Ep. 14 - Beyond the Dashboard: How Data & Analytics Are Powering the Next Generation of Retail

Retail is drowning in data and still missing the moment to act. Scott Benedict sits down with Lee Kallman, Chief Commercial Officer at RD Solutions, to unpack what changed in retail analytics over the last decade and why “access to everything” can create more confusion than clarity if teams cannot operationalize it.

We get specific about where value actually shows up: competitive intelligence that improves pricing and assortment, better item matching and data governance that makes comparisons trustworthy, and a stronger understanding of who the shopper’s real competitors are when baskets get split across multiple retailers. Lee also shares how brands can walk into buyer meetings with marketplace intelligence that goes beyond “here’s my product,” using category context, promotions, and even ratings and reviews to build a sharper collaboration.

Private label and omnichannel retail add new pressure. We dig into the data behind store brand trial, why small price gaps can drive switching, and how quality perception changes the playbook for national brands and challenger brands alike. Then we tackle omnichannel integration, loyalty identity, and the messy realities of third-party platforms like Instacart and other marketplaces where pricing, promotions, and MAP policies can drift away from a retailer’s intent.

Finally, we look ahead at AI in retail, real-time decisioning, and what has to change operationally to keep up, from legacy systems to electronic shelf tags and faster store execution. If you care about retail data analytics, omnichannel strategy, pricing strategy, and turning insight into action, this one will sharpen your thinking. Subscribe, share with a teammate, and leave a review, then tell us: what is the hardest part of making data actionable in your organization?

Transcript

Welcome Why Retail Runs On Data

SPEAKER_01 0:08

Well, hello everyone, and welcome back to the Digital Front Door. I'm Scott Benedict. Today we want to explore something that I think we've been tracking is one of the most critical, and I think one of the fastest evolving aspects of retail, and that is the power of data and analytics. In an omnichannel world, data really drives everything from pricing to promotions to assortment decisions, even how quickly products move from the shelf to the shopper's cart. But many organizations really still kind of struggle to turn insight that comes out of data into action. To help us kind of impact or unpack this topic, I'm joined by Lee Kalman. Lee is the chief commercial officer at RD Solutions, a company that was redefining how data becomes execution in the world of retail. The great thing about having Lee here is he brings more than 30 years of experience across analytics, marketing, retail operations. And he's really, he and his company have helped both retailers and consumer brands transform billions of data points into smarter decisions and better performance. So, Lee, it's so exciting to have you here. Thanks for joining us. Thank you. All right. Well, so one of the things I wanted to kind of start off by asking you is that, you know, you've been at the center of retail data and the revolution of how data is used for a long time. And I'm kind of curious, from your perspective, how has the industry's use of data evolved maybe over the last decade or so? And what's really driving some of the acceleration that we're seeing in how data is being used, both by brands and by retailers today.

SPEAKER_02 1:58

Yeah, that's a great place to start. I mean, I think the fundamental thing over the last decade is just the ease of access to data. Yeah. Right. We're in the competitive intelligence space. Um, 10 years ago, the internet didn't exist from a grocery perspective.

SPEAKER_01 2:14

Indeed.

SPEAKER_02 2:14

Um, I have to I often, you know, say, I finally get to clarify that. Cause usually I'll say e-commerce didn't exist in the domain we're we're playing out. Oh no, e-commerce existed, not in grocery, right? Yeah. Um, and so all the data that we were collecting 10 years ago was by our field team going in stored and collecting data. Right. So there was all sorts of sample, every client had a different sampling methodology to get to the data that they wanted. Um, and so, you know, our big our biggest clients 10 years ago are getting, you know, we're we're what they're getting today, our smallest clients are getting many factors of that more because of the availability of data online. Yeah. Um, so you know, instead of having to say, I'm gonna, I'm gonna sample these stores, then I'm gonna explode those prices out to this geography, it's reasonable to get all the data. Right. Um, and so, you know, so on one hand, you've got this this accessibility and access to virtually every data point you would ever want. Yes. Now, the flip side of that is is what do you do with it? Right. Um, but you know, in the last 10 years, that's certainly been the biggest, the biggest component. And I think we're we're kind of at this inflection point now of as folks are starting to be able to really use a lot more of that. Because for a lot of years, what we're finding is clients were getting web data, but they were basically then parsing it down to fit within the box that they created when they were getting in-store data. And so we're we're kind of at a turning point there.

SPEAKER_01 3:42

No, and and that makes sense. And it seems like we we had more data about what was happening online than we had about in-store. And certainly the interplay between the two uh was very siloed. And I think we've seen that kind of evolve uh in the last year, last few years to where it not only does it help you understand what has happened, but uh I get the impression it's gonna at some point start to help you predict what's going to happen in the future. And I don't know if you guys touch on that, but is that something you see maybe coming down the road?

SPEAKER_02 4:17

Yeah, I mean, it's it's all I mean, you know, predictive analytics is is is a slightly more sophisticated way of thinking about trend data. Right. Right. So the more historical data you have, you can identify trends, and that starts to sort of drive what's what what might happen or what's likely to happen in the in the future as as AI and all these other technologies becomes more robust and more more more central to kind of a retailer operation, I think that will further accentuate what can be done there. That's kind of what I meant by that inflection point.

The Gap Between Insight And Action

SPEAKER_01 4:48

Yeah, no, I think that makes sense. And one of the things I noticed, uh spending some time in your roadside is that one of your marketing taglines is this concept of turning insight into action. And that really spoke to me because one of the things that concerns me as a former merchant uh is that uh the goal of more data is not to win a trivial pursuit. It's to turn data into some sort of sort of action. I'm I'm curious, where do you see maybe some of the biggest gaps between collecting data and actually executing upon what the numbers tell us in and how do leading retailers maybe operationalize analytics in store as well as online?

SPEAKER_02 5:28

Yeah, so well, I'll talk to that both from kind of a retailer perspective and and a brand. I think from a from a retailer perspective, you know, part of making that data actionable is sort of that foundational data management, data governance you bring to it. It's not the sexy stuff, it's not what people love to talk about. Right. But without that, you don't have any, and especially as private label um only increases in the percentage of the assortment, right? Having UPCs to sort of drive your data connectivity isn't the most reliable. And then you think about the web where there's not a lot of, there's not UPCs on a lot of sites. So you've got to have mechanisms to say these I these are the items I'm gonna compare. Um and we start bringing in club stores, now you've got different pack sizes. Yeah. So there's a lot of that nuance to it. And so it's it's an area we've got technology and tools as well as methodologies and processes that that are a lot of our clients use. Um either we're managing that for them, or in some cases we're sort of providing a framework that they're managing that internally. Um it's always in partnership because there's a lot of subjectivity when it comes to is does this item go with that item? Um, I always talk when we talk about that with clients, always this line of to the effect of, you know, whenever we've shown sort of similar items to clients, if we have 10 clients in the room, we'll get, you know, nine to eleven different answers as to what's the right answer. Right. And and that's kind of the point is there's not one answer.

SPEAKER_00 6:59

Yeah.

SPEAKER_02 6:59

So it it certainly that area for them to figure that out.

SPEAKER_01 7:03

Now, and that kind of uh brings me to uh more specifically a retailer's point of view, having been one for most of my career, and and we obviously we operate now in an environment of there's rising costs, tighter margins, shoppers' behavior, consumer shopping behavior is becoming more omnichannel, is influenced a lot by a lot of different things. How do you think retailers uh that that you work with uh make the best use of data to drive smarter decisions? And I realize that's probably a big question because it depends on the functional area. You're talking mind of marketing to supply chain. Where are we maybe seeing data make the biggest impacts uh in in different functional areas across uh the clients that you work with?

SPEAKER_02 7:52

Yeah, a lot of so from a retailer perspective, a lot of the data that we're providing um it's it's going into pricing, it's going into the merchandising team. So you kind of price and assortment from a competitive perspective. And and you know, as you said, there's there's more noise in the marketplace today than than probably, well, certainly than ever has been. Um and so what that means is you go back just a few years, you know, if I'm if I'm a retailer, I've got real clarity as to who I'm really competing with. Right. In today's world, you might have that one main competitor, but when you look at the way consumers are shopping and just the way the baskets are being broken up, yeah, I I might be shopping four different places. And and it's not just if if I shop, you know, if I shop at a at a um at a low price provider, I might be also shopping at a high higher kind of perceived quality of Whole Foods. Yeah. So like we retailers didn't think that way years ago. And so is this if you shopped at a at a Walmart, maybe you shopped at an Aldi, but you're not also shopping at a Publix or a Whole Foods. Right. And so like all those rules are kind of out the window right now, yeah. Which, you know, is good for us because it means you need a lot of that data. Yes. Um, but it also creates a lot of chaos. And so, you know, it it it's it's I think the retailers that are doing a good job sort of breaking through that have some degree of of clarity in terms of what their strategy is, who they who they're trying to be. Um, because you if you try to respond to every signal in the marketplace, yeah, you're gonna be all over the place.

Brands Bringing Smarter Category Stories

SPEAKER_01 9:24

Yeah. So it feels like not just the data itself, but the context of that data is is probably how sort of decisions are made, whether you're a retailer or a consumer brand, I would, I would think, right? Yeah. Yeah. Yeah. Yeah. And it's it's interesting because a lot of our listeners either represent consumer brands or their broker partners. And for them, I think the real question, and I come at this from the perspective of a former buyer having brands sit in front of me and wanting them to be the most informed in terms of what they're trying to sell me and what insights are driving that. How do you think brands can leverage analytics to build a stronger relationship with with their merchants, uh, with their retail partners, really letting data drive some of those those conversations? Because it feels like in areas of collaboration, we're we're a long way from the peddler coming in to sell the buyer with here's this product, how many would you like, to a very different kind of collaborative relationship. Yeah. What do you think what are maybe some of the best practices you see?

SPEAKER_02 10:29

We're we're seeing some some of our brand partners having some really good breakthroughs when it comes to going into those meetings with a really broad understanding of the of the marketplace in general. Yes. So it's not just here's my product, here's who I am, here's all the great things I'm gonna do for you, but showing that you have a real understanding of the category as it relates to that retailer, where you might fit in, how you're different from what they already have. Yes. Um, and so that's a component. I mean, we deal in first party data, then all the third party data that we collect. And so it's within that third party data, um, we kind of look at that as marketplace intelligence, yeah, that we can provide, you know, what what are the other items in the category, the the whole, the broader category, even going at a department level sometimes.

SPEAKER_00 11:14

Yeah.

SPEAKER_02 11:14

Um, what's most comparable to what I have? Where are the price points on that? How they promote it. Yes. Even getting into ratings and reviews, so you kind of get a sense of what's popular, what's not. Yes. So it's it's that, it's, it's, it's, it's the old, right, instead of just going in and talking about myself, I'm gonna go in and talk about kind of the whole environment.

Private Label Quality Changes The Game

SPEAKER_01 11:32

That and I'll tell you, that's one of the things I loved as a buyer was a supplier coming in with data facts and insights that built upon what I already understood and really challenged me to make better decisions. So I I love seeing that in my impression, and part of why I I thought you had an interesting perspective is it feels like we're living in a bit of a different world uh on that, where that data is not nice to have. Yeah, it's a it's a need to have. And and so one of the things I was gonna ask you about was I I know that you and your team recently published some data that showed that about 86% of US shoppers have switched or at least tried some private label items. I think the pandemic may have driven some of that. Inflation has driven some of that.

SPEAKER_02 12:19

Yeah, I think I think the pandemic brought a lot of that, and and it was because of price sensitivity, but also just items being out of stock. Yes. So I'm gonna so I'm gonna get what I can get, and then those habits have have come forward. Yeah. And so, yeah, I mean, pricing has always been a key driver, a key differentiator between the store brand and the private label. And you know, not surprising. You know, we we did a follow-up study recently on that. Um, 89% of consumers said they'd make they'd switch to a store brand if I could save 20%. Like that's not surprising, but then 56% said they'd save if it they would switch if they save 5%. Right. So it doesn't need to be a big, a big savings to make that switch. Right. What's relatively new over thinking of the last couple of years um is where the quality comes in. Right. So 64% of consumers said that they perceive store brands to be as good, if not better, than the national brand. Right. Um, and when you look at the the what's going on in the marketplace, and um, you know, Walmart's better goods brand is a great example of that. And um, you know, Unify and their wild harvest, it's you know, people are moving away from the store brands being the store name.

SPEAKER_01 13:32

Yes.

SPEAKER_02 13:33

Um, and that's obviously very intentional because I want to build a brand beyond the store, but you're only gonna get that brand here. Yeah. Um, and you know, the they've there's retailers have had a lot of success with that. Um, you know, it's interesting. I I gave a talk at a conference, a grocery conference a few weeks ago on store brands, and all the people wanting to talk to me afterwards were brands. It wasn't retailers. And it's a relatively recent thing that we've seen of sort of this, okay. I need to understand that. And so we're doing a lot of work to sort of understand just what are those, what are the items in my category? What are the what are the price variances between my item, between the national brand and the store brand? So it, you know, it all comes back to having visibility to what's going on in the marketplace.

SPEAKER_01 14:20

And it feels like that that that's made uh the marketplace perhaps even better because now those those private label brands were originally felt like were conceived of just as to hit a lower price point or an improve the retailer's margin or both. Right. And now it's a much more thoughtfully arrived at data-driven decision as to where you insert a private brand. In some cases, to your point, uh, Walmart's better is a great example where you have a private brand that's an upscale or an upmarket solution, not just a lower price or an entry-level price point solution.

SPEAKER_02 14:57

Yeah. And you know, the other, the other curveball kind of being thrown into that are all the emerging brands um that that exist. And so it it creates this noise of I think from a lot of perspective, consumers don't necessarily is it a store brand, is it a national brand? I don't know that most consumers really care at all. Um, it's just a brand. I like the item. Yeah. Um, but there's, you know, there's more of these challenger brands on the shelves than ever before. Yeah. Um, and they're all, I think, taking advantage of, you know, a lot of the big CPGs have gotten really big. Yes. And as a result of that, they, you know, the bigger you are, the slower you move, and therefore you're not very nimble. Right. And that's created this white space for the retailers to kind of fill the void of what consumers are looking for. And that's obviously where a lot of um a lot of these challenger brands are coming from as well.

Omnichannel Identity Instacart And Control

SPEAKER_01 15:46

You know, it's interesting you mentioned that because one of the things I I heard at a conference, uh someone giving advice to challenger brands is that you don't go in and sit in front of a buyer thinking that you're going to knock out tide in laundry detergent. You're not going to talk. It's can you use data to show the buyer that you're you're providing incrementality, that that you've got additional sales that you wouldn't have gotten if that challenger brand wasn't there on the on the shelf. My point here is that it's data is informing those decisions, both for the for the challenger brand making the argument to the buyer as to why I I want to be carried, and for read uh for buyers to make good decisions off of and and the the common theme there is the data and the insights that come from it that maybe nobody was looking at previously, right? Yeah, no, that's that's that's spot on. Yeah. So one of the things I want to talk about is is the evolution of Omnichannel, which is not a new concept. What's really been interesting to me is is we've gone from very siloed uh data and and and and information to a more integrated view of the uh of the consumer. And I and I say that with a little trepidation because not every retailer has connected this customer A is this person online and this person in the store, and that and that you have a full holistic view of a of a shopper. And I'm curious how retailers and brands are kind of tackling the challenge of of integrating data sets between online and store to where they can understand consumers' behavior. Someone searching online but goes and walks into a store and buys it, but that's the same customer interaction. It just feels like connecting data into a full holistic view of a customer is still somewhat early days in a lot of retailers because the consumers are shopping differently, and retailers have just figured out how to put that data together into a holistic view.

SPEAKER_02 17:57

I think very early days. I mean, you know, the the consumers light years ahead of where everybody else is in this because a consumer doesn't think in terms of I'm gonna buy you know in-store online, they're not they don't think omnichannel, they think I'm shopping. Yes. Um, 90% of consumers now are shopping across both channels. Right. What's interesting is those consumers tend to spend one and a half times the amount that somebody that shops in a single so like consumers are are doing it. It's like they they've adopted it, um, they're off and running with it. On I think on the retail side, it's it's a little bit slower. I mean, you know, it's use the word siloed, and that's very much what we've historically seen. I think some of our um some of our more uh innovative clients are starting to sort of look at things much more holistically. Um, you know, I think what what we see a lot of times is where omnichannel is mostly thought about within retail is at the you know the C level of the organization, because you have to get that high because a lot of organizations, you've got pricing, you got separate pricing teams, you've got separate merchandising teams, yeah, and they don't really come together. Um so that's not yet not yet. And and it's it's a challenge. And I think in a lot of cases, they're trying to figure out how do you do that. And you know, ultimately it's you know, I mean Instacart's an interesting component in in this part of the discussion because you know, a lot of retailers jumped at Instacart kind of early days of COVID because they needed an e-commerce solution. Yeah. And, you know, and and what they then learned was, well, I've most have learned is I've lost control of my brand. Um, you know, and it's you know, both in terms of sort of the the uh promotional promises, the brand promises, pricing strategies. Um, you know, you see, you see all sorts of things on these third-party sites where you know they're doing deals directly with CPGs, and it might be the exact same deal across, you know, the same promotion that will be on a, you know, at one point when Walmart was all was on Instacart, there was a you know, buy one, get one offer for a Walmart for on Walmart through Instacart. Yes, on um a couple other retailers, none of which that was part of their promotional strategy. Um, what you've seen in in the last few years is Instacart adapting to that. And there's now you you can sort of just use Instacart for the back end. So they're taking control of their brand, but but it's still, I mean, I was I was with a retailer a couple weeks ago that Instacart is their e-commerce strategy, and they're priced 20% higher on Instacart than in store. Yikes. And in their their minds, well, that's Instacart. Yeah. And and but nobody shop, nobody thinks they're shopping at Instacart. Instacart's who's delivering it. Yes. But I'm shopping at this retailer. So still your brand. Yeah, so consumer, right? So it'll that's there's a whole thing to be played out there that'll be really interesting. But I think retailers have a have a long way to um there's still some evolution to be done there to truly look at that because you you can do things online. I mean, there's a lot of interesting things going on from a promotion perspective that you can do online that you can't do in store. And so obviously, all the you know, highly custom offers, um, you can execute that online in a different way. Um, there's some really innovative the um Walmart's Walmart Cash program is a really interesting program. Um, you can't really execute something like that in store. And so you're gonna have some differences. It's not that everything's going to be the same. And I've long maintained that you know there's different value propositions across different channels. Um, you know, way back when, when, you know, in the early days of Web Van, um I it was right, my daughter was was born, and so we started using Web Van. I lived in Atlanta at the time. I wasn't worried about how much more I was paying. I was paying because I didn't have to take a little infant into the store. It was the convenience. There's a value prop associated with that. And so there's there's some recognition of that across the board.

SPEAKER_00 22:05

Yeah.

SPEAKER_02 22:05

Um, you know, one of the interesting things when you when you talk about this from a a uh manufacturer's CPG perspective, you sort of then you start to get into all the third party marketplaces. Yes. Because that's there's most retailers aren't doing as good of a job as maybe they can be in moderating that. It's very much the Wild West. And so, you know, it ultimately, you know, it it it may it's not a good look for the brands when you have, you know, an item could be priced 40, 50, 60 percent higher through one of these marketplaces, or sometimes it's the other direction, leveler. Um, but you know, you're violating map policies and but um you know, so it it's but all this will as as time goes on, um, you know, I think eventually be dealt with. But these are these are a lot of the things we're talking to clients about and solving a lot of these problems for them.

SPEAKER_01 22:57

Well, one thing that occurs to me while you're talking, you know, when this this for this concept of omnichannel and of of consumer shopping across channels really uh broke into my consciousness was when I was with in the uh in the wholesale club industry when I was with Sam's Club, and the the great thing that we had there was the common denominator of of a of identifying a member uh was the member number translated across online purchases and and in club purchases. Today, beyond the club channel, uh it feels like either uh loyalty programs or uh pending card data is the two ways that you can connect a consumer's behavior online and offline and and then unlock that data to drive insights and and hopefully drive uh uh uh more connected promotional activity. Is that from your perspective, given what you do, is that kind of how a lot of retailers, when they finally realize, yeah, we should do that, that is that how they're connecting someone's online persona and in store persona?

SPEAKER_02 24:07

Yeah, I mean, there's a lot of third-party um applications that that sort of manage that. We where we get involved is is more we we start to look at at analysis of T log data to kind of look at item segmentation. So we're not so much getting into those kind of custom one-to-one offers or specific shopping behaviors of individuals. Um, but it's it's all these things and even even those lanes there within a lot of retailers, even that stuff siloed. You've got teams that are making that are digging deep into that and they have they have this breadth of information, but that's not necessarily always being used across over into pricing or even into a so I think you know that's a common theme, and and we're seeing, you know, I think lately we're seeing more and more um cross-organization um sharing of this information. Yeah. Um, because a lot of it's there, it just needs to be unlocked.

Fixing Store Problems In 72 Hours

SPEAKER_01 25:03

That that's the thing, particularly when I think about what you and your team do, that that's that's part of the guidance that I think you have that kind of agnostic perspective because you don't have a horse in the race. You want the retailer or the brand to be more successful. Yeah. And that's that's what your company does. But if they don't have the data connected somehow, it's hard to unlock all of that, particularly if it's siloed parts of the organization.

SPEAKER_02 25:27

Well, that it kind of hits the the core of a lot of what we do, and what's really unique is the ability to sort of take the data and make it actionable. We talk a lot about sort of this idea that you know, information without action just leads to anxiety. Um, but it's actually being able to connect the dots. And you know, one one uh relatively new example of something we've rolled out recently is on the brand side of things, is a platform where we're taking in third-party signals, first party signals, and using that to identify store issues. And then, oh, by the way, we've got a few thousand um employees in the field. So this idea that we can identify an out-of-stock issue, a potential phantory issue, whatever it might be, and within 72 hours have somebody in the store to solve that problem. That's awesome. So it's exciting. It cuts that down because I think what we've seen otherwise is best case scenario. I'm getting first party data, but I don't, I'm getting it and I'm dropping it into Excel and I'm doing some work and I hone in on some issues and I find the hundred stores that there's an issue going on. I now need to find somebody to go in these stores. Best case scenario, you're three, four, five weeks in. Yeah, you've got other problems at that point.

SPEAKER_01 26:42

You've moved on.

SPEAKER_02 26:43

So we've really cut that down. But that that taking the data and making it actionable is the big, big thing.

SPEAKER_01 26:49

Yeah. And that kind of leads me to the next question, which is really uh this concept of of what we affectionately call a data-driven culture about you know, connecting people and processes. And obviously, technology technology is a pretty critical component, but a culture where analytics drives outcomes, to your, to your point, is it feels like we're still emerging, still in early days in some cases. And is there any kind of recurring themes or things that you see or that you advise clients, hey, this is maybe some of the organizational or cultural shifts that you need to make to truly unlock the value of the data and the insights that are available to us that, you know, whether you're a retailer brand, you're not really putting it into action to point.

SPEAKER_02 27:37

Yeah, you know, I mean, I think from a company culture perspective, it's this idea that context is key. Yeah. So it's the people that are running, generating reports have an understanding of what the use case is. What am I actually trying to get to? Yeah. Um, you know, with the the the still the solution I mentioned before, we can monitor and go in store and fix things. There's all sorts of providers out there that are doing the first half. Right. And, you know, and and they talk about how they use AI and and all this stuff. And I was like, yeah, but they don't fix it. So, you know, again, it's like if if you can't resolve a problem, you're just giving me a problem. You're narrowing it down, perhaps. Yes. Um, so I think uh context is key. I mean, we we work with um, you know, some of the some of the top some of the teams that we work with that that seem to be really excelling and from a retailer perspective seem to be excelling. It's when the people that we're working with really do understand the use case of what they're trying to do because there's so much nuance to it. Right. You can it's easy to sling the data and and generate reports, but if you don't really know what you're looking for, what's the point?

AI Limits Legacy Systems Shelf Tags

SPEAKER_01 28:53

Exactly. I think that leads me into the to the last question I wanted to ask you. And and I'm gonna ask you to look forward a little bit over the course of the next few years and what what do you think retail analytics becomes? Obviously, uh we can't have a podcast without somehow the phrase artificial intelligence weaving in here. But between AI and real-time data and predictive modeling, uh can you can you foresee kind of moving forward? How does uh retail analytics change over the course of the next few years? And maybe as part of that, what what kind of expertise, what kind of training, what kind of skills do people need to be successful in a either if they're on that full time or if they're just leveraging data to do whatever their their job is in a in a retail business?

SPEAKER_02 29:45

It definitely feels that we're we're on this prefaces of real real shift of things. I mean, if you think about just from a pricing perspective, the the limiters to in today's today's world for most retailers are very real. And that is while I might have access to infinite data, I'm using legacy systems. Yes. Um, there's you know, there's still access databases and green screens actively being used across the retail universe. Um, and so you have you have that as a limiter. Yeah. And then the other limiter is all right, you want to make price changes. Well, in most cases, you still need a human being to print out a piece of paper and go put that on the shelf. Yeah. So, you know, and that's been that's been what sort of lagged a lot of this. Now, I think, you know, I've talked to a number of clients in the last, just even the last few weeks, and everybody's sort of saying that the ROI on electronic shelf tags finally is starting to make sense. Yeah. I think, you know, Walmart's announced that they're rolling that out. Yep. Um now, you know, it's easy to kind of then get caught up in the discussion of um, oh, you know, real-time pricing, it's gonna be like Amazon. But the reality of it is you can't, uh yeah, I'm not sure. I think we're we're there's a cultural component there. You can't the price of milk can't change from the time I put it in my basket to the time I get to the exactly. It's not a virtual uh uh uh uh shopping cart there. Right. Um, but could you know, could we be seeing more more change more price changes um overnight? I would think so. Because those are those are the limiters. I mean, I think we talk to most retailers, why do you mostly change price every week? Because that's the process and we've got enough resources to do that. So yeah, I think between that being a very real sort of limiter coupled with all these other technologies that will only get better um at taking all this data and helping make decisions, um, you know, I mean, it it's interesting. Uh, we you've you've been you've been in in this game to know that, you know, are merchants ready to sort of hand off the decision making to AI?

SPEAKER_01 31:49

Um I can assure you it's hard.

Key Takeaways And Subscribe

SPEAKER_02 31:52

Yeah, it's and and I and we've and I know there's some really strong solutions out there that have some really, really strong ROI statements, but there's still that that uh hurdle that that this is how they've always done things. And and I'm sure it that will start to kind of erode. Um, but those are those are the I think those are some of the key things to start that or why we'll start to see real change in some of these areas in the next few years and see a lot of accelerated um evolution, if you will.

SPEAKER_01 32:24

That's awesome. Well, it's been an outstanding conversation. I think you've kind of reminded us that data isn't just about visibility, it's it's also about velocity, the speed at which change needs to happen, perhaps faster than it has happened. Uh, and making good quality decisions based off of that data is something that uh really it's where retail is is headed and it's where the the winners in retail are not only those that can see what's happening right now, but can use uh data to inform kind of actions and what they're gonna go do next in a lot of different areas of the business. Great. Thank you so much. Uh it just feels like at the end of the day, retail is becoming a data business, powered by human decisions still, uh, but collaboration. So thank you, Lee, for for joining us. It's been wonderful to have you on and to kind of share these insights. Absolutely. Thanks for having me. You bet. For our listeners, uh, we hopefully you've found this uh this episode valuable. We hope you'll uh subscribe uh to our podcast and that you'll join us the next time on the digital front door. And I'm Scott Benedict. Thanks for watching.