← The CPG Guys
The CPG Guys
Expanding What's Possible for Retail Execution with FORM's David Gottlieb & Jeff Wrona
00:49:02
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- [00:00]
A
Hi, I'm David Gottlieb, Chief Revenue Officer at form, formerly Chief Revenue Officer for Trax Retail prior to the recent merger.
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B
And I'm Jeff Rona, VP of Product for Image Recognition at form. And you're listening to the CPG Guys Podcast.
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C
Hello and welcome to the CPG Guys Podcast. Set at the intersection of commerce and tech, your hosts Sree Rajagopelan and Peter Vs. Bond explore how brands and retailers engage consumers in a digitally driven world. And now, here are the CPG Guys.
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D
Hello and welcome to this episode of the CPG Guys. I'm of course Sree, your co host and also CRO and co founder of Think Blue Consulting, your trusted partner in your omnichannel development journey. Get in touch with me at sri@thinkblueconsulting.com do listen to my older daughter's music at www.rhearaj.com and follow Lara Raj. My younger daughter is a member of the world's fastest growing global girls group Catfi, who are currently at Lollapalooza, South America and all five of the largest countries South America from Brazil to Chile to Argentina to Colombia. A lot going on there. And then we're excited about Coachella, which is next year in California. I'm of course joined today by my co host and co founder, Mr. Peter V. S Bound, who also moonlights his head of industry and client engagement at Flywheel, the commerce acceleration division of Omnicom. Peter, how are you man? You just came back from Orlando. We met up. We just did the national sales meeting keynote for bars. But how was your time with your daughter Nadia? What parks did you go to? What happened at Disney down in Disney World?
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E
Hey Sree, I was with my aspiring pop star daughter, only 7 years old, but hey, there's room for that opportunity. We went to both the old and new Universal Studios and then after you and I gave our keynote and you headed out of town, Nadia and I went over to Magic Kingdom. There's nothing like going on her favorite ride at this moment. She's been to it at four different parks across the world and love talking about that and we had such a great time and it was particularly great to be on stage with you down in Orlando. Met some really great people, have a lot of new friends. Saw some old friends too. But getting excited for you and I reconnecting in a couple weeks.
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D
Awesome. Peter, make sure you're subscribing to our podcast on preferred listening platform where you can get our latest episodes and go back to consume some of the fun 575 plus episodes we've already published. Now let's move to our guests. We spend a lot of time talking about retail media digital engagement, but if the product isn't actually on the shelf when the shop arrives, you've lost the game. I recently made a huge LinkedIn post about this issue about poor supply chain promises as well as the lack of connectivity between product availability at the shelf and retail media campaigns. Today's guests are absolute experts in solving the deep complexities of in store execution and supply chain visibility. For the record, my post wasn't planned, I just chose to do it anyway. The first expert I'd like to introduce is David Gottlieb spent over 20 years entrenched in retail and manufacturing technology, bringing a wealth of experience from leadership roles at Accenture, Oracle, Market 6 and QD. Today he serves as the Chief Revenue Office at Forum, a company that just made massive waves in the industry by merging with Trax Retail to create an absolute powerhouse in computer vision, task management, shelf intelligence. And joining us also is Jeff Roner, VP of Product for image recognition and Form. Jeff has been developing solutions for enterprise customers in the CPG retail space for over a decade. At Go Spot Check, who we know very well and form, he's currently focused on driving product vision and strategy as it pertains to AI and image recognition. In the new Combine. Org, we're going to dive into how they are completely digitizing the physical world of retail and why dashboards don't sell products. Hell yeah. But decisions on follow through do. Please join us in welcoming David and Jeff to the CPG guys. David, Jeff, welcome to the show. It's great to have you on the CPG guys. How are you both doing?
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A
Doing great. Thank you so much, Sree. Thank you, Peter. It's fantastic to be here.
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B
Yeah, excited to be here. Thanks a lot, guys. Awesome.
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D
And the digital line edits of this episode will of course include links to both their LinkedIn profiles, the company's new company's corporate websites for our listeners to access while we go on with our conversation. So I'm going to jump in and David, I'm going to hit you right up. So let's start right at top with the elephant in the room, which is of course you both emerged. The new company is called Form. When you combine traxxas global reach with Form's innovative model training and deployment capabilities, what can CPG brands expect from this new merged company? Every day at execution,
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A
it's really super exciting for the team and I'll just share A bit about why I think this is transformative for our customers on both sides, on the form side and on the track side, and also for the industry for those that we don't yet work with today. When I think about form and I think about Tracks, we're almost like children that were raised by different parents and now we've come back together as a family where we belong. And it really feels like that to the team. And the reason I say that is if you think about where form kind of grew up, it was really all about how do you best take a very complex set of tasks and organize them for people who work in retail to be able to execute them successfully, do them with high quality and accountability, and then later kind of got into image recognition, whereas tracks kind of grew up with image recognition. We kind of pioneered the space. We developed the early models before AI was a hot topic, we were doing sort of our version of AI. And now that we've brought these two companies together, it creates a few interesting dynamics. The first is now we have best in class task management, so field retail orchestration execution at the shelf paired with best in class image recognition through the combined assets of both companies. And that's pretty unique in the industry. We don't see a lot of companies innovating in that direction. And we think that creates a powerful set of capabilities for our customers to be able to have one tool that helps them do what needs to be done in the store, focus on the priorities that are important to the brand and to the manufacturer and even to the retailers, and at the same time use the power of computer vision not only to inform how to prioritize their time in store, but also to help provide feedback upstream to category management, to headquarter selling processes, to trade all those things that sort of become interconnected to this, this data asset. So we're super excited about that, that sort of conjoined capability. On top of that, you are probably aware that one place where Trax grew up a little bit differently is we have always focused on true multinational global CPG companies as our sort of target customer mix. And as a result we've really built an infrastructure of a go to market capability, a customer delivery and support capability, customer success in all the countries where our customers need us to have them. And so now it allows us to really look at those set of form customers who are actively supported by task management, for example, today, and help them by supporting them around the world where it's important to their business. So it brings that global reach to a new set of customers and that augmented set of product capabilities.
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E
So siblings raised by different parents. David, you've now put the Lindsay Lohan formed the parent trapping that head for the rest of the day. Thank you for that.
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A
Well, Jeff. Jeff's the pretty. Jeff's the pretty twin. If there's.
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E
Well, well, let's bring Jeff into the conversation. Hey, Jeff. Competitive intelligence at the shelf has historically been fragmented, to say the least, and very delayed in terms of the recency when with this new joint capability you have in the new form. How does proactively onboarding the most popular SKUs in each region ship image recognition from just reactive reporting to more of a proactive competitive edge?
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B
Yeah, thanks, Peter. It's a great question. It's something that we're really excited about. I think that one of the things that when we first started, got started off doing image recognition and something that I know the folks on the track side experienced as well, is step one is get us a product list, right? And okay, cool. I can provide you all my products, but it's often rare that someone has a full, active, like up to date list of competitive products also in the market that's clean and ready to go to train a model with. So it's something that had always been kind of a sticking point is, hey, we can get really good and accurate at your products. But looking at the competitive landscape was always a challenge. One of the things that we've been doing on the form side, which we're excited to bring into the merger, is a strategy of training and deploying shared image recognition models across multiple customers within each region. So what this means is that like every customer, customer who would be subscribing to one of these models would, would basically benefit from not only visibility into their brands, but also visibility into what's going on with the competition. You know, the other. Another exciting part of our technology offering is that the way that we are training these models is that even if we're, you know, whether we're, we're acquiring product list information through, you know, syndicated data providers or we are getting them from customers directly, we also have the ability to, as we're analyzing this data and training models identify what are the most popular unknown products in the market. So the model will actually become trained on products that we see the most commonly. Now we have a process in place for going out and essentially looking up that product information and proactively onboarding it. So closing the gap in terms of what is the known product universe becomes a lot more attainable for us. And so like David was saying, you know, I think it's really by combining a shared model approach that form has been working with the image recognition space lately, with the extremely powerful tools that Trax has built over the years, mainly, you know, their KPI engine functionality that's really robust and customizable for each customer's needs. You know, we're in a spot to really, I think, deliver visibility for brands and retailers, but also not only their own product information, but competitor information when it comes to things like product presence, positioning, pricing, POSM execution, share of shelf relative to the competition or specific competitors out of stock detection, promotional pricing, which also is a big focus for our customers. Again, what are the competitors doing in the market? How can we respond in real time? And so the offering really, when it comes to the customer value, when all of this is done at real time with this kind of speed and precision that a manual process or subscription to a syndicated data provider data feed simply can't match, you know, it becomes a game changer. So really what we're trying to do is make that process as seamless as possible, get as much data as possible as quickly as we can so that ultimately brands can use this information to take action quickly as a broader part of their data strategies.
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D
But no process can be seamless without a pretty solid tech stack behind it. So I'd like to pivot into details on the tech stack. You know, the word on the street is AI. There's a big article today on McKinsey getting hacked by AI, which is wild because their entire business model depends on the database where they go back and dig stuff. But David. So having a very important tech stack and protecting it is the name of the game these days. So, David, we'll ask you first and then Jeff, I'll ask you to chime in. Let's connect the word agentic AI. What does that realistically mean for a CPG organization in the next three to five years? How are you guys thinking about it in the industry? It can swing from hype and all kinds of announcements to the reality of Sparky and Rufus and two plaid retail platforms that I think we're all familiar with. Or is it actually going to be an efficiency, operational revolution in the mix? So, David, you go first.
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A
Yeah, definitely. I'll start by saying I, I don't think it's hype, I think it's real. And manufacturers need to be thinking about what their points of leverage are vis a vis AI platforms. And it's not all things to all people. Without a doubt, the Way I think we're looking at it is it's almost a cliche to talk about how CPG manufacturers and retailers are awash in data, right? They have no shortage of data. They get it all over the place. Where we hear from them on the challenges is more around how do I actually sift through this and understand what's actionable, what's valuable, how do I take advantage of some of this insight information to create value in the business? And when you think about the evolution of large language models, the kind that maybe are involved in the hack, you're talking about sri, it's nearly a perfect fit to help manufacturers and retailers better understand how they can activate against data and insight coming from tools like forms. And the reason I say that is if you think about what we do with our field execution toolkit and specifically image recognition, we're generating a lot of data, right? At any, at any point in time, our customers understand the nature of execution. Jeff mentioned some of the metrics, availability, you know, brand blocking, am I leading the aisle, am I compliant with my planogram, all those sorts of things. And it all sits in a database. And what's great about that is it's a nearly perfect environment to train a private large language model so that you can then interact with that model and ask questions. So level one is sort of like imagine chat, you know, chat cpg. So hey, where am I losing share of space? Which, which parts of the country should I be concerned about? Who are the new competitors that are gaining space and how many have achieved at least five facings in the category? So you can ask questions like that very naturally. I think we've all become comfortable with that type of interaction with LLMs. And this can be a very purpose built private one specific to a manufacturer. The agentic piece sort of comes on top of that, which is to say, hey, what if I had a bunch of smart agents that look a lot like my, my analysts maybe, or if I could, if I could sort of amplify the power of my analyst team and, and they're constantly looking at these, at this same data set and, and looking for trends that I should be thinking about. So instead of asking the question, it should be, hey David, did you know there's a new competitor? I see them in the Southwest, right. They're probably not showing up in your syndicated data yet because maybe they haven't hit the ACV that sort of registered, but they are gaining space and it's
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E
something to be thinking about.
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A
And if we can help manufacturers come
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E
up with the right sort of curated
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A
army of those agents, it can really be a sort of value builder and an amplifier of the investment they make in not just the technology but their actual team. So that's where I think we get really excited about what the future may hold at the intersection of kind of where we live and AI, more generic kind of platform AI. But Jeff, you've probably got a much more informed technical perspective than I do.
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B
I certainly agree with everything that David said there. And you know, just overall when it comes to AI, it's, it's no longer a buzzword. I think that people are interacting with AI in various forms in tools all the time, more and more. I mean it's, it' anything, right? If you're, you know, whatever bi tool your company's been using now all of a sudden has a little pop up to go into AI mode and start running queries without filters, but just typing them in with language, you know. And so people are going to be getting more and more accustomed to interacting with these AI type tools. And you know, it's, it's really, I think going to be about recognizing that the tools are going to be as good as the data that you can provide to them in order to make these decisions and run these queries to drive the most effective decision making. But really a lot of these agents I think are going to be very effective at more and more complex tasks. And right now it's going to be like analyzing this real time data, driving actions, potentially managing things like inventory, executing various supply chain actions, making recommendations, you know, on focus areas of the business, as David was alluding to. But really if these agents are effective at doing these things, it frees up time for the humans to be focused on more mission critical tasks and strategic initiatives that the agents are capable of doing. So yeah, I mean really overall, I mean I think it's like when we first started getting into the image recognition space, you know, when Trax was doing it even before us, we were doing it on the go spot, check, inform side. I mean it was, everybody was like wow, like this is awesome. Like we can actually measure and tell and know where we have the best share in what chains or what areas of the country. I mean we were at the years ago we were competing against like in some cases a pen and a clipboard, you know, where people were doing inventory checks and surveys and so digitizing, that was a game changer. But now it's, the strategy is shifting towards how do I bring all of my different systems of record together, whether it's warehouse depletions and sell through information. The in store execution which can come from the image recognition to give you a really robust data set of visibility on what's actually happening in retail and then combining that with things like the point of sale data, maybe potentially even other demographic data sources or other things that you're keeping track of that are meaningful to the business, layering some of these AI agents on top of that can, can really, really drive a lot of effectiveness for the business if done in the right way. So I think the important thing is from our standpoint like the image recognition data and that super granular level positional data of what SKUs are in what spot, what are they priced at in each store, on what day, what time, like that's a ton of information. But that alone becomes kind of like a foundational layer for I think an overall AI strategy that's more robust with other systems of record and data warehouses.
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E
Jeff, let me follow up with you then on this and then the last David to jump in. But the holy grail has always been linking in store execution to sell through. Right. And if you were building the modern CPG tech stack from scratch, what happens when image recognition data is integrated directly into sales, supply chain and marketing system?
- [18:50]
B
Yeah, definitely. You know, and that is the holy grail, I would agree. You know what a lot of people are talking about and circling around, how do we make all of this data come together to have us operate the most most efficiently and the most effectively when it comes to sell through? So yeah, you know, I would say that like including the like real time in store data that can come from image recognition, this is pretty much an essential component of success in retail these days. You know, I guess like kind of to think about this the other way, I think there's like the impact of missing out on this data as an input to some of these different AI tools and overall strategies is if we don't have that input from what's happening actually in store, then you know, slower response times to in store execution issues or inability to be aware of and respond to competitive actions in real time. Maybe your direct competitor launches, launched a new innovation product or is running some kind of a big price discount or promotion that's going to drive revenue for them, adjusting supply chain, you know, quickly. Whenever we're detecting out of stocks, for example, being identified on the shelf, you're not going to get that as a leading indicator in real time. Without a system like an image recognition, you know, the syndicated data would going to be kind of a look back on what happened so you can analyze maybe why? You know, I think like a good example would be like in a world where we didn't have image recognition as part of our tech stack that we designed, you know, if I'm like a category manager, for example, we spend all this time and effort in analyzing the space planning components and how do we best optimize for sales that's going to be good for us but also for the retailer. I would have no way of knowing like were the planogram schematics that we had set effective, do we need to spend time changing them and doing more research around that or is it just simply that the plan was not executed at retail? So it's really that lens that gets you into the day to day, the real time that I think is really important to have as a part of any decision making tech stack, you know, well said indeed.
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D
I'm going to move us from tech stack into, you know, the stock market had a little bit of crash on generals today. And one of the big reasons that the analysts are talking about is a GLP1 environment. And if I start looking at the macro environment, certainly GLP1 medications are reshaping consumption patterns. Those who deny it, large brands at this point, I don't know what to say. Snack brands. And we're seeing broad reporting about Gen Z consuming significantly less alcohol in general. How do you, how can you connect shelf label shelf level data to basically point out leading indicators of these generational behavior changes even faster than syndicated data? Because syndicated data is about a week late every time and for execution in store, you have to wait and assemble the data.
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A
Yeah, let me, let me jump in on that.
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E
Sree.
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A
It's a crazy time in the industry. I think you pointed out two of the kind of macro trends that we see a lot. We work with customers across snacking and built Bev. So those are certainly top of mind for us. And I think the reality is the change shows up first at the shelf and there is a potential to get sort of the canary in the coal mine early warning signal if you're keeping a close eye on what is the shopper experience in the store. How is the set changing? What's the mix of products? Right. When you look at the, you know, at the beer set, do you start seeing 0.0 creeping in and becoming an increasingly high share of facings? What is that telling you about what shoppers are buying and how retailers are responding to that? Those are changes you can see immediately, right? You can see them as soon as you get a look at the shelf at the category, what's on display, what's being promoted and develop your point of view on how the marketplace is changing much faster than you can get a handle on kind of your syndicated data. And on top of that you can get it at any store that you want and you can draw conclusions at the store level versus trying to make sort of panel level decisions that are, that are based on an aggregate looking at you know, a DMA or a set of stores which it can sometimes be tougher to draw specific insights with that level of sort of roll up in, in the syndicated data. So I think in both those ways it's, it's sort of the nature of, of shelf level data that, that can be captured with tools like image recognition that can be an early warning signal especially in independents in different classes of trade, you may not get in your full syndicated fee.
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D
Let me remind our audience that today we're speaking to David Gottlieb, Chief Revenue Officer and Jeff Rona, VP of Product at Pharm.
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E
Jeff, building on these macro headwinds, tariffs have been to say it minimum, a wild ride driving incredible price volatility in an environment where US consumers may honestly be struggling to afford the basics. At the same time, there's a heavy investment in food waste reduction technology. Right. Is in this margin compressed world. Does flawless in sport execution become the single biggest lever brand still control or is there more to this?
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B
Yeah, I mean I think that like you said, I mean with the current economic pressures, particularly when we're talking about like grocery retail, which is where like a lot of our customers are operating, I mean executing programs well both in store and online I think has become like table stakes just to stay in the game. It's something where you certainly have a lot of leverage that you can pull at that point of sale in retail. So having visibility into exactly what's going on there can really help to have a positive impact quickly in some of these, these tough economic conditions. I mean like some of the like consumer behavior trends that we've seen shifting and I'm not sure if you know, others that you guys talk to on the podcast or in the industry would be saying similar things but you know, a lot of a shift towards from a customer having like value seeking behaviors. Right. Like the price and promotional programs are potentially more important to that buyer than actually staying brand loyal. Right. Or the, the brand recognition itself. I mean we're seeing some stats where you know like over 80% of shoppers have modified their purchasing Behavior and more, more of a shift towards like private label or towards discount retailers or things like that. Another one was like stock up strategies as a shift towards that where wind government people, you know, Maybe roughly like 40% of shoppers will strategically bulk buy or stock up whenever they see items on sale that aren't necessarily perishable goods. You know, and so like that if you're running a promotion or something or you've got a price discount out there, a two for one, somebody goes in, sees that deal, likes the product, knows they're going to use it, forever, cleans you out, you know, then that becomes an out of stock issue for you that you want to be able to account for and optimize around. But really, you know, I guess in regards to some of the other trends that you mentioned around, you know, food waste for example, and reduction technologies, I think, you know, there's certainly also been a trend in with particularly I think younger generations, but across the board towards more like fresh and healthy type food options which you know, tend to be, have a shorter shelf life just because of the nature of what that product is. You know, what we've seen is a focus also around like loss prevention in addition to just like the shelf execution. But in some of the like larger retailers that we are working with from an image recognition standpoint, that's always been like their biggest focus area where their eyes light up. It's like, wow, we can have a serious impact on loss prevention if we are able to do this image recognition thing and look at out of stocks for categories like fresh produce or fresh meat and seafood, things like that that have a small shelf life so they know what should be there and what should be present. So if they can do a quick scan of that shelf and say oh yeah, these things are out, but we see that we have them in the back stock. Like there's, there's an action immediately to take because the longer it sits not on the shelf in the back, the shorter that shelf life is just sitting there without even anybody having the opportunity to buy it. Yeah, I mean those are some, some of the interesting things I think that we're seeing from like a benefit standpoint. But it's really cool. Like the technology now has advanced to a point where you know, like our image recognition can tell the difference between like a, a bin of parsley and a bin of cilantro on a shelf in grocery. And like I can't even do that myself, like and I gotta really look closely and read the label. Right. You know, so it's it's cool. As the technology continues to advance, there's a bunch of different applications in categories that five years ago we didn't think we'd be operating in. But really I think like all of these trends and the technology continuing to get better and better make it really imperative for both brands and retailers to focus on that flawless like in store execution and that's really where like form tracks and our combined technology stack come into the equation.
- [28:21]
D
Of course we talked about tariffs, we talked about trends in the industry, we've talked GLP1, we've talked about food waste reduction technologies, margin compress world. We then jumped into how savings is the name of the game today, especially price and promo. Obviously shelf technology can help with all of that but I want to jump to running the business every day. David and when the merger was announced you said something in simple English dashboards don't sell products. It's the actions, the decisions, the follow through do the actual execution. The R industry historically has not been good at following through with the execution so creating a massive execution gap brands get a dashboard. First of all the data is outdated because of the nine day lag. It will show critical out of stock but you can't really have a workload in place with a nine day lag to fix it at the moment. How does your or tracks as AI powered image recognition directly with forms mobile task management close that gap between identifica and issue and saying I can take an action on it now and actually fix this before our promo runs out.
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A
Well first of all Jeff, I want to say that if you invite me for dinner I'm hoping that you're using technology to figure out if it's cilantro or parsley because I want to make sure we get the we get the recipe right.
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D
It's interesting David that he chose that example because being being from a Southeast Asian origin use cilantro in a lot of cooking and one of the biggest struggles I have when I'm in the store, when I go in store to buy produce, is identifying the difference between cilantro and parsley and retailers don't merchandise it. Well yes, I can relate to that Jeff. No matter who makes one of you, it's a problem I deal with all the time when I'm in store and
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A
I'm starting with people.
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B
I can get you a link. I was just saying we can get you a link to the mobile app for the next time you're out there.
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A
Yeah, we can make you a user shree but no thank you for the question. It's interesting without being hyperbolic the way we think about this, the nature of sort of in store conditions data is this industry could be at a point of inflection almost as significant as when electronic point of sale data became sort of ubiquitous. And when you think about what that meant to the industry, it meant, oh, now we can do perpetual inventory, now we can do computer assisted ordering. And so in a way the modern supply chain is an outcome of that sort of development in retail. And if you think about today, now, what, what Jeff and I are talking about, retailers and manufacturers can now essentially have access to a similar but extended data asset that describes what are the conditions in store. They can do that on a continuous basis. And in order to, to sort of solve the problem that you're talking about, which is how do I go from hey, I got a bunch of problems to now I've solved those problems and I'm seeing the benefits show up in my, in my scan data right at the register. You really have to be mindful and thoughtful about sort of plumbing data into the fabric of the business in all the places where those impacts can be realized. So the sort of simplest example is just doing it right there in the store. So if you're a retailer or if you're a DSD operator or someone with a direct retail team, the beauty of the technology that we're talking about is that literally as you're standing in front of the shelf and interacting with it using a mobile app, it will tell you essentially, hey, thanks for scanning the shelf. Here's the things that are incorrect and here's how to make it right. Whether it's achieving my merchandising principles of success or getting better aligned with the planogram, you can be very clear and not have to have that cliff board example that Jeff gave earlier of sort of, you know, trying to understand across a complicated, you know, 40 foot snack set what's wrong and what's right and what do I need from the back room. So just making that a lot more seamless is much easier with, with technology. So that's sort of the most, the most basic example. But, but not all problems can be fixed at the store level. So if you think about things like, you know, distribution voids for things that are, that are century centrally programmed, we have to create pathways for the same data that we're talking about to flow up into and inform trade planning tools, supply chain tools, enterprise level systems, because decisions that are, that need to be made oftentimes can happen at the headquarter level to influence things that actually show up in the store. So it's not just, you know, solving a problem because I've got backstock or I didn't get a display built, but actually leveraging that data to. To inform people in different places in the company that can actually have impacts on those. So it's, it's kind of all the above.
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E
Fabulous. Now the form team has been very vocal recently about how creator led and celebrity founded brands aren't just changing marketing. They're actually completely rewriting how disruption shows up on the physical shelf. By the way, can you be a celebrity today without having your own tequila, gin or rum brand? I don't think you can.
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D
Wait a minute, Peter. Are you saying the Raj family needs to have its own set of brands?
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E
If you guys actually drank alcohol, I would recommend that. But since you don't got beauty and skin care, that's a different story.
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A
Totally a possibility.
- [33:41]
E
Absolutely. But I guess here's my question. What new unique execution challenges do traditional CPGs face when they're now competing with the speed and the most importantly emotional connection of these newer challenger brands?
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A
Yeah, this is one of my favorite topics. I find this fascinating both to the point that Shree was.
- [34:04]
D
I'll tell you something, David. We've been talking about a bunch of trends. This one is a little bit more profoundly impacting cpg because large CPG doesn't like this and the reason they don't like it is it outsources the creative to a third party and PR doesn't get to control the narrative. And all the risk mentality that the no risk mentality that large CPG has. When you get into social and creator led, you cannot really control it. So we're super curious in hearing your viewpoint on this speakerphone.
- [34:38]
A
Super interesting sree and it's one of my favorite topics to discuss. I actually spoke about this recently at an event in Europe with one of our clients in the liquor industry where this is probably the most visible. And I think the dynamics are such that a, the creator brands, especially with real star power, have the ability to show up and grow faster than traditional consumer brands. So when, when a big, when a big multinational launches a brand, they put a bunch of marketing muscle behind it. And that marketing muscle with traditional channels is just no match for the celebrity endorsers, the social media, you know, things going viral, all of those contributors drive growth in a way that I think is really challenging for traditional brands. They're responding to that maybe in a couple of ways. Most clearly they're acquiring those brands, right. So we've seen lots of examples of, you know, Casamigos, Aviator Gin Teremana from the Rock. So in the liquor space, you know, very commonly that, that's been the response. Same thing with energy in the beauty side, which you were joking about. But this, this probably is a real opportunity for your family. I think it's maybe been less about, you know, acquiring to, to, to, to capture that growth. I think we're seeing the, the more traditional players try and compete by hiring more spokespeople, which has always been the strategy, but trying to adopt some of that same playbook with social media and sort of influencer driven marketing. All of that being said, you know,
- [36:13]
D
David, Peter and I had an opportunity at Cagney. We were down about a month ago in Orlando watching some of the largest CPG brands in the world. We had a chance to actually see l' Oreal bring that to life. They're one of the best at this.
- [36:27]
A
Mm, that's amazing. Yeah, it's, it's incredible. And it, it kind of goes back to what we talked about a minute ago. If, if you just say, you know, th, this problem statement exists alongside the problem statement of GLP1, alongside the problem statement of 0.0 in alcohol. The common underlying theme is things move quickly. And so the more that my company or my CPG manufacturer clients can have access to information on a real time basis, it allows them to increase the agility by which they better understand the market dynamic and can respond to it. And that's really the key to this same challenge as well. Could these big liquor companies who have been acquiring celebrity brands, creator brands, maybe they could have bought them a lot cheaper if they had seen them coming sooner before they gained the kind of market share that they did. And that's the sort of opportunity that I think exists in the market, whether you're in the beauty space or in adult Bev or another segment. Because we're not, we're not seeing the end of this. I mean, Mister, Mr. Beast Bar, as you guys have probably seen his products, right? He's starting to show up in the kind of meal replacement space. And so I'm guessing there won't be a section of the store that doesn't experience some disruption driven by these type of creator brands in the next few years.
- [37:50]
D
All right, David, you pointed out before that despite massive focus on E commerce alone over the last few years, the vast majority of retail sales, 80 plus percent still happen in physical stores. It's a discussion on the Consulting side I have every day with retail. However, because of e commerce shoppers can now walk into those stores expecting a seamless, high availability experience. How does leveraging AI and then granular SKU level shelf intelligence help brands manage their physical presence with the same precision and responsiveness as their digital storefronts?
- [38:26]
A
Yeah, this is exactly the issue, David.
- [38:29]
D
I want to piggyback one other thing to that question, right? So at first let's talk about leveraging what you have to actually have the same responsiveness as a digital storefronts in the in store model. The second thing is I'd love for you to highlight upon when you ignore trends like the e commerce trend was largely ignored by retail outside of the big big guys like Walmart, Kruger and maybe Amazon who did it perfectly. I really want retail, especially the super regionals, to listen to your message here. What would be your big message to them?
- [39:06]
A
Okay, excellent. That's a tall order. You're putting me on a pedestal. But I, I will take the challenge. The first thing I would say is expectations have never been higher and we've trained shoppers and when I say we, I mean Amazon has trained shoppers.
- [39:22]
E
Right.
- [39:22]
A
Everybody has a very familiar e commerce experience. They understand the motion. And when you think about what that offers you as a shopper, it's things that are really basic but really powerful. So when you go to Amazon and you're looking for a product, the first thing you're going to do is search and then you're going to probably filter and then you're going to sort and you're going to find something that meets your needs, that has good reviews and you're going to feel very comfortable making that purchase decision. And that's really hard to do in physical retail, or at least it used to be. And when you think about where this is all going and the opportunity that retailers have that are, that are operating physical stores, it's really to extend the power of that sort of e commerce experience into the store by leveraging smart technology. So let me just give you an example of what that can look like. And this is technology that's real today using image recognition that Jeff and his team have built. So imagine instead of being a CPG rep, I'm a shopper and I've got that same kind of computer vision smarts on my phone and I want to stand in front of let's say the beer set and I'm going to ask my phone, hey, help me find a beer that is brewed here in Colorado where I live and it's gluten free because my mom's coming over and she's
- [40:36]
E
got a gluten problem.
- [40:37]
A
And I can actually hold up my phone and through my augmented reality lens, my phone is recognizing all the products on the shelf because that's what image recognition does. But then further, it's going to apply my filter and it's going to highlight and put a box around all the products that meet the need that I've just described to my technology device. So very much like my Amazon online experience. Now I'm doing that, I'm in the store and it's a real time engagement with the shelf on top of that. It can then show me reviews from whatever, you know, user generated content exists out there so I can make a purchase decision. I've also created a really interesting engagement
- [41:15]
E
moment for the retailer and for the brand.
- [41:18]
A
So now I know that maybe Peter is standing in front of the shelf,
- [41:21]
E
maybe it's not me.
- [41:22]
A
And he wants to buy beer. We know exactly what kind of beer
- [41:25]
E
he wants to buy.
- [41:26]
A
We can communicate in real time. If you think about sort of how does retail media play into this? We know that one of the manufacturers has a product that exactly meets his need. He's probably not in their purchase history. Would you like to market right now to Peter in this moment of truth at the shelf? So the whole experience can really come together powered by the kind of technology that we're talking about. And I think that is not every shopper, but what a lot of shoppers are really going to value as they make that difficult, you know, trip to the store and throw the kids in the back and do all that. Putting this kind of technology in their hands is going to really make that experience richer and more rewarding for shoppers and a lot more sticky for retailers. To answer the second part of your question, when you think about the super regional guys, there's a leapfrog opportunity here because all of what I just described doesn't exist at Walmart, it doesn't exist at Target, it doesn't exist anywhere. Yet today, sometimes being smaller can be an advantage because you can move faster. And so I think the message for the super regional guys is where's the opportunity to innovate here and sort of do something that is fundamentally different than what we're seeing in the big national grocers? And is there an opportunity to do that in a way that helps protect your customers, your shoppers, and make sure that they're not looking for alternatives when they get in the car and throw the Kids in the back, that's, that's sort of what I would offer to them.
- [42:49]
E
Sri.
- [42:50]
D
Well said. Well said indeed. Over to you, Peter.
- [42:53]
E
All right, gentlemen, we, we like to close our episodes out by looking into the proverbial crystal ball virtuals that might be in our case. If I'm thinking out about five years. I guess my question is will investors value CPG companies less on historical brand awareness equity and more on the execution, intelligence and data matur that they demonstrate in their business operations? I mean if two brands I guess have equal product quality and trade support, does the one with superior image recognition driven visibility, are they going to be the winners in with everything else being equal? David, you first.
- [43:36]
A
Yeah, I would love to claim that, Peter. I think that that might be a bit hyperbolic. However, if you, if you look at it just on a fundamental basis, investors are looking for growth, right? They value the brands that have the most headroom for growth. And so I think there's an argument to make that growth potential is not just a function of brand equity and the portfolio. It's really going to be a function of what manufacturers have a proven ability to execute at scale and do it consistently and meet shopper expectations. And retail execution clearly is a part of that and the platform that Jeff and I are talking about is also a big part of that. So I think there's a role to play and I think that execution is absolutely a critical factor in sort of proving out that headroom for growth.
- [44:24]
B
I was going to say something similar like would also love if this image recognition data was the solution that kind of was I guess the five year out crystal ball. But I think it's really about all of the different data sources and how they're going to be working with this data. This is definitely a critical input for making these, these big decisions. But like, as we've been talking about, we really see this as an essential component to being able to like grow, share and ultimately win in retail is getting a read on exactly what's going on in the store but also tying that in with all of your other campaigns whether it's, you know, E commerce or the other data sources that you have in your organization. So yeah, I mean really it's, you know, that we've, we've seen it previously too where you know, certain brands can stand out from others even if they might be a little bit smaller or not quite as well known but become the category captains and who are the ones that are actually making recommendations and, and helping set the planograms and Things like that because they, they have the data and they have the expertise to say, hey to the retailer, we're a partner. We know all this information. We know that if you move this thing here and we set this here and you allocate this amount of shares based to our products that we' both going to benefit from higher sell through. I think it falls in line with that same. Same trend is like, you know, just becoming. Staying up to date with the latest data, data, trends and everything and being savvy about how you're making decisions is going to be valuable to investors, I think in the long run.
- [45:57]
D
No debate about that, gentlemen. So let me remind our listeners, you can find all of our content by simply going to a web browser and you can type cpguys.com that easy is the URL. If you or someone you know is something to contribute to this ongoing discussion on the CPG guys, drop us a line at contactpguys.com to our audience of over 43,000 plus LinkedIn followers, all organic, I may point out. Thank you for the clicks, likes, comments, direct messages, meeting us at trade shows, coming to our events, doing dinners with us, recording episodes with us, and of course to our sponsors. We're always grateful for you. The show doesn't exist without all of you as one big family. You work with us all year and we're grateful to have you as your audience and partners. Thank you. Peter, what's your big takeaway today?
- [46:40]
E
All right, the erstwhile gourmand in me wants to talk more about the cilantro and flat leaf Italian parsley differentiation. But zooming out, just the fact that there are so many applications to image recognition, both from the standpoint of brands finding bigger trends to understanding what the conditions are at retail, which we know in groceries where 90% of sales are still occurring, right, that's a big deal. But it's also about the consumer experience, right? Me as a consumer being able to take my phone out, focus on the shelf, and be able to quickly identify the products that are relevant to me. There's just so much value. It seems like Forma's tapping into some really powerful capabilities that are going to fundamentally improve how brands connect with consumers and how consumers can be receptive to all sorts of products that are retail. I'm really excited about this. It's a great conversation.
- [47:36]
A
Thanks so much for having us. Really enjoy the conversation.
- [47:39]
B
Yeah, yeah, it's been great. Thanks a lot for, for having us on, guys.
- [47:43]
D
Thank you, gentlemen. Thank you, Peter. That's a wrap of this episode of the CPG Guys.
- [48:00]
C
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