The Retail Journey
Welcome to the Retail Journey where we will cover important topics, interview industry stakeholders, and address emerging trends as we journey through our mission of helping our listeners thrive in retail. Your hosts for this show are CEO James Harris and CGO Charles Greathouse.
The Retail Journey
Unpacking Retail's New Normal: In Conversation with The CPG Guys Bryan Gildenberg
What happens when you bring together retail strategy and influencer Bryan Gildenberg into a deep dive into the transforming landscape of retail? You get to explore the fascinating world of data analysis, the impact of AI, and the powerful new strategies that are trending for category growth.
In this podcast, Bryan shares from his experience and expertise on why a digital-first approach to retail media in the US is crucial and how it contrasts with other markets. Bryan also shares about his experiences with Walmart Luminate and the escalating importance of first-party data. You’ll gain a fresh perspective on the evolution of product discovery and how data is reshaping the retail industry. We'll also navigate through Walmart’s category management and its influence on brand growth. Discover how emerging brands can level the playing field using category advisorship and innovative data-driven strategies. You'll also learn about the potential risks and benefits associated with AI in retail and the need to comprehend the algorithms behind it.
Join us on this enlightening exploration to expand your understanding of the retail market, along with Bryan Gildenberg's intriguing insights and personal experiences. This is not just another podcast episode, it's a journey through the evolving retail landscape.
*Books mentioned during the podcast: "The Coming Wave" by Mustafa Suleyman and Michael Bhaskar, "The Experience Machine" by Andy Clark, and "Tomorrow, Tomorrow, Tomorrow" by Gabrielle Zevin.
Hello and welcome to another episode of the retail journey podcast. I'm one of your hosts, Charles Greathouse.
Speaker 2:And I'm James Harris, and today joining us is Brian Gilbert. He's the founder CEO of Confluencer Commerce and you might recognize him from the CPG guys podcast.
Speaker 3:Hey how you guys doing, yes, so CPG guys. Member and host of the podcast fast forward, which this will also be airing on with, with all the legal permissions that you have available to you, and it's Confluencer Commerce, just because it's like influencer, but we're conning people.
Speaker 2:So so we were straight up about it, no.
Speaker 3:And I also help run a retail research business called retail cities on the managing director for North America as well.
Speaker 1:So Brian is up to a few things.
Speaker 3:Yeah, keep busy. So running around, and thank you very much for inviting me down here to have a little chat and get to see the lovely confines of Northwest Arkansas again. Hadn't been here in a while.
Speaker 2:So it's a good you're here for on a good week.
Speaker 3:Yeah, it's crazy hot down here, so it's warm. Yeah, we've been having meetings outside all day, because that's what we do in the middle of November now.
Speaker 1:That's what we do, beautiful day in Bentonville At least global warming is a myth, right, so we got that. Got that, you heard it here first, all right.
Speaker 3:Captured. Just throw that out there.
Speaker 2:So we'll do that in the highlight we're not here to talk about that Okay.
Speaker 1:So, as we all know, the retail journey is nonlinear and you're no stranger to things perhaps going as planned, perhaps not. You and James have an interesting thing in common, and that's 15 years ago. Yes, surprise, I'd love to, just you know, get in a little bit about, like the man Brian Gildenberg.
Speaker 3:Well, yeah, so James and I each share the delight of having boy, girl, 15 year old twins. So that was enough for me. That was a Canadian football two and a half, as they say. As they say we punted on third down and got a rouge, but you kept going. So good on you.
Speaker 2:One more.
Speaker 3:One more. So yeah, so two 15 year old kids and I currently live in scenic Newark, new Jersey, which I've ever been there you know I am exaggerating at scenic properties.
Speaker 1:They are interesting.
Speaker 3:Ever flying into Newark airport and you look to your right, you'll see Newark, just wave. I live in one of those tall buildings and I'm staring right at you. So, oh, that's amazing.
Speaker 2:There, you go.
Speaker 1:I love it. When did you first know you were going to be a CPG retail influencer?
Speaker 3:I had no idea that I was going to be in the retail business until I was recruited, quote unquote, by back when the old business that preceded Cantal retail, where I spent a large part of my career, as an old business called MVI, run by a gentleman named Daniel Connor, still runs around our industry, and that was a really small business, and a friend of mine from business school started working there and he said you should come work for some. Like I don't know a thing about retail Nothing. And he's like that's fine, We'll teach you retail. It's like you know how to write, you know how to teach, we'll teach you the retail part. And that's the superhero origin story. My background had nothing to do with this industry at all. I'd worked in the financial services industry, the petrochemical industry and the nonprofit industry before I got here, so I love it.
Speaker 3:So many of us here in retail didn't intend To be in the retail space and Well, and now I somewhat, sometimes unintentionally work in the nonprofit industry, but that's part of the fun of being a sole proprietor. So, there you go so. But yeah, I've been doing that. I've been in this space for about 25 years now, so most of that it can't are a little bit of an omnicom in for the last year on my own Okay.
Speaker 2:Well, and it seems like all three of us have a pretty good relationship with data. Sure, maybe that's a place to start. Okay, why not? Let's start. And we've got some data changes in our Walmart world, yeah. We're all dating data, so to speak. Walmart.
Speaker 1:Luminate, so let's start there.
Speaker 2:What are the big trends you're watching seeing there in terms of Walmart Luminate and the changing environment for data?
Speaker 3:Oh, wow, and this is one I would probably I'm going to bounce some of this back to you guys because you're much closer to the as the Brit say, much closer to the coal face on this problem than I am.
Speaker 3:I do think that, look, there's obviously as the retail world becomes more digital and as retail media becomes a bigger deal, and those two factors are related to one another, particularly in the US, which is where retail media is a very digital first ecosystem.
Speaker 3:If you actually go around the rest of the world, you'll find that retail media is not necessarily a digital first ecosystem, that in a lot of markets around the world outside of the US and China, retail media actually started with the Omni Channel brick and mortar retailers as a brick and mortar phenomenon first that's not true in the US and started as an Amazon phenomenon here and has obviously been exported notably people used to work at Amazon to a wide range of other retail platforms today. So there's a big componentry around how the digital ecosystem can drive and create demand. A lot of that is database, and then you've also got the retailers looking at the world where first party data is becoming more of a scarce commodity and data in general as Google seeks to go on the journey of degradating its cookies, which sounds like somebody left the Oreos out.
Speaker 1:No more cookies.
Speaker 3:But that first party data now becomes increasingly important. The ability to mine that data becomes increasingly important and the retailers for years have been monetizing their own data. How Walmart's approaching that problem is not necessarily new and not necessarily radically different. Do you think it's really interesting? I'd be curious for your point of view on what that.
Speaker 3:You know and some of us at this table know more about this than others, right, but in terms of how you would expect that to change the vendor relationship with Walmart. I mean obviously now with the two platforms for Luminate, one of which is basically what you used to get through the old DSS slash retail link platform. The others are more sophisticated version where I can see deeper channel analytics as well as shop or behavior analytics. Just curious to see how you think that's going to change the way vendors approach the problem here. I know you know more about the disease, but you know more about this than I do, so for once I'll ask you questions that are babbling uninformatively about a problem that's a great question, love it and we might have different perspectives on it.
Speaker 2:From my perspective on Charter is it's there's an inadvertent, I think, separation of the 20 biggest companies and the 5,000 big but not as big companies, that this kind of levels the playing field a little bit. Everybody has the same data set Interesting One.
Speaker 2:One might use it more for turf protection, where another might use it for gaining turf, yeah. And then for the smaller businesses that are on basic, walmart still leans very heavily on their suppliers, whether there's one person in the office or 50 people in the office, so they have to have a certain amount of data to be able to grow their baseline. One, because those are important businesses and brands to Walmart, so you can't just turn that off and gives them a little runway to hit the critical mass, to where purchasing Charter makes sense.
Speaker 1:Yeah, yeah, my point of view. It goes back to some of the approval discussions when we were trying to launch Walmart Luminate. Right, scott McCall, chief merchant at the time, was around when DSS came out and the impact it had. Walmart was the first grocer to go coast to coast and in his mind and I subscribed to the same perspective. The availability of data for decision making, for understanding performance, transparency to inventory Was the key driver of how they were able to scale, adapt to changing markets as they expanded from the central to the coasts to be able to actually serve customers coast to coast. So I think it played a revolutionary role Back when dss came out.
Speaker 1:I expect, now that we're in a much more digital environment, that walmart luminate specifically the charter, you know, subscription will empower a similar revolution because we're understanding the customer in a new, different way that has not been understood before, unlike in the nineties. Walmart's not the first to this game, and so I think that there's a little bit of catching up perhaps required. Certainly a first mover advantage For folks that get access early on and those that are able to take this data, turn it into meaningful stories, not just for the brand, for their categories.
Speaker 3:I think it'll have a significant impact on how shelves and e-commerce platforms at walmart evolve over the coming years yeah, I'll offer a couple of observations, having watched this sort of play out in different places and in different countries. One of the concerns of what was walmart if I'm worried about him, right, so, um, so, but one of the I think one of the things that does become an interesting challenge and you talked about it, james in the sort of the big versus everybody else. Look, if you're asking people to pay a lot of money for data, that's not going to benefit small companies by a large right, that's just. There's no, there's, there's no algebra that makes that work out particularly great. And if you look at kroger and look, kroger's a wonderful business and my dear friends are high. But if you look at the shelf of kroger and you look at the percentage of new and innovative products are on the shelf versus the percentage of not new and not innovative products, it's not a high ratio. And part of that is because kroger is different objectives with the shelf than walmart does, notably around private label kroger shelf, private label penetration and average categories about two x what walmart's so cool, right? So some of that space is taken up by kroger's trying to do some other stuff.
Speaker 3:But I don't know that between that and the heavily large supplier dependent way the category management works at walmart, that you're creating an ecosystem which it is easy to find the brands that are going to grow the category, and that would probably be my. I think it'll be interesting to see how the merchants who have and you guys know this better than I do, the merchants have to learn how to do that right, especially in categories where there are big cbg players that are presenting the woman assortment that may or may not be an assortment that is as innovative as the category needs to be. They've had to work super hard to go find these new brands. They've had to hit the trade shows. They've had to go to expo west. They've had to really immerse themselves in this new ecosystems. They may not be getting as much information about what's new as they used to research direct to consumer. Yeah, well, yeah, and just really you know, and you know looking at the amazon top sellers list, which right now is the most freely available way to kind of understand that anyway.
Speaker 3:So I do think it'll be interesting to see how, how accountable, walmart can keep brands that don't make most of the innovative products in the category for growth in the category and how you don't lose sight of that and how you and this is an age old conversation at walmart about you know how much growth is the category partner really want to plan in.
Speaker 3:So they've got their objectives to hit too. But and then just how, how that process works and increasingly, as this type of data becomes more of the language, of how the joint business plan unfolds, it'll be interesting to watch and I do think it's also interesting when you put that in the context of some of the, I think, some of the lean and walmart is going to do from a joint business planning process which will make it a, I think, a more I don't say more labor intensive, but certainly more intensive process, with more and more suppliers trying to get to a broader joint business plan. I just think it's going to be interesting for for brands and for businesses like yours to be honest, to try to help some of these small brands, like you know. You know I don't want to just shamelessly advertise your product, but I do think small brands are going to need help down here, probably more than they used to, and they already needed a fair amount of help. I don't know that. I don't think that's a fair statement, or not?
Speaker 2:This is just speculation on my part. Yeah, nothing to base this on. Yeah, but my yeah.
Speaker 3:So so disclaimer Brian does not know the future.
Speaker 1:Yeah, so that's how it is. None of us work at walmart, yeah.
Speaker 3:None of us have a Ouija board either, so for those of you not watching on video, we are not. We're not, say on Sigma Future Right.
Speaker 2:But my thought, because category advisorship started during my career. It's not a long thing. At least at walmart Right and in the early days, you'd have a category advisor, a captain, yeah. You might have a co captain, sure, and or a challenger.
Speaker 3:Yeah, yeah, you'd have the validators, basically.
Speaker 2:Validators the two old guys on the puppet show sitting the balcony.
Speaker 3:But that's P&G and Unilever or Crafts and General Mills, statler and Waldorf, by the way, if you ever want to know what their names are.
Speaker 2:It's the biggest share brand and the second biggest share brand usually were the way that kind of worked, because they had the resources to do it, I think, with not so much on the channel or POS inventory. You know the non category advisors aren't going to have access to that, but they will have access to category level transactions, yeah, so I think a good merchant has three or four or five validating challenging advisors.
Speaker 1:Well, I mean, for the first time, you'll have a potential emerging brand, you know, as long as they're sized well enough and have the aptitude to understand data and to use it to make decisions. Yeah, which isn't the usual start point, there are certainly data native brands that are emerging in the market today. Yeah, as they have that approach, they now are able to be at the same table, the same data available to them, and not just on the category side you can unashamedly use it from a sales perspective.
Speaker 1:I distinctly remember in the my hair care days with Unilever, l'oreal, procter Gamble telling me the future of hair care with decided confidence, no uncertainty. And yet they disagreed with each other enormously.
Speaker 3:Yes.
Speaker 2:As.
Speaker 1:I'm listening to three different titans of industry explain to me exactly what's going to happen, and well, they can't all be right. Yeah, somewhere in the middle is a bit closer to right. I'm excited for that to happen, not just in the categories that have multiple major CPG players, but now, through help of you know, folks like us and other brands can come to the table with access to that data. Yeah, then, in the past, the little guys never had access Right To that kind of a function.
Speaker 3:And I think, too, it's going to get interesting when you look at how product discovery works and do it because so much product discovery today lives in the digital and the content world. So, whereas people used to come to the shelf and see something for the first time and I was talking to Andy Murray about this and sort of talking about the old days when P&G had Swiffer in the stores for six months before they had television advertising and nobody knew what the heck a Swiffer was so they had to, like, really use the store as a way to explain the product, because that was the only way anybody was going to discover before the national TV campaign hit. Obviously, today that's not the way any of that works. And what's national TV? Yeah, well, yeah, so I mean. Yeah, I was talking to a friend of mine this morning who's like my kids don't know what live television is, right, they're teenagers and they've never had it at all.
Speaker 3:I think the interesting thing is is that when you, when you, look at this, I do think that the importance of Omni Channel here gets way more important, absolutely Because small brands can play in the digital world relatively easily. They can make an impact. Through Walmart Connect, they can start to do things that start to gather momentum in the dot com world, that are then sort of a proof of concept, if you will, for what they're going to be able to do. And I think that sort of Omni Channel launch still set Is going to be much more important. And the ability to use retail media and digital shelf presence to be able to think about launches and just going to be important for small brands, but even for big ones as well, to be able to show the merchant that look, there's momentum here, there's capability here and we know how to reach the audience we're trying to reach. And, by the way, plus points if that audience I'm trying to reach is an audience you're trying to bring into the stores. Yeah, yeah, that's not your core audience.
Speaker 1:Or bring back. I mean, for the first time as a merchant, being able to see repeat purchase rates. Yeah, I mean you talk about momentum. In the past it was just dollars, but not every dollar is the same. No, if you're, if you're attracting very valuable customers, that's one thing. If you're attracting someone who's coming back more often, more frequently and then even just with the data for the first time, actually having clear line of sight to e-commerce sales, right, yes, you know, walmart's got an incredible platform for selling and in the past, with DSS, you didn't quite understand what was a digitally initiated sale versus an in-store initiated sale. And I know people that thought they were doing two or three percent online and discovered they're 15, 20 percent once they actually saw the data.
Speaker 3:And this is going to really impact category management too, and this is something that's been an issue down here for a while and I think it's particularly it's particularly cute in certain categories where the pack size variation from what people buy in e-commerce versus what they buy in store is dramatic or the brands that they buy, because now all of a sudden, the shelf's trying to do two jobs it's trying to be a selling platform, but it's also a warehouse for the online pickup, for the online pickup and delivery, and getting the assortment right for that is really hard. And in trying to figure out what the balancing act is between holding power in categories where e-commerce is disproportionately skewed towards a couple of brands and disproportionately skewed so it's pack sizes that take up more shelf space versus variety, as a real and without data, I think it's been hard for the brands to really sit down and have an intelligent conversation with Walmart about what that shelf's actually supposed to look like and what it's actually supposed to do.
Speaker 2:I think there's a positive down the line that comes from this change, and obviously it's a painful change for some. Right, we're paying for something now that we didn't pay for before, but we talk about this a lot. I've heard more and more from Walmart that category growth is looked at like this that a brand grows more if the category is growing than if they're just taking share from another brand in a non-growing category, and even if they're not.
Speaker 3:Walmart doesn't care if you're taking share from another brand, and most large brands have understood the language. And it's actually one of the real interesting challenges that large branded companies have when they're trying to reconcile their commercial plan with their media plan, because the media ecosystem has no idea what category growth is.
Speaker 3:They know that there are things they can do that will grow a category, but they're generally not accountable for it at all.
Speaker 3:Whereas once you get into this ecosystem and it's particularly for the larger brands that are here category growth is such a big part of what this team is like, what the team's down here are paid to do, and it's such a critical KPI for the company. And yet media teams still come down here and are trying to, you know, wondering why Walmart can't connect with them to do conquesting. It's like well, why don't you do conquesting? Because we don't want you to do that. It's a total waste of time, for I mean not for the media team, but for Walmart as an entity. There's an interesting argument to have about whether conquesting makes your advertising more valuable, which is a different question, but this whole back and forth, I think is going to be really interesting in trying to teach your entire company as a brand that category growth is an objective here and that growing the category, yes, it grows brands more, but even if it didn't, it's obviously what Walmart wants. The customer gets a vote.
Speaker 1:So in your time exploring, understanding, learning, retail, consulting folks, as you talked to us brands that are on the largest side of the spectrum and the smaller side of the spectrum, Can you talk to me about bringing category growth to life and how to get someone above just staring at the brands trying to grow it and paying attention to the category? In both of those contexts it's a really good question.
Speaker 3:I think there's, that's one where the cop out answers to say you know it takes a village, right, but it kind of does. And I think that I do think that large brands partially and almost entirely, I think, because of the pressure that large retailers have put on them to drive category growth and not just Walmart but other ones have changed the way they think about innovation and at least can think about it in multiple tiers. I've got some innovations that, yeah, I'm just putting on the shelf to replace something else, right, and I'm not expecting it to outperform what was there before. I'm just expecting that the performance of the thing that's already there is going to decline.
Speaker 3:So I'm going to replace it, right, and it's not really going to do much more. Apart from that, I've got some that, yeah, they're share grabbers for me. I tend to talk about those less than a JVP. I put them in, but they're in the back of the deck. So, and then I think a lot of the innovation cycle, though, and a lot of the work that I used to, that we used to do at Cantar with clients, was helping them root innovation back in legitimate consumer trends. So, charles, those future hair care presentations I've seen more of those than I care to think about in my life right, totally, and for a number of for water and water companies that you're talking about, yeah, You've probably built all three of those.
Speaker 3:Yeah, we did it all. I was confused but informed. I was blind, but now I see, so so the so yeah, but the confused but informed.
Speaker 2:I got to put that on my business card. You can take that one.
Speaker 3:So so I might be on my tombstone. So the but, the idea there, is that that should not just be a goofy PowerPoint that you started meeting with, but you should be able to trace the innovations back to that, yeah, exactly.
Speaker 1:And what?
Speaker 2:consumers want.
Speaker 3:How are what's going to make the consumer spend more in this category? Right, and if they're going to spend more, that means that you've got to solve a problem for them in some basic level that they weren't solving on their own. Yes, equity is great and people will pay more for premium brands, and you know Sachi and their love marks and all that stuff. Cool, right, but in the end, if I'm not solving a problem for a consumer, I'm probably not justifying the the, the incremental expense that they're going to route to this category, and I think that's particularly acute anytime the economy gets kind of ropey, right? So so I mean, you know there's most of the great innovations that grow categories solve the problem in a different way, yeah, and the other thing is that they often solve it though it might be more expensive than other things in the category, it's cheaper than, however, you were solving the problem before the compensating behavior was more expensive and either real terms or time.
Speaker 3:Yeah, so if it was 20 bucks but it was cheaper than an outskipper, right? So so that's the, you know, that's the, that, that sort of trade off thinking, that sort of category growth and that. And I think today, like in food, it's a massive opportunity in food, given how expensive food at food at home has become through delivery services. You know, if you look at Uber Eats and DoorDash and the premiums that the restaurants charge just on their menu pricing to make their own economics work, and then the service charge and the gratuity that you need to add or you get the world's worst Uber driver.
Speaker 1:The slowest at least yeah.
Speaker 3:Yeah, if you're not going to take. I mean, now all of a sudden you're out. You're out literally $20 more than you would have been to go to the restaurant for the food delivered to home. And now all of a sudden, walmart or any retailer, it's an enormous opportunity to say, hey look, just come buy food here. Right, we got food. We have food you can cook in a minute Like you'll. Your kids are hungry, do this, it's half the cost and it takes half the time. Like that sort of proposition you could. You could slide any solution you want into that and almost any price point you want. It's still cheaper than that.
Speaker 1:Right, and then you're bringing it to large brands and small as a small company, small brand, I think a lot of people make the mistake of deselecting themselves from that conversation. Yeah, do you think smaller brands have the rights to be in that conversation with their merchant and how do you guide them to?
Speaker 3:I think smaller brands are often liberated from the existing solution in a way yeah, that larger brands are not. I think oftentimes a lot of the innovation in categories has come obviously has come from smaller brands. And you know, pre-covid, if you looked at the degree to which small brands in the United States were outperforming large ones pre-COVID, they were growing two and a half times faster than larger brands, and there's a reason for that. They were solving problems differently, right, and they also were able to reach consumers that were trickier to reach in more innovative ways, because they weren't the prisoner of an existing media budget. Yeah, they were a marketing mix model that, god bless, it was built in 1989.
Speaker 3:Right, and look a lot of friends who work in marketing mix modeling and they're smart people. But any model is a prisoner of the assumptions that built it, right? Yeah, you know, it's like you can do whatever you want to your house in terms of putting extensions on and stuff, but the foundation is foundation, right. So, and there's only so many extensions you can put on that thing before it doesn't code anymore or it tips over.
Speaker 3:And yeah, and that the foundations of any model or the assumptions that built it, and one of the things that I think people are starting to unwind now is that a lot of the media spend in the world has been guided by models whose assumptions were the television works Right and if it does, and for a long time it did.
Speaker 3:Yeah, and you know, ponzi schemes work until they don't so so so not, and but it's like the whole idea here is that the way in which you reach consumers has changed fundamentally. Yeah, I think brands that aren't a prisoner to the old way of doing it, generally speaking, start out with a little bit of a head start in that race and are also generally speaking and centered to solve the problem differently. So, they're solving the same, the same way, why would they be there? Yeah, so why would they even exist?
Speaker 1:Yeah, I see the the the problem if it's not focused on the customer and making the customer's life better. You've missed the point.
Speaker 2:And to your point as a large brand.
Speaker 1:Your problem might be a self-created problem, because the marketing mix was one thing one year and last year was this thing, and you need to lap that thing instead of just paying attention, being liberated from last year's budget and just looking at the customer.
Speaker 3:Well, I remember talking, as you were using hair care as an example I was talking to a hair care brand about this and this will be lead us into, I think, some of the stuff that AI can do in a minute, right? Yeah, so I was talking to a hair care company about this a couple years ago, probably a few now, and they were, I think what was the trend? I was coconut oil or something like that, one of those things, right, just one of those trending ingredients. And like, well, we launched this product and it flopped. And you know, we you know, because we're telling them about the need to be on trend and we were talking about how this launch failed. And I was sitting there and I was like, okay, and in the meeting, I just go into Google Analytics and try to find out when the search term coconut oil had been Four years before it was literally 12 months before the product had launched, yeah, and it's like, yeah, this thing was cool a year ago.
Speaker 3:Yeah, and unless you really thought about how to maintain and build that momentum which you can do, by the way you can do that, but unless you thought about it and you just thought you were going to catch a wave you know waves don't last forever, right? Yeah, otherwise people would never stop surfing. Try to catch them after they break.
Speaker 1:So, yeah, it's a little more hard, yeah, sand?
Speaker 3:is coming. Not as much fun from what they tell me. I don't surf, so, but it doesn't look like as much fun when you catch the wave after a broke.
Speaker 1:So I just know from YouTube.
Speaker 3:Yeah, exactly.
Speaker 2:Not a surfer 100 foot wave like the show, so don't have the balance. My family is laughing at me right now.
Speaker 3:Yeah no, anybody that's ever known me is laughing hilariously at the idea of me surfing.
Speaker 2:So so you mentioned AI. That's where we wanted to go next. Yeah, there's going to be some people listening that roll their eyes and then there's going to be another group of people listening oh, what's this? What's this going to do? Right? What's your? What's your take on how AI enlarge or down to chat, gbt, what it can bring to retail?
Speaker 3:Well, look, I think there's. I think there's a couple of things, and one of which is yeah, we chatted about something yesterday, but I think one of the things that's really important is that you learn from the last two eye rolling initiatives that companies have deployed in the quote unquote digital world. The first was D2C and the second was the metaverse. So you think about all the buzz around D2C, particularly during the pandemic. It's like, oh, we got to reach all these consumers and then the metaverse came along for some reason and did stuff. That's great, so it was awesome. So so it was the. It was the RFID tag of its time, right?
Speaker 2:So. So I mean, who knows, I called that?
Speaker 3:QR codes were a solution in search of a problem for years and finally COVID gave them their moment. Maybe something will give the metaverse its moment, like we're never allowed to leave our houses ever.
Speaker 2:That's the only way we can talk to each other.
Speaker 3:Let's hope that happens. The challenge there, in addition, there's two things. Number one, the initiatives, and this is the problem you have with AI and the risk right, which is that a lot of companies are doing this because their board of directors wants to know what the AI strategy is. They asked the CEO with the AI strategy. As the CEO doesn't know, the CEO goes and yells at the CTO and says what's our AI strategy? And now, all of a sudden, you have a need to check a box on what the CEO is reporting back to the board. That's what happened in D2C and that's what happened in metaverse. The other thing with D2C was is that you had an ecosystem that was trying to sell you what I might charitably call as a bill of goods on some of that stuff around. What that thing was supposed to do and there was a fear thing involved in both On D2C was first party data was a big one.
Speaker 3:You need to collect first party data. Collecting first party data is an awesome idea, and if you have a really cool idea in D2C, that's a really good way to do it. If you approach D2C as though your objective is to acquire first party data. That's like saying I'm coaching a football team and my objective is to win the game by scoring more points than the other team. Not incorrect, I mean certainly a good idea. You would probably need some supporting documentation on how you hope to accomplish that and, in particular, you would need good players and a plan.
Speaker 3:And companies didn't do that. They said we're going to score more points than the other team. Oh, we need players. Let's just pick up some guys off the street and throw them on the field to what happens. Yeah, it didn't work. A lot of brands don't have a reason to connect to customers or consumers in a D2C way, and we're deeply disappointed by that. It didn't replace anything that was already being done, or replace something that was already being done perfectly fine. That was the same problem with the metaverse. The metaverse replaced something that was already being done perfectly fine, which is real life. So for most people, real life is cool.
Speaker 1:So, and I don't need some of us need a second, second life.
Speaker 3:Yes, right, a third life or whatever the metaverse wasn't replacing anything. I think the difference in AI and we'll now we'll get into the nuts and bolts of this, because AI most of what people are talking about. When you talk about AI, they're actually talking about chat GPT, which is a product owned by a company, open AI, which is a form of text-based generative AI, which is a form of generative AI, which is a form of AI. So let's, we have to do our little biology homework Shout out to my daughter who hates her biology homework and but we've got to go through the process of phylum genus, species, whatever, right, like AI is a much bigger concept than chat GPT.
Speaker 3:That being said, if you just look at text-based generative AI, just to start there, because it's where everybody kind of starts the conversation today it's got enormous because what that can do is that actually does replace something people are already doing, which is searching for stuff. It's like, ah, okay, finally, an intuitive business application for something that somebody has developed from a technology point of view. That's going to get really interesting, right? So that's that's a whole conversation to have around how, as the customer gets more use and consumer customer, you know, you all say customer, I say consumer, because in my world the customers the guys up the road here. So, but on the consumer, shopper side, how does that change the way that the consumer expects, expects text-based solutions to solve problems for them?
Speaker 3:And my guess is that will dramatically impact what is already a pretty shaky leg that search stands on in this ecosystem, because today more product searches have started on Amazon than on Google for years and now more product discovery takes place on TikTok than anywhere else. So now I've got two very different search algorithms, which are TikToks and Amazons, that are driving a lot of product discovery and a lot of shopping behavior, and Google is just kind of there doing its little thing. And now, if you get something else that replaces that, you're going to very quickly find that there's no unified search architecture for shopping anymore, and that's got enormous implications for the 23% of global media spend that's spent on search. You know it is the, depending how you account for it. Arguably the largest media platform in the world is not even product retailercom search, but just actual general website-based search Searching for information.
Speaker 3:Google Bing shout out duck, duck, go. That's true, although, yes, ultra-vista, let's go, let's go, let's keep going, yeah, so next on Dead Search Engines.
Speaker 3:It's so, yeah, so I think you've got a really interesting conversation there about what that means. Then I think, though, if you look at what the and you know, you've seen Amazon today with their third-party network they've already enabled most of their third-party sellers to generate a lot of their product description pages through AI, and for something where you're not trying to be artistically brilliant, but really more technically compliant, ai is really good at that stuff, right, like, ai is not great at artistic brilliance, but if it just needs to be able to do something that fits a spec, you know it can learn the specs, you can train it on the spec super fast, yeah, and then it draws the right conclusions about what to put in the spec. So that's a really interesting application, I think. In general, though, when you look at AI, like any technological innovation, I think people are expecting oh well, it's going to get all my work done, I can go home at two o'clock.
Speaker 3:Technology never does that.
Speaker 3:What technology does is it creates more things to do, right, and I think that's what AI is going to do, because the minute you start to harness AI again defer to you, gentlemen on this the minute you start to harness AI, you realize that you can do more content variations than you used to be able to do more easily, and you're going to be able to then deploy those content variations against meaningfully different audience segments within the retailer's ecosystem.
Speaker 3:So, instead of having one product description page or one promotional campaign, you may have 30 or 40 or 100. And you've got retailers today, like Kroger, who are really good at giving you granular audience and behavioral based segmentation data back, so that if you wanted to run 4,000 meaningfully different campaigns at Kroger, you could do that today. You've got the data to do it, just no one knows how. So I think there's a really interesting question, whether it's text based or image based stuff like mid journey, and then Amazon now also enabling its first party sellers to use AI to generate a variety of product images on its site for your product description page, all of which seem to be very rule based and all of which are probably going to end up to the consumer, who may not know, but they're all going to feel like every clip art presentation we sit through in PowerPoint, right, like the same 75 clip art images on every PowerPoint presentation.
Speaker 3:I've seen this before and any websites Wait dude, it's with arms in the rear Awesome, so that's cool, we're doing great, and so, yeah, so that's the. I think there's a risk to some of that in terms of the sameness of the, unless you're really smart about how you train your AI Incorporate.
Speaker 2:Yeah, to incorporate Demographics or.
Speaker 3:Just incorporate anything interesting. You're going to get what the AI was originally coded to do back, which I think is the risk of being very, very samey, but I do think you're going to see more outputs. You're going to see more. You're going to be able to get to more outputs faster. That's just going to create more work on the data analytics side and if only there were an analytics business around that. Could that, could comment on that. I would ask them, but I'll just sit quiet.
Speaker 2:And there's so many applications to analytics. We use a few of them today, but are exploring you know what. What? What should we be incorporating? Yeah, just a kind of a personal view. I think a company like a Cantor Cleveland, a research group that trains on POS data, trains on full category trade, trains on item, launches success, failure, media, demographics, that, the, that a lot of things that require an analyst to read multiple things and then do some searching and then kind of white space, ideate around what this means as a overarching story. I think that's something that AI can really accentuate.
Speaker 1:Yeah, yeah, and I think to your point, the impact. Where does it actually hit the road? What's the thing that you're trying to accomplish? Your coaching analogy I kept picturing a business plan and like what's the plan? Well, the plan is to make money Like this is great. I feel like that's the right plan, but how?
Speaker 3:I used to have a slide in the deck like this. It was Albertsons mission statement, or like their, their, their corporate strategy, and it was like a whole bunch of stuff about gaining market share and driving revenue. It's like there's a bunch of outcomes in here, right Like, and this is, we're going to score more points. The other team, we're going to get more yards. It's like, yeah, how, oh, and it's not the current Albertsons one, by the way.
Speaker 2:So no, no, no knock on the current management team.
Speaker 3:Those are. Those are people that are going you know blessed.
Speaker 1:When we were building out the digital merchant product group, we brought on our first data scientists to lead data science within Merch, prakar Majorta. He's still there. We went to the Toronto Machine Learning Summit and we blew people away by applying, yeah, ai, there's a role focused on explainability. If you're in retail and you need to hire someone to do explainability, I mean that happens because a board member said you need to do AI and then you couldn't understand it. You needed to explain it. So you created a role for explainability, like their job is to explain what happened.
Speaker 1:You know there's there's a side of that. That's really sad because you've missed the point, and the point was to make better decisions, perhaps more decisions, without having to actually spend more time looking at things. You know for data science in our world, it's looking at future out of stocks and building the algorithms necessary to identify where you're going to be out in the future, right which, without a healthy input from a data standpoint and good machine learning to be able to understand all of the different store, item, customer trend combinations, you're not going to be able to see that future out of stock. Yeah, and with one more illuminate, it gets ratcheted up to an entirely different level because we're now looking at shopper behavior Right and seeing how shopper trends evolve and anticipating well with repeat purchase, the way it's trending, with new to category purchasers, with new to retailer purchasers. Here are the things that are more valuable and that empowers a better decision on behalf of the merchant.
Speaker 3:Well, and that, and the great advantage of AI is, is that it can. It can incorporate provided you know how to train it a multitude of demand signals, so many, and then you just have to learn how to wait those appropriately and then that get. That allows you to look at abroad, at abroad, at a broader field of vision. So I think that's, I think that's big one. But this in defense of the explainability department, not that I have any particular vested interest in it, but I do think there is a really important role. For you know, people talk about machine learning all the time as a competency. Well, look, machine learning, that's what machines do right, and very technical people are the people that adapt machine learning. I think the critical competency for companies as they move into this world won't be machine learning, it'll be machine teaching. So I'm going to borrow what Andy Murray actually puts it this way he goes, he goes.
Speaker 3:The fifth P in the four piece of marketing is going to be the prompt. How do you prompt the computer to learn differently? And I think that one of the things that I've observed through some dear friends at work at Amazon, that they've taught me over the years, is that Amazon's computers aren't smarter than other computers and Amazon's people are smart, but they're bell curve smart right. The thing Amazon's better at than any other business in the digital world is their people are better at telling computers what to do with another Correct.
Speaker 3:They have people understand the tool. They are people that are very good at the explaining department. The other way, they're very good at explaining business requirements to a technical team. So if you think about the people that grew up at Amazon who are product directors and product managers, they're very good at developing the business requirements for a technical solution to this. That's a really scarce skill in an analog business and it's a hard skill to hire. It's a hard skill to value and it's a hard skill to train for. But I do think the ability to teach machines is important Totally agree.
Speaker 3:And then the ability that gives you to speak how the machine speaks to some degree and to explain back to people that are less technical how to think about what the business requirements would be to train AI. This is going to be a AI training to be a very big business.
Speaker 1:Otherwise, you're just asking someone to trust that it has made your decision better than you would have made it. Yes, In the day at Walmart, visiting the Ecom team trying to understand why my top items weren't showing up where they should, I kept being told oh, that's algo driven. I'm like that's super great. What about the algorithm is making my number 700 item show up number two? Oh, it's algo driven. I heard you. What about?
Speaker 1:the algorithm and so, I think, understanding what's going on. What are the levers that are being pulled to your point as the coach? What's the actual game plan? Are we heavy on defense? Do we have a weak spot in the lineup? Where are the actual things that are going on? So I know how to trust, validate or use the things that are coming out from AI.
Speaker 3:Well, there's a tire cottage industry of people that historically were dedicated to understanding how the algo worked right and decoding the algo. I mean, there's a bunch of smart people around that did that for a living. I think that's the thing. Machine learning. It's actually going to be really interesting for search engines, to be honest, because machine learning and AI will be able to decode the search engine really fast, I suspect. So there's not going to be a lot of secret sauce to that stuff anymore, which I think is another reason why search is becoming increasingly problematic medium, because it'll just be way easier to buy it than it used to be because AI will decode it more quickly.
Speaker 3:The retailers are always looking to innovate their search algorithm, both to quote unquote improve experience, but also really to prevent bid optimization by knowing how the algorithm works right. So they make more money by confusing people, to be brutally honest, and so they have to keep changing the algorithm to make it so that they know more about their inventory than you do. Because, as my old friend Irwin Gottlieb, the old chairman of Group M at WPE, said, just lean back in his chair and me once he goes. You know, the whole history of making money in media is when somebody knows more than somebody else and he's not wrong. That's a really good way to think about the problem. The last piece, I think. So this demystification of AI, I think, is really important, and the ability to that ability for people to act as, like you know, human duolingo platforms, if you will, between the machine learning world and the machine teaching world, is gonna be really important. But this machine teaching thing is gonna be a really critical competency for anybody that's trying to work in the AI world.
Speaker 2:Yeah, that's, demystifying is the right word. There's still some mist in the air, but I Sure, yeah, demisting, yes, Demisting yeah, all right, I think we are time for the lightening round. All right, there we go. What? Let's start with a big one. We try to talk about failures. What's one of your biggest failures that you've learned the most from?
Speaker 3:Or so yeah, apart from leaving my phone charger or my AirPods at O'Hara on Monday. So that was a fail. Well, I mean, I always go back to the piece where you know. I think in predicting retail trends, you know if you're it's a great Boston sports radio DJ named Eddie Anilman who said you know anybody who's right more than 50% of the time ought to go to Vegas and retire. So it's like, okay, that makes sense. I feel like you know, when you get to predict things, you kind of gotta be right a little bit more than 50. My first one, though, was my first project I worked on in the retail industry, which was in 1997, where I boldly predicted that to the newspaper association of America thankfully, they're not around anymore, so sorry about this when I boldly predicted they should double down on their advertising for Circuit City, because clearly Best Buy was gonna go out of business and Circuit City was gonna take over the consumer with a truck of trolls.
Speaker 3:So that was incorrect. Yeah, yeah, Spoiler alert.
Speaker 1:You heard it here first.
Speaker 3:Spoiler alert, that wasn't true. That did not go down. Yeah, so and then, yeah, I think but yeah, I mean that was. I think that the I think most of the time in the most of my learnings have really been more on the commercial side of trying to grow a small business, and I think the thing I've learned, probably more than anything, is just because something is a good idea doesn't mean you should do it. Yeah, and anybody who knows me knows I have a. I have a propensity for distraction, which is, if you've observed on this podcast, which is quite high.
Speaker 3:So, and that propensity for distraction can translate itself into doing too many things that are of interest, but that you lack the bandwidth to be able to scale if you're doing all of them. And the choice to do a bunch of good things is not necessarily a better choice than the choice to not do that good thing and to do one or two things. Well, Got to hear, I think, most of my. Most of the failures in the world are probably were. Some were just terrible ideas, but for the most part they were good ideas that were bandwidth constrained and then got executed very poorly.
Speaker 1:Yeah, the Donnie Smith former CEO of Tyson. Yeah, taught me about aggressively pursuing your to don't list. Yes, yeah, your to do list is great and everybody's got one of those. But if you don't have a to don't list, you're probably wasting a lot of time on things that's not going to add up to much. Yeah.
Speaker 3:Strategy is all about what you don't do. So one of the good Jack Welch quotes. So Love it.
Speaker 1:So All right, and what's on your reading list?
Speaker 3:Don't you guys talk about failures? Oh no.
Speaker 2:So we that's, we asked the question, you just try 90% of mine in business and trying to do too much and it's okay, I might get it, so, all right.
Speaker 3:What's on my reading list at the moment? There's a book about AI which I've forgotten the name of, but it's the big book about AI at the moment, written by the big guy on AI, and I cannot remember the name of it, but it's a. It's going to the bookstore. It's the book on AI. Haven't loved it so far, to be totally honest. It's not moving me anywhere.
Speaker 3:The two things I'm reading that are most interesting right now are a book called the prediction machine. I can't remember the author, but it's a book about how the human brain processes information and about how, how incorrectly, we've thought about that, in that the idea was, historically, that you would sense the world, take that sensation, apply a model to it and observe, but what really looks like it happens when you look at the neurological science of it is that the predictive engine you have in your head is way more powerful than your sensing of the outside world, so that you're basically you need to train the AI model, which is your preconceived idea of the world. You need to really work at that, otherwise you will just see what you have always seen and then the data. You'll use the data to calibrate. That idea of what you've always seen has enormous implications for being observational and present in moments.
Speaker 3:Also has enormous applications for things like anxiety, where you are presupposing a bad outcome and it's really hard, if you're not wired that way, to use data to tell you to not be that way. So there's a bunch of neurological and mental health aspects to it, as well as just generally the importance of remembering to be present, to shut off your predictive engine and just to observe. I mean Marcus Aurelius Gandhi, everybody who's ever brought into philosophy book. Basically, all they're writing about is shut the predictive engine off and see the world for what it is. So that's a cool read. And then a novel called Tomorrow and Tomorrow and Tomorrow, which is awesome so far.
Speaker 2:I'm gonna check that out for sure. And then last one here, at least for me, is you have a bucket item, bucket list item that you're gonna accomplish this year.
Speaker 3:Is that like next 12 months, or by the end of 2023? More to come on this front, but if I don't do something that looks like a book by this time next year, I will be disappointed. I like it.
Speaker 1:Awesome, let's go, hold that hold that Hold that thought.
Speaker 3:So, more to come, so, but that would be my. That's something I've always wanted to do, and I've just never had the bandwidth to do it. I don't have the bandwidth to do it now, but what the hell? Awesome, no time with the present. No time with the present I love it.
Speaker 2:So there you go. Well, thank you so much this has been. Oh, thank you guys, this has been great, and we're gonna throw this on the Fast Forward Podcast as well.
Speaker 1:Yeah, excellent.
Speaker 3:So I'll put a little intro on that and then we'll rock and roll. So really look forward to, obviously, if Charles is always good to see you- and.
Speaker 2:James has been great really meeting you on the screen.
Speaker 3:It's great to meet you and spent a lot of time together before, so thank you very much for the time.
Speaker 2:Yeah, absolutely. Thanks for all the time you give us and thank you for listening. You can download, listen to all of our or watch all of our podcasts on highimpactanalyticscom or on Apple Spotify and other podcast services. Thank you very much. I'll see you guys next time.
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