Hi, Shelley Kohan here, Retail Unwrapped. I’m very excited. have Tim Robinson here with me, Senior Vice President of Commerce of Blue Yonder. Thank you. Yeah, very delighted to be here. I’m so excited because you’re here in person. Here in person. How rare is this? I know. I usually have all my podcasts that are virtual. So I’m so thrilled to you here I’m pleased to be in New York. It’s great. And the weather’s not bad. Weather’s not bad. Yeah, it’s a bit British. It is. very familiar. It’s a bit gray and damp, but no, very good. Yeah, you’re lucky. Last year was like a mess. Yeah.

So what I’d love to talk to you about today is so returns. Yeah, you got to talk about returns in January, right? Because that’s that’s a big problem for a lot of this is the sweet spot as they say So tell me a little bit about what you’re seeing out there and you know, what what’s different today? Then say a year ago holiday. And what do you what do you look for in the future? Yeah, so I mean, it’s a great question because I think returns, you know as a subject in retail supply chain is very hot

You know, so there’s a lot going on. There’s a lot of investment. There’s a lot of talk. And I think that’s because ultimately there is a lot of opportunity. There’s a lot of opportunity to do things better. I’d say the thing that’s changed the most for me is ⁓ there’s been a real shift in the last couple of years from ⁓ returns being a kind of customer service challenge, a customer experience thing. You know, if you’ve got to create great returns experiences so consumers continue to shop in your stores.

And whilst that remains very important, returns now are being seen as inventory, the thing that they are. These aren’t wasted items that you can’t resell. This is valuable inventory. definitely. Exactly, yeah. And so therefore, there’s been a real shift from how can I dispose of these returns as low cost as possible to how can I harness these returns, understand what I’ve got, get them back into stock, get them back out there for full price.

And so if you think about what that means from the supply chain and what that means from a, well, almost like philosophy, philosophical perspective, there’s, there’s a lot more to do ⁓ in order to, in order to resell a returning item at full price, but the industry has all the data. We have all the information. We have all the capabilities about just putting it in the right place. So this year we’ve seen much more widespread ⁓ use of kind of data, data science, analytics and AI.

as tools to manage your returns challenge. That’s amazing. Yeah. So I’m anxious to hear how that’s happening because I know that there’s a lot of consumer behaviors that don’t help the whole return scenario for retailers. Yeah. You know, bracketing, the ordering more sizes, the colors problem, size problems. There’s all kinds of reasons for returns. how can we work better as an industry?

to get those returns more manageable and are you now using AI? Yeah, definitely. So I would say as a first principle, the vast majority of returns exist for very good reason. Because in order for consumers to shop online and to have the best experience, you do want to try different sizes on, you want to try different colors, different fits and that sort of stuff. And so they do exist for a very good reason. I think there is a danger in the industry that we do, we end up talking too much about bracketing.

because it’s a tiny, tiny proportion. really is. I’m not saying you don’t have to address it, but it’s a tiny proportion. The vast majority of returns exist for very good reason because they drive up sales. They drive consumers to your online journals. when I think about what’s the consumer’s role in all of this, I think it’s about if we can give consumers better visibility of what’s going to happen to your returns.

and give them choices that allow them to behave in a way that reduces the impact of that return, then I am absolutely sure that we will see exponential change and exponential benefit. If you think about, you know, I’m old enough to come from a world where back in Europe, you didn’t have to wear a seatbelt. You know, it was your choice, you in the car. And of course, over time, that changed, legislation changed. But ultimately, it was societal.

shift. was, you know, you’re behaving poorly, you know, you’re being irresponsible if you don’t wear a seatbelt. And that shift happens. And how did it happen? Well, in Europe, it was through very overt campaigns and the spreading of information about what happens when you hit a car and you don’t have a seatbelt on. You know, it became very, very, very, it became sort of a big topic, much talked about. If you think about the return space.

you know, we might complain about, these consumers, you they buy four and return three. Don’t they know what’s going to happen to their returns? Well, no, they don’t. They rely on us to make sensible decisions and do sensible things to deal with their second life. So I do think like changing, giving more visibility to consumers about what might happen to this item. If you want to return an item, if you’re prepared to drop it at this location that allows us to put it in this, you know, it goes into a location where it’s going to be resold and maybe that’s free.

But if you don’t want to do that, that’s inconvenient. You want to drop a return this way, that’s actually going to cost us and our business money and you’re going to have to pay for it. But give visibility and transparency because it’s all there. The data’s all there. I love that. Well, first, I love the fact that your whole mindset is so different on returns. Like you actually feel like the customer should be able to try multiple things on. It’s part of the sales. That’s what drives the sales. Yeah, definitely. And I do think our industry is kind of like trying to figure out the all the

challenges with returns and trying to change consumer behavior. That’s not just that doesn’t work, right? No, no, not at all. I think we can influence consumers to modify their behavior, but the core behavior that creates this challenge is important. And it has been a huge driver of the growth of e-commerce over the last 20 years. And so, you know, if you weren’t able to return items.

free cheaply or for free or readily, then this industry would not have grown at the rate it’s grown and it would all look very different. This hall here at this trade show, the stands would look very different if e-commerce didn’t exist. And so we’re back to a day where it was all about point of sales and tills. So ⁓ we’ve got this great industry now built up on the back of changing consumer attitudes and demands and behavior. I think what we’ve got to do is we’ve got to rely on consumers to give us accurate information

the data we need in order to be able to do the right things with returns. It rely on them to behave differently when we provide the information. So if we provide information about this returns route is a more expensive, more impactful returns route. Let’s tell the consumers that that’s the case. If that’s what they need to do, then that’s fine because need is needs that exist. But let’s just give the information and then let’s do what we supply chain professionals should do, which is

use data to make sensible decisions to reduce our impact and increase our profits. It’s of no different in that regard. is. Let me ask you question. Are you seeing in terms of the consumers? I’ve read and seen a lot where consumers are making choices about where to shop based on return policies. Are you seeing that? Very much so. that’s a that’s a real trend. That’s a real trend. So we did a we did a survey recently of consumers across the US.

Australia, Asia Pac and Europe. And that was a resounding finding, you know, that nowadays one of the big drivers of not just where I’m going to shop once, but maybe loyalty, you where I’m going to repeat shop is down to the returns policies, how strict they are, you how many choices I’m given for returns drop off. Does it cost me? Doesn’t it cost me? All of those things are big factors in modern consumers deciding who they’re prepared to spend their money with.

⁓ And you know, I get it. I can see why. Because I think, ⁓ you know, the point we made earlier on, it is very much part of the experience now. It’s part of shopping online is being able to behave in this way. But also, I think it’s a trust thing. Definitely. Because it gives the consumer the sense that this retailer trusts me. They trust me that I’m not bracketing or they trust me that I’m you know, I’m not I’m not sort of just behaving badly. They trust me that this is what I need and therefore they’re going to react to it.

Yeah, it kind of does drive me a little crazy when retailers create policy around the exception. Yeah. Oh, it’s literally it’s it kills me. Yeah. Like designing a policy or a process or a system to deal with the 1 % or the minus 1 % of, you know, less than 1 % of consumers that might be trying to trying to break the system or fiddle the system or whatever it happens to be. It makes zero sense, really. Yeah. You know, because a lot of cost.

⁓ gets generated by creating this exceptional ⁓ process and system. And ultimately all it does is it switches off the 99 % of loyal, you know, well behaving customers. That’s right. And do you, does Blue Yonder do any work in terms of like fraudulent returns and minimize that? Yeah. So the great thing about the amount of data that we collect. So, you know, we have

hundreds, thousands of retailers that rely on our ⁓ various elements of our returns platform to deliver these experiences to consumers, the ones that we’ve just described. So we gather a huge amount of information and we see that. So we can track that information across like a single email address or a cohort of consumers in a particular geography maybe, or consumers buying particular SKUs and particular items. And you can see anomalies, you can see exceptions.

And actually you think when people are talking about return fraud, probably three or four years ago, the answer seemed to be cameras in shops, looking at the behavior of a single consumer, you know, and they’re all having to open every single return to see whether it is the thing, you know, I thought it was shoes, but it’s a brick, you know, The in practice, you don’t, that’s madness doing that. That is expensive. And it’s like, you know, as you described earlier, it’s a process to deal with this mind with the sub 1 %

of cases, the way you track it is through anomalies in the data. Because as consumers, we pretty much behave the same repeatedly, time and time and time and time again, often with multiple different retailers. So here in the US, for example, we power a very large returns drop off network for a major carrier. And we do the same in Australia, same in Japan, same in Europe for different partners. We can see changes in behavior patterns that highlight where these kind of

all what I call organized and curated fraudulent activity is taking place. You know, the odd one here or there, you know, may get missed, but in the round, fraud is detected through anomalies. And it’s the data that tells you that. So I have another question for you, and I hope I’m not putting you on your spot. But if you could tell me what is your ideal return scenario from a consumer perspective? Yeah, so.

Yeah, I think about this a lot. makes me, not the most popular guy at parties because this is like one of my favorite subjects, but I think about this a lot. What’s the panacea of returns management? And I think it actually comes down to both the customer experience, but also the what next, the so what. So I feel like for most consumers, we know that

We’ve got a very good idea which items are likely to be returned. So let’s say Tim’s bought three jackets, three Navy jackets. We know he’s not going to keep all three of those jackets. We just know. And so to be able to communicate with that consumer soon after they’ve received the delivery, to get real data about which of the three, why that one, why these two or whatever, and start to engage with the consumer at that point, I think would be the perfect start to the journey.

But ultimately for me, the sort of the eureka moment is the day when Tim goes online, therefore like responds to my prompt, tells me that he’s going to send this particular jacket back. The jacket’s fine. It’s just the wrong, it’s the wrong fit. I’m going to keep the, I’m going to keep the longer fit. I can then allocate that skew to an outbound order. So when Tim rewraps that item up and goes to a drop off point and he drops it off in that drop off point.

the label that’s being printed is going to Mark. Oh, that’s amazing. So it’s never actually going back to a distribution center and being touched again because we trust him. We know that he tried it on, rewrapped it, put it back in the package, print the label at a drop off point. Mark lives in the next zip code. Instead of going all the way back to some state where it gets handled in a warehouse, waited and then refulfilled, just go straight in that way and you end up with this completely symbiotic kind of environment where nothing sits still until such time as it’s until such time as

customer wants it. I love that scenario. So that’s what we’re working towards. We’re working towards exactly that. And if you think if you’re running returns management for a retailer and you’re running order management, so we’re matching orders to skews and to fulfillment. And we and we’re feeding transport management systems, we can print the right labels, we’re powering these drop off networks. That’s the ideal scenario, you know, the kind of you keep that keep that skew alive until the customer is ready delighted for you find that

customer that wants it. love that. I love the fact that you spend your off time thinking about this too. Yeah, it’s sad, it is me. What else can you tell us about BlueYonder, anything else you want to share with us? Yeah, think, you know, some of what we’ve talked about for returns, I would say is really good, really illustrates what BlueYonder is all about. that is, we’re a supply chain technology business, supply chain software business.

But we’re one of, and there are many, you only have to look at show like this and there are thousands of us. In practice though, there are very few that operate across the entire life of a skew of an item. So, you know, we, as a business, we run planning tools, the commerce tools that ⁓ I lead and I own around. once you have the planning tools, forecast, make a judgment.

procure stock and items. The commerce tools is then the kind of the brain that shapes that interacts with the consumer, shows what options are available, creates demand. And then you’ve got the execution side of our business, which is then around how you fulfill that warehouse picking, transport management, deliver on those promises that you’ve made the consumer at this point. So we manage that all end to end, but we also go right back down through the manufacturing supply chain. So in many cases, I like

I’ll walk into a supermarket in the United Kingdom and it’s fascinating. It also makes you very proud to work for the business because I can look at a shelf and I can see consumer goods and I know that our technology and our capability has been involved in the planning, manufacturing, delivery, execution of all of those things that are on that shelf. And I also know that at some point later tonight, there’s a very good chance that one of the consumers are going to go online.

They’re going to pick a basket digitally. And one of these supermarket colleagues is going to come and pick that item again, put it in their basket, create a basket, put it in a road vehicle, take it out to their house, scan it in the customer. And we’re in all of that. We’re everywhere, you know? And so, and that’s like the, you know, we’re trying to kind of create what use technology to create a world where, where any, any customer kind of preference that you could imagine can be, can be fulfilled.

But you can do it in a sustainable manner. And my boss talks about sustainable abundance. You we’ve all got used to abundance now, but have we now got a sustainable abundance? The reality is no. So we’ve got to move to a world where you have sustainable abundance. if you’re like today, in the most part, if you’re a fashion retailer and you want to buy, you want to sell a hundred t-shirts, you probably buy 140. Right. Because you know, there’s going to be some waste in the system, you know.

Whereas I think better use of technology at every point of the supply chain allows you to buy 100, sell 100. Exactly. So that’s the, of course, that’s the big objective. That’s the trick. That’s amazing. Well, thank you so much. It was great thank you. It’s been great. Yeah, no, thank you very much. I look forward to it. know. Thank you. I think it’s been very exciting. Yeah, it’s good. a lot of activity, a lot of different…

Not just retailers are here, but a lot of vendors are here. distributors as well. Yeah, it’s great. It’s like the whole collaboration of the industry coming together. I’ve done this for a long time, actually, about 15 years now. And I was saying to somebody earlier on that the pace of change over the last five years, it’s eye watering compared to the previous 10. As in the previous 10, you could walk around the show and it genuinely would be shelving and.

I remember that. remember that. And it’s very different now. It’s amazing how it’s very little hardware here these days. I think the other thing, so talking about your how blue yonder is really across every kind of touch point. I think now in our retail industry, we’ve never been more collaborative. Yeah, exactly. Across not just the functions, but across the industry. And I think that makes us better retailers. It does. It does. And I think, you know, there’s obviously a lot of

There has been skepticism about things like AI across all industries for a long period of time. But I feel like that skepticism really doesn’t exist at scale in retail anymore, particularly not in supply chain, because everybody sees how it works and how it’s evolving. But it forces collaboration, really, because AI requires multiple data sources. requires, and actually can start to influence and intervene.

in not just your bit of the business, but in your colleagues bit of the business. And therefore your colleague suppliers and your colleague supply chain and, and, and, and, so it forces that kind of rethink about how the industry operates. So it’s a bit of a force for good, even though there are worries about AI and its impact on humanity. think in our industry, it’s a great force for good. Yep. Well, thank you. And thank you for all the you do for the industry. No, great. Thanks very much.

I’m so excited we’re here at the NRF retail on wrap and we have with us Ethan Chernowski. Chernowski. always forget. It’s close. It’s great. We nailed it. Nope. We’re going to say Chernowski. Did I do it right? Chernowski. What is it? It’s Chernowski. Yeah. All right. Anyway, you are CMO of Placer AI and you guys have a lot of rich data and analytics and I’m excited today because usually you and I speak or virtual and today we’re in

Nice, it’s amazing. love it. So anyway, so I’m dying to hear what are you seeing? You get lots of information, get lots of data. Maybe do a quick what Placer AI is and then tell us what you’re seeing. Yeah, absolutely. So Placer is a location analytics company. That means very, very simply, people vote with their feet. We show you how they vote across the United States every single day.

Excellent. And you do all kinds of, I think personally I’m not biased, but I think you put out some of the best reporting of the industry. I’m always going to your website and looking up your reports and all your analytics because you kind of look at the business not like an analytics company, but you kind of look at the business like a retail. I think what interests us is this idea that you go from

metrics and data to opinions. Because I think what ultimately the way the data is used by our customers is how do they inform better decisions for their actual businesses. So for us, it’s first of all, it’s just super interesting and such an exciting space to get to monitor and look at. But so much of what we’re trying to show is you might completely disagree with the conclusions that they have and that’s absolutely legitimate. But to go from a metric, a number, a data trend to an informed opinion about something, I that process is so.

I think it’s great and we’ve shortened the time considerably from like five years ago. Like decision making is like very quick in no time now. I feel like some of it’s almost like too quick. Like it’s funny every time you go to one of these conferences you hear about like what are the big themes that are being discussed and you’re like well remember two years ago when you told us it was gonna be this it doesn’t change that dramatically that quickly and so I feel like sometimes you want

really, really rapid decision making and there are certainly places for that but in a lot of cases it’s almost like take a deep breath let’s decide is this thing that was something we think is going to be here forever is this thing we think is going to go away in the next few months is this something that’s going to be you know dictating the way retail operates for the next decade and I there’s so much variability there. Yeah absolutely so tell me what are you seeing in the data what have you seen transpire over the past year and what can we look forward to?

So I think there’s a few things that have really caught our attention as being foundational into what retail is going to need to do in order to drive success in the coming years. I’ll give you one that starts with the consumer. If we think immediately post pandemic, we saw this mission driven shopping trend where people are going to retail locations. They’re spending lots of time in those locations. If you win the visit, you win the basket. It’s not just about the number of transactions, it’s about the number of items that are in that basket.

What we’ve seen over the last few years is that really dissipated. So visit durations are down. The number of visits for every category per customer is going up. So people are going to more locations. They’re spending less time there. And I think this is so critical because, again, let’s put on that time machine hat and go back to 2020. We were told convenience is king.

And I think what we’ve learned in the last few years is that’s absolutely not the case. Interesting. It doesn’t mean convenience isn’t important. Right. But it’s not king. Right? There are things that are much more important. So value, product, experience, brand affinity. These things have a lot more significance than we sometimes give them credit for. Right. And I just want to mention something about value. Because value is really important. Value doesn’t mean cheap. Or…

Low price. Value means the worthiness in the eyes of the consumer, right? I agree with you completely, and I think it’s one of the things that you hear the terminology tossed around. But it’s almost like…

Because it’s so fluid, it’s difficult to pinpoint. So what is affordable enough? What is valuable enough? And I think that’s why elements like caliber of product, elements like experience and brand, they matter more because value is somewhat of a moving target. so…

think about retailers that really nail the experience, people are willing to spend a little bit more. When people, the retailers that don’t do that, value becomes more of an issue, but it’s not because the price was off, it’s because they don’t perceive the overall experience as being worthy of the price that you’re charging. Right. So tell me about in-store experience and what any information you have regarding visits or duration. You mentioned the duration went down.

What else can you tell us? What’s interesting is when you look at data like that, see shorter visits, you see more visits, and so you can clearly see that the battle is going to, again, how do I get the visit and I win, to I’m gonna get the visit, how do I maximize my share of the list of things that need to be bought or purchased? When you take that as true…

implications from an innovation perspective are massive. So where are we going to invest our time and energy? Is it going to be shrinking the journey in store? Like I don’t think that’s the thing that really moves the needle, but I go to elements like retail media, especially in the physical environment, and though it’s kind of not as hot and exciting as it was a year or two ago, think it’s unbelievably important because that need to maximize the kind of value.

The dollars per visit, so to speak, increases. So what helps improve the customer journey? What helps drive more purchases? What helps drive, I don’t know, just monetizing the visit itself? These things are unbelievably important, and I think those are going to be prioritized as we continue to see things fall out in the next couple of years.

That’s so interesting. So who do you think is really killing it? When you look at the data and you look at this consistency of visits over time, who’s really killing it? There’s the ones that never surprise. And it’s almost necessary to call them out because it’s easy to overlook because they’re so consistently good. So Walmart, such a great example of just effective execution, consistent growth. Even the way they do e-commerce, the way they leverage.

their in-store capabilities to drive that e-commerce growth. Costco is such a great example. I think, Costco is an amazing example because I think we gloss over some of the crazy things that they do. you can go to Costco and you know, you have an expectation of what’s going to end up in that giant, that giant cart that you’re reeling around.

But I think one of the things that’s amazing about Costco is you’re also renting cars. You’re booking travel. That doesn’t make any sense. It really doesn’t, and yet they do it so effectively because we love them, we trust them, we appreciate their relationship. It’s something that’s really special. when you call it out, I know someone who gets their hearing aids at Costco. Again, in what planet is that a normal journey to go on? But yet it works because they’re so strong, they’re so trusted. And then you think about smaller players that certainly get lots of hype.

HEB, their ability to be authentic and really locally focused. But then there’s players that I think are well positioned because of things that they’re doing, but also changes in the market. So things like Michaels. Michaels was a really strong performing retailer. And as the year went on, we saw their visit growth pick up pace. And that’s because two of their biggest competitors fell off. Joann’s and… And Joann’s and Party City. And so you see this incredible combination of a really strong retailer and a great opportunity. And I think those are the ones where you’re like, wow, this

is going to be exciting. Love that. So what can you tell us on consumer behavior? What are you seeing differently? What do you think is going to happen in 2026? I think it’s going to be, I mean, there’s nothing more boring than saying it’s going be more of the same, but I do think it’s going to be more of the same, which is this. A shopper that is basing their purchase on the things that they love, a shopper that’s willing to visit more places, I mean I was on a panel earlier today and the terminology that was used that was both funny but also incredibly like excellent, it’s a promiscuous shopper. Like they’re not just for you. Like they’re going to go to other places and you need to know that. And so how do you lean in to those things that you do exceptionally well?

What makes, it’s not like a lost leader mentality of how do I convince you to come and then you’ll hopefully buy other things. It’s how do I create something great so that you’ll come? And I think that is a mindset shift, especially when we know how prevalent value is, where it’s not a race to the bottom of who can make things the cheapest. It’s who can create this incredible experience that’s so affordable. I love that. Who said that comment, do you remember? I don’t wanna, I’m gonna butcher his last name, but a brilliant guy from Giants.

Oh nice, yeah. Okay, so yeah, I agree with that. And I think it’s very difficult because as you kind of hinted to, the consumers, the behavior changes based on the scenario. Like today, for me, I gotta go to my son’s baseball game. It’s all on convenience. Tomorrow, I’m shopping with friends. It’s all about social interaction. Also, I think one of the big things we forgot is that, or we didn’t want to admit, I don’t know if we ever forgot it, we like shopping.

even like going to the grocery store because there is something about walking through the aisles and like what am I gonna choose what’s gonna inspire the dinner that I don’t know what I’m making yet in two nights or which I don’t know for me that like it’s because it’s silly but you know walking through the cereal aisle with my kids and they’re like well which version of Cap’n Crunch are we gonna choose like there’s something exciting about that journey and I think the more we embrace the fact that this isn’t just something we have to do it’s something we are choosing to do the more we can elevate that experience. Yeah, now I agree with that.

I think the whole physical stores and the experiential retail are really gonna win out. So Placer.AI has been around for a long time. Seven years since we launched. That’s great. So what are you planning any kind of new features coming out over the next few years that you can tell us about? Yeah, so I mean there’s we have a heavy focus on trying to make the data even more accessible even easier to leverage so lots of things where like one-click reports where you can go in

filter out some key details that you’re looking for and then have that in your inbox within a handful of minutes. That’s what we’re really focused on. How do we speed up the process from that eureka moment, this idea that you want to explore to getting a real insight that’s going to help you make better decisions. There’s a lot of obviously emphasis on AI and how do we enable these AI components to better access the data, allow you to answer questions more directly.

to be a little bit more specific and tailored to what you’re looking for, these are the areas that focus for us. So clearly you’re using agentic AI, right? I would imagine, yeah. You’ve probably been using it for years. mean, we’ve been, yeah. The AI trend has been one that we’ve been leading into for quite a while, but it’s like a never-ending exploration, and it is very complicated, and it’s hard. You want to make sure you do it right, and you do it justice. Yeah, because if you do it wrong, it’s a whole trail of events that occur that…

Absolutely. There’s a lot of trust that our customers put into us in terms of the caliber of the data and what it’s indicating. So to make sure that the tools and products we create are ones that our customer base can trust is a huge element.

Anything else you’d like to add or anything else that you’re seeing? I mean, I think the biggest thing is remembering that we’re operating from a position of strength because it’s so easy to forget that less than a decade ago, the dominant retail narrative was stores are dying, people hate shopping, we’re going to order everything to our house. And now we’re seeing almost the exact opposite. It doesn’t mean e-commerce isn’t amazing. It just means this conception of a zero-sum game in retail is false. And so many channels are important to creating that ideal experience. embrace that holistic view, the better the retail experience we’re going to create. Yeah, I definitely think going to the direction of the connected store and really connecting all those pieces is definitely what consumers are looking for. And if you think about the younger generation…

So Gen Alpha and Gen Z, they’re used to this instantaneous information at their fingertips. They don’t even want to search for information or search for things. They want everything immediately given to them. And that’s only going to escalate as time goes by. So whatever, we can do real time to make sure we’re meeting the needs of that consumer in the moment of the shopping experience. Right?

Well thanks for being here today. great having you. my gosh. So, place your AI. Thank you.

And see. Nice.

Hi, Shelley Cohen here. so excited to have Jay Hakami here, CEO and founder of Skypad with me in person. I’m so excited. so much for having me. It’s a pleasure. Absolutely. So we’re here at the NRF show in the Javits Center. And wow, AI is everywhere. Everywhere, Those two letters. Agentic AI is actually picking up very large. I mean, you know, we’re in the data field.

So for us, initially AI was a search engine, you to be able to search faster, get information faster. But with Gentic, now you can do predictive. Now you can give assortments. Now you can do recommendations, which is a lot more interesting because now data talks to data and the results come out. So it makes it a lot more interesting than just another search engine, which is amazing by itself because, know, today you type in a few words and you get the answers you want.

which is kind of supersedes kind of Google on steroids, if will. But with agent thinking, moving to a different field where data speaks to data and results come out. it’s amazing for us, especially as a company that deals with data all day long, between retailers and brands, we see it as a huge opportunity for us in the marketplace. know that you have been working with data analytics for, I don’t know, decades, probably. 25 years. 25 years. Decades.

And I really am interested in hearing from you. for me, and now I’m a retailer, I’m not a data person. And I do understand retail tech, but not at the level you understand it. And when I look back at the past few years, I saw kind of this kind of slow tech, tech, tech, then five years ago, it got very fast. Today, I feel like I read something today, or I look at something today, and tomorrow it’s different.

Talk to me a little bit about the speed to which it’s changing and what you guys are doing to kind of stay on top of everything. Well, it seems that the retail merchandisers, specifically in the merchant side, they used to do things based on gut and feel, right? You touch. You want to see. But what’s happening as we progress in the years, it’s about the data. It’s about trends. It’s about looking at data and trying to predict what’s going to happen later on.

Joanna Hollern (02:24.782)
So I think we kind of stumble into this space, but it’s actually a great space to be in because the look and feel is still there, but the data confirms it or makes a change in decision making. So over the years, you’ve seen companies, retailers and brand innovating, continuously deploying different technologies to improve their business. And that trend will continue, especially with AI. is a huge change.

It’s much bigger than the internet back in the day when that started. So you’re going to see a major changes where actually companies, retails and brands are going to be more technology companies than merchants. I know, right? In a way, in a way. Did you, so today the CEO of Google was talking about like we’re right now in this most transformative place ever in the history of retail.

No doubt. So what’s your take on that? Well, there’s no doubt. I you’ve seen all the dynamics happening in retail today all over the place. And I think with the new tools that are coming to the market, especially with AI, AI-Gentic, there’s going to be a humongous change. You’re going to see the conversation is going to be more about technology, data, insights, predictive, than it’s going to be more on the human touch, which is kind of a shame in many ways.

but it kind of confirms one another because you still need the human feel to do what you do. But I think the data kind of confirms it. So I think, you know, what what Google is saying is now we’re coming up with tools that enable you to do from imaging to to data, data management, things in retail that they never did before. a company like Google or Microsoft or any other big players to do this, it shows the movement.

moving more into technology than the human touch. Yeah. So Skypad, tell me, if you could tell us illustrative examples of how you’re using agentic AI or AI, what’s different today than was even last year? What are you seeing in the future? Well, when we started the business back, well, Sky IT group has been around for 25 years, and I did say that before, but Skypad has been around for 18 years.

Joanna Hollern (04:46.879)
Initially, we were started as a data collection company, collecting data from the retailer, aligning it with the brand style information, and then providing insights. Today, with AI and AI-Gentic, what we’re doing is we’re getting into the predictive side. We’re going into the planning and allocation based on AI. We’re doing dynamic AI development with dams, with digital marketing assets.

We’re doing things that we never did before. We dabbled a little bit back in the day with machine learning, which is, know, but I tell you, we were not successful. was too technological to do what we wanted to do. With AI, we can do it in an enormous amount of speed, launch it quickly, and show results almost immediately. So we’re excited about what we’re developing.

a slew of products coming out with AI. And one of them, we just launched here at the show, which is basically just type what do you want to know? And it gives you the answer, gives it to you statistically in graphs in any way you want to see. So you don’t have to click and point anymore. You can actually ask the question, which is already an AI enabled platform. But there’s a lot more in the background that we can do with data talks and data and gives you, oh, you sold that red over there in this time frame.

Maybe you should consider adding more inventory to that place or reduce the green because it’s not selling in one location and doing fantastic in another location and giving the merchant the insights to make decisions much faster. just to give you just so I understand this. So you’re saying that today a merchant or a brand can say, OK, tell me where are my 10 best wide leg jean pants stores selling and what colors the top and boom.

Well, we can do that today. That’s easy. that’s easy. Yeah, we’re doing that today because we’re collecting data from the retailer. We are aligning it with the the information we get from the brand. We’re putting it together so the brand can actually make a decision what’s selling, what’s not selling by geographies, by product attributes and by time dimension. But today with agentic AI, what you’re going to see is basically telling you, this information, this this product is going to be selling very well.

Joanna Hollern (07:12.097)
based on these parameter in this location. So future sales. Future sales. Predictive. Predictive. We’re looking at the rear view mirror. AI is giving us the that’s amazing. That’s what we are so excited about AI and agentic AI. So you’re basically, you’re essentially setting up buyers and planners for absolute success.

because you’re telling them ahead of time what’s actually going to With one version of the truth. But don’t forget, we’ve got the buyer and the seller looking at the same platform, looking at the same analytics, the same projections, and they’re coming up with the same result. They don’t have to have a dialogue about it. They have that information readily available today with agentic AI. And that’s the real key. And the beauty about a company like us is that AI without data is like glass water with no water, right?

So we have all the data, just a question of how do we treat it? How do we combine it? How do we manipulate it? How do we get to the results, the end results we want to get? And that’s the beauty about what’s happening in SkyPad today with AI. That’s very exciting. And I know that you said predictive analytics. You’re very excited about predictive analytics. What else excites you about AI or agentic AI? Well, I’ll tell you everything. Our development right now is

80 to 95 to 95 % AI. We’re not doing any pure development like we used to do before. It took us a long time to come up with a product. By the time we scoped it, developed it, tested it, today with AI that process is much faster. We can come up with solution like planning or market prep. These type of solutions, we can come up with two, three months ready to launch to the customer. And we will be

introducing that in the next couple of months, the next couple of quarters to our customer base. That’s amazing. So the cycle from idea to launch is so short. It could take weeks, could take months, but it’s not going to take years. And that’s the beauty about technology company doing the things that they’re doing with AI. Especially because you work a lot of collaborations and partnerships with the actual brands.

It’s not like your technology company out there. Believe me, we don’t. We don’t develop anything on what we think we need to develop. We we sit with the brands. We talk to the retailers. We get insights before we do anything. I learned that the hard way, by the way, I was sitting in the side with I was saying, oh, let’s develop this and this. No, no, no, not anymore. We talk to the customer. We see what the demand are. And people saying to us, we would love just to type in a question. Give me just type in a speaker. I want my CEO to use this.

Type in a question, how was my low heel shoes during South Dakota? Give me the answer, give me the chart. How did it do in September versus October? Give me the information. I don’t want to click and point anymore. Going away from that, it’s a question. So even with voice, you can do it with voice. You can do it on your cell. Okay, you can go to the merchant, to the retail and ask the question on your cell and get the answer. Here’s the answer right here. So these are the things that you’re gonna see with AI and agentic AI. We’re super excited.

I cannot stop talking about it because it’s just such a huge change from the traditional way of doing things to the do it. I mean, it’s so fast. It’s so easy. It’s so just amazing. I love that. And I love the fact that you actually went and asked your brands what they’re looking for. And if you think about the workforce and the young people that are coming into the workforce, so now they’re growing up and they’re coming out of an age where they’re used to

talking into chat GPT and getting problems quickly solved. And so now they’re in the workforce. And so when it makes sense, that that’s what they’re expecting. Exactly. And quite frankly, when we develop SkyPad, it wasn’t developed for dinosaur like me. It developed for the new generation. so basically the new generation is accustomed to that, to talk to it and get an answer immediately. And the answer is to be immediate. And that’s the beauty about this whole thing. Now we’ve got the data, we’ve got the tools.

Now connect the tools to the data, bring the data out as fast as you can so you can respond to the requester. And that’s really the key. In our world, the requester could be the brand or it could be the retailer. Either one. You want to make sure the answer is the same for the same question. Of And that’s the key about AI and AI-Gentic is the fact that you need to have the data in the correct way to make sure the answer is correct. But otherwise, people are going to make mistakes. Of course.

business decisions are being made on the information we provide. So we’re very keen about what we do and how the information comes out. And it goes to a rigorous QA before we launch. We’re a little bit slow because we want to make sure it’s perfect when we go out. And so you talked, I just want to talk about the product life cycle. You talked about how that’s going to shorten greatly. So I grew up in the era, I’m not going to call myself a dinosaur, but.

I grew up in there was nine to months product life cycle. then, know, Zara hit the ceiling in H and so that became six weeks. So are we thinking less than six weeks now? Well, in our world, it could be. It could very well be. If you want to create a solution, for example, let’s talk about market per. We can actually develop it today based on the data we already have. We can develop in six to eight weeks.

we can launch it in, you know, in 10 weeks. So what I’m saying is that the cycle time and the fashion industry has been shortened considerably considerably. by the way, our development time is shortened as well. So we’re enabled to give the our consumer a much faster technology to be used to accommodate their shortened life cycle on the supply chain. So let’s talk about the

ultimate consumer out there and they’re using and use cases because I feel like everything we do whether you’re working with a brand or you’re working with a retailer that all goes back to the consumer. Do you have any insights about? I’m a big, big believer, big believer that the retailers should be treating the consumer as well as they’re treating their brands. I think and we have a lot of stories about this right now as we speak.

but the brands are their partners. And if we don’t have this hub that provides information to both sides and sharing of information from both sides, the ultimate loser is by the way, is the consumer. Of course. Because all of a sudden you have sizes nobody wants or colors nobody wants in a specific location. So the dialogue between the retail and the brand is so, important. As much in my opinion is important as the dialogue.

between the retailer and their consumer. And these are the things that I think most retailers are realizing today. You cannot ignore your brands. You need to talk to them, discuss based on information, based on data, based on insight, based on trends, how things are moving or not moving, and then make decisions. And these are the things that I think the retail is beginning to understand, that it cannot be a siloed situation where they’re only addressing the consumer. need to address the brand as

I love that. And you’re so right, because it all goes back to the consumer at the end of the day. At the end of the day, the consumer, because the consumer wants to come in, they want to make sure they’ve got what they need at the right place at the right time. And if you don’t have these insights, you’re to come to a store and you only have red and you don’t want red. You want the blue. you will. By the way, if you have the red that size four, not the one you thought. So all these things are going to be addressed much faster when you’ve got.

AI embedded into your platform. And Jay, I have to give you high five and lots of recognition, because I know you do a lot of work with students. We do. And you know, I have a personal passion of educating students and helping students understand the next wave of retail. So I want to thank you for all the work that you’re doing with students. Absolutely. We love it. Naomi, one of your professors came in and said, you know, we would like to bring your students to your facility. More than welcome. We’re across the street from FIT.

So I think that’s becoming a trend and hopefully we’ll get our product into your faculty as well. think that, you know, SkyPad and actually in Europe as well is becoming a tool that schools, fashion schools are beginning to show and teach. And I think that’s a big benefit. And I appreciate the fact that you’re endorsing us in that way, but we love having the students. think they’re bright. And this is the future at the end of the day. You know, we need to have that future come up.

There are future merchandisers, future CEOs, VP and SVPs of the industry. And if we don’t teach them now, and if we don’t do it, who’s going to do it? That’s right. And I think you’re right, because I think with students, you said something early on, and that is you have to get, we have to have young people that are students playing with the AI. No doubt. They have to start to understand it. You can’t just say,

you know, no, no, no. And then they come on the industry and they don’t know what to do. So I mean, if I had one advice for young students is jump into Gemini, jump into Copilot, jump into Chia GPT, the slew of tools out there that can actually educate you about AI. Because once you go to the workplace, the first question you’re going to be asked is after, you know, after a few questions is, what have you done in AI? Have you played with any of the tools? Have you learned about it?

So you need to be able to really mention some of the things you’ve done in AI. I think it’s key. I love it. That’s great. Any closing thoughts for us? Well, look, I’m a big fan of FIT, as you know that. We have, I think we have about seven or eight, if not more, folks that came from FIT. we love the people that come in. Many of them are coming as interns. And today, some of them are managing big projects for us.

across the globe with SkyPad We have over 3,000 subscribers and a very vast network of retailers in the US and abroad that we support. And the talent you produce is amazing. Thank you. you. But again, getting back to the education, really gear up on AI because it’s not going away. It’s not a fad. Well, thank you so much for all the work that you do and for making our merchandisers and allocators in our

industry being you know giving them the tools to be much better at what well we do it with love so thank you so much thank you.

my gosh, I’m so excited. We’re here at the N.R.F. show, Retail Unwrapped, and we’re in person. All right. It’s great. George, I have George Shaw here, who is the Senior Vice President of Standard AIs. AI Strategy. AI Strategy. That’s kind of a tough question, That’s right. So welcome. It’s great to have you. Thanks for having me. It’s always a pleasure, Awesome. So I’m dying to hear what you’ve been up to, what’s going on, and tell me what you’re seeing at the N.R.F. show.

Wow, so a lot’s been going on. ⁓ My company, Path Air, was acquired by Standard AI. That’s awesome. We announced that on Friday. Like Friday? Just now. my God, that’s great. Yep. So I’ve had a new job for about a week. It’s going great so far. I love it. It’s fantastic. Standard is an awesome company. They came out of Autonomous Checkout. So they built a lot of fantastic technology in order to solve that. And now they’ve pivoted into analytics, which is really my wheelhouse, stuff that I love. So it’s a really, really nice fit. And we’re going to figure out how to scale.

computer vision and analytics. I love that. So tell me a little about, so I’ve heard a lot about AI, GenQ AI and computer vision. what I’d love for you to tell us a little bit about is what is computer vision in today’s retail world? What does that look like? So now the, one of the big trends that’s happening now is using existing cameras. Retailers had the, had the insight and, and I want to say companies like Path or my old company helped to, helped to educate them in this, but they could use their existing cameras.

Instead of having to install a bunch of new cameras in order to see what their shoppers were doing, use the cameras that already there, because the science came forward. So the computer vision technology, the software made it so that we could use the security cameras they’ve already got. So think that’s the biggest trend. We see a lot of that. A bunch of companies that are working on doing that. ⁓ And retailers are starting to understand also the value of that data. What can you do with computer vision? Exactly. What are you doing with computer vision in that store environment?

There’s lots of different things you can do with computer vision. What Standard mostly does and what Pather did was to track people as they move through the space, anonymously. So we use the security camera, we take that feed and we turn people into dots moving around a map. Pather, had one dot. Standard has 26 dots that represent a person. What that means is we know where your arms are, so we know if you’re reaching out to touch a product. We know which way your head is pointing, so we know where you’re looking. If you’re looking at a media screen, for example.

we can tell that you’re looking at that screen rather than just standing in front of it with your back to it or something like that. So this is something that computer vision has been used for for a while. ⁓ There are other purposes for computer vision as well, looking at products and all sorts of other things, but that’s what we do. That’s great. So you’re monitoring the path of the shopper as they’re in the store, reaching, you know, if they’re bending, standing up, looking at something, all of that. That’s right. What’s the ultimate goal? What are you going to do with all that information?

So every retailer sort of has a different use for that. They all have some different metric or some different thing that they want to learn, something else that they want to understand depending on their particular environment. ⁓ Luxury retailers, for example, they want to know a lot more about the interaction between their staff and customers. How long is it until somebody’s greeted? How long does the staff spend with the customer? Is their selling behavior happening? Does it lead to a transaction? Things like that. Specialty retailer, similar. lot of retailers want to understand the shopping journey.

So when I come in, where do I go? What products do I look at and not buy? What do I ultimately buy? What does that behavior look like across different shelves and fixtures? This happens in beauty, happens in apparel, even in grocery. They want to know about that full shopping journey. But also retailers wanting to know where people are focusing their attention. So for media, that’s one that’s really important to us right now is measuring in-store media and being able to do that in a way that’s accurate.

Again, if you have your back to the screen or you’re on your phone, you’re not actually, you shouldn’t be counted as an impression. You didn’t actually see that ad. But if you’re there watching the ad, that’s an impression. So this is something that retailers are starting to measure more as we see a lot more in-store media happening. Yeah, the retail media networks is just growing so big and it’s now, when you walk into a store, it’s everywhere. So I can see how that can be beneficial. Are you able to connect the KPI? So let’s go back to your example in London.

So you have this interaction of an associate. Can you then look at the KPIs that came out of that? Like the sales, know, what the, know, UPT or average transaction, all of that. Yeah, yeah, always tie all the metrics that we would collect to the things that ultimately the retailers care about that affect their bottom line. So whether that’s the, you know, the selling behavior of the staff or how people are shopping. Queues is another big one. Monitor queues and help retailers to keep the queues short. If nobody wants to wait in the long line, that’s a, that,

affects conversion that affects ATV. So they’re looking at those metrics in relation to things like queue or engagement with staff and so on. That’s exciting. So tell me, what do you have on tap for 2026? What are you guys kind of focusing a lot of the development side on software wise? This is the year to scale computer vision. I really believe that. been doing this for a long time and I think now is the time. And the reason is because we’ve got much deeper technology than we have.

We’ve got much better data, it’s more granular, it’s much more accurate. And to do autonomous checkout, you have to be 100 % accurate. You never make a mistake, right? And so the analytics are extremely accurate. But then what we’ve also done is prove that we could scale that kind of technology. And so those two things are coming together, chocolate and peanut butter are coming together. And it’s looking really good for this year to be able to scale this really powerful deep tech. I know that. And when you say autonomous checkout, you’re talking about self-checkout.

So like Amazon Go or just walk out. That’s where you really you think that’s going to grow bigger this year? No, I think I think I think that is sort of ⁓ sort of maybe leveled off. ⁓ But a lot of those companies that were doing that are now pivoting into analytics and more operational analytics, you know, selling behavior and just sort of analytics that I’ve always worked on. No, that’s great. That’s great. And so when you look back on the past year, I know you’ve been looking at consumer data for a long time.

What consumer behavior changes have you seen that you think retailers would be most interested going into the future? Ooh, that’s a good one. That’s a good one. ⁓ We see a lot more engagement. So people are coming into stores and wanting to interact more with staff. ⁓ think that speaks a lot to why people shop in physical stores in the first place. We want to see people. We want to touch the products and there are other reasons, of course, but we really want to interact with people. And so I think we see that in the metrics that we collect. We see more of that.

see retailers caring a lot more about that. It’s a question we get a lot more than we were before. So think that’s one of the trends that I’m seeing at least. No, that’s great. So what else do you want to talk about in terms of what’s happening at Standard AI? are you excited about? What keeps you up at night? You know, I’m excited about all this tech. I’m a nerd. I’m really into the technology that they’ve built and that I now get to enjoy continuing to develop a bunch of really cool stuff that we do.

We can measure the total time somebody spent in store. Even in a huge store, even with just a single camera, we’re able to do that. We’re able to, again, understand media impressions, all these different metrics. I won’t give you a laundry list of all the metrics, but there’s a lot of really interesting metrics that we could collect. I’m super excited about that. What keeps me up at night is whether we can do this at the scale that we want to do it. Whether we can deploy that sort of tech to the thousands, tens of thousands of locations that we’re chasing after. Yeah, the details is it.

The devil’s in the details. The devil’s in the details. right. Exactly. So I think a lot of retailers get overwhelmed with the amount of details and the amount of data. how do you suggest retailers kind of unify that view so that they can actually make quick decisions? I really feel a lot of that is the responsibility of companies like ours.

I think we have to simplify the whole process and we have work to do. It’s not there yet, but we have to simplify the process of deploying the technology to make it faster. We have to make it easier to get the tech out there. And then we have to make the data more useful. Retailers don’t want a bunch of dots moving around maps. Even heat maps are of limited usefulness. They want the metrics that they actually care about. So that’s up to companies like us to figure that out.

Give them a very simple, clean, clear dashboard that you can use operationally at scale. I feel like most of that is on us. In real time, right? In real time. We want everything real time. Yeah, yeah, absolutely. Well, again, while you’re doing autonomous checkout, you have to operate in real time too. So our system is super efficient, super fast. That’s great. Anything else you want to share? No, I think that’s it. I really appreciate you having me on. Absolutely. I’m excited. excited to see what you guys are going to be doing this year. I’m going to be watching you.

and saying all kinds of cool things that you’re putting out there. Because I know you’re trying to retailers really understand data in a measurable way. Absolutely. We want to help them just be better retailers so that we can all have a better shopping experience when we go into the store. Exactly. And give them data to do that. Awesome. Well, thanks so much for being here. Thanks again, Shelley.