The Digitalisation of Everything, with Barry McGeough

Barry McGough from Google's ATAP Innovation Studio breaks down how fashion is being digitized across three areas: 3D design and smart manufacturing, IoT-enabled garments like Google Jacquard, and digital experiences from AR try-ons to shoppable social media. He argues the digital experience layer will connect the ecosystem first, driven by consumer demand for seamless interactions.
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Hi and welcome to another episode of Fashion Made. I hope you're all doing well. On this week's show, we've got Barry McGough, who works in Google's Advanced Technology and Projects Innovation Studio. They're responsible for creating Google Jacquard and Solace platform technologies and turning new ideas into finished products. Um, so really interesting guy. Some of you might know him as former Group VP of Innovation over at PVH. Um, so obviously very interesting, someone who's been around the industry, fast tech and technology for a long time. So yeah, our conversation is pretty, uh, far-reaching, pretty broad, um, but also very interesting for anyone involved in this space. So, um, yeah, I hope you enjoy. On today's topic, the digitalization of everything. Uh, quite a broad one there.
Yeah, it is, but it's real.
Yeah, for sure, for sure. Talk to me about the digitalization of everything within a sort of fashion retail apparel context.
So this is something that we've been seeing for a while anyways. I'll probably reiterate this in our talk, that what is happening with this concept of digitization of everything, a ton of gasoline has been poured on this fire. These things were actually well in process. When we talk about the digitization of everything, I think, depending on who you are, you have your own constituent point of view. So if you're a designer, you're thinking about digital design and product creation and designing in 3D. If you're in digital commerce, then you're thinking about the digitization of how you can sell. But really what we're looking at is this idea that we're coming to a very rapid sort of dénouement of end-to-end digital product creation that starts with the idea and then ends— those digital assets are created and then it works its way through the product creation and selling and commercial cycle and then even into end of life. So I like to think of the digitization of everything in our sector in basically 3 different buckets. First of all, I would think, kind of look at digital product creation and say, okay, what happens there when we're thinking about PLM, 3D design, those things that are sort of very well known to us? When those assets are created in 3D, then those assets are portable throughout multiple environments. When we start to look at, can we validate those things, then there are now data-driven research companies like, that are working on heuristics that can start to tell you test trends. Will it— is it desirable? Does it work for your brand? Is it on brand for you? Do you have any consumer insights? Eurotech is a great example of someone who's working on that right now, based in Paris. Then you start to think about what happens in the digital supply chain. So digital supply chain was starting to work anyways in terms of the digitization of everything. So you think about what happens when you're making product digitally. When you can start to automate manufacture. It also becomes a digital process because you're getting closer to that one-to-one manufacturing scenario. So then we start to think about, okay, well, if there's this digital product creation bucket, then there's also what we refer to as digital product. So digital product would be product that's connected to the internet in some way, shape, or form. So that's kind of— that's very much the work of what's happening at Google right now with Project Jacquard and Project Soli. You see what Nike's doing underfoot. Under Armour trying to digitize their physical product so that it's connected in some way to the Internet of Things and it starts to generate data and experience. And when that data comes around, you're able to interact with your product in unique ways. Can you gamify what you're doing? So for instance, if you are— if you're a runner, Or you're a cyclist and you're on Strava. You have an app and you can, you can, or MapMyRun, you can figure out where you're going and then see where other people are going. And then you can plan a route and then you can compete. So what have you done there? You just gamified running that you just did it. Now, if something's happening underfoot, that can give you data on how you're specifically running or training or biofeedback. Then all of a sudden that data can become more interesting. That is connected to the IoT. There's also— so that's very obvious, I think, when we talk about the digitization of product. The other component of it is the digitization of product and what we call XaaS, or the sort of anything-as-service model. So as we start to think about the digitization of product in different ways, not just is it physically connected to the internet, we can start to think about, product-as-service, software-as-service, internet-as-service models, where we're starting to create these digital assets. So, for instance, Rent the Runway or Farfetch, right? They are digitizing their product, but they're saying, okay, well, we can rent you something and then it has to come back. Well, how is it tracked? What are the mechanisms that it's tracked back? That's going to be a logistics trail, there's going to have to be some product identifier on there that can be scanned, maybe RFID, right? That product's digitized, and then its journey is also digitized. So if, as we start to look at different ways for people to transact, product will become more and more easily digitized. So you think about rental models, subscription models, think about Stitch Fix. The way Stitch Fix works is that it sends you a box of items that are based on your personal and demographic profile and psychographic profile. And then they want you to buy all 5 things. So when you buy all 5 things, it's great. They got it right. If you send back 3 things and you send back the cowboy hat, they say, okay, well, you don't like cowboy hats. We'll never send you a cowboy hat again. They use algorithms and deep learning or machine learning to learn more about you as a one-to-one consumer. So what they're looking for is increased consumer satisfaction, less returns, and a better business model, but they're using data to do that. So that box has just been digitized. So if you're thinking about this idea of digital product, there are two— there are several ways where product becomes digital. And this becomes even more important as we start to talk about the changing retail landscape What are different paths to purchase? And how can we start to increase consumer satisfaction and, if we're going to spark joy, right, in what it is we're doing with our end consumers? How do we get it right, better every time? That's the digitization of product. That's a huge bucket. But there's a third bucket, like the bigger bucket is the digital experience, right? So if you think about digital experience, there's a couple of different ways which we're starting to see that the digital experience is enabled. So RFID, it's been in our supply chain for years. It's becoming cheap as chips, right? So what are we doing now with near-field communication where you can embed, permanently embed a 15-cent near-field communication chip in a jacket or a backpack, and it takes you to a URL that gives you a unique consumer experience? With that near-field communication chip, take you back to a PDP page? Would that near-field communication chip take you to a brand's YouTube channel where they're constantly refreshing content? So you have a unique experience with that brand. That becomes CRM, that becomes know me, that becomes know my brand, relationship with the brand. So think about what's happening with QR codes. They're ubiquitous. I'll talk about this probably a little bit later, but if you think about what's happening in QR codes, that makes everything shoppable. So the QR code is the paper or physical manifestation of a consumer experience. So you hit your phone to a QR code and something comes up. It's ubiquitous in Asia, right? The NFC chip would be almost like an embedded QR code that never goes away. Because if you have a QR code on a hang tag, you rip it off and throw it away. But it's permanently in the garment. So what do we do with QR codes? How do we start to empower digital experiences with brands? so that we get that more robust relationship with them. So we're also looking at things like, you know, beacon technology is out there, but it could very be very, be very much like QR codes where beacons were sort of been there, done that, but they could definitely come back as we start to beam information back and forth to people that they feel is relevant. Um, energy harvesting Bluetooth. If there's a company called Wiliot who's doing powerless Bluetooth, So it basically lights up using ambient energy from phone or from the light in your closet, and it will be a beacon to give you data back. So what's the data that you can get back? You can walk through a closet with energy harvesting Bluetooth tags and everything, and you can take a physical inventory of everything in your closet. Or you can say, hey, you know, there's I see that you have, you know, a Calvin Klein jacket in here and it's September, maybe time to dust it off, or that jacket goes great with that scarf, right? So, or one of the use cases is these Bluetooth beacons have sensors on them, so these weight sensors can measure what's inside of a bottle. So if you're in a hotel and you drink half a bottle of Jameson, you get— they charge you for half a bottle. These are, you know, there's, there's a refresh and replan models that can happen when something— and I'm not just talking about apparel, but consumer goods are digitized in some way. And these— and certainly, it's super interesting for FMCG companies who are looking on replenishment models for everything from Tide to toothpaste, right? And then think about what Avery Dennison is doing with their everything model. But they're embedding the digitization of products so it can be tracked from the beginning of life to end of life. So what does that mean for certification of some blockchain-type certification that something is organic, or is cruelty-free, or was made in a factory that is certified, or is GRS certified, if it's generally recycled? And what happens at end of life when you want to recycle that item? What are the material contents in it when it goes into a waste stream? If we really, really believe in circularity, how will circularity manifest itself through the digitization of things? But that's on the passive side. And then on the active side, you have what's happening with the consumer experience, right? So what's happening with AR and VR? So how will AR/VR experiences start to enhance selling in the selling environment? Can you have a 3D interaction with a thing online? Can you— there's a company I love right now, they're called Wannakicks, and they allow you to virtually try on a shoe on your own human foot in your own human living room, and they 3D pop a shoe on your foot and you say, that's super cool. And then what you can do with it is you can push it to Instagram. Then you get social selling. So you can ask your friends, hey, does this look good? Do you like it with my jeans? You know, does this color look good on me? Right? You can start to get social permission. And with social permission, someone will say, Yeah, or ew, or, you know, try the brown one, or whatever it is they want to try. So you're using augmented reality to increase consumer satisfaction, consumer validation, social selling, consumer experience, time on site, all these things that we even more today want to encourage those kinds of behaviors. And then we start to look at how we use these visualization tools in the apparel industry, right? So we're in the early days on the cutting edge of the digitization of fit. What does body look like and body fit? And there's dozens of really, really good companies out there that are, that are looking at ways to use the, the, the three, the multi-camera angles to get, um, to get perspective from your phone to give you real data back on how you, uh, how you fit. Is it from phone? Is it from a survey? Um, is it from generalized, general and anonymized data that comes that gets put through an algorithm that's highly accurate, that's data. But when we start to look at ways where we can use the digitization of data around us for fit, then we can start to think about, OK, will this shirt fit me? Will it have the right ease? Is it going to be comfortable? Is this the brand for me? I can see it on my human body. I can know that it's going to fit. Less returns. So there's a business reason, business case for this. You want to get less returns. Higher consumer satisfaction, you want to have people come back, and you can work on your retargeting efforts in that respect. But also, and it's also happening for footwear. So what happens when you start to digitize footwear? Feet are a much harder thing to scan, but you start to be able to see what's happening when you're looking at bodies and feet. And that gets into the evolution of digital doubles. So I love what Katie Baron is doing. And she's part of Stylist, but she's connected to Matthew Drinkwater at London College of Fashion, who just does amazing work in this space. And this idea around digital doubles or digital twins starts to become super interesting because we're taking these sort of flat pedestrian and functional use cases to say, "Will this t-shirt fit me?" Okay, that's great. But if we start to do a digital double or an avatar of ourselves, then we can start to think about how does it really look on me? What's the drape? What will it look like in a social setting? What happens when I lift my arm? What happens when I move? All of a sudden, you're having a real experience with your product. And if you're having that real experience, then you'll be able to have a better, a better sense of satisfaction. You can start to, to crowdsource design from a digital perspective. And then again, similar to MONOKICKS, you'll be able to push these ideas around social selling. So right now on Instagram, multiple brands like H&M, you can buy the things that you see on an Instagram post. Okay, that's great. If Instagram posts something and you like it, you can buy it. That's awesome. NBC has just launched their second gen of shoppable TV. Shoppable TV is in its inception, you know, a year and a half ago was a QR code on a TV that you see an item and then you can hit the phone with the QR code. If you QR code with the phone, you can buy it. But they've just gone into video format with people that have touchscreens now. That whatever they're watching on, you know, Law Order or, you know, 911. That's our new sort of stupid binge-watching show, then you can click on that, you can actually touch it and buy it right there. Shoppable TV is going to be a really, really interesting way to create new commerce. And one company that I really, really like right now is Site, S-Y-T-E, and there's a couple of people that are doing it. And they actually are going in using AI, like deep learning models and deep AI models to be able to tag things that are in people's normal day-to-day Instagram, like, you know, your auntie wore a big white hat to an Easter parade and you can just click on your— she took a picture of it and you can click on her hat and figure out where to buy that big white hat with a peacock on it. So they're able to do all this sort of, sort of web scrape, social scanning, and then applying data on it to be able to make even people's normal posts shoppable. This is all things that are happening when we're talking about the digital experience and our expectation. I mean, look, our expectation is Minority Report, you know, move your hand back and forth in the air and you can do whatever you want. And I'm kind of pissed myself that I can't do that yet. So when we talk about this idea of the digitization of everything, going back to digital product creation, digital product itself, and then the digital experience, those kind of buckets that we put put it in, we're actually talking about different ways to get to Minority Report. And to me, the mind-blown fact of all this is that all this is being driven by the exponential technologies that we, that we talk about in an abstract way. But, but assume— we have to assume they're coming and they're happening in different industries, telecom, mobility. But when you think that what's happening with AI and 5G and and these big technologies, the exponential technologies that are driving this. We're pushing this way because we want to, because we need to, because consumers expect the Minority Report motion to happen. But it'll all happen as we push, push, push against the current constraints of where, how fast data can move. Because it has to happen in the cloud and it can't happen on the edge. When it happens on the edge, then you'll have real-time AR, you'll have real-time edge computing for mobility, you'll have real-time data back so that people will understand and brands will understand end consumers and we'll understand brands. We'll be able to do this. So we, in the innovation community, keep a real sharp eye on what's happening on, on, in exponential technologies, because that's the event horizon, that's the power that will enable all these things which we want to happen anyways. And all this is being driven by the end consumer's expectation, and it's only gotten more intense with, with the current climate.
Yeah, I mean, goodness gracious me, there's a lot there. But, um, you know, those buckets that are quite separate and actually can act within their own silos sometimes. Which of those buckets do you think is going to be the first mover to have this sort of total zenith of connectivity?
So I think it's probably going to be the digital experience. That's going to be the one that's the most obvious. I think if you think about what's happening in in the digital experience space. We are going to be leaning in hard to the online direct-to-consumer experience as the— so look, there are some things that were already happening when you think at retail consolidation. I mean, 2 years ago we were talking about the retail apocalypse. So if they say, as predicted, that by this time next year 50% of department stores will be closed, we can't actually be surprised because we've been talking about it for years. So it's just an acceleration of something which is already happening. When we're thinking about nearshoring and onshoring, that was already happening anyway. So the idea that we're going to have to have shorter and leaner supply chains, that was already happening. So the idea— and one of the reasons we were talking about as an industry nearshoring and onshoring is because we were seeing the need for personalization and customization on everything from— like, personalization would be to put your, your monogram on a dress shirt or to have a pink collar lining on a white shirt because you like it, that's your jam, right? And then the customization part of it is how can we customize fit? All the work that's been happening over the last few years about looking at being able to digitize the human body to get to better fit, we're coming from two different directions. One, how do we minimize returns? And two, how do we increase consumer satisfaction with the brand so that they know that when they buy that double extra small, that it fits my human body perfectly, even though when I go to another brand, I'm a large? How do we make that How do we make that connection without the standardization? So we were looking at the ability to make in smaller and smaller cohorts. Anyways, think about Starbucks. Starbucks has really done a great job traditionally in trying to figure out how to digitize their cohorts to figure out what certain demographics and psychographics will need and order in certain ways. And you know, one of the really big success stories around digitization was what Starbucks' ability to be able to buy online and pick up in store. BOPs, there's two companies that have done it really well in the States, Starbucks and Target. They use data to do it. But what they needed to do was figure out how to get smaller and smaller cohorts. So if you're like this and have these traits and do these things and have this general commute, live in this zip code, you're probably going to want your coconut milk skim whip latte with a caramel, you know, flippy flap, right? We're going to need to order 10 of those, not 2, right? So having those digital cohorts has been really interesting in other adjacent industries. Similarly, we know that we're— I don't know if we're not there yet because we're not digitally— we're We're not a digitally native industry, right? But we know that we'll be able to— we need to be able to get to smaller and smaller cohorts. And that was already happening anyways. So all these things were already happening anyways. And now, sort of just a ton of gasoline has been thrown on the fire to say, wow. So I'll give you a kind of an example. A gentleman who's a super good friend of mine is the SVP of a running company in Seattle, running shoe company in Seattle, and he told me just last week that their e-commerce business has gone up 300%, over 300% in the last several weeks. 15% of the visitors have never run before and 65% are reporting highly increased mileage in their runs on a regular basis. So they need the interaction with the brand more than ever. So what they'll need to do is increase their digital presence to be able to accommodate new runners. They— maybe they were only preaching to the choir before, and now they say, wow, okay, well, we need a whole new digital platform to be able to react to that cohort, right? And then how do we react to people that are than doing on higher miles if, for instance, their goal is to run injury-free. Right? Just changes everything. So they're gonna have to lean in harder into their e-commerce platforms and everything that they do based on the data. And then have a closer and closer relationship with the end consumer. And I do believe, and I'll go out on a little bit of a limb here, You know, one of the things that we see from a data perspective and a GDPR perspective is that we do pay a lot of lip service to the need for us to have privacy. Now, I— and this is just me talking, okay? I don't know very many people who read the fine print when they get an app on what the permissions are. Usually people just accept. I've never read the legalese. So we're allowing people into our lives every single day. It's interesting because, and I'll talk a little bit about this in our talk, but, you know, what's happening in Asia is the abdication of privacy and the trade in Asia, China specifically, for a better quality of life and more data coming in which is useful to your everyday life. So really, the ideas on privacy in China are not really— they're different than ours. They don't have the same level of privacy expectation. One of the things that's allowed them to deal with the current situation is the fact that there is no privacy per se. There's very little privacy. I don't want to exaggerate. Um, but that means that the data on citizens' travel behavior proximity, that can more easily be tracked and traced and then can be managed in an epidemic situation. I do believe that our ideas around data based on what's happening with COVID will change. We— if you can keep us safer, I'm gonna bet that you don't care as much as you used to care about privacy, which means that we're gonna— they're gonna have more opt-ins, and we'll be able to know more about our consumers than we did before, because frankly, they want us to know more about them. You, you kind of get angry at at the brands if they don't know who you are, right? If you don't know— of course you sent me something that doesn't fit, what's wrong with you? So we do have a high level of expectation that brands know me on a one-to-one basis. I do think that we'll know more about them, be able to meet that expectation, as we start to see privacy relaxed because of what's happening now. But that's, again, that is a lot more me talking than anything else.
Yeah, I mean, it's very, very interesting, and I think you're absolutely right about our relationship with data, um, certainly in the US and, you know, UK. I'd agree with that as well. You know, we feel like it's an invasion of privacy giving away our information, but at the same time, we do it willingly sort of every time we click accept.
Um, so it is quite a for you to say that in England. There's an amazing statistic where there's more CCTVs in England than in any other country in the world, like 100 to 1 or something. I'll butcher the statistic, but it's an insane number, right?
Oh yeah, absolutely. You know, there's people watching us. There's not enough people to watch us all the time. And that's the interesting thing, you know, you know, they're just cameras that are turned on and, but Again, coming back to your point, we do have a strange relationship and I'd agree with you that after this, if the value proposition is that you are going to keep me and us as a whole safer now and in the future, then yes, you know, we'll absolutely click accept and be willing to give a little bit more away.
Yeah. There's an interesting announcement just last week that Apple and Google are working together to develop to develop a tracking app that you— it's optional, but they'll track your proximity to people that have tested positive or negative for COVID. I don't know anyone who wouldn't get the app in one single second. And they're saying, we can't really necessarily guarantee that there's full privacy here, but there are hundreds of millions of people that will click yes to that tomorrow, the day it's launched.
Oh yeah, absolutely, absolutely. So what does this mean for consumer behavior, you know, sort of this sort of changing landscape? And some of it, as you said rightly, was changing anyway, and this has been a bit of a catalyst for that. But how really is this sort of technological shift, how's it going to change the consumer's approach to the shopping experience? And also, how do the brands change their operations? To connect with this increasingly digital consumer?
I certainly thought about that a lot. You're starting to see a lot of research coming through about acceptance. So, you could say that there was a generational divide. And so, millennials and beyond were born digital. They were always, you know, I mean, they were born with blistering fast, you know, high-speed internet in their hands when they were babies, right? But other people, you know, previous generations were not digitally native. They have— they've had to kind of learn in and lean in. So when we're talking about this general idea of acceptance and consumers and who has money to spend, there has been some reluctance to buy into this idea of not just e-commerce, but just the idea of having these digital experiences. And frankly, they're there are new skills and new tools. But there's some amazing data that's coming in about how rapidly people are leaning into digital experiences now because they have to. So it's a moment of— it's necessity-driven more than anything else. But that becomes a catalyzing moment in the digitization of everything because people are going to have new skills, they're going to be able to understand, there's greater technology uptake. And then so they're going to be able to trust the experience that they're having. It will be incumbent on us to be able to deliver on that experience. So that's going to be really, really interesting. And one of the things that— so I love this. There's a great Harvard Business Review article that's out. It's written by a woman called Rita Gunter McGrath. And it's around digitally driven planning. And it kind of talks exactly to this. And it kind of, it makes the distinction between digitally native companies, like small startups, or like I mentioned, like Stitch Fix, or Harry's Razors, or Warby Parker. They were built on a digital model. So they can be more nimble. They have open APIs, open SDKs, right? So they can, you can bolt on really quickly. They can try things. But when you're an incumbent business, you're more of established enterprise, it's really, really hard. And so I think what's really challenging for incumbent businesses is they don't know how to jump in. It's like double dutch, right? You got two jump ropes going at the same time and when do you jump in, right? And what if you make a mistake? Then you get ropes in your legs and you fall on your face. And the rope on your leg and falling on your face analogy is actually akin to wasting time and wasting money. And no one has any time to do that, especially now. So what, what she talks about is this idea of digitally driven planning that gives you permission to learn your way into solutions that work, right? Because larger companies can beta test things which are low risk. So if you can say you're going to try one solution which is not— look, if I wanted to build an end-to-end digital solution for a large enterprise like a VF or a PDH, that's a multi-year, multi-division, multi-multi-million dollar proposition. And at this point, with e-commerce figures in almost every area, except for grocery, and maybe even grocery too, growing at triple digits, you're gonna have to get digital really, really fast. So how do you do it? You can't build this sort of grand plan. You have no time because this is really about creating revenue now. And this has created a fierce urgency of now moment for all companies that weren't born digitally native. So what I like about this digital digitally driven planning philosophy is it gives brands permission, bigger brands, to try things and beta test it. You can A/B test and say that worked, that didn't work. Go in, try something, test it, do more of that, do less of this, and build the strategy that maybe in the beginning feels a little bit hopscotch, but in the end, it pulls together something that looks like a digital plan. Because ultimately, it— look, everything is about data. Everything is about data. The data that you can gather is not just around consumer behavior, but it's around being able to drive consumer experiences that will create new product lines and new businesses as well. So companies that don't have a data strategy, they don't have data management, they don't have a data lake, they're really, really— they are at a disadvantage. And there's something really Interesting that, you know, being in the Google environment has been fascinating. They actually, um, the Google Cloud team has a product called BigQuery, which is something I didn't know about because I'm, I'm not a, not a hardware person. Um, you know, I'm apparel, accessories, footwear, uh, and innovation in that space. That's what I do. Um, but they have something called BigQuery and it basically is a cloud version of a big data server that allows you to bring in sort of, you can call it, you know, garbage data or contaminated data. Because usually you have to clean up your data, then put it in data lake and then manage it. They have a way to use an AI model and an ML model to clean up that data as it goes into their cloud lake and then to be able to use it immediately. And it's interesting because, you know, a few years ago, When I was at PVH, I was visiting Silicon Valley and visiting Google, and it's when Sundar made his big pitch to say that Google wanted to be an AI company. I didn't really think of that. It wasn't obvious to me as an outsider, because Google to me, especially at the time a few years ago, was really all about search. So, but as they started moving into the hardware business units, working with Nest and Chrome and those hardware areas and developing projects like, like Jacquard that we work on now, which is the physical digitization of product with Jacquard and Soli. You— I see every single day the power of the ML models that teach and learn these, these business units to make them better and smarter all the time. That's totally data-driven, right? And so I love the idea of something like BigQuery because instead of having to do it backwards and clean up your data to get it in, they're using AI and ML to clean up that data for you. Those machine learning models are working to make sure that it's fast, efficient, and inexpensive, which is an amazing, amazing way for people that aren't— companies that aren't digitally native to get into data management. Because if you follow this digitally driven planning tool like Rita McGrath says, then you're going to be putting together a hopscotch of solutions, which in the short term will give you the results that you need. And let's face it, we need short-term results today. But in the longer term, as you start to aggregate that data, there will have to be an IT strategy that says, what will you do with that data and how will you manage it from a CRM perspective, from a retargeting perspective, from a brand building perspective, from everything that's happening on D2C. And then will you digitize your product in that way? Will you decide to go to rental or subscription models because your product is now digitized and you know which cohorts in which areas are transacting in different ways, which will say, "Hey, a subscription model, for instance, makes sense." So, I feel like why I glom onto this, idea is that we have permission to try things now and to beta test it, and we have permission to back into it, figure out our digital strategies from a tactical way, and then create a strategy from that as we sort of emerge into a more normalized area where people have accepted purchasing, transacting, trying avataring online. We're going to be totally good with that now.
Yeah. Do you think that people as consumers now are happy with the lack of perfect replication from physical to digital in their sort of shopping experience? I.e., the shoe that you might try on with an AR app, you know, obviously you're not going to know fit preference or something like that. Do you feel like people are ready to make, uh, to spend their dollars, um, with those imperfect solutions, as you might call them?
Well, I mean, that— so that's— I got— I caught a lot of vision when I saw Katie Barron's video on, on digital doubles, because that makes it more, um, it's less clunky and more, uh, more personal. Your own personal face is on it, your own personal body type is on it, and then you're wearing, you know, something from Levi's or or LV, or, you know, you say, "Oh, I love that. I do love the way that looks." And you can place that digital twin or avatar of yourself in an environment in your house. In the same way, look, Lowe's has done an amazing, amazing job, and they've transformed furniture buying. Same with IKEA. You can get a couch, do a VR version on your pad or phone, and then say, "What would that couch look like in my living room?" living room. Okay. I don't like, I thought I wanted brown. I think I want blue. And then, you know, how high are the legs? What pillow? You can buy pillows, change the pillows. Literally like, I want this pillow, this pillow, this pillow, this pillow, side tables, whatever it is. You can do your whole living room and then buy now. Boom. Just push that button. Buy now. So, so in that same way, there's a much higher level of acceptance. In certain sectors. So I would buy a couch. I bought a little couch on Wayfair last week. I didn't do a digital version of it, but I had to physically measure, I had to get out the tape measure, I had to kind of go through and it was hard. It took me— I went on the site 3 times. I'm just telling you a personal story. I was on site 3 times, I kind of messed around with it. Happily it worked. I didn't measure it wrong. I really like it. It It was inexpensive and a nice couch. I'll show you a picture sometime. But I would have done it much faster if I could have visualized it. So the higher the resolution and the better veracity of how that looks on my own human body, my own personal snow— you know, human snowflake, the more I'm going to be able to like it. And that's why, again, I caught a lot of vision from what Katie said. Because I could see what it would look like on me. And then I have a higher trust level and with higher trust, I'm more willing to transact.
So nice. Nice. What was that?
Katie? Katie Barron?
Yeah.
From Stylus.
Fantastic.
Yeah, I think you can, you can, you can grab it on YouTube.
Fantastic. Well, look, Barry. Yeah, we'll do. Hey Barry, look, thanks so much. That's amazing. I mean, there's so much here to get through, you know, I'm I'm sure we could speak for hours. Um, so perhaps we can have you on again another time soon.
Would love to. Yeah, thanks. I love this. I appreciate it a lot.
Thanks, Barry, for joining us again this week. Um, it's been really, really interesting chat. Um, that's all about all we got time for, um, this week. But, um, just before we go, on next week's show we have Michael Longegan, who is professor at LIM College. And so we're obviously going to be talking about addressing the digital skills deficit, something I know is close to everyone's hearts out there. And also how academia can support the industry as a whole and what the challenges are for them in particular and how really we can all work together to address those. That should be a really interesting conversation. Hope you can all join us again then. Until then, stay safe, take care, bye-bye.










