AI-Powered Store Teams - How Microsoft & SYNQ Are Transforming Retail Frontlines

S5E10 Unleashing AI-Powered Store Teams

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[00:00:01] Casey Golden: Well it's a good thing retail and, and tech has finally become friends because this is all gonna take a lot of teamwork.

[00:00:08] Ricardo Belmar: That's right.

[00:00:10] Jeff Strasser: Well, think of, the analogy here, the parallel to that would be if you could have self-driving cars on your existing car. Just by upgrading the software on the backend, like how cool would that be?

[00:00:20] And so that's kind of where, where we're, we're heading together. From a retail standpoint, we can enable a lot of this really cool, really impactful AI technology using hardware that's already there. That's a way to get started faster.

[00:00:32] Ricardo Belmar: We're not just talking about automating tasks, we're talking about AI that can actually augment store teams, give new capabilities to serve customers better, faster, with more confidence.

[00:00:42] Nolan Wheeler: and then you just talk PLU for dragon fruit and two seconds later, bang, you've got the PLU, right? So I, I'd like to see anybody else grab the bind, the three ring binder from 85, find dragon fruit better than that

[00:00:54] Show Intro

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[00:01:06] Ricardo Belmar: Welcome to Season five, episode 10 of the Retail Razor Show, the only retail podcast of the Top 10 All Time Indie Management Podcast charts on Goodpods, and the highest ranked retail podcast in the Top 100 Indie Marketing Podcast charts on Goodpods. I'm Ricardo Belmar.

[00:01:23] Casey Golden: And I'm Casey Golden. Welcome Retail Razor Fans to retail's favorite podcast where we cut through the clutter to give you sharp insights on what's happening in retail today, tomorrow, and where we get real about what's driving the future of retail.

[00:01:40] Ricardo Belmar: Today we're diving into one of the biggest challenges retailers face right now. How to empower frontline store teams who are being asked to do more with less, shorter staffing, longer task lists, and higher customer expectations. And most importantly for our discussion, how do you best leverage AI to accomplish this without adversely impacting your store [00:02:00] team's morale.

[00:02:00] Casey Golden: Exactly. Associates are juggling endless corporate tasks while still trying to deliver great customer service. It's a balancing act that often leaves both employees and customers frustrated, and nobody likes being micromanaged.

[00:02:17] Ricardo Belmar: that's true.

[00:02:18] Casey Golden: But here's the good news. AI is stepping in and it can actually be a game changer here.

[00:02:24] Ricardo Belmar: That's right. We're not just talking about automating tasks, we're talking about AI that can actually augment store teams, give new capabilities to serve customers better, faster, with more confidence.

[00:02:35] Casey Golden: To help us unpack this, we've got two incredible guests joining us. First, Jeff Strasser, General Manager of AI Business Solutions for Retail and Consumer Goods at Microsoft. Jeff brings a wealth of experience in helping enterprises harness AI responsibility at scale.

[00:02:53] Ricardo Belmar: And we're also joined by Nolan Wheeler, CEO, and founder of SYNQ. Nolan's team is doing some fascinating work [00:03:00] connecting the two-way radios that associates already use every day, with Azure, Open AI and, and technology so frontline teams can get instant answers to customer questions, hands free, right in the aisle.

[00:03:10] Plus so much more that we'll hear, hear about from Nolan.

[00:03:13] Casey Golden: Together we'll explore how AI can reduce the burden of those endless task lists, free up associates to focus on customers and even unlock new ways of working that weren't even possible before.

[00:03:28] Ricardo Belmar: And as always, conversation is focused on real world impact, what's working, what's next? How retailers can just get started preparing their teams today.

[00:03:37] But before we dive in, we have a quick favor to ask. If you're enjoying the show, hit us with a five star rating and drop a short review on Apple Podcasts, Spotify, Goodpods, or you know, wherever you're listening.

[00:03:47] Casey Golden: And don't forget to like and subscribe on our YouTube, so you never miss an episode.

[00:03:53] Ricardo Belmar: Plus check out the other shows in the Retail Razor Podcast Network. Retail Transformers, Data Blades, and Blade to Greatness.

[00:03:59] Casey Golden: [00:04:00] You'll find them all in your favorite podcast app or together on our YouTube channel.

[00:04:05] Ricardo Belmar: That's right. So with that said, grab your favorite beverage, settle in, get comfy. Let's get into it. Here's our conversation with Jeff Strasser, GM of AI Business Solutions for Retail and Consumer Goods at Microsoft. And Nolan Wheeler, CEO, and founder of SYNQ Technologies on AI enabling your store teams.

[00:04:27] Welcome Jeff Strasser & Nolan Wheeler

[00:04:27] Ricardo Belmar: Welcome, Nolan. Welcome Jeff to the Retail Razor Show.

[00:04:29] Nolan Wheeler: Thanks for having us, man.

[00:04:31] Jeff Strasser: Morning. It's great to see you.

[00:04:32] Casey Golden: So we've been excited to have you both on the show as we've been looking forward to having a deep dive conversation about frontline store teams and learn how AI might make things better for them or already is.

[00:04:45] Ricardo Belmar: That's right. So of course we figured who better to help us break this down than to go to a top expert at Microsoft helping retailers tackle big operational business challenges, plus someone who's at the leading edge of AI enabled solutions for store teams. So you both are two ideal [00:05:00] people to help us dig into this.

[00:05:01] Casey Golden: So before we jump in, we just walked through a bit of your bios in your intro, but Jeff, Nolan, why don't you give us each a quick rundown of your background to kick us off.

[00:05:10] Nolan Wheeler: Go for it, Jeff.

[00:05:11] Jeff Strasser: Yeah. Happy to happy to get things rolling. So, yeah, it's great. Great to be here. So Jeff Strasser, I've been with Microsoft for a number of years, but have spent the last, , good portion of that focused on our retail and consumer goods industry. And really on the way people work. And so, you know, my team works across kind of the, the entire SaaS portfolio at Microsoft.

[00:05:30] So think everything from identity and Windows, which of course is super prevalent and important in a retail environment to, you know, to more modern tools like Teams and Copilot and Agentic AI and taking what was, you know, a, a fairly disconnected experience for the frontline employee and seeing how we can partner with partner with retailers on, I I would say slowly but effectively bringing those technologies into their stores.

[00:05:59] Because as, as we all [00:06:00] know, it's a it's a well run and very very tightly run process in how stores operate. And disruption is typically not, not a good thing. Um, but there is so much opportunity. And so finding that right balance is, is we like to, to spend our time. And, and Nolan, no one is an important partner in doing that.

[00:06:18] So Nolan why don't you go ahead.

[00:06:19] Nolan Wheeler: Thanks Jeff. Yeah, thanks for having us on. Long time listener. First time caller. I love the Razor. So, yeah I, I come, I come from retail brick and mortar. So I, I worked starting out just, you know, pushing carts and filling shelves and then worked up and through supervisory and into store roles, district roles, regional roles.

[00:06:35] So, feel like I've got a pretty good decade of experience within those environments. And then, you know, founded Sync, which was the opportunity to try to bring some better tech technology into the workflow. So, you know. Counterintuitively, you know, where we're at today is a lot of leveraging the legacy voice tools, a lot of leveraging radio leveraging paging that super sounds counterintuitive.

[00:06:54] You're gonna apply AI right, in terms of like the, the, the leading technology. But you're gonna have legacy [00:07:00] voice as the conduit into it. But, but that's really what's accelerated the opportunities within retailers to say, Hey, we have these friendly tools. You know, what is really being said on these radios?

[00:07:09] What, how many times are we getting people to come up, you know, asking for cashier help upfront? So that's, something that Jeff and I have been digging into deep lately. You know, there's some great Zebra stories that are out there, but we just don't have enough of them yet. So it's just a matter of like, what are the tools that we have, meet people where they're at as opposed to where they should be.

[00:07:24] And that's, that's the, the focus of what a lot of what we do today.

[00:07:28] Ricardo Belmar: All right. Well, thank you both.

[00:07:29] Challenges Faced by Frontline Store Teams

[00:07:29] Ricardo Belmar: Let's let's get into it then and start talking about frontline store teams. It's one of my favorite topics to, to dive into retail. I feel it's an area that stands to gain so much from AI, but of course, as you both mentioned, right, there's a balance to strike between how do you do that without being too disruptive, but still bringing the benefits? And, and of course there are, I, I think naturally some skepticism. Potentially right with a lot of store teams that they, maybe it's fear about being replaced by an AI tool, which I think as we'll get into it, we'll see, that's not really what this is about. It's really more about how to [00:08:00] help and see how the, you know, that might take shape. So let's level set a little bit on, on what we're dealing with before we jump into where exactly the AI can help. So I, I guess this maybe opening thought here for both of you. How, how would you characterize today, how are, for example, reduced store staffing levels changing the day-to-day realities for, for frontline teams?

[00:08:19] And what are some of the pain points that you think are the most urgent that really wanna solve and address for store associates right now?

[00:08:26] Jeff Strasser: Nolan, you wanna get things rolling?

[00:08:28] Nolan Wheeler: sure. Yeah, yeah, for sure. Yeah, I mean, I mean, so many things in Frontline we learn from somebody else. So when there's few elses out there it's like, where do you get that knowledge base, right? So, you know, everybody has kind of what I almost kind of consider like checklist training. There's some training, there's some videos.

[00:08:43] Back in the day it was a VHS. Right now it's a little bit more through like a web application, but that really doesn't translate into, okay, now I can go and do this. So that, that's the biggest thing. Again, it's all about communication and how do you. How do you get access to training materials? How do you get access to, what was that person who had been there for [00:09:00] 30 years to help you make your first bail?

[00:09:01] How do you turn that into something that's voice driven or, or, or running off of the zebra. So, so it's that augment to kind of fill in that void of where did those people go?

[00:09:12] Jeff Strasser: Yeah, listen, I was, I was one of those people many, many years ago watching VHS videos. I can remember very distinctly on how to bag groceries at Publix when I was 14 years old. But and, and I will say, just as a side note, that training still sticks with me every single time I go grocery shopping.

[00:09:28] Whether it's I'm bagging my own, or I'm criticizing how somebody else is bagging my groceries. That doesn't go away. But I think, I think to Nolan's point, the, you know, there are fewer people and everybody's being asked to do more. And so how can we use the tools and technology to help guide them to be more adaptable in the roles they're doing so they can accomplish more, whether that's with things like, more real time or just in time training or support through various backend systems.

[00:09:54] Not just, you know, paper manuals of content, which still exists in a lot of cases, but, but. [00:10:00] As they work through various processes in the stores, they're getting guidance whether it's in, you know, through a a, a radio or on a device if they're, if they're fortunate enough to have one. And so being able to get more outta the people we have, being able to onboard people faster so they can pick up these roles and responsibilities within the stores more quickly.

[00:10:19] You know, the, the dynamics of the labor market have changed so much and and people have to be more adaptable. And it's a great place where technology can help but not break the kind of tried and true process within the store.

[00:10:31] Casey Golden: When it comes to like task overload and customer service trade-offs for both, have you seen evidence that long corporate tasks lists are, are pulling associates away from customer facing work and what's the biggest drain on time, morale.

[00:10:49] Jeff Strasser: I, I got one quick thought and, and and Nolan, I'd love to hear your thoughts as well. I think the one thing we see is, and we hear from customers is no matter how the task list is, is created, [00:11:00] whether it's dynamic, whether it's, you know, from store leaders, um, whatever the, the processes that gets that task list created the employees in the stores will still go complete those tasks the way they know how to do them, and in the order they know how to do them. And sometimes the process is over-engineered you know, from a corporate standpoint or stored leadership standpoint, or, even from a technology standpoint without the without maybe the, the consideration for how are things really done on the ground.

[00:11:27] And and so I do think it, it adds complexity, but there needs to be a dose of that collaboration with the stores and how things really get done. And every store may be different based on the people and is the, are, are the processes they put in place to, to build and assign tasks dynamic to that to that store or that market or the talent they have in that store?

[00:11:46] You know, versus just a defined list, which is, is probably too rigid to apply to hundreds and thousands of stores.

[00:11:52] Casey Golden: Makes sense.

[00:11:53] Nolan Wheeler: Yeah, and I think a lot of it comes down to like the, the flow of work and the disruption. Imagine the four of us are sitting here on this conference call [00:12:00] and Jeff says, everybody stop. I gotta go do something for two minutes. Gotta help the customer. And then we all come back like that disruption in terms of the efficiency of that workflow.

[00:12:07] So, you know, we are out there as those frontline associates completing those tasks that at the end of the day, the customer absolutely comes first in terms of getting that transaction made, making that good experience happen, making sure that we have that repeat visit. So it's a matter as well of, how do we get good, notifications within the store?

[00:12:23] How do we give good customer help technologies? Because I don't think that folks really think about the math and the economics of what does disruption do when we're midt task and we need to go do the core of our business, which is let's get customers through the store, through the till and off their car in a happy, help, helpful way.

[00:12:39] Casey Golden: So I'm gonna stick a pin in here for myself and the audience that may not have this experience. Personally,

[00:12:50] I work the retail floor for nearly a decade. I never had a task list. What, can you give me an example of, us all an example of what you mean by what [00:13:00] would be some tasks.

[00:13:01] Nolan Wheeler: I mean, I remember it was, and Jeff, you and I talked to Ron Thurston about this. I mean, for, for, thinking back, you're talking about VHS tapes, but, you know, I, I remember that one of the best lessons I got in my early days was take a piece of paper. Fold it into eight pieces and sections and that was like your task list, right? And it was a matter of going through your environment, at like a shift change over, management change over whatever. Understanding where are we at, what needs to be done, where are we behind, where did we get ahead so we can help somebody else out.

[00:13:26] But you know, those tasks are things like planogram or things like setting up promotionary ends, you know, on the cycle to support the flyer. It's a matter of like looking at price changes and the price changes that support that. Just general things in the store in terms of condition of the shelf, facings, , maybe you're in grocery or really focused on your rapid consumables.

[00:13:44] So looking at dairy, looking at, popping chips and those really labor intensive aisles. So, those tasks are around maintenance of the store to make sure that we look like we're supposed to be able to shoot a commercial on this thing, because that's what we wanna put forth.

[00:13:54] Casey Golden: Okay, perfect. No, that helps. I mean, I, I made everybody fold in 90 degree [00:14:00] corners and they

[00:14:00] Ricardo Belmar: Yep. Exactly. Yeah. Yep, that's right. Yep. That's right. That's right.

[00:14:14] AI Solutions for Retail Operations

[00:14:14] Ricardo Belmar: Now kind of working a little bit more into where we can start to insert AI into these things. Jeff, let me ask you firstly, what, what are some of the ways that, you know, you, you see things like generative AI and conversational agents and things like that, that either help shorten task lists, maybe automate some of these things, help it go faster and just keep, just to help keep associates focusing on customers.

[00:14:35] Jeff Strasser: Yeah, so I, I think there's a number of ways, to take what is often a very kind of call it paper, whether that's a digital paper or physical paper process. But gen the thing general AI is great at it's being able to right, take large amounts of content and reason over it and understand the language.

[00:14:53] And so just getting to the starting point of taking, kind of physical SOPs and turning them [00:15:00] into kind of digital conversation or, or right or task list, depending on what the experience and the application that's being used to start to digitize those things and start to being able to push them out and, and put in place a system where they can be you know, electronically distributed down to a user.

[00:15:15] They can be checked off when they're completed, but also collect feedback on those. And the nice thing about feedback, especially in the context of AI, is that feedback can now be understood at scale, right? So if it's somebody's either speaking feedback to a task. Right. So they went and you know, they were making a maybe changing an end cap, but there was an issue with the, the, fixtures that were, you know, delivered by the vendor or whatever it was , to be able to capture that at scale across thousands of stores. You're not gonna have somebody who's going and listening to that feedback one by one, but when you can programmatically absorb it all, reason over it and say, Hey, there is a critical mass of consistent problem where, you know, this fixture falls down.

[00:15:53] Okay, now we have an issue where we need to change the merchandising. We need to change the layout. We need to give feedback to the vendor that, wherever they're, [00:16:00] wherever they're getting these, these fixtures from is a, as a manufacturing problem. So there's this scale of information that can both be delivered down much more quickly than before with much less labor from a corporate standpoint. But also the feedback and as the tasks are completed in a positive way or, or maybe not as positive way. The good and the bad and can, can be collected and that all goes kind of goes to inform what's working well in the store, what's not working well in the store, where there needs to be more focus and attention and where things can be done can be done better.

[00:16:30] So even at just, just that like, you know, language, large language all is being able to understand it's great. Like the technology exists. We all use it day to day, but now incorporating it into the process and flow of the business to optimize the, the business and the operation of the business is probably the, the most fundamental way and the most basic way that you just couldn't do at scale. There weren't enough people to do that work.

[00:16:50] Ricardo Belmar: Yeah, that's a great, great example. Great example of, of leveraging the, the gen AI capability to, to quickly summarize right? And really synthesize what should you do about something without having [00:17:00] to require someone to pour through, what could be hundreds and hundreds of inputs, right? Yeah, that's a great example.

[00:17:05] So Nolan, let me ask you, things you mentioned earlier kind of like where, where you're living in this store tech environment where you're. Looking at existing technologies that, that retailers are used to, like radios. Maybe taking other simple kind of inputs to help digitize some workflows.

[00:17:20] But traditionally, right, a lot of retailers look to things like, where can I add a mobile device or add or hand a tablet to a store employee and leverage those technologies and apps on those things to try to make them , more productive or, or help them make some, make life easier in a little bit. How are you, how do you look at approaching that kind of change and, and, you know, looking for ROI from these kinds of things without having to deal with all the extra capital investment, all, all these extra, you know, new devices and things. You know, do you have any examples of what kinds of things you're, you're really looking at today for this?

[00:17:53] Nolan Wheeler: Yeah, I mean, in a best case world, everybody's walking around with a Zebra device, right? I mean, you've got the power of scanning, you've got a [00:18:00] screen, you've got some voice enabled opportunities there, so on and so forth. So, you know, the fact of the matter is, is that, you know, there are some really innovative retailers out there that.

[00:18:07] For them. It's been table stakes for a number of years. It's a one-to-one relationship where we've got enough Zebra devices to support a one-to-one on the associate side. But it's really just not the, the common kind of deployment of devices out there. I mean, deployment device isn't just, Hey, I phone Zebra and I bought a device.

[00:18:23] It's, you know, I've got a device and now what's my mobile device management strategy? What's my identity? What's my sign in? What's my training? So suddenly, like if you actually really get critical. You start to look at it and go like, oh, you know what? There's a reason why we haven't deployed a bunch of these devices and a lot of these different verticals of retail because with turnover and training and just the inability to find staff, it's like, just gonna keep doing this radio thing.

[00:18:43] We keep doing this paging thing, you know, the, the, the bar of training and theft and devices and charging and all that type of stuff. So, when we wanna deploy them. Yeah. We, you know. Ideally that's the, the future state or the current state we should all be at. But you know, it really starts at, you know, your management and your supervisors and so on and so forth.

[00:18:59] And if we're [00:19:00] talking about tasking today, the person who's running around the store doing facing, or doing cleanups or helping a customer at a locking showcase or getting into a fitting room, they're probably the last person who's ever gonna get one of those devices. So it's just this matter of like when you, when we're thinking about devices and strategies and tasking, you know, how do we.

[00:19:17] Share devices how do we create like that culture around sharing devices? You know, we, we love listening to paging traffic and radio traffic. 'cause a lot of the times they're complaining that they don't have enough devices. And the ivory tower doesn't know that because the ivory tower doesn't, can't hear that radio traffic.

[00:19:31] So a lot of it just comes down to, it's as we deploy those devices, how do we democratize the access and how do we make sure that. Legacy stuff can talk to new stuff so that we have a bridge to get to where we can go off of and, and leverage it. Well, of what Jeff said, which is a ton of documentation, how do we have that filtered and how do we leverage AI to get that distilled in kind of a step by step process, whether that's through a Zebra or that's through a a radio.

[00:19:55] Casey Golden: So hands free voice first assistance.

[00:19:59] Voice AI and Real-World Applications

[00:19:59] Casey Golden: Jeff, what's the operational and like safety case for putting company governed LLM agents into voice channels for associates?

[00:20:07] Jeff Strasser: yeah, so So there's a lot of technical and, privacy and security considerations that need to be taken, taken taken into account. And I think this is one of the, one of the challenges that, and it's not even specific to, you know, to frontline, but in general that organizations are really struggling with, right?

[00:20:23] There's, every week there is new, bright, shiny object to go chase, right? Something that hits the press. It's some new language model, it's some new consumer tool, and you get every leader within, a retail or any other business, you know, or the board saying, Hey, have we selected at this?

[00:20:40] What is this? What are we doing about it? Without the consideration of what's behind it, right? Whether that's regulatory certifications, that's privacy compliance. Europe, it's, GDPR or California, it's CCPA and all these, you know, all these other things to be considered of when you are a large a large organization.

[00:20:58] And so making sure you're [00:21:00] partnering with. Companies, and that could be, you know, that could be Microsoft of course, but it could be anybody that has the, is delivering a platform that provides you kind of a secure and compliant foundation to build on. And then lets you iterate really quickly. So one of the ways like we work with, with Nolan's company is because he's building on our platform, right?

[00:21:21] When our customers engage with him, they know that they have a foundation of, enterprise capability and support and governance and security and responsible AI and all these foundations that are inherent into the platform, so he can go, so they can go work with partners and ISVs and solution providers that are really innovative in a very specific part of the business like Nolan is when it comes to frontline retail.

[00:21:45] And so I think most important is, and when, when a CIO or a CISO or, you know, a operations leader goes to, their leadership or the board of directors, right? The most important thing is how are we avoiding risk? [00:22:00] And so kind of that form and who you work with is as important as what is the solution we're solving because the potential risk is so great when you're dealing with so many consumers, so much personal data, employee data, conversations, things of that nature.

[00:22:14] Casey Golden: Well it's a good thing retail and, and tech has finally become friends because this is all gonna take a lot of teamwork.

[00:22:21] Ricardo Belmar: That's right.

[00:22:23] Jeff Strasser: For sure. Yes. AB absolutely. And, and, and retailers have been, have been great partners. Like everybody's looking for ways to drive this innovation and deliver better customer experiences and deliver better experiences for their employees. It's hard, it's hard at scale. For sure is hard to distribute environments, and there's so many complexities that are unique to retail, whether it's, the workforce, the churn in the workforce.

[00:22:45] The, the, you know, geographic diversity of the environments that all these retailers are in. The omnichannel nature of business where you're connecting, you know, digital and mobile experiences into physical experiences. There's so, so much uniqueness to retail, but so much opportunity that, [00:23:00] that genuinely people are looking to solve which will be better for all of us down the, down the road.

[00:23:04] Casey Golden: Nolan, how do you design assistant interactions so a voice AI helps an associate in the middle of a conversation with a customer? Rather than just creating more steps or like, does it interrupt them?

[00:23:17] Nolan Wheeler: Yeah, it's interesting. There's a lot of retailers that either A, prefer voice or they just have no choice because they haven't made that investment. Or they're lagging on that investment on the Zebra devices. Right. So, you know, couple of examples of how that these are real world examples.

[00:23:31] You know, we've got a an apparel group and all the folks that help people at the fitting room, they don't have devices, but they've got two-way radios. So for them they're able to do a request to an agent for inventory. So someone comes outta the fitting room. Apparel, apparel's really heavy in, in radio because apparel is very complex.

[00:23:47] You've got size, style, color, so on and so forth, right? So you, it's not like this box of craft dinner versus the other box of craft dinner. So a lot of need to kind of go and check stock. You know, I find buying shoes one of the most [00:24:00] painful things left in our world. Having just done back to school with my two daughters, I buying shoes was

[00:24:05] Ricardo Belmar: Yeah,

[00:24:06] Nolan Wheeler: rough.

[00:24:07] So,

[00:24:07] Casey Golden: Footwear needs like little sticky, like iPod eye trackers or something because I swear every time I find want a shoe, it takes 45 minutes for them to come back and

[00:24:17] Ricardo Belmar: that's right.

[00:24:18] Casey Golden: the left.

[00:24:19] Ricardo Belmar: Yeah.

[00:24:26] Nolan Wheeler: Yeah, so don't get me started there. That's a totally different conversation.

[00:24:29] Ricardo Belmar: That's another podcast,

[00:24:30] Nolan Wheeler: That, that is all about like empowering the customer. Yeah, your, your, your, your customer is at times, like in that example your best associate, right? Like people are so willing to do a little bit of work if it can just make their experience that much better.

[00:24:41] But another conversation for another day. But yeah, I mean, you know, that retailer is using an agent in the ear and when they're making the inventory request, you know, it's asking for this product information that a lot of the times already doing today. Like, there's a lot of retailers that will have somebody in the back room and they'll have a sales associate on the floor and it'll say, Hey , Tim, can you check in the back room for [00:25:00] this? You know, that's now agentic and that's the ability to now say automatically. 'cause Tim really didn't, doesn't need to be, you know, spending their time doing that. They can do higher value tasks. This is the inventory. And the cool thing that this one retailer's doing with us is if the agent comes back with inventory of zero it'll automatically prompt for the zip code.

[00:25:17] So they'll say, you know, what's the customer's zip code? And now we can tell the customer, you know what? We're sorry we don't have it here, but we have three of them at this location. It's on your way home or it's just a little bit out of town. And per the shoe example, customers really are willing to put in some of their own cycles to get to the, the success, the success state, right?

[00:25:34] Data-Driven Retail Insights

[00:25:34] Nolan Wheeler: So, so that's an example of kinda like what we do in terms of the agent side of leveraging voice with legacy voice tools and, and applying an agent that creates better experience for the customer because it's reduced time and better outcome and, and an easier experience for the, the associate not running into the back room or running to a kiosk.

[00:25:50] Casey Golden: It just saves the associate some of the like constant headaches of looking for the same thing over and over again, rather than just coming out with the answer like the solution still needs.

[00:25:59] Nolan Wheeler: [00:26:00] And, and the, and the key here is, is that now we have that data, right? Like prior and before that, it's like, , Jeff and I talk about survivorship bias. You know, we just don't know, like we know all the success because that's POS data. We don't know, the shots we take and miss in, in retail because that, that data doesn't exist now.

[00:26:16] You know, and you, I think you'll see this, you know, we're in the Zebra booth in at NRF this year and we're gonna have a conversation about the full life cycle of this data, which is, the buying group now gets to know, hey, we would be selling more stuff if we had those sizes. Like in real time, getting that feedback from the associate without the associate having to punch at a report.

[00:26:32] So there's a full lifecycle of the data that supports your ops, your buying, your future buying group, seasonality. It's, it's super cool to leverage and, and transcribe that data

[00:26:42] Jeff Strasser: Yeah, nobody, nobody's after they miss a sales opportunity because they didn't have a size, is going into a feedback system or a computer and saying, we didn't sell a product because 11 Brown.

[00:26:55] Casey Golden: Yeah, I mean the miss list is very important, very important. People fight over [00:27:00] inventory in some, some parts of retail, right?

[00:27:02] Jeff Strasser: And even, even for optimization, just in the process, like you think about. You know, so even that example, Nolan, where, you know, radio calling back to somebody in the, in the store room to bring out an item, but that dialogue of that conversation, and there's four other people selling shoes on the floor.

[00:27:16] And, and the overlap in those conversations. And think of where like, you know where a restaurant has come, right? You place an order, shows up on the screen in the kitchen, they deliver the order, right? And there's. Red, yellow, green, like, you know, how long has the time been since that request was made or that order was placed?

[00:27:31] You know, the same thing should happen over the radio, right? Hey, I need size 12 of this shoe in, in, you know, brown. That should just show up on the screen and somebody can see in order whether these have come in. If it's not in stock, it doesn't show up on the list. And then they immediately know that they don't spend time of somebody going and chasing down boxes to see that it's not there.

[00:27:51] They can immediately move to that, where is it most closely available to, to the store we're at currently and can prioritize customers. So one person isn't you [00:28:00] know, how often are you the person waiting for that shoe and like the four people sitting next to you have gotten their shoe from the back room, but they forgot to bring yours, right?

[00:28:07] And so there's so much opportunity that's even been learned in other parts of, of of the business that can be applied to scenarios.

[00:28:14] Ricardo Belmar: there's, there, there's a lot of rich information there that in, in a normal sense, right? None of this has been trackable. Right? So this is all data that you were not collecting because your Verizon mentioned, right? No, no one's gonna stop their workflow to go say, oh, let me write down and record in a database somewhere that we didn't have this and couldn't get this for this customer and they didn't buy that. You know, they, you only really ever used to know what was purchased and you kinda had to back in To everything else, and now you have an opportunity to keep track of all the missed opportunities. And I think back to your previous example, Jeff, within the generative ai, where you could have the same, you have AI kind of analyze that and tell you, without a person having to dig through all of this information, right, just immediately, here's the summary.

[00:28:56] Here's what happened, here's what didn't happen, and now you can take action on [00:29:00]that.

[00:29:00] Jeff Strasser: And, and what's the value of that data? Not just to the retailer, but to the, to the supplier. Right. So if, you know, if they're, if a sale is being lost of shoe brand A to shoe brand B, because there was an inventory. What's the, what's the opportunity for the retailer then to sell that data back to their to their suppliers to be able to better s stock merchandise, you know, maybe plan their assortments and, and inventory levels differently.

[00:29:25] I mean, there's a tremendous amount of Right data's king. We've been saying that forever. There's so much data that's being missed in all the conversations that are being, that are being had.

[00:29:34] Ricardo Belmar: Yeah.

[00:29:34] Nolan Wheeler: you think about I think it's a, Home Depot made that recent announcement of every staff member spending a particular amount of time in store, which is fantastic. Like it's, that's where the, the rubber hits the road. And I, and I love that leadership around that. You know, imagine listening to voice traffic, whether it's pages or radio traffic or whatever the legacy voice is, 'cause the legacy voice, or if it's, you know, zebra's PTT or whatever, right?

[00:29:54] All the, all those voice conversations, transcribing them and then running them through not only a copilot, but a [00:30:00] plurality of copilots, right? You're running it through a customer experience copilot, you know, you're running it through a loss prevention and safety copilot. You know, that's the most powerful thing ever.

[00:30:07] Now you've got, basically, you've got 4,000 agents, if you will, doing 30 different copilots across every single hour of business, writing back every day, and in real time, saying, here's the reality of what's happening in stores.

[00:30:20] Casey Golden: Oh, I love the idea of corporate, knowing exactly how tedious and frustrating a day on the sales floor can be.

[00:30:28] Ricardo Belmar: Yeah.

[00:30:32] Jeff Strasser: As consumers, we probably love for corporate to know what our, well, you know, what our not so great experiences are in store as well. 'cause I'm sure those, those bad experiences that we have don't make it back to corporate. Nobody's reporting on how poor of a job they or the store might have done in a certain

[00:30:47] Ricardo Belmar: right.

[00:30:48] Casey Golden: Yeah, great. The good ones and the bad ones. Like

[00:30:50] Jeff Strasser: Yeah.

[00:30:50] Casey Golden: it's, it's a huge opportunity for hq.

[00:30:55] The Power of Voice Agents in Retail

[00:30:55] Nolan Wheeler: There's another retailer working with that you know, thought about this in the inverse way. So the one [00:31:00] way is to think about, okay, let's just listen to the natural language, but they actually promoted it and they said, you know, nobody fills out the suggestion box anymore. But what about if we've created an agent that allowed you to complain?

[00:31:10] And, and, and this is not to foster some type of, you know, negative culture within the environment, but so often. You go into a store, I remember doing store visits and you go, why are you doing that? And it's like, oh, well we do this because that is broken or that doesn't work. And you go like, Ugh, painful.

[00:31:25] Like painful. Like, so be able to actually report, you know, something to say, Hey, just does everybody know that this happens in my store? And you know, actually creating a, a positive culture to foster, you know, ideation from the frontline up to say, I work here every day. And what we do is silly.

[00:31:41] Jeff Strasser: It Remind no, that, that reminds you of you know, if you tie that back to, your, your own life and you've got an issue with whatever, an ankle, right? And you start overcompensating on the other leg and you cause more problems because the first problem wasn't that bad. It could have been solved, but you've created so many issues by [00:32:00] working around it that it's, it's that much, that much worse that it's the same thing.

[00:32:03] Casey Golden: Right.

[00:32:05] Integrating IoT and Voice for Seamless Operations

[00:32:09] Casey Golden: So how should retailers think about integrating voice agents and like IOT devices and workforce systems so AI. Can augment existing workflows rather than, I don't know, fragment them, re them, keep them fragmented. What does that look like?

[00:32:23] Nolan Wheeler: You wanna go, Jeff, or you want me to go?

[00:32:24] Jeff Strasser: Go ahead. You can get us rolling.

[00:32:26] Nolan Wheeler: Yeah. It, so a lot of it comes down to there's a lot of just day-to-day repeatable things that occur, and it's a matter of like, let's leverage some IoT to assist with that. You know, I work with a retailer that does a lot of cash in their business, and it's a matter of like, what does that process look like right now in terms of requesting just the simplicity of, I've got 15 grand in my till.

[00:32:47] 'cause it's a really high end group. Can you come and grab, you know, escorted security to come and help me with my drawer. Those repeatable tasks. Even that customer assistance task of, Hey, I get it, you've had to lock up a bunch of your merchandise, but you [00:33:00] know, I've got my iPhone and Amazon sitting right here, and you've got a bunch of friction sitting in front of me, and I don't have a positive feedback loop in terms of what that looks like.

[00:33:07] It's that idea of are you really coming out with size 12 or are you, am I never gonna see you again? So I think IoT and voice in that positive feedback cycle all through the mobile device. Just like you said, Ricardo, with you know, almost like the McDonald's like experience of there's my menu board and there's my order number and I know I'm being served. The Uber effect. You know, that's a lot of kind of where we're at today.

[00:33:27] Jeff Strasser: Well, and let's go back to the shoe example. Like if you're, if you're in a, you know, maybe a discount shoe retail, right? There are big stores, you know, there's, there's a lot of stuff on the shelves, but you're, you're digging through things. There's not enough people in store to help you. Like there may be in like a small boutique store or a specialty store.

[00:33:43] And if you had a mechanism like on your device to say, Hey, I can't find. I can't find this product, but I really want it. And it would notify somebody in the store room or maybe somebody who's, if it's, really small, small staff or light on staff, somebody at the, at the cashier who's not [00:34:00]working with another customer, and it would keep you up to date on the phone.

[00:34:03] Like, Hey, they've acknowledged that you're looking for this product. They're going to look for it. You know, hang tight, keep sitting where you are look at some of their shoes and we will, you know, we'll or maybe using beacons like, we'll know where you're in the store and we'll bring it to you.

[00:34:15] And so like that feedback level is so valuable. Like when I think about the scenarios that I run into back to buying shoes.

[00:34:22] Building Effective AI Agents

[00:34:23] Jeff Strasser: But, but also the thing I love about the technology and, and like the agent architectures that we work on with customers is, you know, no one's talking about this in the context of, legacy radios with voice agents. We talked about Zebra devices, which could be, you know, screen or voice to the same agents, but there's, legacy processes that, like call buttons, which may just be may just be push a button and, and it lets you know what's, what's happening. Or it could be voice enabled, right?

[00:34:48] Or you could have mobile device. Voice enabled or text enabled, but the architecture of the agents can be built and exposed to all these different endpoints. They might be, various tweaks, different instruction sets, different limitations of [00:35:00] what it exposes to a consumer versus to an employee.

[00:35:03] But the general architecture and like the, the data behind it, is the same, and it's just where you plug them in on your digital experiences, your voice experiences in stores, your, your customer experiences in the store. What's available to the staff via, RF radio. So these things scale really well and they can address like, pain points that a lot of people are having with very similar architectures and data on the backend and small tweaks to those kind of instruction sets or what the agent's being asked to do.

[00:35:30] Right? If your, your agent's gonna talk differently and maybe. A little bit more thoughtfully to a customer, but with an employee, you wanna to be really short, like short, precise, move quickly. But customer, you wanna be a little bit more thoughtful and understanding. And and so that's just a, that's a cool thing about the technology and how all these things can be built and how they can talk together.

[00:35:50] There's so much scale that can come from the right design and the right architectures.

[00:35:54] Nolan Wheeler: Jeff, I, I just want to add to what you, 'cause that's brilliant. You gotta build that agent, you see you, you've [00:36:00] gotta get that repository and you've gotta get all that documentation, right? And then you build that agent and then it's really a matter of democratizing the access to it. We know of so many frontline folks that have built these agents and then the usage is really low because the could, because it gets back into that complexity, right?

[00:36:14] It's like, okay, now I gotta go get my Zebra, or, and now it's like my password and I don't have it. And this is like, it's hard enough to even get folks to be engaged with their payroll password, right? So it's a matter of like, how do you democratize that access? And it kind of comes down to like, okay, let's look at what's easy.

[00:36:27] Voice is the easiest, right? So there's no password. And if there is a password, it's trivial. And or very shortly will be just voice enabled password credentialing with voice. But it's just a matter of even just going to a phone and picking up a regular phone and just hitting pound, you know, you know.

[00:36:42] Whatever, 2, 2, 4, whatever it is. And, and now, you know, getting that just locally off of your telephone system to ask that question, it really is just we just have to meet people where they're at. And we've seen it already, Jeff, with folks that have had, had agents and, and the usage is low. You make them voice enabled [00:37:00] through legacy equipment and the usage skyrockets.

[00:37:03] Jeff Strasser: Yeah, the the technology is so powerful. I, I like to think about it like, you know, self-driving cars, right? So self-driving cars are amazing, but it requires a massive investment to have one, right? You have to buy the car. It's not just about like, what's in the cloud that will enable your self-driving.

[00:37:19] Well, think of, the analogy here, the parallel to that would be if you could have self-driving cars on your existing car. Just by upgrading the software on the backend, like how cool would that be? Well, kind of, this is where we're heading. Like maybe it's not a one-to-one. Like there may be better higher levels of fidelity or things like that, but if you could go, enable a huge portion of the value of the self-driving car from your current car without any incremental, like, you know, another 50, 60, $80,000 investment, like that's a big deal.

[00:37:46] And so that's kind of where, where we're, we're heading together. From a retail standpoint, we can enable a lot of this really cool, really impactful AI technology using hardware that's already there. That's a way to get started faster. And, and if there's one thing we talk to [00:38:00] our customers about, like the, the way to make an impact is just to start.

[00:38:03] Don't wait, don't wait 10 years to find the, build the right strategy. You're gonna be 10 years behind and efficiency and margin impact and all these things that are gonna make you less competitive. So start now and then you'll iterate and iterate and iterate and invest and iterate. And.

[00:38:18] Ricardo Belmar: Right.

[00:38:21] Starting with AI: Metrics and ROI

[00:38:21] Casey Golden: What are, so speaking of starting, what are the right metrics to track? To know when AI's been introduced to the frontline to know what's delivering measurable results like the fastest. What is that quickest, ROI, so that anybody ready to start understands like, this is what you're chasing first.

[00:38:42] Nolan Wheeler: I get asked that a lot, so I don't mind starting this one off, Jeff, in the sense that I am, we always find that folks learn what they can do and then suddenly they go oh, where, where, where should we start? What agents should we build? And, and we're always actually trying to like pump the, pump the brakes and say, let's just hold off.

[00:38:57] Let's do a 90 day harvest of data, [00:39:00] whether that's PTT data on a Zebra, or whether that's radio data or comms data over the phones, through paging or whatever. It's let's not speculate and just guess and let's just build this agent. Let's let you understand what the problem is. Let's use a ton of co-pilot to understand where that goes.

[00:39:13] And now we'll actually have a ranking system to say, we're gonna start with this one because the data says that it's best suggested, and we're gonna go here and here and here, and we're gonna watch all that PTT traffic to see that we're actually driving it in the right direction, and that we haven't created what Jeff said earlier, which is, I've got a bad ankle and I'm gonna sprain my other one because I'm, I'm, I'm over indexing it.

[00:39:32] Right? So that's where we love to live, is let's just slow down and look at where this novel data is that you're not listening to, to drive that decision.

[00:39:40] Jeff Strasser: Yeah, and, and I, I'll go back to what we were talking about earlier with kind of just, establishing the process and the platform on how you're going to tackle things. Because once you have that data, you wanna be able to iterate quickly, and every part of the business is gonna have a different metric.

[00:39:53] So I think it's, it's hard to say like, what is the one metric it could be. Loss. It could be just [00:40:00] top line sales. It could be a certain, a certain department. It could be a certain product, it could be a certain brand. It could be, minimizing returns or impact on returns. I think there's so many different, different metrics, but being able to iterate quickly, okay? We're gonna deploy an agent and experience to our employees that's gonna, are, we're attempting to address, metric X by doing Y and we're gonna go do that for 90 days. And if we start to see movement, we're gonna double down on it. And if we don't, we're gonna quickly iterate into something else.

[00:40:26] And when you have the platform and the tooling in place, you can quickly iterate. If you're going kind of bespoke, Hey, we're gonna spend a bunch of money, buy this thing, implement it for six months, you're kind of, you're kind of committed and no one's willing to back up on that. And that's where you get into problems where there's massive investments made and everyone's afraid to say, Hey, this isn't working.

[00:40:44] So everyone just keeps dumping more money into it and more money into it. And it, and you start to lose the, you lose the, the mind share, in the frontline because everyone's seeing that this thing isn't working. But somebody spent so much money that they, they can't, they can't say, Hey, this thing I spent, you know, $5 million on in the last.

[00:40:59] You know, eight [00:41:00] months was a failure, and so it just like x-rays a cycle of, of bad things. And so think about the process and the platform and the iteration, and to Nolan's point, collect the data upfront. And then you have a list of things to work through and work through them quickly and find value.

[00:41:14] Double down, no value. Skip, maybe you come back here.

[00:41:18] Ricardo Belmar: Yeah.

[00:41:18] Overcoming Barriers to AI Adoption

[00:41:27] Ricardo Belmar: Is, is that the, is that sort of the, the secret to kind of addressing any skepticism that may come up from either operations team or, or other store, frontline store folks who are, who feel like they're trying to preserve some autonomy and, and maybe are concerned this is gonna take away from that because they're not sure what the expectation is.

[00:41:35] Is that really the, the answer is to kind of tackle it that way with a more bite-sized approach once you've gathered the data and just keep iterating.

[00:41:43] Jeff Strasser: Yeah, I, I think it is. And I think getting the store's input as well you've gotta do, you, you can capture a lot of data, but talking to, there's, there's no, there's no replacement for having human

[00:41:54] Ricardo Belmar: Mm-hmm. Right.

[00:41:56] Jeff Strasser: and, you know, doing your store business and understanding what's working and where do you need help.[00:42:00]

[00:42:00] Oh, we need help because this notebook you have that's now covered in grease and dirt and, oh, I can't look up PLU codes on okay, great. We can probably fix that problem relatively quickly. Or you know, in the bakery there's a manual and I have gloves on and I'm covered in whatever, flour and sugar.

[00:42:16] I don't understand how I'm supposed to flip the page. Great. We can probably, put that in your ear and deal with it. So, you know, I, I think getting the input, like maybe even if it's not the hardest, the highest ROI, the things that can be impactful to the people carry an ROI of their own, whether it's in employee satisfaction or it's in reduced churn which ultimately does impact impact the cost of business.

[00:42:38] Yeah.

[00:42:39] Nolan Wheeler: I, I love what you said around, basically, I think of this as simplicity, Jeff, like AI came out and got, you know, well, I mean in terms of the mainstream chasing effect, executive C-Suite says we got, what are we doing on this? There's a bunch of pressure and then it becomes like the art of the possible and you know, I'll give an example.

[00:42:55] We were talking to a DIY retailer and their agent is about building [00:43:00] codes and like walking a customer through, well, this is the installation that you need and need to do this and this, and this. Super highly complex and literally no usage. It just needs to be like those simple things and like some of the things that work for us the best.

[00:43:11] It's just like the cashier agent, you know, just here's all your produce codes, here's all your bulk food codes in your ear, and instead of flipping through the book that has not been maintained and it's got sticky notes in 12 different colors of pen, you know. It's not that sexy, but it's a massive cost savings.

[00:43:26] It's got implications in terms of half the time it's, I turn around as a cashier to the other cashier and interrupt their transaction as well to say, what the heck is the code for this, you know, weird ethic item that I, I'm not familiar with even, even in my own culinary experiences. So a lot of it to your point, is like simplicity, but like where the rubber meets the road and where it impacts customer and, and the associate in the store.

[00:43:47] Jeff Strasser: And, and, and then you can get, over time, like that's EE Easy path, right? That strange, strange looking item. Maybe you don't even know what, what it is or how do you ask the agent? You know, this bizarre, [00:44:00] fruity looking thing that I know came from the produce section, but I don't actually have any idea what it is.

[00:44:05] You know, it can be something that you can start to describe. Right? And so you describe it and then the agent in your ear can say, Hey, I believe that's fruit X, Y, Z and this is, this is the code. And then, you know, longer term, yes. Like when you're, you're doing that at scale, you could get to computer vision, all sorts of things where it just.

[00:44:21] It sees an image of, it detects what it is and the codes automatically in our system. But that's a lot of work and a massive amount of capital investment. You know, that may, may be worth it in the long run. It may not be worth it in the long run, and it's a lot easier to just say, you know, shiny red thing.

[00:44:35] It's about the size of a baseball. What is it? It tells you, and here's a code

[00:44:40] Nolan Wheeler: And, and the, the customer who picked it off the shelf knows exactly what it is. So it's just Hey, I'm sorry, but what is this? And it's like, well, that's a dragon fruit.

[00:44:47] Jeff Strasser: also

[00:44:47] Ricardo Belmar: right.

[00:44:48] Nolan Wheeler: And it, and it's just and then you just talk PLU for dragon fruit and two seconds later, bang, you've got the PLU, right? So I, I'd like to see anybody else grab the bind, the three ring binder from 85, [00:45:00] find dragon fruit better than

[00:45:01] that.

[00:45:01] Ricardo Belmar: Right.

[00:45:02] Yeah. Yeah.

[00:45:03] Casey Golden: All right, so then at the end of the day, what privacy, security and governance controls do retailers need to put around voice and the LLM access? So sensitive data and brand guidance.

[00:45:16] Ricardo Belmar: Hmm.

[00:45:17] Casey Golden: Remains protected.

[00:45:18] Nolan Wheeler: So one of the things that we've been doing is we have a plurality of different agents in terms of the, the name of the agent, right? So we've got maybe generalist help. And maybe we've been, we're okay as a retailer or as a frontline worker business to say, you know what, we're okay with ChatGPT or we're okay with OpenAI.

[00:45:35] And that agent's name maybe is Toby but maybe there's another agent that just is, is boxed in. And when it's a sensitive question, and maybe that's Enzo, you ask Enzo what that question is. So what we've been doing is we're saying, okay, based on your level of, of, of comfort. Let's create this plurality of different agent names that curates the size of the, of the dog yard.

[00:45:56] And then that's where the data can be substituted and put in [00:46:00] there. And then a lot of the times it's just gonna have to come back and say, this is just not something that I can help you with. Go and talk to a manager. Go and see this. Go and log onto this web portal, so on and so forth. So we've been ring fencing it based on name associated with privacy and the implications thereof.

[00:46:15] Jeff Strasser: Yeah. And, and, and from my perspective, it's exactly what I covered. So I, you know, I'm not gonna, not gonna repeat myself, but it's, it's. Getting on the platform that, that you feel comfortable with as an enterprise that has the security controls and the governance and the compliance and the regulatory approvals and all of those things, because that checks a lot of boxes.

[00:46:33] Yes. It's gonna be up to you or partners like Nolan to as you're building those agents in detail on what can access what and how can it talk back to you and all those things. But but if you don't know where these agents are running or where the data's sitting, that's, that's your risk profile, right?

[00:46:48] And, and a lot of the issue in kind of chasing bright, shiny object is you don't know where a lot of these things e exist, how they're built, now anybody can, probably vibe code their way into a startup, [00:47:00] in a couple weeks time. Like you. Who knows what the security architectures and foundations are behind that, and where the data's sitting and what the controls are, and who has access to the, you know, the you know, the admin portals of those things.

[00:47:13] There's a lot to be concerned about when you're just plucking things off the shelf.

[00:47:17] Casey Golden: for sure.

[00:47:18] Ricardo Belmar: Yeah. Yeah, absolutely. So, so I mean, these are all great examples of what, what retailers can be doing right now, today.

[00:47:24] Future Capabilities and Getting Started

[00:47:28] Ricardo Belmar: If we, if we start to look ahead and you think about, what are some of the capabilities in your minds, you're thinking that retailers could be doing, over the next 12 to 24 months that maybe they haven't started into yet, but that you really feel, there, there's the power to do with this technology that AI can enable for them.

[00:47:42] And how should retailers start to prepare for that, just in terms of, their own people, the processes to really capture that potential value. Now, in that timeframe.

[00:47:51] Jeff Strasser: I, I think you just have to start from a cultural standpoint, like we said before, just get started, right? Start with these, start with voice. Start with simple agents, things that improve the process for [00:48:00] the employees and the customer in the store. And focus the impact there to build your process and build your learning and build the impact and show, hey, there's ROI in investing in these things, which we know that there is when they're done right, and they're targeted at actual problems or opportunities.

[00:48:14] But I think the long term's amazing, right? So now you start getting into things like using cameras that you know exist in the store or could exist, and as the fidelity of those cameras and commuter vision improves back to the beginning of our conversations, right? You see an issue, a merchandising issue, or you see a product that's sitting on the floor that shouldn't, should be on the shelf and has fallen over, right?

[00:48:33] Automatically generating tasks. Assigning it to somebody. And then, you know, not only are you capturing the process, you're capturing, Hey, this product keeps falling off the shelf at like every store. What's the issue with the box or the, or the, the shelf or something's going on here. That's wrong.

[00:48:47] And so there's not only a data to be captured, but a lot of automation in in the operation of the store itself. Kind of daisy chaining all these amazing technologies that exist, but it's not a replacement for getting started. You [00:49:00] can't just start you know, at the, at the most, at the coolest, most high tech thing.

[00:49:04] That sounds amazing because you won't, one, it, it'll be you won't be successful, but two, you won't have the support of the business. And that business being the frontline employee all the way to the CFO, who's writing the checks, that this is actually gonna be worth the investment and worth the time to learn and implement in the store.

[00:49:20] Nolan Wheeler: Yeah. Jeff, I mean, thank you for that answer. 'cause it parlays easily into mine, which is, I think people are just fearful of starting. And I think that, and the reason why we, the genesis for us, the reason why we got into legacy comms is that we were losing so many opportunities because the response from the business would be like, we love what you guys are doing, but we just, we're not there yet.

[00:49:40] We're not there. And you've heard this and, and a bunch of your team have heard this, you know, without me, right? It's like their world is our world as well. It's like the excuse or the reality is, well, we don't have enough of ruggedized mobile compute devices, so this is a no go. This is a blocker. And then even if they do we don't have a device strategy on terms of shared device or identity or login or whatever the case may be. So [00:50:00] then that's another blocker. The, the thing that I love the most from 2025 that I've stolen from a retailer is they told me, you know, Ricardo, you and I were talking about NRF before we started this call at NRF last year. A retailer that's got 4,000 stores and over a hundred thousand devices out there, predominantly radios.

[00:50:16] They said, we're just in device purgatory. I'm like, whoa. You know, they, they just need a bridge. And again, that's where you've talked about Jeff. You're like, people just need to start. So once people realize that they, they can, this related to each other, would love to put a zebra in everybody's hands, but they're like, buy a hundred thousand devices tomorrow. You know, there's no interoperability gateway, there's no it's just we're fearful and every single year we say we're not gonna use radios next year. And every single year they approve the budget for radios, 'cause they're stuck again in that purgatory.

[00:50:45] And I told them when they said it, I'm like, I'm so stealing that in terms of kinda like the reality and the pain of where it is. So once you realize that AI has kind of taken the ability to take legacy voice and then with an interoperability gateway connect. You know, traditional legacy [00:51:00] voice with a modern zebra device.

[00:51:01] And now you can slowly roll and now those a hundred thousand devices, now it actually can be, let's, for the next five years, buy 20,000 devices and slow roll those management supervisory full-time staff. And then at the very last moment, it's gonna be that seasonal associates' gonna have a zebra in their hand.

[00:51:18] At least now they have somewhere to start and they can get out of the purgatory.

[00:51:21] Ricardo Belmar: Yeah, that's a great point.

[00:51:22] Casey Golden: Has been a great discussion about AI enabling frontline store teams. I really appreciate you both sitting down with us and teaching me and our audience a bit more on how AI can help these associates and help customers by removing a lot of the friction with in store ops and having flashbacks this entire hour going, oh wait, oh.

[00:51:48] Ricardo Belmar: Yeah. Yeah. There's just. Yeah, there's so much I think, to take away from, the collective insights you've both shared today. Hope that our [00:52:00] retail leaders who are listening or are watching this episode, they're thinking more now about how they just need to get started. I, I think maybe that's probably my top takeaway, right?

[00:52:07] Is that all these various things that you both mentioned, the key is just get started. So I guess maybe before we, we go and before we close out lemme ask you no one ask you, first you, if someone in the audience wants to reach out to you, learn more about what you talked about today, connect with you on how you and and sync can help, what's the best way to do that?

[00:52:25] Nolan Wheeler: Yeah, no, for sure. I mean, hit me up on LinkedIn. You can DM me. Um, go to the sync tech.com page. There's a lot of information there about AI radio and some of the stuff we talked today. Jeff and I have a YouTube channel that we do modern Work Monday, where we talk a lot of these topics.

[00:52:38] You know, at the end of the day. This truly is just about access to information. People just don't know that this is out there and they're living in the purgatory and they're living in that world. To, to your point before I pass it to Jeff, it's like step one for a lot of these folks is let's just start transcribing some of this voice and just understanding the reality of what the frontline is really going through.

[00:52:58] When you know that, that, that [00:53:00] corporate visit, somehow they all know that. The corp visit is happening and that store looks better than it usually does. So it's just a matter of here's, here's the reality and here's how we can best support people because we're living a true world versus a world where we just spent a bunch of labor to make a store look good.

[00:53:12] Because we know in 48 hours

[00:53:15] Casey Golden: So it says

[00:53:15] Ricardo Belmar: Right.

[00:53:16] Casey Golden: through or whatnot.

[00:53:18] Ricardo Belmar: Yeah,

[00:53:18] Yeah.

[00:53:19] Casey Golden: I got those stories.

[00:53:20] Jeff Strasser: Yeah. And, and likewise for me LinkedIn. LinkedIn is great. Connect with me there, you know. Absolutely shoot, shoot me a dm. It's Nolan and I could, could, could go on for hours having this conversation. We do. But we'll we try to keep it pretty concise over, over, talking with, with y'all on our, on our calls.

[00:53:37] But yeah, it's just like, it's super exciting and, um, like we said, get started, partner with, with technology providers that you trust that have experience, and, you know, and, and don't try to, don't try to bite off more than you can chew. Go be successful with, with small wins and parlay those into, into bigger bigger effort.

[00:53:54] Nolan Wheeler: Yeah,

[00:53:55] Casey Golden: This is great. Thanks so much, Jeff. Thank you, Nolan.

[00:53:58] Nolan Wheeler: thanks guys.

[00:53:58] Jeff Strasser: Thanks guys

[00:53:59] Casey Golden: Ricardo, I'd say [00:54:00] this is a wrap.

[00:54:01] Show Close

[00:54:07] Casey Golden: If you enjoyed our show, please consider giving us a five star rating and review on Apple Podcasts, Spotify, or Goodpods. Remember to smash that subscribe button in your favorite podcast player and like, and subscribe to our YouTube channel so you don't miss a minute.

[00:54:23] I'm Casey Golden.

[00:54:25] Ricardo Belmar: Please follow us on social and share your feedback at Retail Razor on LinkedIn, Blue Sky Threads and Instagram. Subscribe to our Substack newsletter to preview the best highlights from each episode and get bonus content right in your email inbox. Visit our website at retailrazor.com for transcripts and more info about each episode and our amazing guests.

[00:54:45] The Retail Razor Show is the original show in the Retail Razor Podcast Network.

[00:54:50] I'm Ricardo Belmar.

[00:54:51] Casey Golden: Thanks for joining us.

[00:54:53] Ricardo Belmar: Until next time... Stay Sharp. Stay Human. And Stay Ahead.

[00:54:56] This is the Retail Razor Show.

[00:54:58]