You Can Track Your Products’ In-Store Journey

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Data rules in the ecommerce digital world but is more challenging to collect in the physical world. But tracking millions of pieces of merchandise across your store floors so your customers and staff can find any product in real-time is now a reality. Unified commerce is here. Join Shelley E. Kohan and special guest Ronit Eliav, Chief Marketing Officer of Nexite as they discuss how virtual apparel tracking maps with real-time data lets your merchandise seamlessly tell you their entire life story — from the factory floor to their final destination in the customers’ closet. The win/win? A deeper emotional connection with the customer through trusted, transparent intelligence.

Special Guests

Ronit Eliav: Chief Marketing Officer of Nexite

*Transcript By Descript

I think AI is a hot topic. I think there’s also a lot of buzz around it. I think that a lot of retails are also a little confused on the different types of AI that are out there. So, and what AI can actually do for them. But if we think about it in the most simple terms, AI is meant to Okay. Help us do things that we can maybe do on our own, but maybe do it faster, maybe do it better, um, and automate a lot and use intelligence to really kind of delve and optimize.

Retail Unwrapped is a weekly podcast hosted by Robin Lewis and Shelley Kohan from The Robin Report. Each episode dives into the latest trends and developments in the retail industry. Join them as they discuss interesting topics and interview industry leaders, keeping you in the loop with everything retail.

Hi, everyone. Thanks for joining our weekly podcast. I’m Shelley Kohan. I’m very, very excited to welcome Ronit Eliav,  the Chief Marketing Officer of Nexite. And for those who don’t know Nexite, you will soon learn how empowering this company is in making retailers and brands.  by using real time data to drive performance metrics.

So one of my favorite descriptions used at the company, and I love this, is Nexite enables your merchandise to tell you their complete life story from the first stitches in the factory to their final destination in the customer’s closet. So let’s jump right in and welcome Ronit.  So thank you, Shelley.

I’m excited to be here today and to share what’s happening in our industry, specifically also with Nexite, our company, and with some of our customers as well.  Well, it’s great to have you here. And I know, you know, historically retail is really about connecting the customer, uh, to in a physical way, right?

It’s emotional and it’s those strong emotions that create that bond with the consumer. And also it’s that emotional connection that increases loyalty. It increases frequency of visits, higher spending. In fact, I read an interesting statistic that 95, 95, 95 percent of purchasing decisions are made based on emotional connections.

So what I love, Ronit, that you’ve said is quote unquote, retail is physical at heart. So tell us a little bit about that idea.  Yeah. So, um, I really believe that retail is a physical experience. Um, it started as a physical experience. What we’re doing is a physical experience. If you think about it, when you go to a store, um, You want to touch the items. You want to see the items.

Even if ultimately you purchase them online, you will want to feel your item. You will want to see what it looks like, you know, in the fitting room. There is a joyous experience to go shopping, whether you do it with your friends, because you want to turn it into a social setting, or maybe because you want to be on your own and you just need some time to get away.

I think that shopping in itself, where, you know, Retail provides us with an experience that is in the real world and becomes more meaningful when we touch and feel, um, and emotional, like you said, when you think about it in the real world, but even if you think about it from the retailers perspective, the retailer themselves Is a physical experience.

Think about it. They have thousands of pieces of merchandise. They have hundreds of stores, maybe thousands of stores globally, and they’re responsible for thousands of staff members across the globe. That’s a very real experience. These are not, that’s not a digital webpage.

That’s actually things that are physical and live in the world. And if you think about all of those physical experiences coming together like a puzzle piece, it really puts together. A platform in the real world with lots of data that the retailer can then use to better their business, to optimize their business, but ultimately also to better the customer experience at the stores in real time.

Yeah, I, you know, definitely. I think when we talk about the physical world of retail and shopping, you and I are very aligned on this. You know, it’s social interaction, right? And immediate gratification. I mean, those are the ones that really, in my mind, make that physical experience different. And the physical world has Always been more challenged with collecting data.

It’s very easy to collect data online, but it’s more challenging to collect it in the store. So maybe you can give us your view on this. Uh, I’ll call it digital world. Yes. So I think if we think about  e commerce,  And what they’ve been doing, um, over the past, you know, since specifically, I think, um, over the past 10 years, but even before that, um, is really about understanding what their customers are doing digitally and how they can improve that experience while they try to bring it out into the store.

But if you think about e commerce, what do they look at? They look at how many people come to their website. How long the shopper comes in, sits on a specific page. Does the shopper scroll down if the shopper scroll down? Was there something that a call to action maybe on the bottom of the page that would move them to put something into their basket?

How long something’s been in the basket? Sometimes as a shopper, you’ll get a reminder. Oh, you have some left in your basket that all of those things Um, actions are meant to optimize the sales funnel so that you could better so that you could better sell. Right? So you can better convert. But if you think about all of those actions, and even the words that we use sales funnel, um, abandonment, um, tracking of customers, those are all physical aspects.

They all have a real function. Physical point to them because they’re mimicking what’s happening in the real world. But in the real world, we have no way to really get this information. Besides, I want to say hearsay, right? Staff can tell you that, um, but it’s really hard to aggregate the data. And then once you have the data aggregated, it’s really hard to use that data for conversion because it is not, it’s very segmented.

Yeah, definitely. And that, I think that makes it a challenge, uh, more so in the physical world, right? One of the things that I want to ask you about, because, I mean, it’s the hottest topic out there, AI, AI, AI. Um, and I know y’all have been using AI for a very long time, but maybe you can tell us specifically, you know, how does AI specifically help physical retail, and how is Nexite using AI to advance the outcomes in retail stores?

Okay,  so I think I think is a hot topic. I think there’s also a lot of buzz around it. I think that a lot of retails are also a little confused on the different types of AI that are out there. So, and what AI can actually do for them. But if we think about it in the most simple terms, AI is meant to. Help us do things that we can maybe do on our own, but maybe do it faster, maybe do it better, um, and automate a lot and use intelligence to really kind of delve and optimize.

So, I think that there’s a lot of different AI solutions out there, but I think the differentiation between AI solutions that are out there. And the AI solution that Nexitebrings to the table is that  first time that we’re using AI with new data parameters. What do I mean to say here?  AI is based on data.

And for the first time, Nexite is creating real world data that doesn’t exist yet. So today you don’t know how customers are shopping your stores in a sales funnel type metrics, right? We don’t know what they’re seeing what they’re picking up what they’re trying on and then ultimately what they’re abandoning But when you take those new metrics those new data parameters and you actually use them you’re creating not only AI But you’re creating a new Form of output from the AI, something that doesn’t exist today.

So if I think about, um, things that we’re using AI to help solve in a very, uh, in the most simplest way is we’re able to take our solution and our machine learning algorithms will understand the customer journey of everyone through the store. But not just the path that they take in the store, but actually how they convert in different areas of store.

So what are, are there areas where people are picking up items and taking it to the fitting room more so, um, than, um, just picking up and going out to buy? Um, or is there areas that are abandoned? More were able to take all that data and build a virtual money map of the store. So it’s an actual replication of every single store within your chain and overlay it with all of our data so that you can understand what areas are more converting.

You can use that to better understand.  How to how to map out stores and what merchandise to put in your hot spots, the areas that convert best as opposed into cold zones. For example, we’ve had a customer who was able to understand that they had items in a hot spot that would sell just as well, even if they were in the farthest corner of the store.

It was just an item that was had very high conversion. And what we did was we identified that we can move that item to the  cold area and open up the hot spot area for items that maybe need more exposure, which is another use case that we support. Retailers will always tell you  That, um, they have no items in the back room or all of their items are on display or all of their items are displayed in the right place.

And what we learn time and time again, is that they’re not actually in the right space. Or maybe there is more items in the back room, or maybe there’s certain items that need more exposure because we see along the sales funnel that they move from the right place.  Our sales funnel, like I mentioned, shows that they were picked, tried on, and then ultimately purchased or not.

So, seen, did the customer see it, did they pick it up, and did they try it on? And what we can find out is, are there items that need more exposure in order to be picked up more? Maybe they need to be placed somewhere else in the store. And by identifying that very early on, or like I said, identifying, um, where something churned early on in the sales funnel, we can actually avoid things like overstocking, um, and coming to the end of the season, um, with that extra merchandise or really what I like to think about it in terms of in season optimization, we will really use our AI to make sure you.

You achieve full price sell through as quick as possible.  So it sounds like what you just described is one, you can help retailers with sell through percents and really, you know, selling through items within the store, but also conversion. Uh, one of the questions I have is that. You mentioned the fitting room and being able to track the fitting room.

Are there metrics and, and data around, uh, merchandise that gets tried on as opposed to merchandise that’s not tried on and, you know, uh, conversions with people that go into a fitting room, which those that don’t, can you get to that granular data? It’s actually, um, very interesting. First of all, we can get for the, get down to that granular data.

And what we’re learning more and more is that, Not all stores behave the same. Not all brands behave the same within all stores. Um, and even within clusters, you know, because if they’re breaking them down into clusters, some of the some of the, um, the behaviors are very different amongst merchandise amongst categories, um, amongst the floor layout.

And what we’re able to do is actually take the data and really localize.  Store assortments and allocation using that data to make sure that those items that are being picked are ultimately going to be sold. So, for instance, if we see that there are stores that require, um, genes to be, to be pushed at the fitting room more often, we preemptively let the store staff know, you know what, when someone’s holding up a pair of jeans, suggest that they go into the fitting room with it because they will convert higher.

While we’ll say to them, don’t waste time with. You know, t shirts. They don’t need to try it on. They convert very well. You can get very granular, granular down to the store. But what you can also do is take those insights, mimic your your best stores and actually teach those lower performing stores what’s happening at the best stories and maybe what they need to do also to improve sales.

That’s unbelievable. I love that. And I find it really interesting. I never really thought that within a brand, within a store, the conversion and fitting room behaviors might be completely different. So I love the fact that you could localize a lot of the data and make it really actionable, which is really key for retailers.

So, uh, let’s move into our, uh, kind of last big topic. And this is a big one. So really understanding, you know, the customer experience for manufacturing through end of life. So let’s break it down a little bit. And if we can start with kind of delivering that ultimate customer experience. It’s very complex process.

Everyone says, Oh, retail is so easy. You buy something, you put it on a shelf, you sell it. Well, no, actually it’s a very complicated business. And so one of the biggest frustrations and questions is, you know, understanding inventory location, like where is our stuff? Yes. I think, um, I think it’s funny, right?

You just put it on the shelf and it sells. No, it doesn’t really work that way. But I think if we, if we head back to manufacturing,  And we think about how do we make the decisions of how many we want to manufacture, um, how many do we want to send to each store, how many, um, do we think, um, you know, will sell.

I think a lot of that information until date has been to use previous sales and inventory data and to use a lot of gut feeling. I think one aspect that we’re changing is. You don’t really need to use gut feeling anymore. Now you have many different data parameters that you can use to make those decisions.

Data parameters from the live physical store. I also think that if you think about, um,  tracking, so you know what, you have the manufactured, you’re now sending all your merchandise out there and it all has to come to the right stores at the right time. Understanding where your merchandise is along the, um, along the supply chain is critical in making sure that you get it there on time to sell on time and that you get the right amount there to avoid overstock to avoid understocking.

Because you don’t want a customer to come into a store and not see something and to avoid overstocking because you don’t want to get to the end of the season with that extra merchandise, especially in Europe, where there’s going to be very strict laws about what we’re going to do with, um, with overstock.

So I think understanding the precise location of every item. First of all, helps you control that because I can now say, Okay, these items are here at D. C. They need to be spread out over here. But I think with next site, you have another extra element that says to you. And here’s how your local behaviors behave.

So you need to allocate locally to this X and to that Y. And these are the assortments that are the right assortment mix for those stores. So I think that’s the first. The first part is really understanding where the item is. And with our solution, you have what we call the location pulse. And, you know, in real time, Every 30 seconds where that item is located is specifically in the store.

And I can give another example. As I mentioned, you don’t want a customer to come in and not find something. It could be that the item that they’re looking for is in the fitting room, or maybe it’s in the bathroom. But when the customer goes to the shelf and doesn’t see it, they get lost. Sometimes they’ll go ask the salesperson.

If they have the patience, they’ll wait for the salesperson to look around. Maybe the salesperson will walk over to the POS, take a quick look. That takes time. It breaks the entire customer journey and the customer experience. When you have a solution that tracks not only real-time location, but availability, is the item even available to be sold?

So yes, it could be in the backroom, but maybe I’m holding it for my, um, my, um, both his stock, et cetera.  This helps alleviate that break in the customer experience.  Yeah, and that’s important because when you break that you said it so nicely about, you know, you break that experience and there goes that emotional connection.

It’s now the experience is not optimum, right? And it’s it’s then you got to recover from that. So I think that’s great. Um, another question I wanted to ask you is what are you seeing on the consumer facing side? So. I, I see all these, you know, back of house technologies and things that are helping and softwares and all that, but what, what is, what’s helping, what are customers expecting today when they walk in?

And what are you doing to kind of help aid that shopping journal journey on the front side?

I think that’s a great question. I think customers are expecting, I think there’s lots of things that customers are expecting. Right. Cause we know that customer expectations are through the roof these days and they deserve it. Right. Um, I think the first and foremost thing they’re expecting is if I came to the store for something, it should be there.

That’s the first, most basic step in the, in the sales process. But I also think they’re expecting the experience to be as comfortable for them as possible for some people that might be express checkout. They just want to, you know, check in and check out for others. It might be a much more personalized experience.

They want to be able to get all of the product information. They want to be in the store and maybe, um, have someone walk them through the store. I think there’s a lot of different customer expectations and a lot of different technologies, but I think one thing that brings a lot of it together is while we’re using technology, I think it’s important to remember the customer doesn’t want to have to learn a new technology.

Customers don’t want to come in and learn how to figure out your kiosk. They don’t want to go into a fitting room where maybe you’ve installed some sort of item to tell them all of their product information. And they’re thinking, wait a second, is there a camera in there or, um, some, you know, I don’t need that information while I’m in the fitting room.

Um, I think that a customer feels comfortable. With their own mobile phone. And I think when I use my mobile phone and I go in, if I can use my mobile phone to do check it, I feel safer because it’s my phone and I know what information I put into my phone. So I think while there’s lots of in store technologies, I think retailers really need to focus in on how they can use the customer’s mobile phone more so that the customer feels more at ease.

So one of the items I think that they’re expecting is to come in and see what they want. Another item I think they want to be able to do is to use their own mobile phone. And I think they want to be able to extend that emotional experience even post purchase. So if I think about it, the store has not, the retailer has an opportunity and the customer wants that opportunity as well.

So Just because I left the store with my item doesn’t mean our relationship ended. And I think when you have a lot of data on the merchandise that the customer purchased, you can really continue and, and that data can communicate through a mobile phone. I think you can really extend the relationship and create an emotional connection like you mentioned.

Oh, that’s amazing. I think, I think one of the other challenges with having all that software in a fitting room is that Then the customer spend so much time there and then now you’re fitting room conversions go down because people actually can’t get into the room. So I, I love the idea of the mobile phone because it builds personalization.

It builds the connection and they’re comfortable with it. Right,  so let me ask you. Yeah, go ahead. No, I was gonna say that’s right. I mean, in the end of the day, think about this experience. I’m on my mobile phone at home. I see a shirt that I like at a specific store. I then take my mobile phone. I go to the store.

Imagine I can get a full virtual map on my phone says says to me, walk through the store. Your shirt’s over here. But as soon as I get to my shirt, imagine a pop up comes up and says that shirt goes great with the pants that are to your right. And then I can walk over there and, you know, and then, uh, but I don’t see my size and then it says to me, don’t worry, there’s one available.

Just click here and you can notify someone to bring it out to you. That’s a great experience.  And that’s on my phone. Yeah, I love that. That’s amazing.  Um, what are you all doing any work in terms of post purchase? I know at the beginning of our podcast, we said from stitches to customer closet, what’s happening on, you know, once the customer leaves the physical store, what’s going on?

So that’s really up to the retailer. I, Our technology specifically is encrypted, um, with a lot of privacy, um, built into the tag itself. Eventually, what the retailer will be able to do is allow the customer to opt in, much like in GDPR, and then they can actually, the retailer can build out post purchase,  um, programs.

Using the technology that’s on the tag. So they’ll be able to offer things like Authenticity is this I that they could do even in the store. So is this an authentic? X bag, um, or, um, where was it created? All of the digital passport information that lives on the tag and that can go with the retailer or it can actually be moved to the customer.

But if you think about things that are growing, like secondhand market, resale, um, digital product content, that all lives within the tag. So if I was a consumer and let’s say I purchased something from a store and they, you Pass the tag over to me. I can opt in and then I can keep all of that digital data that I have from the tag.

And if I wanted to resell it on a second hand site, I don’t need to have it offended by a third party. The actual, it’s actually imprinted and embedded in the actual product itself. Um, the digital content is embedded in the product itself. So all of those events would be recorded and then given to the customer.

So it would help the resale market. It helps with authenticity. Eventually I could see maybe some of the big brands creating East stylist programs where they know that I purchased this item. I then can then, um,  Take the items, build an e closet with all of the items that I have. The e closet knows when I wear the items, and it can basically say to me, you wore those black pants last week, uh, this week maybe you want to wear it with this new blue shirt that we have.

So I think there’s a lot that you can do because the data  That’s amazing, and especially since the second hand market is so big. And I love the idea of the e closets, and you know who’s going to love that idea? All those Millennials, Gen Z, and Gen Alphas, they’re going to be loving this kind of virtual, you know, closets, uh, in the future.

So, that’s amazing technology, and it’s very helpful. Let me see if I can summarize key takeaways, and of course, I’m going to ask you to make sure I get these right. But creating, number one is creating the ultimate. Customer experience through digital retail from manufacturing through end of life, which is what Nexite does.

AI and data leads to control. So being able to control that journey and that experience. And lastly, and I know our listeners know building emotional connections with customers brings deeper loyalty, higher spend, longer lifetime value, but you actually have a tool that can provide Retailers, the ability to actually do that, which is great.

So if you had one piece of advice to give our audience, what would you say?  What must they act on right now?  I think shoppers, um, customer expectations, what customers want changes so rapidly. And like I mentioned earlier, retail is a puzzle. It’s about millions of pieces of merchandise, thousands of stores, thousands of staff members.

We want to make sure all of that is functioning correctly together at every given moment so that a customer can walk in and have the ultimate experience. And so that if you don’t. Meet the customer experience. You can improve it in real time right away so that you don’t lose that sale. I think you can’t do that unless you really understand how your shoppers are shopping in each of your stores.

And today, like I mentioned earlier, you may know what you’re selling, but you don’t know why you haven’t sold something and you don’t know where you had the potential to sell more. Had you had more out there? And those are two questions that Nexiteis answering.  I love that. Thank you so much, Ronit, for being here today.

It’s great. Great having you. Our listeners certainly got a very good education on the abilities and capabilities in physical retail stores. Um, I also want to, uh, tell our listeners about next week’s podcast, which is very exciting. So we have a great guest next week as well, who is a true American story.

We have Bayard  Winthrop, who’s the founder and CEO of American Giant. which is a company he founded to address what he saw as a lack of affordability and priced high quality American made products. So American Giant literally has the best and most well made hoodie ever. So tune in for that. And the last thing I want to say is I want to invite our listeners Hey, if you have ideas, comments, please make sure you go on to the robin report.

com website and under contact, you can send us your thoughts and ideas for future podcasts. Thank you so much, Ronit. Thank you, Shelley. Thank you for having me today.  Thank you for listening to Retail Unwrapped. We’ll be back in one week with another podcast. Please subscribe on Apple Podcasts, Spotify, or any podcast service.

If you have questions, ideas for a podcast, or anything else, please contact us via therobinreport. com.

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