And I don't understand what's wrong here, but it's not working. And I think the reality of that is going back and looking at the history of how we arrived here and the moment that we're in. And I think to switch gears a little bit, I think if you go back 20 years before the internet, 1998 or whatever you're sitting at your work computer, you don't even have the internet on your computer, right? I mean, it's hard to even imagine the world back then, but that's the way that it was. And marketing your organization was print, maybe some partner distribution methods, but it was expensive. Print is really expensive to send out. And so TV ads are there, there's some phone advertising, but everything is an expensive channel. And so you reach is relatively small. It's relatively limited by your geography, right? Well, digital comes into the picture and completely blows that paradigm out of the water, right? Now you think about buying an email list and you're actually rewarded for sending it out to more people than it can actually, like the more people you send it out to, the lower the cost of purchasing that list goes down for the, right? So you're rewarded for your reach. And what that did from an economic standpoint, it allowed companies to enter markets where they were not previously competing with their brand, right? To create, oh my God, now I can reach the world with what my product or message is, and I can sell to the world. So for 20 years, we focused on reaching, reaching a building capability, digital capabilities that would help us reach audiences, right? And even bad marketing with the kind of reach you were able to achieve with the digital world drives your organizational growth. It just does. I mean, fractional return on that investment means massive growth for your organization, just based on the scale that you're currently achieving. But it's really lazy marketing, to be honest, right? That reach and frequency marketing is lazy. And so you've been purchasing all of these capabilities. You've been buying MarTech stacks, AdTech stacks. You've been building analytics teams and data lakes and data environments. You've been hiring media teams. All of that has been growing in investment, but it's all working as like, we have to build up this function. It's never existed before. We've never had an analytics team before. We've never had a data team before. And so the mission of those organizations has been about how do we build and deliver some value immediately and then scale this organization to what it's going to need to really drive the growth of this company. So we're sort of stuck in that time where these functions are still working in silos, trying to do analytics activities that show we could be the best analytics organization in the entire world. We could be the best content creative people in the entire world. We can be the best, we need all the MarTech tools, right? So the MarTech teams are out buying things that the organization doesn't even need yet, just to have them, right? And I think that's not how it's actually working, right? I think we've saturated the growth market. We've reached every corner of the market. We can possibly reach. And now it's about quality of marketing, getting back to getting away from reach and frequency and getting back to timeliness and relevancy, right? Which means, hey, I actually have to understand my customer better than I've ever understood my customer before, in order to show up in a timely and relevant way to that customer, right? And that's actually what all of these capabilities we've been building have been designed to do. But when you look at the system that they're operating inside the company, they're still working in these vertical silos, instead of working together on horizontal problems, like growing the company with its customer base, right? So I think that's a bit of how we got there, which is understandable, given the thrust of digital and digital capability and the speed at which that's grown. And then it sort of explains why we feel like we're underutilized in the same system as well. Why people aren't doing more with the data that we're creating. Why test and learn isn't being adopted as fast as it should be. Why media dies at the front door of the company and OmniChannel doesn't connect to it, right? Like I think all of these problems are functional silos out of that sort of arc of growth and evolution that's happened over the last 20 years. - And one of the things related to what you were just talking about Rusty is that really resonated with me. I've seen it so many times in organizations. Like you said, it's like the best content team in the world, the best performance marketing group and they produce a lot of reports with their analyst partners showing all this like progress and like, you know, performing above industry average for, you know, those different campaigns. And so with the way you talked about the book, it's like, how can we be doing so much that says we're doing well, but we're still not getting to where we need to go, and the way the system responds is, well, we just need to be doing more. And I was like, great! (laughs) Highlight underlying, start. I was like, that is such a repeatable pattern that I think people absolutely feel. But like, when was the first time you started to like, take us back and acknowledge, boring more on top is just, you know, not moving us forward anymore. Like, when do you have like a specific moment or story where that realization really started to come to life for you? - It's a little of two things. Again, it's a little of having jumped silos to build these functions out, and then getting the GSK and owning sort of every touch point of the customer, the entire customer experience, really was like, oh my God, now I'm sitting on top of this entire organization. And I'm saying things that they can't soft. Like, this is like a square peg, and the problem I'm trying to solve is a square peg in a round hole operationally. Like, no one can function the way that I'm asking for them to function or solve the problems that I'm throwing onto the table. And so, transformation sort of has to happen around that. And I think leaders experience it every day when there were the ones, you know, a chief marketing officer is responsible for, I don't know, 20% growth. And they go in every year and planning season, and they set that goal on the table, and they say, hey, our goal this year is having handed down to us is 20% growth, right? And in that room is the head of analytics, it's the head of media, there's all these different heads in there of all these different functions. And as soon as the media's over, everybody leaves, and everyone's gonna work really, really hard to try and achieve that goal, but they're not gonna talk to each other, and they're all gonna work in their little silos. Like, the solution to that 20% growth is sitting somewhere in the data strategy or it's somewhere in the media strategy or it's somewhere in the martex stack. It's not, it's not, it's all of those things functioning together to solve that problem in a way that we have not set up the company to work or more importantly to reward, and that's what you're talking about, because later on in the year, after we've had that discussion, and everybody's going off into their silos and is trying really, really hard to make that goal happen, to try and be the hero, we're gonna get together quarterly, we're gonna talk about results, and we're gonna talk about, we've built new data tables in the data, and we bought this new, we replaced this software with some new AI driven, whatever, and like, we built new customer segmentation model, like we've got it, we all worked on stuff independently, but the dial's not turning, because it wouldn't, it wouldn't give in those pieces, independently working, rather than, you know, working together on a common problem, so. Hey Tim, imagine for a minute, you're an e-commerce marketing leader, and you just launched a new checkout yesterday. And now, you're wondering, did performance change, or did the tracking break? Yeah, it's so important, and with the State MCP server, you can connect an AI assistant to your State account, and you can ask it, things like checking the container to confirm that the tracking domain is valid, review usage before and after launch, and you can show what changed by browser or client. So, instead of digging through infrastructure screens, you can get a plain English operational check. Yeah, you can also review daily usage, see which domains are generating traffic, and check for unexpected costs or surcharges. That helps an in-house team answer an important question faster. Is this a marketing problem, or a measurement problem? Yeah, hone in on the solution, and to do that, click the link in the show description to learn more about the State MCP server, and how it can help you. Michael, ask wise, prismversion3.0, now speaks MCP. That's great, I love acronyms. They make me feel like I'm in a meeting, I forgot to decline. Well, in this case, it means Prism can plug into Cod Desktop, Cod Code, and other MCP compatible tools. Ooh, I do like that, so Prism becomes part of the workflow instead of another tab I'm pretending is organized? Exactly. From Cod, your users can query the workspace, trigger analyses, and pull results into whatever they're working on. Oh, I love that. Less way to that come from more. Oh, look, a usable workflow. Yeah, and with Prism's memory engine, skills, permissions, and admin controls, the context stays managed, not trapped in one person's chat history. Really useful. 'Cause I think Cod told me this last week is not a governance model, not exactly. So go to ask-y.ai and join the wait list. And pro-tip use code APH to jump to the top. That's ask-deleter-y.ai and use code APH. Prism, fewer tabs, smarter agents, less workplace archeology. I think you see it every day. I mean, they really think you do. The advantage was having sat above all of those functions and going, okay, you know what I don't need? Is more exposures with no one going to a high-value action on my website. Like, are you working with the Omni Channel team to deliver, like after we expose them, to deliver a journey that moves them closer towards the high-value action that I want? Oh, no, you guys never talk. Okay, this is a system that produces and rewards this. And now we need to change the system that we're all operating in to reward, to give you a different problem to solve and to reward you for working as hard as you're already working, but to solve a different problem than what you're trying to solve today, right? So. - And what you said really hit home of, it's time for us to turn back to thinking about how timely and relevant it is for the customer. And I have also found working with a lot of my clients is that in the pressure of activity, like you were just describing in the silos of their organization and the pressure to do more, get more out of it. Or at least that's, again, the habit that we've created. People very quickly lose the lens of the customer and the customer experience. And like at the end of the day, that is what all the functions that the company need to work together to change. I am curious how have you found a way to help teams get back to thinking about the customer or helping teams reach across to the other teams involved? And I'm curious from the different positions that you've held or now even moving into consulting, like you mentioned, is there anything you use to kind of convince people of that or scenarios where you've been able to help change those working habits? - Yeah, and Julie, two things there. I think first, I probably even said those words too, getting back to the customer experience. Honestly, it should have always been about the customer experience. From the beginning of time, right? When it was a small hardware store that you walked into in your neighborhood, like they knew in order to do business, they had to help the customer solve a problem. And I think as this digital era has helped company scale, I mean, any company you take, if you go back 20 years and look at what they were, you know, the number of people that work there, the size of revenue, all of that, that is a magnificent scale. And I think that challenges companies to figure out how to even grow their organization to be that big and handle that much customer work. But I don't think we ever should have lost track of I still actually need to be good with customers. That's why I called a little bit of lazy marketing in between because it did get away from that, even though it shouldn't have. And now, if you're going to grow, you've reached as much as you're going to grow with that marketing. If you want to grow that baseline from what it's at, you've got to get good at the customer experience. You have to solve customer problems again. So you've got to know your customer better than you ever have before. And again, the good news is all of this tech stack and everything we do is actually ideally designed to solve that problem. You're just not using it. The cover is a shovel upside down, digging a hole. That's actually the metaphor that's trying to be conveyed on the front of the cover. You have the right tools. You've just got to flip it over and use the other end. And it will solve the problem for you. So to your point, Julie, I think what I like to do, I always, as a leader who's led a lot of transformations over the last 10 or so years, I always think it starts with vision. I think you sit down and you talk about, what do you need to be in five years from now commercially? What goals do we need to be achieving five years? And how do we have to operate in order to achieve that? And well, we need to do more when you're OK, OK, great. A fundamental question I love to throw in there that's sort of a blockbuster question that really stops the conversation in its tracks is, OK, what are the customer problems we have to solve in order to turn them into better customers? To achieve that result, you just talked about. And they just stop. And there's no answer to that. There's just silence. And I go, look, fundamentally, marketing is about changing mindsets. If they were already going to buy it, I wouldn't need to waste money marketing to them, right? That I wouldn't need to do that. So it is about changing a customer that isn't going to do this to some degree, maybe some customers are further away from doing it than others. But in some way, it's about interjecting myself into that customer and changing an outcome that benefits the customer and me at the end of the day. And if I'm asking you, what is it going to take to change the mindset of your customers or what problems stand in the way your customers being better customers for you, then I don't know how you're ever going to achieve those goals. That is fundamentally the question that the only way to achieve growth is solving those problems for your customer. And the fact that you're sitting here quiet tells me, we haven't done enough to know our customers and what problems they have that are preventing them from being better customers for us. And that's something we better get back to doing. and look. I'm not the first person to preach customer eccentricity, but I think it's been a forgotten concept. And I think people, many companies would say that they are customer centric 'cause they have a lot of customer data. But that customer data is a lot like saying, this side of the river holds the biggest fish. So if I fish here, I catch big fish. It's not how to catch them. It has nothing to do with how to catch them. And so you really don't know your customers 'cause you don't know what the problem is. And therefore you can't solve it and move big fishes or small fishes over to the side that you want them to. And so I think it's about that. I think that's the moment where they kind of sit back in their seats and go, you know what? Maybe we actually don't know the key to that question. And knowing it is unlocking the future for us. So how do we do that? And so you've got an ear to start talking about how you start solving that problem, right? And how you start getting back to knowing your customers again. - And you know what's interesting? You talk about knowing your customers. Another thing I've run into a lot is when we get into like segmentation of customers, again at the thought of, oh, we'll figure out who's alike and then we'll market to them accordingly, right? It's like getting at the idea of caring about the customer, figuring out how to work with each user type. But sadly, the first thing I see a lot of my clients reach for is they segment them based on outcome. They say, who are my big spenders already? Or who are already really loyal and who are the people who are not loyal? Which is interesting because it's so backwards to thinking, well, wouldn't you describe them by similar characteristics? And then you'd hope to interact with them to then drive the actual outcome measure for the different groups. But I find it really interesting that so many companies end up actually segmenting on outcome, which seems so backwards. It's so about you, not about your customer, right? You're saying, and I get it, it's particularly in pharma, right? Like that's an industry that I spent time in that I could see right away grew on a really expensive resource called a salesperson showing up at a doctor's door, right? Which I don't know, cost something like $300 every knock on a doctor's door. And though that ability has drastically been reduced by legislation, they don't really have the ability to do what they used to be able to do. Or BS is effective with sales folks as they used to be able to. So they're going digital, but it's exactly that, Julie. When I think about sending a very expensive resource like a salesperson out, I can't send them out to very small customers, but the customer opportunity is very small. I have to send them out to the place that they could have the potentially biggest impact on my bottom line. I get it. But when you extend that thinking to digital, you're making a mistake, right? Like digital doesn't cost the same amount of money. And that was, you were putting the problem set on a human to interact with another human to figure out what the problem actually was that needed to be solved, right? Now, you've got a digital ecosystem, which can reach bazillions of people, very, very low cost. But you don't know the problem you're solving as you're blasting all this stuff out all the time. So you still create segments that are like, these are the biggest fish. Let's spend the most marketing dollars on these biggest fish when in reality, if you step back and you said, you know what? There's probably only four or five problems that my customers have that if I could solve these problems, they would be a better customer for me, right? And if you segment your customers on that first and say, OK, here are big fish and little fish that all share the same problem. And if I can solve that problem, I would turn all of them into better customers for me. Now, some of them, within solving that, there may be different ways of solving it. I may send a rep out. And maybe I wouldn't send a rep out to a small one. But I know the problem I'm sending the rep out to solve. And I know what I'm asking my digital marketing or my customer journey marketing to solve as well. It's just I'm deciding how much to put into the solution. But the solution is the same across the board in terms of the value that has to be exchanged with that customer to move them from where they are to where I want them to be, right? So I think that segmentation has a place. It just isn't the first cut of segmentation. It's a second or third layer of segmentation that says, OK, once I've segmented on the problem, I need to solve. And I've got solutions to that problem, which is a portfolio of solutions. I can decide which of that portfolio of solutions I should invest in, which customers based on cost and potential return on that investment. And I think if a company gets that far in there, having and hawing about the incremental value of a solution on a certain subset of users for a problem, like, I'm sure they're doing pretty damn well. Because that is like top tier thinking, if you've made it to that step, I want to come meet your company. Yeah, like, honestly, totally. Well, and so I cannot wait to talk about some of that portfolio stuff in the way you're talking about thinking about. But I want to go back a little bit to the transformation it takes to be able to get to what you guys were just talking about. Because I know you reference like the cover of the book is about like turning around the tool like you have it. You're just not using it correctly. But I do have the privilege of being in your circle and so I and you're also the king of analogy. So I can't wait till we do the tally at the end of the episode for all the amazing analogy. See, it was, and there's so many that have stuck with me. But I remember you were talking about a team that was mobilized and ready to do some of this work. And I think the way you phrased it, hopefully, I don't butcher it is like, we're ready to work together to make things giving dinner. And the request I'm getting is for a side of cranberry sauce, more cranberry sauce, just like put more cranberry sauce on my plate. And so I want to talk a little bit about like, ooh, needs to be involved in some of this transformation. And how do these groups kind of work together? Because like Julie said, getting an organization to like put aside your segmentation that you've been so emotionally like your crutch for the past however many years to something that you're talking about with this transformation. I'll go a little bit more about like what that takes and who you have to get bought in. Yeah, it's a great question. And as I just mentioned with the customer centrity, right? Like I'm not the first person to preach customer centrity. I mean, that's been out there for a long time. I think there are, this entire book is not about any one unique concept. It is more about all of these concepts that companies are putting into play. Like they think they're being customer-centric, but they're not applying it correctly. They have agile, but they aren't totally applying it from front end to back end. It's only a tech build. It's not a front end strategy, right? So I think it's on, this book is about a lot of those tools, not just MarTechStack and hadTechStack and teams that you have built, but also ways of working that you've deployed, but you've only got like a percentage of it's deployed, right? Because this is where it comes together, right? I think at the, there's sort of an arc of maturity you go through here, right? I think there's sort of, when you don't have functions, you build centers of excellence to create consistency across your organization and to get you over the large investments that need to be made around capability and discipline and structure, you know, the design systems for the UX team, you know, analytics. So you don't have 10 sources of truth. You're down to a limited set, you've got definitions of data dictionary, like all those things come with center of excellence and they're really good and they're really important. But ultimately, when you talk about solving these customer problems, they largely become a bottleneck pretty quickly, right? Because you need localization of the problem solving and not only that, you need quick feedback loops, right? This is where, you know, Val, of all people test and learn, right, is so close to your heart, but how difficult is that to introduce into a company that's organized into the site, like it doesn't work? First off, it takes them nine months to take an idea to market, when it takes nine months and nine months of cost to get an idea in the market, I can't do two of those. I just need to get it out and get some kind of result. I have no time to test any alternate ideas, right? So this has to get these teams that can do this work closer to the front end, be able to deliver pieces of things in a hurry, evaluate quickly with analytics if it's working or not, and pivot quickly. It can't go through year long planning cycles, nine month delivery site, it can't do any of that. Like that, look, you're not going to build that thing overnight, you have to mature to it, but ultimately, when you have a team that is comprised of all of the different functions that make digital run from data strategy to analytics and two kinds of analytics, right, longer term analytics and fast, quick, dirty, is it worth the thing we just put out in the market? How much traffic's coming to the website from that? What are they, are they achieving high value act? Like quick and dirty, to media buying, like all of this needs to be done on a rapid scale with a team that comprises all of those disciplines, right? It's not cheaper, won't tell you it's cheaper. Centres of excellence are really cheap 'cause you scale them across the entire organization. When you start building these teams, you're borrowing discipline from the centers of excellence and you're dedicating them to a set of problems, right? So you might say, in this case, you might say, all right, let's pretend we're at a pharma company and we've identified that there's a set of, there's a large, a valuable cluster of customers who need more evidence in order to write the script for our drug over what they're currently writing the script for. We've got a better drug, but they've been writing that for 10 years, the existing drug, our new drug, better results. But we have to prove that to them in order to get that, right? Now, there are different value exchanges that can happen to do that. You can get them data and white papers that say the results are better. You can have them talk to appear. You can get them to a conference where they see somebody a key opinion leader speak on it. So there's different ways of solving that. But I've got to build journeys to get them to those high value actions. I've got to get somebody to a conference and that means I've got to make them aware of the conference. I've got to find the right people who would be open to going to a conference. Maybe that's geography-based. I've got to build a journey that makes it easy for them to-- there's a whole journey that goes behind delivering that value exchange, right? I need a team who is dedicated to that problem set of not just delivering those value pieces, but also evaluating, are these the right solutions to somebody that even needs more evidence? Or are there better solutions out there? Maybe a podcast on something like this might be a better solution, whatever. So they're looking at not only the tip of the spear, the high value actions, or the value exchange pieces, but also are we getting people to sign up for those things? Are we actually exchanging those value when we pick a customer and we say, we want this customer to attend a conference? How good are we getting them to be able to do that? Are we improving the journey that gets them to do that? Are we-- when they do go to the conference, is that the right solution? Is that moving them or not? That all needs to be rapid design, analytics behind it very quickly. And so you need a team who has all of those disciplines or can borrow all of those disciplines to deliver in that in a very agile or lean way. You're working model with some hybrid of agile, lean kind of on-bonish thinking that you put together to solve that problem. But every two weeks, you're putting something out into market. You're getting results back immediately, and you're saying, OK, this is working or this isn't, working fail, go on to the next idea. And that's where Test and Learn finds its home. With all of these other disciplines, helping to do segmentation more precisely, maybe we targeted the wrong audience with that message, content helping to improve the messaging consistently, time after time-- you got all of that at your disposal to try and solve that problem. Now, it is more expensive. I will say it again than the center of excellence. But if all the center of excellence is doing, is pumping out more cheaper? That's not impact. This is impact, because I'm going to give them a problem. And I'm going to say, here's the population that I know that I want you to target. To change-- this is the population I have to find is having the problem of needing more evidence. And I'll be able to look at that population and say, they've moved or they haven't moved as customers as a result of the actions that this entire team has put forth. So I have a measurable result of impact at the end of that, in a way that a center of excellence who just pumps out websites or pumps out email campaigns or pumps out, like, doesn't have any connectivity to an output or an impact output associated with it. So it's just pumping out actions, but not results. This is tied to a result. Really, how you started to find what, like, a journey. So you were saying it's for a specific audience, like, with the same problem. Because another thing I find is I spend a lot of time talking to my clients and stakeholders about, like, a journey, what they consider a journey. I've heard people say, you know, maybe the poorest, right, is, like, well, the journey should be defined by the business ahead of time. What does the ideal flow? But then these companies spin up, you know, huge websites, huge digital ecosystems. They offer labs. They offer webinars. They offer, you know, e-com online or their sales people in person, right? And it gets very complicated fast. So then people want to say, well, we have all this behavioral data. Let's just use AI to surface the pattern. And that will tell us the actual journeys. But what I hate about both of those is it's completely disconnected to the customer. And so I just, I really like how you put those bounds around it, because I think that's something that I've been searching for, because I've started to just get so crabby when people want to talk about journeys. I'm like, if we're getting journeys again, like, there's no good answer. But I really like, yeah, the angle you're taking on it. So Julie, you just stepped on a landmine for me. Like I hate customer journey exercises. Oh my God. In my life, if I could count the number of times, I'd walked by a room and looked in and saw like this massive arc of customer journey with stars and arrows and boxes. Like graphic designer skills going to waste on this magnificent board that is a customer journey, right? Like from whatever biggest waste of time I've ever seen. Actually, it's an exercise that's probably not a waste of time to do, but is so non-reality, right? So this is the analogy I like to give around this. If we were to take the average American's lifespan and say, well, what's the journey? Well, I don't know, I'm born. If you average it out, you're born, you graduate high school. You're born to two parents. Oh, by the way, you're a family of 2.5. I don't know who the 0.5 is, but you have a 0.5 of a sibling. You go to high school, you graduate, you go to some for your college, you get married, have 2.5 kids of your own, you retire, whatever. Like that's your entire life story. You go on vacations, you retire, that's it. Literally no one in the United States lives that life. Literally no one lives that life. That's what a customer journey on a wall looks like at a company. And no one actually walks through that thing that way. That's an average of people's lives that literally no one lives. The reality is, some people do go to college. Some people are born with six siblings, six siblings, some are born with one, right? Or none, just one individual child. Some go to college, some don't go to college. Some big get married, some don't. Some get divorced. Some have kids with the first relationship. Like it's messy, the real world is messy. You can't create an arc that touches all of those points and pretend that that's a reality. That is not a reality. What you can do is, it's exactly what we're sort of talking about here is say, okay, no, I can't do a whole arc. But if somebody's online shopping for a kayak, I can give them a journey to get them to a kayak. I can detect that and I can get them to the kayak, right? Like, and maybe they buy another one after that. So that's like a divorce. They go through the same purchasing thing again. Okay, no problem, right? If it's fine. Like you can only sort of detect in the moment what their need is and try to solve that need. And you have different needs that you can solve for, but you can't configure them in a definitive way that they're gonna go through them, right? Like even after, even if you say, my biggest problem with this new product launch that I have is I have to create awareness. No one knows about my new product, I'm about to launch into the market. Okay, well, your first journeys are all gonna be around awareness based, right? Okay, great. Let's fast forward five years into your new product out there and a competitor comes into the marketplace, right? Here's a really good customer of yours that keeps buying your product, but suddenly there's a competitor in the market. Well, they might have to go through awareness again. The awareness might be how your product is better than what the competitors product is, right? Like sometimes they go back through the same journey again. That's what I'm saying. So I think to try and create a journey which links all of these sub journeys together is insane. It never happens, but there are micro journeys. And at the end, at the tip of a micro journey is a value exchange. If I can get them to do this, they will move closer to being a better customer for me. And if I can use data and analytics to determine what that need is, which is what I should be using it for, then I can put them on the right journey and score and evaluate my ability to deliver a good journey and a good value exchange to move them towards it being a better customer for me. I think the other analogy that's in the book that kind of works well here is the game of Plinco, right? Which is this old wooden nickel game. Drop it in the top, it hits these nails and there are four buckets at the bottom that have different points associated with them. I think the wooden nickel is the customer. And I think at the bottom are the journeys that we're trying to put them on. Like, okay, if I could get them on this journey, they'll become a better, if I can exchange this value with them through this journey, I'll make them a better customer. Each one of those nails they're hitting on the way down is an opportunity, it's an interaction with your brand that is an opportunity for you use data and that interaction to try and guess which bucket they need to be in at the bottom of that. And that is the game of data and analytics at the end of the day. And I use this to look at patterns and identify what my customer need is at scale for this group of people, this is the problem that they have with our brand. And if I can identify that, now I know from marketing what problem I have to solve, I can measure the actions that I'm taking the journey, that I'm taking to try and get them to exchange that value, which I believe was I can measure all of that and tell you how effective all of that is at changing my customers into better customers. - I like that a lot. And I will say that the one thing that I repeated in my notes was I went through your book, I was like, the process is testing, like in there. And I come up and I'm like, look at it. Like that's, yeah, we're the outfits and I love that. So like if we have these problem mobilized pods that are focused on continuous delivery of the portfolio of solutions that could potentially relieve ourselves some of these problems, like paint the picture. 'Cause the one thing that we didn't really get to talk about too much is like the system and the system's expectations of how people behave today and how they're kind of rewarded for activity to how the system behaves in this like more idealistic vision that you've painted, like can you talk a little bit about that? - Yeah, I mean, again, and we've achieved this, right? I think at GSK, this was sort of the pinnacle of what we were able to do was put these teams together and the reward structure completely changes, right? We're not rewarding activity anymore. We're saying here's a population that needs to move closer to the ideal customer set that we have. And here's a set of problems that we believe is standing in the way. of them being that iterate and solve that problem, right? Validate that we've even got the, like maybe we've got the wrong, the way we've segmented these customers into this problem set, maybe wrong. The, the value, the products, right? And the experience products, the value exchange, experience products, that should, you know, our conferences, maybe that isn't the answer to this problem that we think it is. Maybe that really doesn't move a customer forward. So look at the portfolio of things that we're trying to get them to do. And our ability to actually get them to do that and help us optimize that. And the way, again, reward. Again, I think people today in the silos of the existing system are really innovative and ingenious. I think every team I've ever led has extremely talented people in it who are trying really hard and defining new ways of solving problems for the company. It just isn't latched up to something, a common problem that actually delivers impact, the way that this system does, and that we can reward and recognize those for that kind of innovation and ingenuity against a well-defined problem and a system that can measure the actual outcome of the efforts that they're doing, right? And so again, I can measure the cost of, you know, in a really, in a, with a really broad brush, I can measure the cost of my centers of excellence today. I know how much they cost me. I know how much the tech stack they're working in cost me annually. I know how much head counts in there. I know contracts. I know all the answers to that right at a very high level. I know that cost and I also know how much our impact that entire organization is having out in the real world in terms of growth. I know those two things and I know this model is significantly more expensive than that model, but I can show the results and the outcomes are significantly higher than the money that's being spent in this other model. And when I can do that, I can reward and recognize the people within the system for the amazing ingenuity that they're having within that system. - So in the operating model chapter, you kind of develop this idea of like developing those cross-functional teams as opposed to sort of like center of excellence concepts. So just to clarify boundaries a little bit, and also I think if I was a business leader listening, I sort of have some questions about like, how deep should that go? Should I try to take everybody? 'Cause like some people are just specialists, like they are working on that thing and do I need to throw them in a cross-functional team or is there sort of that structure? And then I set up like a tiger team sort of set up. Like how do you bridge that gap for people or advise people? - Yeah, I think it's a great question Michael. And I think there are, it's hard to put that in the book. The experience and what I think, because I think, well, I say this because I think a smaller company has a different answer to that question than a larger company does. So it's hard to prescribe that clearly. But here's what I would say. I think, you know, this is another analogy for you about. I think potato chips with no ridges break really easily in the dip, they do. The reason ridges were invented is it makes the chip stronger, right? But ridges only go one way. - You can't have to orient the chip correctly, Rusty. - Well, that's correct. - Yeah, yeah, come on. - You know what's a stronger answer, yeah. - I think it's a good answer. - This is our first time dipping a chip. - Anybody who dips horizontally is making a huge mistake and that's the other thing. - There's gonna be half a chip in the dip. That happens, it's not gonna be good. No, but what's even stronger than that, right? Which I would say, if you only went with teams that were, you know, journey aligned, you would have hearts on, it's stronger than the plane chip where nobody's aligned to anything, but it isn't the strongest function that you're the strongest model that you can have. The strongest model is the waffle fry. Seriously, the Chick-fil-A waffle fry is the strongest potato in the world. It can't be broken anyway, you try it. So you get it. Cross-cutting is actually twice as strong as, and I'm sorry, there's probably some engineer that'll tell me that. - You can do a waffle chip. - Tater goes. - Is that a thing? - Has a waffle chip, they do. - They absolutely do. That is a supreme dipping material. - Vehicle. - It's nice, it's real nice. - Yes, yes. So you get the point. I think you can't just go one direction with this. I think to your point, Michael, in addition to these, the players on these teams that are multi-functioned, cross-striped, whatever you wanna call it, still need to belong to a discipline, a guild, which belong, the center of excellence still needs to exist. The work just doesn't get done in the center of excellence. It's now transferred out to these teams. But the members of that team belong to the guild of the center of excellence, because if you just let it go, you lose all the discipline of a center of excellence that has, well, updates the technology and the stack that they actually work in to make sure that continues. That there's a roadmap for that. That documentation continues. That standards for design continue, right? You can't turn it all loose. I think you still retain a small center of excellence that continue to represent the guild and the need of the guild to be able to do its job fast and effectively. I also think it can, in a large organization, you should separate out the value delivery products. So conferences, white papers, these things should be developed by teams outside of the journey teams. Journey teams should be mainly focused on identifying the right audiences, moving those audiences through the content journey and evolving the content journey to more effectively move them to exchange the value. But that portfolio of value things is actually another team that should actually develop and own those. Ultimately, if you can afford to do it, I think if you're a small organization, this sort of collapses a little bit on itself, you know, smaller teams, smaller, see if you, you know, all that stuff. Then you run into the age-old glingerie, Glenn Ross problem, you know, these leads. These leads are really good. Exactly, it's a great movie, by the way. No one has the patience to watch that movie anymore, but it is amazing dialogue. Well, before Michael says what I think he's about to say, I have to ask, the book was written in a very specific format, the way to kind of phrase it. So I think what you need to tell your future readers that are currently listeners a little bit about how you made some of those choices. Yeah, good question. So I actually wrote it long form originally. So it's a 500 page, there's a 500 page version of that book. And before I even started writing the book, I have some mentors that are sort of guiding me through the process of written books before, they are C-suite individuals who sort of were the people I was trying to speak to the most to help them understand why the money that they're spending isn't, you know, returning what they really want. And so I had pitched the idea to them very early on. 'Cause this book is this worth a book and they were like, oh my God, yes, definitely write that book. So they sort of helped me affirm that there was something to be said here. I developed the 500 page, or I send it to them, and they're like, I'm not reading. Like, who are you talking, like, what is this? Like, I don't have time to read this, you know, whatever. And they're like, when you came in here, you told us about this and we were all in, we totally understood it and we were ready to go back to our companies and make a change. Just tell us that's like, talk to us like you did then. And so I had to go back and take the 500 pages and turn this into what is more of a conversation with the reader than, you know, then the 500 pages. It is really meant to be a conversation. It is spaced with timing, which, you know, when you first open it, it'll look like poetry. It is not poetry, but you will, after the first page, you'll sort of fall into this groove of single spacing pauses versus double spacing pauses. And it helps make the points that I'm trying to make in shorter, you know, less stories, less, get to the more, get to the point CEOs sort of speak. And it, you know, it condense the books significantly and it helped me say the same thing in a lot less words that I think C-suite people will be willing to endure. In fact, to funny story here, I'm working, I'm more of a podcaster. I'd listen to things more than I read the physical copy. So, yeah, I get the book published and I'm working on, okay, now I gotta get to the part that I would actually enjoy, which is the podcasting part. And everybody's like, my mentor's like, you have to do it, it has to be your voice. So, you gotta do this. And I'm like, okay, well, I've never done this before. So, okay, let me look in. This was a lot of work editing and all that. But I'm like, wait, there are these great AI products out there. Now, you record like a 30-second sample. And it'll, I'm like, yes, this is it. I'm gonna do this, right? So, I go, I buy the software, I record a 30-second sample. And then I immediately turn it loose on the first chapter of my book. And it actually did a pretty good look. It did a really good job of being me reading the first chapter, which was the problem, right? Yeah, listen, I turn all of my devices to like speak in British, because everything sounds smarter if you have a British accent. I mean, you sound brilliant with a British accent. Like Siri talks to me, because I'd like to think that I'm an around smart piece. So, okay, all my devices speak with a British accent to me. The opposite, right, so you could read the script of idiocracy. But if you do it with a British accent, it sounds like the Magna Carta, it's amazing, right? Oppositely, if you have a Philadelphia accent and you read the Magna Carta, you sound like you're reading it at idiocracy. And that's exactly what I was like, oh my God. Do I, is that my accent? Do I sound like that? It was terrible. So, I ended up having to hire someone to do it. It's almost done, but like it's so much, but I'm not even, I'm only right to the guy in email, because I don't want to hear my voice now, I won't talk. I don't want the phone, I'm just like, "I don't want the ear off there." (laughs) - Water. - My water, water. - All right. This was awesome. - This was awesome. - This is so good. And the book is really good. And it does read, once you get into it, you do read with a little bit of cadence. I definitely picked that up as I was reading it. I was like, at first I was like, "Oh, what's going on with this book?" And then I was like, "Oh, I actually kind of does flow once you get used to it." So it is well worth it. And I don't think it's just for CEOs either. 'Cause I think even when you're sitting in a seat, I think you can advocate for some of these things if you're not the senior executive in your department, you can sort of raise your hand or start to apply some of the principles even in where you're at. So, okay, we do have to start to wrap up awesome conversation. Thank you so much for us to spend too long. And you've been working on this super hard. It's like, "Wow, you've got a lot done." I was like, "What have I been doing?" No, so thank you for all the work putting that together and coming on the show to talk about it. Okay, one of the things we do is go around the horn and share a last call, something that might be of interest to our guests. Rusty, you're our guest, or might be of interest to our listeners and Rusty, you're our guest. What is your last call? Have you guys read this book? Analytics, the right way. Have you heard of it? It's, I'm sorry. Yeah, little plug for Tim. Little plug for Tim. No, that's good. Lately, I have fallen in love. This is the second time I'm listening to the same seven series podcast. It's first time I've ever listened to a podcast twice. It's by Chris Hayes. It's called The AI End Game. And it's about seven podcasts, about an hour each podcast or not terribly long. He has guests on to each episode. What I love about it is it covers every, it's a very top thinking about AI in the world. Everything from philosophical, so he'll have some professors on that will talk about what is intelligence, what is sentience, and AI ever achieve this to the political ramifications of how do we govern this, how do we write policies to control this, where do we need policy to control it, to history talking about AI summers and AI winters of innovation and how we got to where we are and what the weakness is and strengths of where we are and capability is, and even economics. So, you know, what's this going to do to jobs, or what do we think it's going to do to jobs, what's it going to do to the stock market, all of these different things covered in this series, really big thinking, I think, from some of the smartest people in the world as guests, and I really love this podcast. Like I said, it's my second time through it, because I think there's so much to think about, and see differently than the AI software where we're interacting with every day, the more larger ramifications of all of this stuff, which is really cool. - Nice, I'll give it a listen. All right, Julie, what about you? What's your last call? - My last call, funny enough, is actually a David Epstein letter, newsletter, and it's him and Brad Stoolberg, and it's them discussing two books that they recently published earlier this year. The books are the way of excellence and inside the box, and it's a really cool discussion back and forth in a really nice highlight of both of the books, and it really made me want to go and actually get them and read them in full. And the title of the newsletter is How to Pay Attention and Care deeply in a chaotic world. And so I'll just give a few teasers of like quotes just from the beginning of it, but it was such an interesting read. And like I said, I think that the books diving into these concepts more would be super interesting to go and check out. So the first one is the quality of your attention shapes the quality of your relationships, work, and leisure, which is to say the quality of your attention shapes the quality of your life, which really like hit home for me. And then they talked about it's changed from time management to attention management. And then the last one I'll give you is wealth of information creates a poverty of attention. So like those three things just like really caught my eye. So highly recommend reading the newsletter. And then I would not be surprised how many people go and purchase the books for more. - Yeah, Julie, if we're telling people to like trim down, like I think that goes against what we're doing here, but it's over, it's about quality, right? We've got quality here. It's okay. Yeah, that's right, thank you, I appreciate you. Yeah, keep listening to this but cut everything else out. - Everything else, you trash. - We need your full attention, people. - That's right, now what's your last call? - Okay, so mine is a New York Times article that my husband sent me, who is a philosophy major. And the title is The Revenge of the Philosophy Majors. And it talks about how a lot of AI companies like Anthropic and Google DeepMind are recruiting philosophers to join their kind of crew and some of the things that they're really leaning into as some of their skill sets that are different or have a different perspective or angle than others is around like obviously the ethics but like being able to take like abstract concepts and make it easier to digest like all those like conceptual challenges around AI but the one thing that I found really interesting I mean, it's super interesting and they have like, you know, a different quote from different people. I was like, oh, like what do they call like forced-deployed philosophers like thinking of being so funny and that was like, no, they're just philosophers. Like, it's just philosophers, that's the title. It's like, okay, wow, all right, well, there you have it. But it's just so cool to think about like how AI and you know, some of these roles and how it's kind of morphing and changing what is seen as mission-critical to like move us forward but it was kind of a fun read. So that's my last call. - So you're telling me they can't be advanced philosophers. - It's seeing your advanced. - Advanced philosophizing, sort of like how we do it as advanced analytic. - Exactly. - All right, sorry, that's good. - No, good, they're data philosophers. Yeah, exactly, yeah. - I like that a little. - I'll tell him that, he'll love that. But David, in front of it. - Just to build on that for a second, there has been a longstanding philosophical test. I mean, they've been wondering if computers will ever be able to imitate a human for a long time, ever achieve sentence or whatever. And the longstanding test has always been, if a human in a blind test cannot tell that they're having a conversation with a computer, that has been the philosophical bar that sentience has had to reach in computers. If it could do that, then it would be blown that away already. And so the need to define what is it that makes us different than a computer is like a huge philosophical debate right now. And I'm sure that gets right into it. It's really exciting times for that. - How about you, Michael, what's your last call? - Well, mine is a little more fun this time, but I do love a good allegory and a blog post that Charlie Tyson I work with shared with me by a guy named Gerard Rubio. It's sort of an allegorical story about startups. And I thought it was well written in kind of a fun read. So we'll have a link to it. But basically, he's sort of talking about a guy who's decided to start a oven business and goes off into all the different things that happened to a founder through that process. And I think now in this day and age, because it's so easy to do something with AI, I think everyone sort of has this thought of like, oh, I should start a company. And then this will sort of get you through probably the first few years of that pretty easily. And if you were thinking about doing a product, so it's a good read. It's a fun little read. All right, well, Rusty again, thank you so much. What a pleasure. Have you back on the show and hang out a little bit. It's always great to appreciate the insight and the wealth of experience that you kind of distilled into your book working as designed, which is available, I believe, on all the major platforms. So you should probably pick up a copy just so you can say, I have a book by Rusty Raymer. And also read it. It's, yeah, so that's probably more important than say you have it. But anyways, all right. I know as you've been listening, you're probably thinking, hey, I've got a couple of questions or things like that. We would love to hear from you. And the best way to do that is through our website or our LinkedIn. Or you can email us at contact at analyticsour.io. And also, as you're out there listening, please add a review or comments also where you listen. On Spotify or wherever. So we'd love to hear from you or see reviews and ratings is there as well, always is awesome. All right, so I think that's it. And I think I speak for both of my two co-hosts, Julie and Val, when I say no matter what your organization structure, whether you're a center of excellence, a tiger team, or a cross-functional porridge, or you're defining two big customer journeys. Keep analyzing. Thanks for listening. Let's keep the conversation going [BLANK_AUDIO] your comments, suggestions and questions on Twitter at analytics hour on the web at analytics hour.io, our LinkedIn group and the Measure Chat Slack group, music for the podcast by Josh Crowe Hurst. Those smart guys want to fit in so they made up a term called analytics. Analytics don't work. Do the analytics say go for it no matter who's going for it? So if you and I were on the field, the analytics say go for it. It's the stupidest, lazyest, lamest thing I've ever heard for reasoning in competition. You do in the French Quarter, nothing crazy. And we had come out of a place and there was a lady that was really pretty inebriated, I would say. And the rest of us were just like, oh well, and we kept going. But Rusty, because he's such a nice guy, stops to try to help her into a cab and make sure she's okay. And she turns around and she goes, you have the most beautiful salt and pepper hair. Me miles really. Her two eyes are going different directions. Yeah. Go with her. Right? No. It was something so funny because it was like, oh, yeah, it was a Rusty because he tried to be nice. And this lady's like, oh, wow. You're your image cut through the fog that she did, where she saw you clearly. Oh, five of me, I'm sure. Yeah. For the whole group of good looking men that helped me into a cab. Yeah, I think what the story is, he tells. Yeah. Yeah. You this day, he has this image of her guardian angel, amazing. Yeah. He convinced she went to hell unfortunately. Anyway, good times. I can, I can, I can hop into the pivots for analysis. So, listen, I have to write a couple more books at least, okay? Yeah. At least. I'm on it. My movie is next, by the way. So that's you. Oh, well, that's perfect. Perfect. See how it looks movie. That's what I want to hear. Yeah. Nice. The red stapler becomes what would it be? I was told I could have access. Yeah. I was told I could have access to the snowflake tables. Yeah. And if I could just, like, please give me back my access to the snowflake tables. Oh, Gershaw. Can't you hear it? It's all a movie. I'm telling you. Yeah. It's the time between Gershaw, Joe Sutherland, and Gary Angel. Oh, Joe, yeah. Joe. Joe. Wait. There's somebody else. Yeah. He's going to teach you them a pen on. Three. Oh. Have we had Chelsea on three times, too? I thought so. Yeah. Because we did two and quick succession last year with her. Well, this is what I was trying to do now. Yeah. Is this, like, a high problem of, like, 2010 where it's, like, capital basin. So it doesn't. Yeah. Look, it's like a real company here. Tim does all the work, and he's got four bosses to help him when he did wrong. Oh, boy. You know what? You know what? Oh. Meanwhile, meanwhile, Tim's over there typing into Claude and Claude's like, you're empty right. I did forget about that guest, you know, and you're right to bring that up. You're right to call me out on that. That's right. When was, like, the last time, like, how many times have Tim and Mo fought or something? Oh. Oh, what triggers Tim? Like, those are always-- Because it takes up on, you know, it's an argument or-- It's pretty, it's pretty good. Rock flag and turn around that shovel.

Podcast Summary

Key Points:

  1. Analysts often repeat outdated processes without critical reflection, leading to underutilized capabilities despite significant investment.
  2. The core problem stems from siloed organizations that focus on reach and volume rather than timely, relevant customer engagement.
  3. Digital transformation over the past 20 years led to over-investment in tools and teams, saturating growth potential and creating a need for quality over quantity.
  4. True customer success requires solving actual customer problems, not just segmenting based on outcomes or past behavior.
  5. Cross-functional teams must operate with shared goals, blending data, marketing, and analytics to test and learn in real time.
  6. The book emphasizes shifting from activity-based rewards to outcome-based success, where impact is measured through real customer behavior.
  7. Customer journeys should be micro-focused and dynamic, not rigid, linear arcs that don’t reflect real-world complexity.
  8. A hybrid model—combining centers of excellence for discipline and cross-functional teams for agility—provides the strongest balance of structure and innovation.

Summary:

Rusty Ramer’s book *Working as Designed* critiques the stagnation in modern analytics and marketing organizations, where decades of investment in tools and teams have led to inefficiency and poor customer outcomes. The core issue lies in siloed operations focused on reach and volume, rather than solving real customer problems with timely, relevant engagement. Ramer argues that companies have reached market saturation and now must shift from "lazy marketing" to deep customer understanding.

This requires a fundamental rethinking of how teams operate—moving beyond isolated functions to cross-functional, agile teams that test, learn, and iterate rapidly. These teams focus on identifying customer problems, not just demographics, and deliver measurable outcomes through value exchanges. The book champions a hybrid model: preserving centers of excellence for standards and discipline, while empowering agile, mission-focused teams to solve customer problems.

Crucially, success is measured not by activity or tool usage, but by actual customer impact. Ramer also highlights the flaw in traditional customer journey diagrams, which are unrealistic and overly simplified. Instead, micro-journeys based on real-time customer needs are more effective.

The transformation demands a cultural shift in reward structures—from incentivizing activity to rewarding measurable results. His insights are framed as a conversation, not a lecture, making them accessible to executives and practitioners alike. The episode concludes with a recommendation to listen to Chris Hayes’ *The AI End Game* podcast, which offers deep, thought-provoking perspectives on AI’s societal and ethical implications.

FAQs

The core issue is that organizations have built siloed functions with extensive investments in technology and teams, but they're not achieving meaningful results due to a lack of cross-functional collaboration and a focus on reach over relevance.

Because they’ve focused on building capabilities without shifting to a customer-centric model. The systems still reward siloed activity, not collaborative, timely, and relevant customer engagement.

By shifting focus from broad audience reach to solving specific customer problems with timely, relevant, and measurable value exchanges that move customers toward desired actions.

It’s a metaphor showing that organizations have the right tools (like analytics and data) but are using them incorrectly—instead of solving customer problems, they’re just collecting data without applying it.

They enable rapid, agile testing and learning by combining data, analytics, marketing, and customer experience disciplines to solve specific customer problems and measure real outcomes.

Because they represent an average of people’s lives, not real-world complexity. Real customer behavior is messy and varied, and people don’t follow predefined paths—only micro-journeys that respond to real-time needs.

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