PODCAST

Christina Cardoza: Hello and welcome to the IoT Chat, where we explore the latest developments in the Internet of Things. I’m your host, Christina Cardoza, Editorial Director of insight.tech. And today we’re going to be talking about AI shopping experiences with Hillary Littleton from FIT:MATCH. But before we get started, let’s get to know a little bit more about Hillary. Hillary, thanks for joining the podcast.

Hillary Littleton: Thank you so much for having me, Christina. It’s great to be here.

Christina Cardoza: Yeah, of course. Can you tell us a little bit more about yourself and FIT:MATCH?

Hillary Littleton: Absolutely. So, at FIT:MATCH I lead all of the marketing and growth efforts for the company, and over the course of the last two and a half years I’ve established our brand identity through an omnichannel B2B2C lens. What that means is I’m really responsible for developing and executing on business strategies, designing and delivering marketing plans, and focusing on key performance indicators to drive overall success for FIT:MATCH. So my team holds a close relationship with both front-end sales and back-end tech to drive winning go-to-market strategies and product launches.

So, a little bit about the company. For consumers, FIT:MATCH delivers an innovative, personalized, yet totally private shopping experience. During a scan, our patented algorithm actually captures a shopper’s 3D shape and matches it back to a digital twin—so, somebody in our database with the most similar body shape that has already tried on the product. And then the data that consumers receive is completely unique to them. So they get to view their own shape profile; they get to see customized product matches guaranteed to fit their shape best.

And we built it this way because we know a 3D problem can only be solved by a 3D solution. We use 3D shape on purpose; we don’t use any measurements. And the best part is that the experience is incredibly quick, simple, and intuitive.

Christina Cardoza: Yeah, absolutely. It’s amazing to see how far AI has come, and I first heard and saw FIT:MATCH at Intel Innovation during the keynote, where the company demonstrated exactly what you’re talking about. It took a 3D model of an individual and demonstrated how it could provide that personalized experience and retail options for a consumer. Which is something that I love, because I typically dread the shopping experience—you know, having to try on clothes.

Hillary Littleton: I know.

Christina Cardoza: Finding out what fits—that’s one of the worst things for me. So seeing this technology where you can actually go in and then it maps it to you, that’s great. And obviously we heard a lot at Intel Innovation about certain AI trends and advancements going on that are enabling these things to happen.

So, I’m just curious, what are you guys seeing in the AI space, particularly in retail, what trends and advancements really make FIT:MATCH possible?

Hillary Littleton: Yeah. I mean, everybody knows that AI solutions are a hot commodity right now and can be easily accessible, but I think gaining access to the right solutions is really the difficult part. We know that retailers are craving products that are both seamless to integrate, but also lead them to achieve important KPIs for their business. So our tech is revolutionary and immersive for the shoppers, but it’s also impacting our brand partners’ bottom lines in a big way.

And I love that you mentioned that about Intel Innovation, because I think what we learned a lot from the conference is that the need for the technology spans across all sorts of customer demographics. It’s really a universal problem. And it was amazing to see how many people were just so fascinated by the technology that they had to come and try it for themselves following Pat’s live keynote.

And then, just on top of that, Intel’s edge computing has just been so instrumental in the way we scale. It’s really enhancing the user experience. It’s private, it’s quick, but it’s also more cost effective. So OpenVINO technology really just stands out as a prime example for us to commit to the edge optimization. And we really just see immense value in OpenVINO and are really dedicated to integrating it in more of our product offerings going forward.

Christina Cardoza: I want to dig a little bit deeper into some of the challenges you were saying. Obviously in the beginning I spoke about how it’s a challenge for me to go shopping because I just dread the fit experience. But I’m curious to learn a bit more about why has it been a challenge up to date that retailers have faced to provide this type of quality customer experience, you know? And to really provide a comfortable experience for customers in a fitting-experience setting.

Hillary Littleton: Yeah, absolutely. I mean, relating to the fit experience, I know that there are three off the top of my head that I continuously hear from retailers. One is customer retention and drop-off rates—where customers just don’t know what size to buy, or their size is sold out. And just it results in churn rate, lack of loyalty, and just an unsatisfied shopper—kind of like what you were just saying about yourself.

And then number two: leftover inventory due to poor buying, planning, merchandising decisions for the business. And then three: returns. I mean returns is just something that we continuously hear due to the lack of size education for the consumer, and just communication to the shoppers in general: if they don’t know that their size is available, how would they know to go to your page?

So I think by employing our patented technology we can really derive detailed information about this person’s shape that you cannot get anywhere else, and it’s just truly unparalleled in the industry. So we’re just really proud of that. And, you know, for example, we can now not just tell you what size you are, but we can also explain why you’re that size and what you should do with that information going forward. So, yeah.

Christina Cardoza: Yeah, that’s amazing. And, you know, going to the returns and not knowing your size—issues that you mentioned. A lot of these different brands, I find there’s no one size fits all. Like, one size six is not going to be a size six at another company.

Hillary Littleton: Exactly.

Christina Cardoza: So that’s great that you’re not giving sizes really, or you’re not doing any measurements. It’s really based on that 3D scan.

Hillary Littleton: Yeah.

Christina Cardoza: And you also said that you did a 3D scan, and that maps it to a digital twin of the individual. So I’m curious what types of AI capabilities or advancements are you leveraging to provide that personalized, accurate recommendation for the customer to sort of alleviate some of the stress that businesses have been facing?

Hillary Littleton: Yeah, and I did want to just touch on one really interesting point you just made: we don’t ask the customer—the shopper, I should say—for any information up front except for just their name and email. We take the, all of the equating off of their hands and off of the brand’s hands, quite frankly, so all that a shopper sees is—after their scan is the sizes appear for them, which is really, like I said, different from what you see in other fit tech in the industry. We don’t ask you for your measurements—most people don’t even know how to take their measurements. So in that way it’s just super easy and immersive, and just hands off and fun.

But overall I think AI is just really at the core of our platform today. You know, it powers our ability to interpret and leverage that 3D shape information that’s captured using Intel’s RealSense LiDAR sensors. By employing that we can really just get more unique information that this shopper cannot get anywhere else. So on top of being really easy and fun, you’re getting this portal into data about yourself that you cannot get anywhere else. And so we’re finding that customers absolutely love that.

Christina Cardoza: Yeah, I can see all of the customer benefits to this. I’ve also seen through my own shopping experience online that the technology can even help with, how do you want this to fit? Do you want this to fit tight? Do you want this to fit baggy? And then it’ll give you a size

Hillary Littleton: Oh yeah.

Christina Cardoza: Based on how you want that to fit, and even show it on the 3D model. So that’s great to see that.

Hillary Littleton: Yeah. Preference is huge, for sure.

Christina Cardoza: Yeah.

Hillary Littleton: I mean preference is something that has to be built into our technology. We have it built in, we’re learning more as more consumers tell us how they like things to fit, and then we can kind of spit back recommendations based on those things, for sure.

Christina Cardoza: Yeah. So, obviously improving the whole customer experience overall, but on the business side you mentioned some of the challenges with returns and everything. So what about the benefits that businesses will get now from the customer experience from this improved, personalized fitting experience?

Hillary Littleton:  Yeah, for sure. So, we’ve seen incredible benefits so far for our brand partners, including on average a 6x conversion rate for those that are scanning with FIT:MATCH versus the ones that aren’t—20% to 30% higher average order values. Those that are scanning are actually returning 80% less than the ones that aren’t, less than 1% of consumers are buying more than one size—bracket shopping, as we call it in the retail space. And that’s a really big one, right? There’s a lot of fit risk online, and we’ve seen that retailers are telling us that bracket shopping is the number one concern that they have, so it’s great to see that that’s now down to less than 1%.

And then when we think about loyalty, there’s a 2x sign-up rate for those that want to be part of the loyalty program that have scanned versus ones that haven’t. So we’re definitely seeing long-term loyalty increased. And then overall customer satisfaction, net promoter score, has increased by 16 points on average. So we’re really proud of these results.

And then there’s also things that we can build out with brand partners going forward. So, like I mentioned, more insight into their consumers—like what is the data dashboard that we can really customize and serve up to brand partners according to their preferences so they can make more personalized marketing decisions, merchandising decisions, and long-term loyalty building from that data that we can serve up to them. And that can be on product construction, that can be on inventory management. Just getting rid of excess inventory, we’ve heard, is just a huge pain point. So we’re excited to tackle that as well.

Christina Cardoza: I’m definitely guilty of the bracket shopping online.

Hillary Littleton: Yeah.

Christina Cardoza: There’s nothing worse than falling in love with something online, and then getting it, waiting the weeks or days for it to arrive, and then it not fitting, so….

Hillary Littleton: Right.

Christina Cardoza:  I always order multiple sizes, just in case.

Hillary Littleton:  I know.

Christina Cardoza: So it’s great you can do the—you don’t have to go through that fitting experience, which size fits the best, which one should you keep—things like that. I’m curious, because obviously a lot of this sounds like it’s in the store setting, but is there an online component to this as well? How do you work with brands to implement this within the store, and then how can you expand it out, outside of the store for customers like myself who like to do online shopping more than in-store shopping?

Hillary Littleton:  Yeah, absolutely. So, a little bit of background on our products and market. Earlier this year, FIT:MATCH actually debuted our newest in-store fitting room experience for apparel retailers. We dubbed it Fit Xperience, or Fit Concierge, I should say, which gives shoppers the opportunity to get scanned in an in-store fitting room using Intel’s RealSense LiDAR technology and Intel’s OpenVINO.

So, using the LiDAR sensors we can collect that avatar, and it happens in one second. So that’s what’s amazing about our in-store retail solution. And then, like I mentioned, we’re actually able to, within that one second, match it back to an avatar of a closest digital twin that’s already tried on the garments in our extensive database. That entire in-store process takes like 10 to 15 seconds, and consumers get their exact sizes across the retailer’s entire assortment on the spot.

So, I mean, imagine not having to gauge your size or drag in many different sizes of the same product into the fitting room to just see what one fits? It’s a huge time saver for customers. And then we also email the results to the shoppers so they can be used at home. The first retailer that incorporated our concierge solution was Rihanna’s Savage X Fenty.

We’re rolling out the next iteration of the Fit Concierge at a popular shopping center in Los Angeles this holiday season. This new version is faster, with extra layers of privacy and even more accurate. And we’re also with that partnering with a multibillion dollar apparel and footwear brand in the sportswear space, and the entire experience will be accelerated by Intel suite of products. So that is to-come for in-person shopping.

And then for at home, our future plans are definitely focused on bringing everyone the ability to scan using their own mobile phones. So with one scan shoppers will be able to unlock a passport of sorts across brands, offering up recommendations in their sizes. So no matter if you scan in store or at home, your personalized shape profile will be accessible from anywhere.

Christina Cardoza: I can not only see how this would be time saving for the customers but also the business. Like you mentioned, you don’t have to bring all of those clothes into the fitting room; the retail managers or the people on the floor, they don’t have to be—store associates don’t have to be putting this all back on the shelves, so. . .

Hillary Littleton:  Exactly.

Christina Cardoza: It makes for a cleaner space too, especially in stores and you mentioned—

Hillary Littleton: Yeah. I was just going to say, and they can better service their customers. That’s the beauty of it is they know what the shopper really wants and what is going to fit the shopper, so they’re able to offer a much more elevated shopping experience to serve up to them, which reflects well on the brand and obviously that consumer is more satisfied.

Christina Cardoza: Now you mentioned using Intel LiDAR and Intel OpenVINO—which is Intel’s AI toolkit—to make some of this happen. So I’m curious, what is the value of partnerships like Intel, and using their technology and working with them to make the FIT:MATCH fitting room experience possible and to bring this to across doors and to mobile devices?

Hillary Littleton: Yeah. As I mentioned earlier, I think the edge computing is just key to how we scale this. It’s super private; it’s super quick, which customers love obviously. But for brands and for our brand partners it’s just more cost effective. So OpenVINO, it really stands out as a prime example on how we can really scale this to the next level. Partnering with Intel, and we just see this as kind of the infrastructure of how we’re going to build our products in the future.

Christina Cardoza: Now are there any—I’m just curious, are there any additional use cases to this technology that you can see this solution being expanded to, or any other plans in the future to really scale the capabilities at FIT:MATCH into other areas or industries?

Hillary Littleton: Yeah. I mean, look—I think we’re definitely leaning into the effects of how AI can optimize the shopping experience. We’ve built an AI fit assistant that can, like I mentioned earlier, not just tell shoppers what to buy, but why they should buy it. So tools like this integrated with a seamless checkout experience on e-commerce are crucial elements for the consumer journey. And knowing that, FIT:MATCH can provide that solution.

And then recently we also have broken into the healthcare and wellness sector, with launching a scanning experience exclusively built for plastic surgeons and their patients who are going through body transformation. So we’re super excited to see how our shape-matching technology can impact other use cases outside of just fashion retail.

Christina Cardoza: Well, I can’t wait to see these solutions become more mainstream and find them in my own stores or the places that I shop. I just had a baby recently, so my body has changed quite a bit.

Hillary Littleton: Yeah. Absolutely.

Christina Cardoza: So it would take a lot of stress off of me finding clothes that fit if I know exactly what’s going to fit and how it’s going to fit with technology and solutions like FIT:MATCH. So I think this is great, and I can’t wait to see where else this solution and the company goes.

Unfortunately, we are running out of time, so I just want to throw it back to you one last time, if there’s any final thoughts or key takeaways you want to leave our listeners with today.

Hillary Littleton: Well, thank you just so much for this opportunity, Christina and the Intel team. It’s always so fun for me to gush about how we’re innovating the future of retail with Intel. And I would just like to say, I guess for anybody listening, if you’re interested in following along with all that we’re building at FIT:MATCH, to just stay tuned about our news and happenings. We’re on LinkedIn at FIT:MATCH.ai. And Twitter, Instagram, and TikTok as well.

Christina Cardoza: Awesome. Well, I can’t wait to see what else FIT:MATCH does, and, like you said, I encourage all of our listeners to go on the website, follow them on social media, and see how else they are innovating in this space. So, thank you again for the insightful conversation.

Hillary Littleton:  Thank you so much.

Christina Cardoza: And, until next time, this has been the IoT Chat.

The preceding transcript is provided to ensure accessibility and is intended to accurately capture an informal conversation. The transcript may contain improper uses of trademarked terms and as such should not be used for any other purposes. For more information, please see the Intel^® trademark information.

This transcript was edited by Erin Noble, copy editor.