Latest / The Interline Podcast / Bespoke Technology, BNPL, Mystery Boxes, AI Advisory, And A Case Study In Bad Fit
Transcript
- speaker-0: So welcome to the edit from the Interline, the show where we run a quick fire analysis on our pick of the most important fashion and beauty technology stories from the last seven days. I'm Grace, the social editor, and I'm joined by Ben, the editor in chief, and together we have less than twenty five minutes to give you our analysis on the stories that we think really matter. speaker-1: Hello Grace. You're joined by Ben from a very different location this time. So ⁓ anyone who's been watching the video versions of these will recognise a difference in background. Anyone who listens to the audio versions might recognise a slight difference in audio. So I am away from home at the moment. I'm on a kind of working holiday in Spain. ⁓ and as it turns out, the Wi Fi in the apartment I'm staying in is is terrible. So I'm recording this from a cafe by a marina. ⁓ you can't see the other side of our screen. Also put really nice boats and yachts and things over there. ⁓ But yeah, you're getting a very different side of famous speech. On that basis, Grace, what do we have newswise? speaker-0: Yeah, so there's been a lot of news this week that kind of is highlighting the conflicting bets that companies are placing either on general purpose tech versus self built or heavily customized tech, either built just for them or for their sector. Now, on one side, you could say that this is an AI story. Because Thinking Machines, so a company founded by former OpenAI employees, have released new research that suggests that narrower, cheaper AI systems trained on specific domains will actually start to outperform like bigger frontier models. On top of this, this is also like a general technology story as well, because this week we've seen that the beauty giant BeautyPie has shed its own custom tech setup and actually moved to Shopify. And we've also seen the Very Group, so a UK-based company that sells fashion and furniture and stuff like this. They've handed over all of its pricing strategy to agentic AI. But then on the flip side to all of this, I also saw a story from Retail Drive saying that big general purpose chat bots like ChatGPT, Claude, and Gemini, for instance, are actually outperforming brand's own custom bots. And we've also seen that IBM stock has dropped 25% in a single day. So with all of these stories, I really want to get your take on what's going on here. Is general purpose tech the answer? Is custom tech the answer? Or as I suspect, is it all a bit more nuanced? speaker-1: It is all a bit more nuanced, so your suspicion is correct. IBM is arguably the most synonymous name when it comes to like general purpose technology. Outside of Microsoft, if you were to say what is the general software company, it would be IBM. It's i you'd be very hard pressed to define what they actually do. ⁓ and I think the slump in their stock is representative of the way that the Epic Source is shifting from companies spending on ⁓ like big enterprise software to the investments that are being made in hardware infrastructure that's going behind all of the AI buggles. Now the AI question is it's an interesting one on one level, but it's also kind of an inevitable one on the other level. So for a long time kind of pre-Chat GPT, a pre-generative AI this division in AI was between What you would class as ⁓ kind of narrow AI and general AI. Narrow being focused on very specific things, so playing chess, playing go, protein folding, like that kind of stuff. And and they made a lot of advances in that area. The thrust then moved the ChatGPT and Claude and Gemini over to AI chatbots that can do anything, right? If you think about the parameter count, so the size of something like Claude Opus four point eight or what have you. It's huge. It's in the kind of trillion parameter count in other words. Now parameters roughly correspond to capabilities across different domains and knowledge across different domains. So if you go towards Claude, you can ask it anything from what should I wear to can you help me code a website from nothing? Can you help me code a game from nothing? What the thinking machine story is about is effectively saying, Well, that's well and good if the one was one stop to do potentially everything. But it's the perennial kind of jack of all trades, must be none situation where if you have one solution that can do everything, it's it will eventually be outperformed by a narrower solution that is trained in best practices, grounded in data and context, and given specific skills and reinforcement learning that are set to specific. ⁓ so I think that's that's the interesting part. Now the move away from custom tech to ⁓ the likes of Shopify, which I've never been asked to Spotify, ⁓ that something you will see happening in a lot of prices. So there'll be companies that have invested a lot in building out capabilities that they saw as pioneering. They were new to them. They were things that they could not find in the open market, at least in the combination that they needed. The open market marches forwards. So if you as a company spend five to ten years building something, embedding it, training everybody to use it, integrating it with all your other systems, before you know it, what's available as a cheap subscription or royalty based success solution is suddenly better than what you built for yourself. So I think we'll see a lot more of that. Now the general purpose chat bot thing ⁓ is interesting because what that's effectively saying is if you turn up to a retailer website to farm store for it and you want to ask questions about the product, you want to say I'm looking for something that performs like this, it's suitable in me scenarios and so on. That's saying that general purpose tools like ChatGPT are better at that than narrow focused chatbots that have been deployed on eCAM storefronts. Now I I find that fascinating because presumably the narrow bots are better ground built and better anchored in the ⁓ the product mixes and the assortments and the data that those brands and retailers have. Whereas ChatGPT calls Gemini and so on are not. They are big general purpose. They're not embedded in the same way. ⁓ I think that's a reflection of just like pure model capability overhang ⁓ like the frontier models are better at asking and answering questions than the than even the best grounded ⁓ examples of those. ⁓ I think the nuance is only gonna get more complicated over time. If you're a company that sees a lot of value in being able to have one stop shopping, one AI that does everything, one technology statement does everything, I think that's valid. And I think that's especially valid with companies like Shopify really push the envelope on those things. If you do want to custom build, I think the options are still there. ⁓ but I think the options look more like custom building with AI or custom training AI than they look like fully building out bespoke solutions. speaker-0: Now, in previous episodes of the edit, you've mentioned the potential risks of different AI applications and different AI voice mode chatbots actually funneling people towards purchases that include a buy now pay later component. Really interestingly, this week there's actually been a lot of development with this specifically. So the UK government has actually issued new regulations. That are gonna do like more detailed checks into lending companies like Kwana, for example. We also saw a really interesting survey that interviewed 3,000 people. And this was from Park Christmas Savings, which is a company that I'll let you explain, Ben. But basically their survey shows that three-quarters of the people Who use buy now pay later services actually spent more than they intended to. They also said that 35% of them later regretted using these services, and also nearly a quarter of them are still paying off borrowing more than a year later. So this is both a technology and also a social story. So I wanted to get your take on what this means for fashion. speaker-1: Yeah, so I've long considered a lot of these kind of buy now pay later fin fintech companies as debt vehicles and letters d just with a slightly different label on them. The legislation in the UK is now catching up. I'm not the only person that texts that legislation in the UK is now catching up with that. So the kind of scrutiny that would be applied to Flaner is not the only one. There are there are plenty of ways to actually or plenty of ways to spread of spending. what the UK legislation does is apply the same kind of scrutiny to credit for the people who are taking out the borrowing as it would if you were to apply for credit card. ⁓ so I if I was to go into a bank to say, I want a credit card with a 9,000 pound limit, they would say, cool, let me run some background checks and make sure that this is affordable for you month on month, that this doesn't exceed your capability, it's not going to put you in a debt job. Now this seems like a logical step and I think it's the correct step for ⁓ for regulators to be taking. The Park Crisp so Park Crisp Savings is a very, very weird company. ⁓ they they actually reached out to us with the results of this survey. I'd never really heard of them before. I did some looking into it. ⁓ it's a way for ⁓ consumers to spread the spending that they do around the kind of peak holiday season through a mixture of kind of storecards, vouchers and ⁓ and a bunch of other things. They are effectively a another lender, but they are effectively kind of a spending spreader in their in their own right. They're just not classed as like a fintech company. Those things have been running for a long long ago. those statistics that you mentioned are interesting and depressing because spending on things you can't afford is fairly it's an epidemic ⁓ of particularly in the UK but and in a bunch of other places. Now it comes about through a mix of cost of living increases and the fact that people simply can't afford the things that they want anymore. Sure. It also comes about because brands and retailers see this as a way of securing growth at a time when spending is not increasing, when ⁓ bash and share of your spend is not going up. But it's competing against not just entertainment and travel, it's competing against essentials like food. and the Concern that we've had and that we've raised before on the edit is you can put a buy now pay later checkout at the end of a traditional e-comp gym. ⁓ you can have it sit there alongside Apple Pay, Visa MasterCard, and so on. ⁓ and it's it's an option people people can use it as they s as they see fit. ⁓ the difference with AI voice mode in particular, AI interactions in general, is that they are more persuasive and more captivating, more engaging and more likely to encourage people to make a purchase than a traditional e-com journey is. If you then add this idea of that three quarters of people spent more than they wanted to when they when by an I buy by an L paylate was presented to them, that they're still paying off their debt a year later, you see an uncomfortable pattern developing where brands and retailers could see this not just as a way of Securing growth because people spread their spending, but as a way of actually getting people to that point as well, if they wouldn't traditionally been there. Now somebody argued with me about this on LinkedIn later, so I said, Well, how is this any different from traditional advertising? I see it as different because traditional advertising is passive primarily. There's personalization to it. Looking at an image, reading a piece of text, scrolling through an e on the storefront or product detail page, to me feels different than having a conversation either in text or in audio. with an entity that is very good at keeping you engaged, very good at trying to get you to the next step of the journey. ⁓ I know I might be through long on this in the long run, but to me this feels like an an unhealthy hook after an unhealthy hook. speaker-0: Now, a few weeks ago we talked about StockX and you mentioned that some of the new business things that they're implementing, such as creating physical stores and also creating more peer-to-peer capabilities on their platform, was actually putting them on a completely different company trajectory to what they've been on traditionally. So with that, I'm really interested to know what you make of the StockX news this week. So basically, they're launching these mystery boxes, which are effectively bundled up verified inventory that is split into different tiers. And also, I quote, the prices based on current sales data from the platform, reflecting real time demand and also resale value. Personally, I think the concept of mystery e commerce is really interesting, but I wanted to get your take on what you think of this and Also what you think our listeners should be learning about this or what you think they should make of it generally. speaker-1: I'm going to start with a question back to you, which is would you would you buy something like this? Would you would you see value in this? And value, as we said, so the the claim that they are making is, and I'm sure it's substantiated, is that the value of every mystery box is great the contents of it is greater than or equal to the cost. You're not going to spend and end up with something cheap ⁓ thereafter. So from a pure monetary spend point of view, I guess it seems logical, from like a behavioral point of view, I'm interested to see how you feel about it. speaker-0: I think I would do it if I already trusted the brand and if I'd shopped from them before. And also I think if the price was right, like if I really felt like I was getting a lot more for my money. But overall, yeah, I think I would be tempted by it. speaker-1: No, I don't think I would. And I wonder if that reflects an age divide. ⁓ it also I'm gonna sound particularly coming out of the buy now for a later conversation. ⁓ I'm gonna sound a bit cynical again. ⁓ I I it's it's not great that everything's becoming gambling. ⁓ this is this is not not gambling strictly, but it's not great that everything is becoming a matter of playing the odds. So I think you have to read this alongside the rise of polymarket and Calci and so on, none of which are authorized to operate in the UK, but we're all aware of. because people sure like playing the odds and likes where ⁓ where spending is concerned, where now the interesting part with this is that the mystery boxes are all made up of what StockX referred to as their verified entry. So when we talked previously, the different models that they were trying were the kind of live shopping ⁓ creative studio stuff and the permanent physical price. premises they were heads ⁓ setting up unmaintained in New York City and also the fact that they were allowing for trader to trader peer to peer direct interactions. Now the reason that I called that set a different type of company last time is that selling peer to peer and having yourself exist as just the pipes in between is it's the eBay model anyway. It's it's everything it's the it's the thing that StockX has never been. StockX has always been a company that says send send in the inventory, we will verify it, we will grade it, and we will help to dynamically price it. Now you can take the dynamic pricing component of that, which is data driven, which is great. now what I suspect they have is a lot to be verified inventory. To me it just reads like a company that has excess stock setting warehouses that it needs to move. ⁓ and again like that's like that sounds like a cynical lead. Now behaviorally I think this is on point. Like I think stock ex are doing interesting things. I think the right to be going after live shopping. I think the right to be going after best playing like a short business perspective. It's not something that I would invest in because unless I've missed a point, ⁓ you you don't know what brand you're gonna get, you don't know what product category you're gonna get. There's there's there's a lot of uncertainty in it. Now the uncertainty is the fun and the uncertainty is the game for some people. I'm not a gambler and I don't like uncertainty. So I don't think I'd use it from that point of view. It is a very interesting tech Story though, because it is pricing is dynamically driven by data, inventory is presumably dynamically driven and packaged, contiered, and bundled according to information that they have about life for sell-through rates and everything. Long story short, if you have a lot of product and you have a lot of disability into what it's worth at a minute-to-minute level, you could start to build some really interesting things on top of it. ⁓ so I'm kind of watching StockX with two lenses. One is I think it's a damning testimony to the way that people shop, but I also think it's a really smart business that's doing a lot of interesting stuff like that. speaker-0: The next story addresses the shift that's going on with how big companies are using AI. And I know this is something that the Interline wrote about not that long ago, so I'm really interested to get your take on it. Basically, the idea used to be that advanced AI models were so capable that businesses could use them without much help. But now companies like OpenAI and Anthropic. Are spending heavily on these advisory services to help their customers put AI into practice better. And tying to this, the Business of Fashion ran some really interesting analysis this week where they were saying that AI itself would actually or could actually be replacing consultants. And they concluded that typical consulting work, like Building strategic decks, gathering general research, also getting consultants for like one-off projects is all work that is now being replaced by AI. And they said that instead companies would be better to pay consultants to help them kind of like optimize their product search for AI and also help with AI shopping and agentic shopping. They also said that they could use consultants for like designing new AI workflows within their business. I wanted to get your take on all of this. I know you have some strong opinions about service days models, so yeah, what do you think of it? speaker-1: Strong opinions that I have about service-based models stem from the fact that I'm cold-ish. So I've been around long enough to see a time when the majority of software projects came with software licenses, which you would expect to be the primary specs, right? So if you if you were buying a big KillM or ERP or some other big enterprise software, you would say, well, the software is where the bottom line is going to sit. That's that's what this is going to cost me. In reality, a lot of those projects are heavy. heavily, heavily indexed on management consultants, either your kind of big third party, Silver Lloyd, Kurt Salmon, and so on, or direct consultants employed by the technology companies to come in and say, if you can't find the value, let us find it for you. If you can't make this work, let us let us do this for you. and the those are what we class as service days. So ⁓ but how many people do you need to bring in? How many days do you need them for? And and in reality it ends up being months worth of custom work. ⁓ it's it the reason I have an issue with the service days model is that it persisted for far too long as well. It was a relic of the like on-premise custom deployment era, but it persisted into the cloud native software of the service era because it was the model that a lot of companies were built around. Now, in theory, AI is supposed to replace a bunch of that. And the business of fashion analysis is very interesting because ⁓ if you have a big generally capable model like we talked about before, ⁓ and if you've ever sat down, you've thought, hang on, how do I connect sword to this? How do I connect JetGPT for this to this? And somebody's gone, just ask it, just get it to do itself, get it to build skills, you'll have an idea of why that kind of where that difference comes from. now I don't think that's gonna prove to be the case because I feel like we are right back with AI where we were with traditional enterprise software, which is people saying, I We can't find the value. This is not translating into measurable, quantifiable metrics for us. So we need we either need to pull back from software spending or quite a surprise, we need to get external consulties or first party open AI or ⁓ antropic consultants to come in and help us architect and find that value. Now, the business of fashion kind of the two strata that they put this in ⁓ is correct from my point of view, because what they are referencing is They need people need consultants to help them build workflows. People need consultants to help them build logic. People need consultants to help them build different journeys. Cause that's where they're going to find the value ⁓ of of AI, where it is to be found. ⁓ people do not need somebody else externally to come in and put together a presentation to explain what that value is. They don't need somebody to come in and work directly on implementations in quite the same way. ⁓ It's gonna be interesting to me to see how companies like OpenAIS deployment company, Anthropic's new company, which is called O which is like again, like it's it's forward deployed engineering and so on. I'm keen to see if they actually end up being different types of consultants and different types of advisors to what we've seen before, or if in a year or two's time they end up looking an awful lot like the kind of generic best practice model of consulting that we've had ever last time. speaker-0: final story is kind of a comedic or funny one at first glance, but it does have some hooks into a deeper and more serious problem when it comes to fit and product development of mass-produced products from big brands. So it's been a story that's garnered a lot of attention online, but basically a lot of women are taking to TikTok to share how a very specific pair of Zara trousers are causing them to trip up. And this is causing them to scrape their knees, get bruises, or just injure themselves generally. So the trousers are long, they're slinky, they're wide-legged. And it's funny because I actually had a pair of Zara trousers very similar to this in the past. And I remember actually tripping up when wearing them. I assume that you don't have trousers like this, that you haven't bought this specific pair of Zara pants. But with your knowledge of like product development and fit. I wanted to get your take on how did we land here? Like how does a big company like Zara get it so wrong when it comes to fit and product development? speaker-1: So this is two two little things. There's two bit there's two bits to fit. There's like objective scientifical fit and then the subjective like wear testing else. You can have a product like this that technically fits. It fits your fit model, it fits your 3D button if you're doing it on that basis, in the sense that it cinches in the right places, it's loose in the places that it should be, it's comfortable for for somebody to wear, ⁓ it extends well across ⁓ size range or breakers and and and so on. You can do all of that. And still get fits subjectively wrong because nobody is wearing the thing and taking it out and using it. Now companies like Zara and so on are not gonna do a lot of fit of like field testing. Field testing is traditionally reserved for like outdoor wear and running and that sort of stuff where you really need athletes and people to go and test it and make sure that it works. I would say there should be more field testing in ⁓ in general styles, I think, on that basis, because it wouldn't have taken more than somebody walking up and down a corridor to identify something like this as ⁓ as an issue. So yeah, the the the quick answer is more field testing. ⁓ the slightly comedic answer I can give you as well here is I don't own early pads. However, I'm going back to our age disparity, big jeans, huge when I was a teenager, ⁓ like ⁓ is it JNCO, I forget but like the you the big, big baggy wide leg jeans. I remember everybody in my high school, ⁓ when we were allowed to get out of uniforms, had jeans where the entire back was frayed because you just walked on them in your fans or DC shoes. ⁓ and I no doubt people tripped over a bunch of them. The same people who probably got their hands caught in their wallet chains and everything else. Let's see if we're talking about wallet chains in the in the future, because I feel like things are coming full circle. speaker-0: Amazing, that's all the stories.