Ep. 29: PreSize can find you the perfect fit Podcast

This transcription has been AI generated and therefore may have some inaccuracies.

Ep. 29: PreSize can find you the perfect fit

In this episode of The WTiN Podcast, we talk to Leon Szeli, who is one of the founders of the fit technology company PreSize.

Jessica Owen
Hello. My name is Jessica Owen, and I am the Deputy digital editor at WTIN, and this is the WTIN podcast.

For this series, I'll be talking to startups and other new brands across the textile and apparel industry, from sustainable swimsuits to jackets inspired by NASA technology. We talk about products the highs and lows of starting a business, and advice for others interested in entering this space. This week, I am joined by Leon Szeli, who is one of the founders of PreSize, Leon talks about the brand's new technology that helps shoppers find the perfect fit, and how this can reduce returns, increase sales, and also have a positive impact on our planet. Good morning and welcome Leon. Thank you very much for taking the time to join me today, and we can get to know precise and ask you lots of questions about it. So you are one of three co founders. Am I right? Yes, that's correct, right? Okay, so who are the other two people that have founded this business with you? So

Leon Szeli
I have two co founders named aves and Tommy, and both of them are more on the technical side, since we develop a very technical product, so I take care of everything that is not product and technology basically, right.

Jessica Owen
Okay. And so, how do you all three know each other from university? Are you friends beforehand, or co workers? Like, how did the three of you get together?

Leon Szeli
And so we met in Munich in Germany, at an institution called cdtm Center for Digital Technology and Management, which is an honors degree, which is quite interesting, because you have like people from different backgrounds coming together. So I have a background in psychology. Tommy has a background in robotics, and aves has a background in biomedical computing, and we also all from different countries and but the reason why we studied at cdtm was to basically build a digital product and to found a company. And it's yeah, you work in different projects. Usually look you build a prototype for a company, and I Yeah, the prototype we built eventually then turned into a precise and that's how it all started,

Jessica Owen
right? So you must have quite different perspectives, then you must complement each other quite nicely, if you all do such different things. So I want to talk about pre size. Then that's why I've invited you on the show today. So you set up this company last year in 2019 and do you mind just telling me a bit about the company then, and what exactly it is that you do?

Leon Szeli
Of course, so precise is a technology that helps, let's say, fashion companies, online or offline, and by finding their customers perfect fit. So that means the end customer turns around in front of a smartphone camera, and then we calculate the perfectly fitting size based on body measurements, and usually, like the value we we add to the to our for our customers is that we decrease the return rate and we increase the conversion rate. In case, it's an online business,

Jessica Owen
right? Okay, so that to me, I'm not quite, I don't quite understand it. I'm not a, sort of a technically minded so talk me through it then, as if I was an online shopper. So it would, I don't know, say, if you were shopping on H M's website as a customer, then would there be sort of an app or a button, and you would just go from there?

Leon Szeli
Yeah, of course. So you're on the agent M website, you find a product that you like. You're on the product detail page, let's say, a nice t shirt. And exactly where you're wondering, do I need size small or a size medium? I'm always in between. And right next to that drop down with the sizes, you have an additional button that comes from pre size, which is usually called Find my size. And when you click on that, our solution opens, and it's not a native app, so you don't have to download anything. We see that people and also shops don't really like to download another app that you just use once and directly running in the browser. So then we guide the user through a couple of steps. We basically explain to them what is going to happen and that they can record a short video of themselves to find the perfect size. And then you have two options. You can either do it with a second person, so it would be, yeah, just someone basically holding the phone, and you turn around in front of it. But what most users actually choose is self recording, so that is working with the selfie camera. So you just put the phone on the ground, lean it against the wall, like anywhere, for example, in your living room, you take a couple of steps back, and you just turn around like it looks a bit like at the airport security. And it takes. Just a couple of seconds, and you can also wear regular clothing. That's also important to know, so you don't have to undress. We don't need to see you in underwear, just like jeans and pieces. Is fine. And then the video gets uploaded. There's a lot of things happening technically in the background, but essentially what matters to the user is that from that video, we created model, and from that 3d model, we extract body measurements that are extremely accurate. We are an as good as a as a tailor measuring you with a measurement tape. And then these measurements are matched to sizing charts and also to some other data sources to show the user a size recommendation. So for the t shirt, we might show you your size small, and then if you click on another product, maybe your size medium, because, you know, every brand is different, and yeah, the most interesting thing for a user is you it's not just like, not just for that one product, but for every other product that precise supports and also for future visits. So unless you like, gain a lot of weight, let's say around Christmas for then, of course, you have to rescan yourself. But if you don't, you get perfect recommendations until your body changes. Basically, okay,

Jessica Owen
so, so it essentially stores that data. And if you went on to, I don't know, top shops website and their sizings differently, it accounts for all of that, and so you don't have to keep on doing this exactly. Okay? Well, that sounds really interesting. I mean, I certainly have trouble working out what size I am, so I think this would be an app, or, sorry, a web browser, piece of technology that a lot of people would probably be very thankful for. So tell try. Well, as I said, I'm not very technically minded, but what exactly is the technology that is going around in the background? Have you had to take loads of different random people's measurements and compile it? Or how does that all work?

Leon Szeli
Yes. So essentially, what we're doing is we, I mean, we take a video, on average that's like 56789, seconds long, depending on how fast the person turns, and then we select different frames. So a video is essentially just a lot of photos, right? And we take different frames from this video. And we, of course, like account for the background, for example, because sometimes the background is, let's say, not ideal, and very similar to the person. And also, we, of course, account for the clothing to some degree. I mean, if you, if you take the video in a winter jacket, the results won't be perfect, but yeah, as I said, jeans and T shirt is fine. And then, essentially, it is based on artificial intelligence. That means our algorithm has, like is fed by multiple data points. And that is, as you said, on the one hand, of course, like we have 1000s of videos of people, plus the actual body measurements of them, and we can use that to, yeah, to tune the algorithm and to improve it. And what is also very interesting is that when we when we get like, for example, let's say I recommend you size small, and we know how your body looks like based on the video right. And then, as we are wrong, and you actually return, we can use that to improve the system, and that makes it so powerful, right?

Jessica Owen
Okay, interesting. Okay, so we now know how this sort of technology works then, and how a shopper could go about using it. There are other sort of sizing technologies out there. I mean, I know, for example, when I've been on shops, you can input your age, your height, your weight, whether you want the clothes to fit looser or you want them tighter fitting. So how does your technology compare to sort of other things that are out there?

Leon Szeli
Yeah, exactly. So I think there's two main approaches here. One is the one that you described. So it's essentially a questionnaire. You get asked a bunch of questions, are you more on the slim side, on the chubby side, Are you old? Are you young? Do you have bright shoulders, broad shoulders, narrow shoulders, and so on that. Let's say it kind of works. It gives users a good feeling. Hey, this time it might fit. And actually, the return rates decrease a little bit, but the problem remains unsolved. At least here in Germany, we still have shops with like 50% return rate using these solutions, and the reason for that is that they have two major problems. Number one is it's super subjective, like 80% of people think they're above average, and that's how they answer these questions, right? So, I mean, yeah, people just, it's not objective, like it just what you how you perceive yourself, which is not necessarily how you really look like, right? Unfortunately. So that's, that's one problem. And then the second problem is that these solutions often don't use and. Let's say product specific data. So it's just like historic data. So on average, let's say they passed 1000 orders. We know that these they would return to they were not returned. And then they make like, let's say, very broad statement like this. Brand in general is a bit has a loser fit, and the other one and things like this, but they never go on the per product level, which is, I think, very important. Because, I mean, that's where it gets interesting, right? And because, yeah, if you, if you know the exact common dimensions of a certain product, you obviously can give much better recommendations. And the other sort of solutions we see on the market are computer vision based, so not just asking users questions, but actually looking at their body, and not like basically everyone except us is using pictures to do that, and we use a video and where we filed a patent on that approach as well, and it has the strength of Being extremely robust. So with these picture solutions, it's usually like a side view and the front view of your body. And if your body pose slightly changes, you get a completely different result. And also, if your clothing is not extremely tight, and you also get you have, like, big measurement arrows. And these are the main problems with those solutions. Also, almost everyone is building a native app, and I think if you think about it from a user perspective, that just doesn't make sense, because the user experience should be I have this problem. I don't know my size, and I just want to get to us to the perfectly fitting size with a few clicks. And you don't want to get rerouted to the App Store, then download the app, measure yourself once and then never use that app again. That also like kills the whole user funnel and the conversions Exactly.

Jessica Owen
People just want simplicity and an answer straight away, yeah. Okay. So when I looked on your website, it said that this technology is is patent pending, and when do you hope for that to be approved?

Leon Szeli
So yeah, that is actually already a bit outdated. So we fight for a European patent. And I don't know how familiar you are with the patenting process, but essentially, we already got positive feedback on some of our claims, meaning that at least a part of the patent will go through, which is really nice, because it's exactly the, let's say, one of the main technical things we do. And the whole topic is kind of hot, I would say, I mean, there's a lot going on. There's many solutions popping up, and it's, of course, nice as you can protect your unique selling proposition. And so, yeah, this is Europe for now, but we're also planning to expand that internationally, but we are actually mostly working with German customers for now,

Jessica Owen
okay, um, and actually just going back to when you founded the business. I mean, why did the three of you decide to develop this type of technology? Were you personally frustrated with the way that you shopped online? Or what was the reason for starting the brand, yeah,

Leon Szeli
yeah. So it was, I think, a quite nice combination of, like, the just the passion for the technology itself, but also, like, extreme frustration about the problem. So on the one hand, we were just super excited about artificial intelligence and computer vision, and we thought, basically, this is such a cool new like breakthrough technology, maybe there's something we can do with that. And then we actually also found a pretty good problem to solve, because every, every, basically, every person I know has this problem, either they stop shopping online because they say it won't fit me anyways, and if I have to go to the post office, I can also just go to brick and mortar retail, right? It takes the same amount of time, basically. And then we have, like, the power shoppers, like my co founder, Tommy, for example. He's just, like, ordering a lot online, and it just very rarely fits. And yeah, just super frustrating. I mean, it's not just for the user. For users a huge waste of time, for the shop, it's a huge waste of money. And for the planet, it's like a huge waste of resources, right? Just like a nice problem in a sense of just a severe and super frustrating one. And we have a lot of like, anecdotes around how big this problem actually is. For example, we have a friend that just got blocked from one of the major European brands. They just said, Hey, boy, you cannot order anymore. You return too much. I mean, yeah, it's just crazy. And then, I mean, yeah, some other shops like block you from adding the same product in two different sizes. They just say, hey, please decide like you just have you just get one choose wisely. Yeah, and it just like, I think it just like an unsolved problem, despite many solutions out there.

Jessica Owen
Well, it's funny, I clearly don't shop enough online where I thought I did, but I've never heard of that problem of only being able to choose one size or being blocked because you return. So my. I honestly didn't know that sort of thing happened. I

Leon Szeli
think it depends. I mean, you have, I think you have these brands that just say, Okay, we just accept returns are part of our business model, and we might get as easy as convenient as possible for for users. And but then we have shops that just say, we just don't accept that every second product we sell gets back to us. And so it's also kind of like a philosophical question, where every different approach,

Jessica Owen
yeah, and well, actually, I mean that, that idea of convenience as well. I mean, your technology couldn't have come at a better time, considering this COVID 19 pandemic that's just currently underway. Because, I mean, the, I mean, shops since, especially in the UK, have been shut. I mean, I think they're actually reopening around about now, but even so, the way we shop is going to change. I don't think we're allowed to go in fitting rooms here, so that's the main reason. Often people go and shop in stores so they can actually try clothes on and see if they fit. And if you take that away, then surely more and more people will be shopping online and will need a bit of technology like yours. So do you think that you are going to see quite a large uptake in what you do?

Leon Szeli
Yes, and so, I mean, it definitely helps, because, like budgets, budgets are just shifting extremely fast from like classical retail to online. I mean, that has been happening for the last 10 years already, but now it gets even faster. So that's obviously super positive for us as a business. But also, I mean, of course, like COVID 19 hit the whole fashion industry quite hard, and there's still, like, so much revenue generated offline. And I mean, of course, if our customers lose that revenue stream, like it basically completely stopped for a couple of weeks, right? So that's, of course not. I mean, for the industry generally, that's not good and but for us as a as kind of a software add on solution that helps, just for E commerce, and is, you know, like, has a clear return on investment. I mean, it's then, yeah, we, I would say we more like a winner of the crisis. But I think overall, for the fashion industry, like, obviously, especially for, like, some kind of, like, these more old school brands that have like, 90% revenue and brick and mortar, it's, it's not good.

Jessica Owen
No, no. Um. So do you think that technology such as artificial intelligence and the Internet of Things, for example, do you think they're going to be somehow more solutions around those topics are actually going to be integrated into the sort of the textile and the apparel industry because of COVID 19. Do you think it's maybe sort of boosted that sort of industry forward?

Leon Szeli
Yeah, I think for sure, it's like sometimes, sadly, you need a lot of pressure to actually, you know, get up to speed and be more courageous about, like, innovative technologies. And I think especially in the fashion industry, I would say it was not necessarily the most digitized industry yet, but now it's basically the chance, I think of it, to catch up.

Jessica Owen
Yeah, no, I think I agree with you there definitely. And so we mentioned earlier on about how this technology can help a shopper, sort of shop more, shop smarter, and actually find a size that suits them, but from the shop and the retail point of view, I mean, I mean, I assume they're obviously going to be fewer returns, and that will help the business. But how else will this technology benefit them?

Leon Szeli
And so aside from like the return numbers, what we actually found out is that the conversion increase is also quite significant. And the context to that is that you know that on in fashion e commerce, usually there's a conversion rate of 2% meaning, like 98% of users don't buy anything. And turns out, a lot of those 98% and they don't order because they're just too uncertain about the size. They think, oh no, it won't fit me. Anyways, I don't want to go to the post office. It's like a 5050, chance between small and medium, for example. And actually, quite a few of those can, yeah, you can just convince them to buy something by giving them basically increasing the trust in choosing the right size. And that is, that is from a business perspective, of course, super positive because of just revenue you wouldn't have made otherwise, and you just eliminate this uncertainty factor size, and that is a side of the return rates, extremely helpful. And I think then there's also a third aspect to it. It just like, you know, just like the right thing to do, like, no matter if you do it because you're just lazy and you don't want to waste time as a user. You do it. You you care about our planet, and you just think it's super inefficient to, like, send parcels back and forth and repackage it and wash it and iron it again and so on. And, like, there's so many reasons to to get help on finding the right size and that, even just from a marketing perspective, I think it's, it's a great it has a great effect. I mean, it shows that your brand cares about, first of all, their customers, but also about the planet. And it's something new, like when shops integrate us, and it also, like, tells a lot about about the company itself, right? They're one of the first ones to adapt this technology, and there are a couple of other positive effects.

Jessica Owen
So is your technology? Has it actually been adopted by any companies yet, or is it still sort of in that development stage? No,

Leon Szeli
and we already have. So we it's not just fashion e commerce. We do. We also have a couple of other applications in like, direct sales of uniforms, for example. Okay, but we have, like, basically in all areas we are already live. And so we have, I think, 7e commerce stores where we are live, from, like, medium sized to big size ones. And, yeah, I mean, we showed that it that it works like that, people buy more that people return less. But of course, we're still a young company, and there is so many, like, nice features we have planned. We have so many, so many things like how we want to mature the product. But I think you can already say, I mean, it's working. We deliver the value. And, yeah, I think we are right at the stage where we go from having, you know, a couple of reference cases, to scaling it out, also outside of Germany. Well,

Jessica Owen
I mean, you've just said there you are still quite a new company. I mean, you've only been around for probably a year. So, I mean, from a business point of view, then how has the first year been for you guys? I mean, there must have been ups and downs. I mean, how's it all been? Yeah, I mean, overall

Leon Szeli
it has been, like, super, super exciting. It was just a great year. I think I aged more than one year in the last year, for sure. But it's, it's been an amazing time. I mean, it's just like, it's so it's such a great feeling to come to the office and then we have this big screen where we see, like, how many side recommendations we gave and how many users scanned. And just so great to see that number going up and up, because I know every like, it's just a number, but behind every single number, basically there is a user usually smiling while turning around just doing it. I mean, not just for us, but like, just doing it because they like the product we've built, and then also knowing that it just has such a positive impact for like so many stakeholders, it's it's just an amazing feeling. And it's basically also where we founded the company in the first place. We just wanted to build something that has a positive impact, ideally a lot of it, and ideally for a lot of people. And I think this is a technology that has the potential to do that. So overall, it's been a great year. Of course, there are ups and downs, and it's a super just like, I mean, it's a deep tech product. There's always, especially in the first month, there were always, there was always the risk, hey, maybe we can never reach the maturity to actually deliver the value. But now we know that it works, and we know it from multiple shops, from many users, and that's a great feeling.

Jessica Owen
I mean, is there anything in particular that you're really proud of? Is there, I don't know, a point at where you just thought, wow, this is a really big success of us. I'm really, really proud of that.

Leon Szeli
So one thing I can think of is like, so we are a venture capital backed. That means, of course, I mean, we had to convince investors to invest in our company, to even build the whole thing. And we heard like that was quite successful. We have very good investors on board that have a lot of experience in the industry. But from those who decided not to invest, often said, yeah, like, no one will ever do this. Why would I record a video of myself? Like, yeah, no one is like, I would never, ever do this. And our reply was, okay, maybe, and you're not like the target user, but we really think that users will do it, and now we know that they're doing it, and they're even smiling while doing it. And yeah, it's just like, it's, yeah, that's it. I mean, we made a bet, and it was successful, and it is, that is great. Yeah,

Jessica Owen
no, that is great. So, I mean, you said just a minute ago that you're looking to maybe mature the product, and you've got ideas for the future. So are you able to tell me about any of the next steps that you're wanting to take, and the plans moving forward, of course.

Leon Szeli
So one thing, as I said, we see people record videos, and actually way more than expected, but we also see that there is always, I mean, there are, of course, always users that don't, right, but there's still. I want to get help on finding the right size. So what we're doing now, so that's basically, we identified three main reasons to not record a video that is data privacy concerns, obviously in Germany, and honestly that they don't make too much sense, because we don't even store the video. We delete it, we don't even know the name of the people and so on. But of course, it's a valid concern, and let's say I understand that not everyone wants to record a video of themselves turning around. That's totally fine, but we want to help those users as well, and sometimes they're not, let's say in a space where they can record a video. Let's say on the train. In the office, we also get videos of people, but you have to. Maybe some of your colleagues might give you a weird look if you just suddenly turn around in your office. But for those people, essentially what we're doing now is we have so much data from the videos and the transactional data if they return or not, that we can also help them if they don't record a video. So essentially you can skip the video recording part, the result will be much better if you record a video and but also just based on age, with height and gender, we can, we can help you. I mean, you know that from the questionnaire solutions. So that means we cover all of the users that are willing to take a video, but we also cover the ones that don't. And then there's basically, I mean, what we see from our customers. There's basically no reason anymore to stick with the cure questionnaire solution, because we are basically a questionnaire plus a high tech video solution for those who are interested in using it. And so this is one of the main features we are rolling out. And then, of course, everything in the direction of 3d models. So at the moment, we created model of your body based on the video, and it looks pretty nice. It's similar to what something you would get from a very expensive hardware scanner that costs, you know, 50,000 euros. But we're not really showing it to users yet, because so far, it didn't make sense. Because you don't want to see yourself, you want to see yourself with the clothing you want to buy, right? And not all of the shops are ready in terms of 3d product data. But I mean, for us, it's basically just pressing a button and then if the three product data is available, you can see yourself with the product. So that's also a big feature in the pipeline, and one of maybe 1/3 interesting one is at the moment, we tell you, Hey, you're most likely size medium. But there's so much more we can do with the data. For example, your size medium, and it will fit you everywhere perfectly, except on the shoulders. It might be a little bit too loose. And then if you click on small, you see it's perfect on the shoulders, but a bit a little bit loose everywhere else. And that gives you much more context, right? Then it's, I mean, essentially, we're just helping you find the size. But in the end, it's your decision. Maybe you don't care that it's a bit tight on the shoulders for medium, then you buy medium. Maybe you say, actually, it should be loose everywhere, but on the shoulders it has to be really tight. Then you go for small. So we're just like, there to advise you. But in the end, it's the user's decision.

Jessica Owen
Gosh, really? I mean, it sounds like you've got a lot of work on your plate. I mean, it's incredibly clever all the things that you can do with this. So I'm intrigued to see if any shops that I go on in the future will have pre size and I'll get to give it a go a few

Leon Szeli
UK brands at the moment. So I let you know when you can use this. Yeah,

Jessica Owen
that would be great. Thank you. Okay, Leon, well, we're sort of coming to the end of the podcast, but there is one more question that I wanted to ask you, and that is, what sort of advice would would you give to people sort of wanting to start a company in this sort of day and age, and what are the sort of advice you'd give them, the steps that they should take and so on. Um,

Leon Szeli
so I think the first thing I would say is find something you're really, really passionate about, because you will invest a lot of your time. And I think just, yeah, so just having the right people on board, or just having, like, let's say a huge market is not enough. I mean, it's, of course, important, but I think the most important thing is that you're passionate, ideally about the problem you're solving and the solution you're offering. And at least one of those, yeah, I think that is the first tip. And the second one is, most of what you think when you start a business, all of the assumptions you make, unfortunately, a lot of that is wrong. And I see like being an entrepreneur, is finding out which of those assumptions are wrong as soon as possible and then iteratively getting to a solution. So for example, there's very simple tests to find out if you're wrong or not. I mean, for us, for example, we could have spent hundreds of 1000s of euros and tennis have 10 engineers develop a solution for two years just to find out no one is using it. And but what we actually did is like we started working with super small shops, and we said, hey, do you want to record a video? Yes or no. And then we found out, a lot of people said yes. And then we, you know, invested all of the time and resources to actually build it, and it mitigates the risk of it to build something that no one wants, and that's the worst thing that could happen. And, yeah, so I think these are my two tips, basically the tips to myself, to myself two years ago.

Jessica Owen
Well, I think those are wise words. Um, right. Well, Leon, I think that's all we've got time for today. But thank you very much for sort of joining me and explaining to me how precise works. And hopefully we'll get, I'll get to see that myself in the future online. So good luck with the future. I hope it all goes really well for you.

Leon Szeli
Thank you, and what a pleasure. Have a great day.