Okay. Welcome to the first keynote of the day. And as you can see I'm already joined by Sergio Yacobucci, who is senior director of e commerce marketing at Coveo. And he will kick start this broadcast today, walking us through how we can revolutionize, b to b spare parts with AI, and this is obviously a topic that is Both a little bit maybe of a buzzword, and I hope that Sanjay will now break this down for us, what it actually means in terms of business value. But it is also top of mind how we learn how to coexist and use these technologies to the best of our advantages, because they're not going anywhere. They they are here stay. And I think we have fully and clearly adopted that concept over the last year or so. So it is a joy to welcome serge you to our stage. And if you have questions for Sergio, drop them into the chat, we will cover as many of them as possible through the broadcast. If we don't have time, we get back to you individually afterwards as always. So over to you, Sergio, welcome to our virtual academy stage. Thank you very much, Lisa. Very excited to talk about this today. So, you know, revolutionizing B2B spare parts with AI is a is a space that I'm very passionate about and and Coveo is in in general. So I'm hoping that everyone today will get a lot of value out of what I'm here to talk about and, I usually do an agenda slide. So I know it's a little bit boring, but I want everyone to know kind of what what we're gonna cover today in in the session. I am gonna talk about Kavell and do a brief introduction, just so you all have the context of what angle we're coming at this from, and and what kind of challenges we solve. I promise it's one slide. It's very quick, and then we'll move straight into talking about the common b to b spare parts challenges. There are unanimous issues across the the the space, and we're gonna break those down and go into detail on each of those. So We'll talk about the ever changing customer experience expectation and how keeping up with those is very difficult. We'll talk about the fact there seems to be complexity everywhere in the business no matter where you look, nothing seems simple, and will break that down as well because there are elements to that such as data and the people and the business KPIs that make things complex. And then we'll talk about something that has changed and we have adapted over time, but the changing of long standing processes and the internal struggles and challenges that come with, trying to combine the e commerce channel with the with the traditional sales channel. I wanna talk about the future. I wanna talk about the fact that, b to b has a huge opportunity when it comes to generative AI. There are lots of applications for generative AI, in my in my view too many applications and people trying to apply it too much, I genuinely think that b to b has a really, really big opportunity here and has the opportunity to leapfrog b to c because of the amount of data and content that you have as part of business in general. So I wanna touch on that and kinda show you some examples of how that how that looks. So just quickly on Cavell. Cavell is an AI platform. We've been working with enterprise brands for well over a decade now, about seven hundred of them. And we have been helping them achieve what we call the AI experience advantage. That is utilizing AI to to their best ability in order to drive the best business outcome and customer experience so yeah, there's about seven hundred people down the bottom. We have some examples of of people that we work with in in the in the b to b spare parts space. We have about seven hundred AI experts within the business. And what we essentially do is enable these businesses to have a spinal AI capability that powers every element of of any smart interaction required. So be that website or commerce, or customer service or an internal workplace system, the Coveo platform is a composable AI search and genitive experience platform. Where the core belief is that the future is business to persons, so things need to be married up perfectly empowered by those two capabilities. And so, essentially, it's semantic search AI recommendations to make sure people can discover the entire product catalog, you know, through recommendation blocks. And generative answering for complex queries and questions that people have about information, and products, and then unifying that that experience that's personalized across channels. So we work with some amazing amazing brands, and we are a Salesforce Summit partner and one of six SAP endorsed that partners as well. So we know the space well. And when it comes to understanding the the common challenges within b to b spare parts, we've been doing that for a really long time, b to b, and it's specifically spare parts, have been a lot of Coveo heritage and a lot of the way in which we've built our platform has been to help, these types of businesses to to achieve what they need to achieve with the complexities that are associated with that. So we'll go into the overview of what know, we believe are the challenges within within b to b spare parts. And and the first bit is around experience. Customers who shop on a b to b commerce store have a really, really high threshold when it comes to the experience that they expect. They are bringing their b to c experience expectations with them to b to b. I think everybody knows that. But the bit that I think is quite interesting here is that despite it being b to c or b to b, the expectations are actually set by the interactions they have with any brand. And so it's not your typical sort of e commerce situations that might be rising those expectations. It could be as simple as They use Spotify every day, and they use Netflix every couple of days. And those businesses are completely built around providing a unique experience to every single customer. Powered by machine learning and AI. And so anyone that logs into their Spotify or into their Netflix, they all see different home screens, different covers, album art cover or or movie or series, album art, and the categories and how those are powered are all powered by AI, but different for for every customer. And that sets an expectation. I don't think they're gonna bring that level of expectation to every single experience they have online, but it sets the bar for them and therefore creates room for disappointment if that's not met. So very, very difficult to solve that problem, and it's coming thick and fast towards the b to b space in general. And there's quite a bit of catching up to do there to make sure that we can meet those expectations. The second one that I mentioned before is around complexity, and b to b, businesses, and I would argue especially in spare parts, complexity seems to be everywhere throughout the business, because of the amount of data that there is usually a little bit too much. And then there's, you know, we'll talk about this in more detail, but this there's issues with the structure of that data, but then also the business needs that need to be married up with that to result in what every business is trying to do, which is have a successful outcomes and achieve their KPIs. That is usually profit, but it can be other things such as revenue share or shifting stock, we're trying to clear a warehouse. So it's really it's really important that this complexity is understood because the underlying technology that powers this needs to have that context, otherwise it just creates additional roadblocks down the line if you don't have the right technology in place, which is very, very common. We see that a lot of the time that, b to b businesses are shackled by the current technologies that they have and they can't seem to bring the experience to the next level and without doing what seems like an overhaul. But usually if you have a composable approach, you can actually can actually change that on the platform that you're on. And lastly's process, You know, I think we've made really, really good strides to fixing this and, you know, I don't I don't keep bringing it up, but COVID did change. The the world for this in in e commerce, but especially in b to b. And I think that has continued through, but there are still problems when it comes to marrying up that sales and e commerce channel and making them work in harmony. And rightly so there's nervousness around that because of the size of of the of the transactions when it comes to b to b. So we'll talk about all of these things in in more detail and I'm, you know, gonna start off with experience go through to complexity. And then process, and then we'll talk about generative AI at the end. So what is it about customer experience that's that's changed and what is it that they actually expect You know, at Coveo, we believe that those expectations have changed for good. They started to change quite considerably as soon as AI became cost effective enough to use within the customer experience space. That was a big shift. Now with generative AI and people understanding that, you know, fifty five percent of people expect some sort of chat GPT like experience when it comes to shopping online. That's a huge amount of people. That research was actually done by us a few months ago. I'd argue that's even got larger larger now. So you know, when it comes to this changing, it's ever adapting. You need to be able to keep up and you need to make sure you're always meeting those expectations and hopefully exceeding them. But the the requirements from the customer are I expect to have a conversation that's just for me. I don't want a series of links, you know, to sift through with twenty, fifty, hundred pages of information because that's just difficult for me to navigate. I expect you to be talking to me specifically, or if I have a question where I need a longer answer, I expect you to be able to generate an answer for me that helps me solve my problem. And there's a lot of reasons why the businesses wanna do this too, but in, you know, instead they're kinda, you know, shackled by the the tech that they have. That concept of it being just for me, you know, proceeds into the next point, which is I expect my experience to be prescriptive. Customers now know that you know what it is that they're trying to do, or at least you should be able to know what they're trying to do. And they expect you to provide them with a frictionless experience to move through to the next stage. So when it comes to, intent and going, okay, I need to move from this step to the next and then I wanna achieve this next, need to make sure that that's a really easy thing, for the customer to do with the experience that you're giving them. And this is really where Spotify Netflix come to kind of change the expectation. They're really, really good at that. And that's where people are, you know, they they are disappointed if things drop below that level. And then lastly, it doesn't matter the channel that that person is engaging. With you on, they expect the the experience to be coherent. Doesn't matter if it's over the phone via email, via marketing email, or or on the commerce channel, they expect a coherent journey where people understand who they are, what it is that they're looking for and how to get them through to the next step. Channel is irrelevant to them. So I just wanted to talk about how we've done this with one of our customers and show you what the experience actually looks like. So gonna talk about fleet pride. And fleet pride are a huge, heavy duty and trucks, parts, distributor, in the US. Absolutely massive. And they have a huge, huge catalog, and, you know, actually a very good customer experience when it comes to people discovering products on their on their website. But it comes with all of the complexity that I've kind of already introduced And I just wanted to show you, like, the things they're able to do and to to help meet and exceed those customer expectations. So firstly, something that's table stakes, you know, I I would argue, but actually very hard to get right, which is good filters and facets. They have the ability to enable their customers to search within the results that they have. They can filter by what's in stock in particular branches. They can filter by specific fitment, or they can even search within facet categories to find information because the catalog is so large, you know, you can see here just from the screenshot. We've we've searched for break drum and we have three thousand two hundred options there that it's a it's a lot. So we need to make sure the customers can get to where they wanna get to and I'll show you some stats on, you know, why that really matters in a second. Then I think leveling up the experience a bit more is the ability to filter these products and work your way through a fitment finder. And that's exactly what this option is here. You know, you can do the year, the make, the model, and then the specific variant type and click go and then that will that will make sure that all of the, products that are being shown and discovered below fit the vehicle that you're looking for in this example. And that's a really important part of the experience, and that's a really important part for food pride to make sure that they stay ahead of their competitors. Then telling that I think the levels things up a bit more, it, yes, adds more complexity when it comes to a data perspective, but customers want to be able to pick things up in store and find out if they can do it on the same day, especially if you're repairing a a vehicle and you don't have the part If you're in the middle of that, you wanna be able to fight, get that part straight away. I know with, you know, some b to b businesses and, again, within spare parts, you'll have a transaction value that could be half a million, euros or dollars or pounds, and they're not gonna expect to be able to pick that up but there are scenarios where people do need to be able to do that. But marrying that data up between where that customer is, the likely store that they will want to pick that up from based on store geographic location, and then knowing the live stock and inventory information for that store and be able to coherently put that together and experience within within a few hundred milliseconds so that you can return results. Quickly, it's a very, very difficult task. But it's standard. It's become standard expectation. So being able to keep up with something like this is is is very important. And when it comes to fleet pride, just you know, introducing their general search. You know, they're there to to now offer predictive query suggestion based on what it is that you you are searching for. Recommended products within within the search itself as well, helps people find what they're looking for without having to even hit the listing page. And, you know, depending on what that person is doing within the session, and what their intent seems to be, there's the ability as well to make sure that those results that are suggested as a query suggestion are actually tailored to the to the session that someone's in. So they're going towards a particular category. You can still put filter WR in, but the actual res the actual suggestions and the recommendations will be different because they look like they're working their way towards a particular category. And again, it's just helping them move through to the next stage in a friction frictionless way. So why does this all matter? Unfortunately, I can't talk about revenue results, with Fleet Prime, but what we do have is information that shows how valuable this new experience has become, and it shows that when you meet and exceed the customer expectation, it it results in much, much, much better outcomes. So there's been a thirty seven percent reduction in search balances. So people are actually making their way through to the product page in all place the order, which is really important. There's a sixty three percent increase on time spent on page, because people are actually able to use the filters to find the product they need is extremely complex that discovery process, but they they are work they can work their way towards the correct product. And I actually think most importantly because customers value their time so much more and their frustration levels can get very high in the distracted world that we live in, that there's a ten percent reduction in searches required in order to hit the right business outcomes. So people are not having to go in and have, you know, fruitless searches time and time again. They're actually getting what they need through, you know, the the great interaction they're having with finding the products in the catalog. So these are really important, story and shows that how important it is to meet these these customer expectations. Then moving into complexity, sort of a second belief from from Coveo is that only AI can meet the complex customer experience needs and business outcome requirements simultaneously at any sort of scale. There's no way to do that in a manual way that won't break the bank. So, what is it that sits underneath something like a fleet pride in order to make sure that they're able to make the most of AI and scale out an amazing customer experience at the same time. So the first part is data, and data within any business that especially within this space is extremely complex. There's a seriously high volume of it, and there's big variety in terms of what kinds of data it is. So here we're talking about product data, as well as content. And that's somewhere where there's a huge opportunity for for b to b, as well, is that there's a huge volume of of content data. And it's really important that you make the most of that. That's part of the customer experience. It's part of the reason that sometimes people have to pick up the phones to to call in to ask questions when actually those answers could be there for them. So you have this problem of multiple sources of data some of it, on open systems, some of it secure, some of it in one structure, some of it in another, and trying to marry that all up into one coherent catalog is extremely difficult. The other part is millions of documents. Again, especially in this space, depending on what you sell, there are there are a lot of requirements when it comes save the information, usability information, compatibility, huge amounts of information there. That needs to be indexed and you know, made available so that AI can do its thing to to scale that out and help people discover it. And with those kind of like hundreds of thousands of product permutations comes the other issue specific to b to b, which is everybody pays different price and usually way in which that's solved is that multiple catalogs are created. And that creates a huge amount of complexity when it comes to know, updating those catalogs with refresh product information, how long does that take, how out of date can the data be when do you do that? You have to pick certain times to update that data. So that price will price entitlement is a really, really unique part to B2B, that causes a lot of complexity. For for businesses. The second part is that people element. You've got thousands to millions of users, You've got multiple audiences, potentially in different microsites in order to, get through to the to the right customer and allow them to create, do a transaction. You've got the concept of your internal customer, which could be your sales rep and your external customer, and it could be the situation today that actually they are using effectively two different systems to find information about products and content, which we would argue does not make sense, and there's there's there's no economies of scale there, and then you have this experience expectation that comes that comes with that. Now if you layer on the most important part at the end, which is what is the business KPIs and how you're going to make sure that you achieve those, you need to make sure that the system that you have has the ability to deal with this complex data and make it actionable. Understand the people and their intent and what they wanna do next, but also take into consideration what the business needs to do. You know, there are different, revenue, cost and margin metrics that make up KPIs for businesses depending on what it what kind of stage they're at. And there's so many operational KPIs, They need to be fed into that system to make sure that you're scaling out and not harming the business. It's easy to sell things on on on sale or reduced price or only show the cheapest, but is that actually the right thing to do for the business? Or is there a flex within the price elasticity of the product where you can show customers slightly more expensive one. You can argue the value of that with a higher quality and boost the average order value, but let an AI system do that all for you rather than trying to create you know, we've seen people with thousands of manual rules trying to create that experience, and then it goes out of date when the product had to look up dates and changes, or brand changes or a new one's introduced, very, very important part to scaling out the experience and and keeping the business front and center. And then I spoke about this concept of of process and, you know, we we we have got close to this, this winning combination of a sales team empowered and the customer empowered. Now whether they're using the same search, for instance, so sales rep is on the phone, customer is asking them information about a product. Do they search using the same search that the customer does? Not always, and that creates problems because the customer also has the browser window open and they're searching for stuff they're not getting the same information. It creates confusion. It's that poor coherent journey argument that we that we said at the start. But the winning combination really is for these guys to be using exactly the same, and let's make sure we layer in content to that as well. So if a customer is browsing the e commerce channel, and they are going through the process of buying something. Then they have questions, and they're gonna have questions because some of them are ordering know, hundred thousand euros dollars pounds in one go. They're gonna wanna check that their order is correct, and they don't wanna have any buyer's regret. They are gonna pick up the phone. Now if they have that conversation with the with the sales rep, what you want to happen is the sales rep does the same search and they get exactly the same information. And then also when the customer asks something specific about the product, that the rep can very quickly and efficiently find the information they need about that product. And and the content associated with it, that is that is very achievable and achievable very quickly as long as the systems are powered by the same technology, and that's something that's missing at the moment. However, businesses have adopted this hybrid model of commerce channel and b to b sales reps and the ones that are sprinting ahead and outperforming, others. So when you have a hybrid sales approach, that drives fifty percent more revenue than the single versus low channel approach that, was definitely present before COVID. And when it comes to nervousness around using e commerce, what when the reason I use that stat is because it's clear that when you adopt both channels effectively and it empower those two channels effectively, you can achieve higher revenues versus not. So this, yes, there's nervousness, and there will always be bumps in the road when it comes to combining those. You know, you've got a way in which things have always been done with sales reps. You've gotta change that, but there are lots of arguments, for making that something that's that's a consistent approach. But I know a lot of the nervousness also comes from This isn't b to c. You know, if people aren't spending a hundred dollars, they're spending thousands to hundreds of thousands, of of pounds and euros dollars, and that makes me nervous because I think if they're gonna back out of that order or they're always gonna have questions, how are they we're gonna make sure they're empowered to actually press buy when they when they construct an order of that size. But again, it's the case that seventy percent of people are willing to spend more than fifty thousand in one transaction. This is dollars because it was from McKinsey, but then also, there was twenty two percent of people are willing to spend five hundred thousand. So the the the the the intent from the customer is there. I think the more we reassure them about the experience, the more that every time they search, they buy, they receive an order, things are correct, they will continue to trust that experience more and more. Now it doesn't mean that the salesperson doesn't have a place in this. They need to help people through these very, very large transactions, but they wanna do it quickly and efficiently and get through as many as they can so that they can get their piece of the pie, when it comes to securing transactions as well for for the business. So there is a harmony there, but it needs to be achieved by using the same technologies and the business being willing to test and learn their approach, the the yeah. Their approach in order to see what kind of outcomes they can create for themselves. So very interesting space and something that, you know, I I'm very excited to talk to people about if anyone ever does want to and feel free to drop your questions in. I'm happy to give those an answer, but I also wanna talk about the amazing sort of future that b to b spare parts has when it comes to generative AI. Generative AI has been everywhere. And I don't think it's at the point that people are sick of it, but maybe highly confused about it and its application to a business. And there are a lot of issues with GenAI if you're not careful with how you approach utilizing that kind of technology. We have this concept of of five headaches when it comes to GenAI. I'm just gonna touch on a couple of them now quickly. It's extremely expensive, especially if it's not engineered it can cost like a hundred times more than than if it's if it's engineered in the correct way. It's super complex to do that. You need a a lot of AI and data science experts to be able to make that possible alongside the engineers that make that possible. That's a huge problem. It it's it's not the kind of thing you could just switch on and it just runs because it's gonna cost a fortune. And the argument really is there that how do you get the value out of it to to make up for the for the amount of investment that's required? Gartner think that people are gonna start pulling back their investment on GenAI because they can't see the value. And we think that's because people are going too crazy trying to adopt it in every possible way where it's not really the right solution. Just because it's NII and everyone's excited and they're hyped up about it. We don't think that's the right approach. The other things are around making sure that that the answers that are generates generated are extremely accurate. They're fresh and recent. Anyone that's used chat GPT knows that It's only index data up until twenty twenty one. It's fresh and recent and relevant. And that could mean that a document got updated this morning do you make sure that that's in the system available, but super secure. The system understands who has the rights to see certain information within documents if it is applicable, especially in the workplace. So there's a lot of complexity there when it comes to making sure that NAI works. I think, though, it will completely change how people self serve their way to a B2B purchase. There's a lot of examples where people need to pick pick up the phone to validate that they're going down the right route with something. And there are questions that they have. You know, we've just got these examples here, but Are there other parts that you need to consider renewing when changing a head gasket in a in a truck or van or car? What are the types of conformal coatings we can source for our new circuit boards. They're very, very specific questions where actually the information required to answer them usually exists within the business today because it kinda has to. There there are requirements when it comes to producing the right content alongside the products. And if you do have that within the business and it's in, you know, like pdfs and certain web pages, etcetera, you have a massive opportunity to use generative AI, to make the most of an amazing experience. So just to kind of give you an idea if we did drill into this example, Are there other parts I need to consider renewing when changing a head gasket? The answer can be populated around parts that can be considered to be changed and it can suggest that you might wanna change the head bolts or studs, the timing bell, camshaft, with camshaft bearings, and explain that you might wanna those checked. So if someone is placing an order and they're going through the process in this example, they might wanna consider or they might have been told by the people that told them to place the orders. To to order some of these on top of it. And the generated answer that you could get from the likes of the Coveo, Yes. Generate accurate results and show the information required, but they also suggest you go and browse the particular section to go and add those. To your to your car and your overall order. Or if you need more help and you need more consultation, call one of our experts, or, you know, on this number and make sure you're making the right decision. So it can still lead to the sales channel, if required you're helping someone self serve their way, there. And you can imagine these questions can be extremely specific. As long as the content is there to answer them, but that's part of what generative AI helps to solve, that piecing these pieces of information together and structuring the right answer that's accurate, you're able to help these people find out this information, as they're making their way through their purchase. It might even be the case that they're able to educate themselves further the telephone conversation only takes five minutes rather than it taking twenty five minutes. So there's a lot of gains to be had there, but this is why I think B2B has that opportunity b to c does not have this level of content and specificity around purchases. B to B does. So the application of generative AI is game changing for the space. It's still very interesting for b to c. But I think there's way more opportunity here to get this right and help people make their purchases. So something I'm very excited about and super passionate about. And I know we're gonna go into some some questions, now, but I just wanna say thank you for for listening. And if anyone is interested in getting involved in Genative AI, we have a beta program that's closing quite soon. So, if you wanna get involved in that, just reach out to me. I know my surname's quite hard to spell, but take take a look at it there and just pop me an email, and I can put you through to the right teams and have a discussion, but there's no pressure there at all. Thank you, Sergio. And thank you for sharing this. I agree with you. It is it's a very interesting, path ahead. I would say, especially since, you know, you cannot buy what you cannot find. So, you know, this is kind of especially in parts, and since this is a parts focused event, I mean, we we do know that as you were saying, it's a big I mean, it's not only maybe the channel itself, that that is going to be, the the biggest sort of crater revenue. It's this sort of combination of different channels, like the McKinsey numbers, they're showcased. And I mean, obviously, with parts, it's also with spare parts. It's also often the assumption that the customer is in some kind of need when they go look for this. So the conversion should be fairly easy. What do you say? I mean, looking beyond sort of, today's, trends of maybe the spare parts and so forth. What do you say is going to be, you know, the biggest advantage of of these kind of suggestions? Is it the upselling aspect of the customer with the suggestions on what else? Is there for you to look or others have also bought you know, that's a very retail kind of thing to suggest. What do you see as the next next step ahead in terms of of, being able to sell more parts through this? I think it really depends, like, where the business is today and what that experience looks like today. I I completely agree. And I kind of wish I'd mentioned it, actually, now now you say it, but there is always that immediate need usually with spare parts. Yeah. Something's normally broken or about to break. Exactly. So there is there is that immediate need Yeah. And and with that immediate need, I think those kind of three customer experience things that I mentioned at the start, they get elevated even further than than usual. Because if a competitor, if you are in that kind of space where someone can buy their parts from somewhere else, they have they can have multiple contracts, and they have a really nice experience where it's a really great website or great app where I can really quickly find it. I know it's gonna be delivered today, and I can go through that process. They're gonna beat you because there's that customer experience advantage that they have. So depending on where you are, if you don't have that today, that's by far the next most important step Now not not many b to b spare parts businesses are at that space, but there are a few. Normally, when it's a bit more b to b to c, that because there's that pull from the customer that you've had to create that experience. But that's a really, really important part. I think the next step is, is it frictionless for someone to get the thing they need ASAP? If it isn't and there's lots of roadblocks in your customer experience or people can't find stuff, you need to address that straight away. That's one way to making sure you you get your portion of the pie if a customer is able to buy from multiple sources outside of yourself. When it comes to, suggesting new things or extra parts, I think one, that's an amazing customer experience because the last thing somebody wants to do receive the part and then realize they need, you know, they needed a few extras. It's not always the case. The person fixing something or changing something always places the order. So someone else will need to be alerted to that and at least raise the question with the person who is fixing it. So that's one way for sure to increase average order value. But I also think people are gonna call in and they're not gonna use the commerce channel, you want your sales team to be also empowered by, yes, the great search and making sure they can see the products and the content, Also, generative experience. If they're not sure on the answer, they can also ask the same search that longer question and get a longer answer to guide them down the right route. You might wanna look at this manual fitment right, to see what part that person needs for that really old engine, that's being that's that they're talking about. So I I think there is, again, it's about an amazing experience that should then compound into loyal customer base spending more with you and time and time again because always there to meet their needs when they when they're in that moment. Mhmm. And what would you say as a final question because this is obviously, the the concept of AI and generative AI may be more than, now lately has been very I I know it's always disputed. They're the the ones that are very passionate about it and, you know, see it as the the biggest revolution, and I think I mean, as I started off saying, it goes, it's quite clear. It's here to stay. So it's more about how to to properly integrate it. In our business models and strategies, I guess. But what is the biggest assumption or like prejudice if I may against AI that you meet that you think we need to kind of remove from the the table, take out of the discussion now because it's time to sort of move ahead because I guess you get a few objections like all. Of course. Yeah. I I have a huge one that really really bugs me all the time. But just quickly, like, we to hit Coveo, it's AI or die. And we really do believe that, you know, you have to adopt it. Otherwise, you're gonna be outpaced. It's not it's not, you know, like, a generative experience is gonna overtake people's jobs. It's the people that don't adapt and use AI if effectively to make sure their workforce is really, really efficient. They are gonna struggle because their competitors are. So, yeah, it has to be adopted. There's no doubt about that. The biggest gripe I have with AI in general, and I think people listening to this would probably probably agree with me. I am quite sick and tired of people claiming everything's AI when it's not. That's the biggest that's the biggest issue. Actually, underneath is just a set of manual rules of if this, then that, then do this and lots of form. Like an extended Excel formula. Yeah. Exactly. And think it's super frustrating. It's frustrating for an AI business like us because, obviously, we compete in that space and Yeah. Explaining everything. I think it's actually it's not about us is way more frustrating for people going through the process of buying these kind of technologies and feeling like they come out of a process at the end and everyone sounds exactly the same because everyone claims all of these AI capabilities. At the crux of it, it's really, really difficult to build a scaling AI system that is cost effective that will work and generate the right value. There's no way everyone says that who says they have it, have it, but it's so it's very difficult for a buyer to go through the process and figure out who genuinely does. And it's annoying in a way because actually it's the behind the scenes stuff, how the data is structured, how you update catalogs, how you run your models, the really kind of quite not exciting UI, like, oh, this is how you click click and then this is done. It's the non exciting stuff. That actually changes the game because when it comes to, you need to update your catalogs, and then it takes a whole day with the system. That's a nightmare. And then your AI can't run constantly because it's on old beta. I think that's the biggest issue right now is too many claims in that space, and it's tiresome. I can understand that, and I always say that, you know, there doesn't matter also. AI is not some kind of, you know, autonomous robot necessarily that just, you know, goes and kind of tries to conquer the world and doesn't I mean, no one has claimed that, but sometimes it feels like we paint it some, you know, very scientific or very sci fi kind of creature almost, and in the end of the day, it should work for decision makers as a tool, right? That's what it should do. It should be implemented into the strategy. So it is something that I think, we will see more and more of as you say. I think you will be outpaced if you don't, embrace that and kind of make sure also that you because labor is the most expensive asset we have, right? So make sure that your your sales team, for example, is spending their time on consultative sales, maybe instead of admin or other kind of, you know, things that AI could actually help them with. So going to be an interesting, development from here on. Yeah. And, you know, AI loves complex problems. And that's why, again, it's application to b to b and you know, then you go even more complex into spare parts because of, you know, fitment requirements and all, it it's even more akin to sorting that problem out and it loves that space. You know, scaling it out effectively is what it's, you know, that's a great, great opportunity. Yes. You still get that in b to c with people with huge catalogs and there's a lot of complexity there too, but they don't have the issue of usually of fitment. They didn't usually have the issue people paying different prices for their products, it that layers on so much when you've already got a huge catalog, the amount of permutations you can have, a huge. You cannot create rules and manually merchandise your way out of those problems. You can try with, like, some top but you'll never get to the point of of it being great for everyone. There's no way. There's no way. But I will leave the audience with this, that it's definitely, coming. And I think, some of the the most impactful, notes here, right, that I take with me is obviously how it really you know, helps in in terms of making life easier for your customer, number one, and obviously there is space you wanna win in, and I think those numbers where you showcased also the the time spent on the website and the more successful, you know, searches and all of this this is definitely the the future. We can't have people coming to it's almost annoying if you think of it. If you have an immediate problem, you come to a website and you can't find what you're looking for that is very bad in terms of brand. So I really would like to leave the audience with that. I think about not only having a website, but also making sure that you convert or have people that wants to stay in it, in the web shop. So, especially in parts, because as I said, you have an immediate need normally. Yeah. And that is, something that we should really be careful in convert converting to to make sure that our brand is recognized a positive way by our customers. Definitely. So thank you, Sergio, and I will, encourage everyone despite his, tough last name to reach out. You can do it over swap card or, just post this discussion. You can reach out to the corporate team, and we can also, help you get in contact. So thank you, Resarete, for joining us this morning. Worries. It was a pleasure. Thank you so much for having me. Thank you.