Vusion & Microsoft On Why Connected Stores Are Becoming a P&L Priority in 2026 | NRF 2026

Welcome back, everyone to day two of nrf.

This is Amitakh Retail.

I'm Anne Mazinga.

And I'm Chris Walton.

And we are coming to you live from the viewsion booth number 4921.

We will be here all day with loads of interviews for you, including the one that we have kicking us off right now.

We'd like to welcome to the Omni Talk stage here our two guests.

The first one is Jim Norad.

Jim is the chief Operating Officer at Vuzion.

Welcome, Jim.

Thank you.

And next to Jim is Gina Ayala Claxton, the CVP of US Retail and consumer goods at Microsoft.

Welcome both of you.

Thank you.

Thanks for having us.

How's day two of NRF going so far?

We're not yet a cup of coffee in, so we'll see soon.

So getting you fresh in the morning.

Exactly, exactly.

Well, why don't we kick things off by having each of you introduce yourselves to our audience.

And Gina, let's start with you.

Yeah.

So thanks for having me.

I'm Gina Claxton and I lead the retail and consumer goods business for Microsoft.

And so the teams that engage with the retailers and consumer goods companies in the U.S. excellent.

And Jim, tell us a little bit about your role at Fusion.

What are you.

Well, first, I just want to say super excited to be here.

I love Yalls podcast.

First timer.

Yeah, we've been talking about it for a while.

It's good to have you first timer.

On it, but not first timer listing.

I am not.

And loving.

The content's always great.

You guys do such a great job.

But basically 30 years in retail CPG, you know, kind of selling and interacting between the two, 10 years with our good friends at Microsoft prior to Vusion in the last year here.

So it's been heck of a journey and a lot of fun.

Excellent.

Yeah, excellent.

So Jim, I'm curious, let's start with you.

So in you have a lot of conversations with retail leaders, right?

And so what shifts are you seeing that's driving the urgency around the idea of connected stores?

Like, are you.

Well, one, are you seeing a shift?

And then if you are, what's driving that?

Yeah, the shift that we're seeing is really e Comm related, right.

For the most part.

So if you think about, well, you think about all them trying to pick in store.

Right.

So the efficiency of the pick, making sure that the basket that they're trying to pick is accurate because as you know, you know, if we're, if, if they're picking at 91%.

That means the consumer still has an item that's missing right in the basket.

So that lack of satisfaction is playing through the consumer is not a good experience.

And they're going to send them to another, another retailer, which is usually not what they want to do.

So I, I think, you know, that's probably one of the things that are driving it.

And then on the other side of it, just the labor challenges, cost of labor, those types of things, you know, in the store are driving the need for more and more automation and connectivity.

So, Jim, so, so I want to stop there for a sec.

So what you're telling me is it's the operational needs that are driving the retailers versus the vision of like the connected store and being able to understand, you know, how people are moving through spaces like you would an E commerce browser.

What's really getting people excited is the operational dynamics of the bottom line.

Yeah, I think that's the start.

But I think they're also realizing that, that the other element is there as well.

So much of it for me is who I'm talking to at the retailer.

Right.

If I'm talking to the operations people, they care about, you know, the labor situations in store.

Right.

Making sure prices are right.

Right.

Having availability of those folks that type stuff.

But if you're talking to the cmo, right.

Or you're talking to the E Com people, it's a completely different conversation.

So the biggest thing I'd say in my role, knowing who you're talking to, because the angle.

Jim, how many of those conversations have you been in where you're.

It's the first time that those teams have connected on something like connected store almost all.

I mean, and you would really be surprised.

It's like you would think that with everything going from a retail media perspective and them just sweating every asset they have and trying to squeeze every penny out, they still are so siloed as organizations and trying to collaborate together to get to a better end state.

That's why when you see what Amazon is doing, it's like everything that they're doing seems so tightly knitted.

Walmart as well, with Walmart.com and all those different things, I mean, how it's kind of come together versus being siloed.

It's.

It's interesting that they're not there yet.

Yeah, it's an interesting nugget and takeaway though, like, because, you know, from our perspective and having been in retail, like, you know, the merchant merchandising marketers, we've always kind of Been on this idea, but I'm guessing now because of the operational challenges, the financial people are coming to the table and that's driving the conversations to happen more regularly.

I think it's that and then the opportunity to overlay kind of all this new data with AI.

You know, if it makes it easier.

If you think about the operational angle, if you're talking to those folks, being able to reason over the data and make decisions, better decisions, faster than they've ever have before, it's amazing.

But on the other side, from the consumer perspective, being able to help them with shopping and that type stuff, you know, so the data is helping in both areas, but really just trying to set the conversation up the right way with the right person can be difficult at times.

All right, Gina, how do you think about what Jim just said?

Elaborate that a little on that a little bit for us and tell, tell our audience kind of what micro Microsoft's perspective is there.

Yeah, I think zooming out a little bit, the drivers that we also see are, you mentioned margin compression and all the operational decisions that need to be made faster, greater insights.

Empowering the store managers to make those decisions is of course a huge driver for the backbone and the infrastructure that enables that.

But the very personalized customer experience and an integrated customer experience between the different channels that is also driving the need for these types of capabilities as well.

So there is a top line and an efficiency opportunity in the stores.

And we're seeing nearly every retailer rethink how they're going to serve that experience while take advantage of these innovations in AI to drive this new kind of level of efficiency.

Got it, Got it.

Well, Jim, I want to go back to you here.

So let's talk about what the components or the anatomy of the connected store are based on the objectives that you mentioned that retailers are trying to get to.

What does that look like?

Well, today, you know, in most of the stores that you walk in the U.S. right.

They're still very analog, very paper based.

Yeah.

So the idea is to really help digitize those stores so we have data to reason over to help them make better decisions faster for us.

It's all kind of attributed back to our BLE technology and what we're doing from an AdSense perspective.

Oh, okay.

It's allowing us to, to help bring new data sets again, you know, whether it's pricing, whether it's planogram compliance, one of the biggest ones that you guys having been retailers forever on shelf availability, you know, being able to improve that metric is huge to the bottom line, huge to consumer satisfaction as well.

So being able to light those things up in a new way versus depending on the store manager or an associate to walk down the aisle and try to figure out, hey, is the price right?

Is there a price tag up, is there product out?

How do we deal with that?

Being able to do it in a real time automated fashion, it just makes all the difference in the world.

Jim, go back to what Anne said about anatomy though.

Like is, is there a, is there a system that you would recommend?

And Gina, you can jump in here too if you have any opinions on this.

But Jim, is there a system that you would recommend in terms of like, you know, what is the head, what's the heart, you know, what are the, what are the appendages that are maybe nice to have but you could probably live without?

Like is, how, how, how should you think, how should we think about that for our audience?

Yeah, I guess the thing to me is having been, you know, in retail for a long period of time and seeing this technology evolve, you know, it's, the technology that we sell is pervasive and it is, it's rolled out, you know, in different places in the US but so much of it is HF technology.

And the issue with the HF technology that's there is that you can't have a two way dialogue, right?

We, I can send information right to that HF environment, but what I can't do is turn around and talk to the associate.

I can't interact with the consumer.

To me, the whole, you know, the heart of the whole thing, to your point, Chris, is Bluetooth, right?

Because 94% of consumers that walk through the store are carrying a device in their hand is Bluetooth enabled.

You know, every associate day, either is carrying a zebra type device or a Samsung device or something, you know, in the store.

All of those are Bluetooth enabled.

So to me, that's the heartbeat of the connected store.

If we're able to leverage that Bluetooth technology and again begin to interact with everything from the consumer and impacting their journey, offering, you know, offers coupons, wayfinding, you know, all the things that can be helpful there.

And then on the associate side, you know, accurate pricing, again, picking on shelf availability, the list just goes on and on.

So to me you can, you can invest in either one of these techs.

The issue is you can future proof yourself by leaning into BLE because it's an open standard that everybody is invested in, meaning the consumers, right?

You're not asking them to do anything Unique versus kind of buying legacy tech.

So to me, BLE is the heart.

Ble.

Wow.

Gina, any thoughts?

Yeah, I think then, in addition to that, the brains would be the trove of data that's available.

And today, so much of it is still on spreadsheets, on clipboards.

And so what we're able to do now Is leverage AgentIC AI to automate a lot of those workflows and make recommendations to store managers and store associates that really compress that time from signal to execution or delivery or fulfillment for the customer.

Obviously, it's all about speed.

In that experience, customers are demanding speed and consistency.

And so all of that data that's available now, the technology that then sits on top of these systems, can now drive that speed and enable it.

So the data is obviously the key to the whole experience.

And Gina, what technologies are required to get that speed from the perspective of the retailer?

Jim's talking about Bluetooth, but it requires a lot of technologies in the background to make that as fruitful as it can be.

So how do you think about that?

Of course, there's certainly the underlying infrastructure, the cloud infrastructure, the network infrastructure, that's a key component of that.

But then, of course, having your data, you know, in.

In a modernized form, in terms of consistency, in terms of readiness, that's going to drive or prevent speed in a big way.

So the data accessibility and the data readiness, and then on top of that, having an AI platform that is able to, you know, determine the right LLM for the use case, to provide the right security protocols for the use case, all of that observability layer, then enable speed because you're not having to kind of bounce in and out of different systems and use different protocols.

So at Microsoft, we truly believe that this platform approach is differentiating in the pursuit of speed and acceleration.

And it's really that kind of every layer of the stack can give you incremental speed and velocity if you're architecting it the right way.

Gina, how important is it, as a lot of retailers we're talking to are kind of inundated right now because there's a lot of point solutions available to them.

How important is it to kind of have that foundational layer, that cloud compute capability, for them to be successful as they're kind of removing, adding, trying to figure out what they're going to build, what they're going to buy, how that's all going to work and really be operationalized successfully?

Yeah.

In their stores?

Well, point solutions can certainly drive differentiation, and there's a Lot of them out there.

The challenge that you run into is the integration of the data across and also the risk, the security risk.

So our approach is really to provide a common platform, but also flexibility to leverage any LLM to work agent to agent across any vendor.

Because that way you can provide the governance and the common frameworks and the security, but you can also provide that openness for retailers to take advantage of the latest and greatest LLM out there or, you know, a point solution that is going to be differentiating for them.

So really a balance of both we're finding is kind of the perfect, you know, it's kind of, it's the perfect balance.

It's really a hybrid for the retailer to move fast, have that optionality, but still be enterprise ready for scale.

It's very easy to do these, we call them like science projects with a startup solution in a very small test case.

But when you're trying to scale to thousands of stores, you really do need that robust, that governance and that security architecture, et cetera.

It seems very important now, with the speed at which people are chasing the PR announcements, to be first in, you know, first one in to be able to say that they're using a specific technology.

Yes.

That's one thing that we kept hearing a lot at Partner Day day, Microsoft Partner Day earlier this week, is that you do need somebody who's paying attention to governance across the board and making sure that you're protected as you're making.

Taking these.

Yeah, these science projects to the store.

Yeah, yeah, I love the science project phrase.

And then also you said something else I thought was really interesting too.

I'd never heard the phrase before.

Absorbability.

Observability.

Observability.

Yeah, observability.

Oh, I liked absorbability as well in.

The context of what you were saying.

But I can pull that in too.

Right, that works too, Gina.

So, all right, so you guys gave us a very great background on kind of the anatomy of how a retail organization should think about trying to create a connected store.

So, Gina, I'm going to go back to you and we'll close it out on this for both of you.

What are the projects that you're seeing the retailers, when you're in their boardrooms, actually prioritize and how are they thinking about that prioritization?

It's exciting to be at NRF a year later where the conversations are all about proof points at scale.

People have now driven very significant agentic AI led initiatives and programs with business impact.

And where last year was all about going from Kind of MVP pilot to now going into production.

We're now starting to get a body of work with a lot of patterns and great lessons learned.

So I'll say that at this point are definitely prioritizing where they see b billion dollar opportunities in the P and L for efficiencies.

They're absolutely prioritizing where they can bring more capacity to their workforce in terms of enabling their store associates to be more productive, et cetera.

And then they're really also prioritizing that customer experience, that agentic customer experience for top line opportunities.

So when you about where they're going to drive the most efficiency, it's identifying your own internal business processes in merch, in assortment, in demand planning.

We're doing a lot of that work.

And then when it comes to the top line, it's identifying that whole customer experience from the chat box to, you know, to agentic shopping all the way through.

If you're going to deliver that personalized purchasing experience and moment, that has to then carry all the way through fulfillment and delivery and so, you know, customer support.

So how do they enable that?

That's a very complex workflow for a lot of these larger retailers that have a lot of kind of legacy processes.

So those are kind of the major areas that we're seeing.

And then of course enabling all the workforce to be ready for AI.

In our case, it's with copilot and making sure that adoption and change management is constantly happening so that people are driving new behaviors and new ways of working.

And you don't just, just deploy all this great, you know, technology out there and nobody's using it.

Right.

So.

So Jim, same question to you.

Close us out.

Yeah, I would, I first.

Great stuff, right?

Yeah.

But I would say when we're talking to them, they're, they're trying to figure out the investments that they're going to make.

How are they going to fund them?

Right.

How are they going to pay for them?

Am I going to open new stores?

Right.

Am I going to remodel stores?

You know, I need to do all these things to keep up, to differentiate, to be competitive.

But I can't do everything right.

So for us, the thing that we're trying to do is to show them how these things pay for themselves.

Right.

Or bring revenue right to the table as well.

We're trying to solve the traditional problems of again, labor, labor cost.

Right on chef availability, tying it all back to consumer loyalty and making sure the consumers are having a good experience.

All kind of driven by AI.

So to me it's, it's really looking at, you know, we're asking them to spend a lot of money.

Right.

To, to lean into these things.

But how do we make it so that they're going to get a $50 back for every dollar that they spend and do it in a quick fashion because it can't be something that has a 10 year payout.

So for us, we're really just trying to make sure that it is pulling money back to the bottom line and it makes sense for them and lets them differentiate.

Yeah.

I love that you got to prioritize.

You have to.

You do.

Because there's a million things they could do.

Yeah.

Million science projects you can run.

There are.

But it's got to work.

Right.

Well, thank you so much to Jim and Gina for taking Time with us today.

It was so great.

Thank you.

To have you here and to get your insight.

We will be back today with several interviews, so don't go any anywhere.

If you're here at NRF, come stop by the Vuzion booth, number 4921.

Come say hello.

And a big thank you again to Vuzion for helping us bring you all of our coverage here from nrf.

So until our next interview, be careful out there.