Hello, everybody. My name is Adam Thorne from Inside Retail. And today, I'll be moderating this webinar discussing Freedom Furniture's Customer Experience secrets. We'll examine how the retailer is turning casual browsers into loyal customers, and the kind of next generation tech they're using to do so. And all of this comes at a time when the way that customers discover and buy products is shifted with higher expectations than ever before. Now, joining me, I have two guests. First up, we have Federico Jalil, the Digital Product Manager at Freedom Australia. And Federico is a data-driven marketing professional with 10 years of experience in the digital space. He excels in digital transformation and digital product development and management. He's also an expert in data research, analytics, and the implementation of strategies. And next we have Kevin Annfield, who is the team lead of Customer Experience solutions at SAP, and SAP technology works kind of behind the scenes to help businesses understand their customers better, serve them more smoothly, and stay consistent across all the different touch points. Obviously, Kevin and Federico work very closely together to improve Freedom's customer experience. Before we crack on, I just want to remind everybody watching that you can submit questions in the chat box in the bottom right-hand corner of your screen, I believe, and we're going to set aside some time for some questions at the end. Kevin and Federico, thank you very much. And we will crack on, we will steam in. Federico, I'm going to start with you now. Freedom is a fascinating retailer to do this on because it's almost I would say like a kind of extreme example of an omnichannel retailer because many customers would maybe see a product in online and then go into the store to kind of touch and feel it and if it's a bed, they want to jump on it or a sofa they want to sit on it. And then they might think, I'm not sure. And then I might go home and have a little think and maybe buy it online. So I don't know if you could talk me through, what are the kind of typical purchase or the kind of typical customer journeys that your customers go on. Because I imagine, actually, it varies quite a bit. Yeah, sure. So it is a real challenge for us. You know, Freedom has a very wide variety of offerings, you know, going from homeware items all the way to furniture, and that leads to the price point to range from, you know, candles at $30 to sofas at, you know, $8,000. So you can imagine that the purchasing journey will widely change and vary depending on what mission the customer is on. So... It is a significant challenge for us to start to, you know, pinpoint all the possibilities of journeys, you know, with that in mind, our strategy is mostly focused on making the omnichannel experience as efficient as possible. It's very hard to select a number of journeys to optimize. So instead of doing that, our strategy is just to make sure that wherever you're purchasing, there is no friction and there's room for inspiration. So just to give you a few examples, you might have customers that are purchasing a mattress for their main room. And those customers most probably will want to go into the store, test every single mattress, lay on them and make sure, okay, this is the one. Now, if you're purchasing that for your guest's room, you'll be happy to, you know, just purchase it online, get it done. You know, you got your in-laws coming home for Christmas, and you know you need to get that mattress sorted. So, at the end of the day, we do emphasize a lot on making sure that the information is there, that the discovery journey is there and that customers have all the options available for them to discover a product in store and purchase it online, or the way around, discover the product online and just walk into the store and have it delivered to their place after purchasing in store as well. So, that's our focus and it's been a fantastic journey for the past two years that I've been at Freedom to discover and, you know, nail that challenge. Now, before you started to really think about making those improvements and investing in that software, so before a couple of years ago, what were some of the problems you faced with your Customer Experience? Because like you've hinted there, all those products are going to have a very different kind of customer journey, and then all the different customers are going to be different themselves. What were some of the issues you faced before you really kind of invested? Well, from a challenges perspective, I guess, you know, the wild variety of customer possibilities in the customer journey is the number one challenge, right? So, you now, having a disjointed or the opposite of an omnichannel Customer Experience is the very first problem that Freedom has solved. And this was solved prior to me arriving to Freedom, so there was a team already focusing on this. This is years of work to get to the point where we're at today, where the focus was on driving that omnichannel experience. Now, when I joined Freedom and for the past two years, we've been significantly grow in our product assortment due to our dropship program, right? So, you know, if you were to go to the Freedom website four years ago, you would see around 12,000 products listed online, where if you go to the Freedom website today, there are just over 70,000 products available, right? For us to make sure that the discovery was on point was one of the key challenges that we wanted to to solve over the past, fair to say, year and we have adopted this mindset that it's a constant work in progress journey to make sure that that omni-channel experience continues to be optimal and you know remove all the friction from that shopping experience without ignoring the room for inspiration, right? Because sometimes as you remove friction, you might be taking away the inspiration component where you allow the customer to see more products, dig deeper into the catalog and what not, just in order to make it straight to the checkout. So that's a balanced approach that we try to take towards that omnichannel experience. I might bring Kevin in here if I can. Federico just said something really interesting there that they've got like what 70,000 products. Now presumably, no human being can go and work out what the perfect customer journey is to all of them. Is this where kind of technology can help us because presumably, it can do things that can work out things that human beings will struggle to do. Yeah, absolutely. Thanks, Adam. It really is. So we have a variety of different solutions that our customers can use. And I think the key here is that the business people can use to try and work out the right journey for customers to take. A lot of the time, the people that are using these systems in the back, the business people, they have an understanding of the industry and customers and how they might want to buy things. And offering the flexibility to build out those different journeys in a variety of different solutions is probably the key. And driving customers through a journey or the right journey at the right time for them to purchase or look at or discover the right product is really what we want to offer. And with the advancements in AI as well, that I know we'll get to, being able to identify all of the data that is in the background as well, to make sure that these systems can use all of that information that's stored about the customers and drive them through a purchasing journey and then have that post-sale engagement as well. So it really, for us, it's really about the flexibility of offering different tools or very targeted tools like our Customer Data Platform or like our Engagement Cloud and Emarsys. Using the tools to automate and drive those customers rather than relying on someone go oh you know now we need to do XYZ using the tools to do that automatically is the key. Just to go back to you Federico. You said something really interesting before. It's like you don't want to take the discovery element of it away. It is like you do not want to automate things too much that you suck the joy or the magic out of shopping. Tell me a little bit about that. How do you find that balance? Because particularly say when you are buying a sofa or a bed, there is almost a bit of theater going into the shop and trying, touching and feeling it. How do you find the balance between not saying we are going to serve you this perfect recommendation, but also allowing people to work it out for themselves because I know that's very important to customers now. Yeah, for sure. So, you know, I have experience working in fashion as well, right? And in fashion, sometimes you push the customer to go straight to the checkout. And some retailers would just have the checkout button straight in the PDP, in the product page. That's something that we try to stay away from. We want the customer to, and that's the balancing act that we pursue regularly where... We don't want friction in the shopping journey, but we don't want to rush the customer to the checkout. We want to allow for that discovery to happen, right? So when you browse our website, you can see that strategy on the pages. When you are browsing one product page, you can see, let's say you're focusing on sofas, you can see the whole range. You can see all the fabrics. You can also see product recommendations that are tailored to the sofa. And when you add something to your cart, most importantly as well, we also bring in some product recommendations that would improve your purchasing experience where you're shopping for a sofa, you might want to get the... Um the protection plan in it and the care package and you know some cushions and throws and that's just one journey right? The same goes for bedding the same goes for uh you know cutlery tables and the list goes on. So we really focused on making sure that those recommendations were tailored to the customer and that is something that with the focus that we've done on discovery, improving our search, we also brought in the same engine into our recommendations. So it's not necessarily just focused on if you purchase X or view X, you will get Y. It's also about the customer. So this engine that we brought in, is also taking into consideration multiple data points, is looking at what the customer has purchased in the past, is look at what customer has clicked on within a category. So, you know, if you were to be shopping for a sofa, yes, you might get recommendations on cushions, but you could imagine that the offering of cushions is thousands of cushions, right? So, we are also tailoring. The cushion recommendation to the actual sofa that you've been looking at. And this is all done by AI, right? So it is a significant improvement that we see on the performance of those product recommendations, which is a win-win, right. It's a win for us as a retailer because it helps us to improve average order value. It's also a win the customer because it allows the customer to discover products faster and then move on with their lives. Some of them like browsing forever and we see that and we encourage that as well within the shopping journey. So we don't want to rush, we want them to discover, we'll want them to click around and when they're ready they can go and purchase a friction list. So that's been a focus and continues to be a focus for us and so so far we're very happy with that. I'm just going to bring you in here, Kevin. What Federico said was really interesting that maybe in the past they were looking at products and thinking if you buy this product, you might likely want this additional thing. Whereas Federico is saying actually they can look at a customer's history, they can get other data points, they can maybe get a gage of whether you'd like a black cushion or a red cushion. Tell me a little bit more about how a technology is able to do this because this is a kind of fascinating step up. Yeah, it is. And it actually starts, even though you mentioned, you know, you were looking at products in the past, it actually start with the product information. So having good solid information about the products that have been stored and displayed in the commerce journey is probably the most one critical path. Bringing that together with the clickstream. So as customers start to use the site, how long are they spending on PLPs or the list pages or the search pages? How long are they spending on the detail pages? How often are they adding things to their cart? So all of those types of timing and the journey that they're taking through that purchasing process, that's all gathered in the background. And then typically, and especially in Federico's case with Freedom, they're using one of our partner solutions called Coveo, which is in use by a number of retailers around Australia and globally. It's used to generate those AI based recommendations. It is absolutely the best tool in our kit bag or in our ecosystem that's used to get all of that information into a single engine, provide the tooling for people at Freedom or other customers to be able to adjust and drive. There are types of recommendations that they want to make. And then, you know, using the store front and all of the technology that's available, have areas on the page, like on the cart page or on the product details page, that shows those recommendations and make them as easy as possible for customers to get to them and to see them. So it's really, it starts with the boring stuff, product information, but having good quality information that describes those products. We even have some AI tools that can automatically write or rewrite product descriptions and it's really that information that starts and then it's using all of the combination of everything into a single platform, Coveo in this case, to provide the things that customers actually need to click on. It's all well and good to have the recommendations but it's got to be as easy as possible in the place that we know makes an actual difference in the purchasing journey and drives customers into those recommendations. I know there's probably no one single answer that what how much kind of improvement than this can this make? I mean, is that kind of almost like a rough percentage of if you're using these solutions, you're more likely to get a purchase. And also, does this thing kind of improve over time? Is it kind of being trained with presumably the more people use it, the more information it's gotten, the smarter it's getting. I personally don't have any actual figures at hand but I would expect that there would be a definite increase in the amount of times that people add things to their cart and I'm sure Federico's got some information on when a recommendation is made in the e-commerce platform, how that drives the in-store changes as well and customers in-stores. Yeah, we do. So of course, these tools, when you engage in contracts and whatnot, you also need to make sure that you set some goals to deliver an ROI. And we do measure how they are performing for us and we have seen fantastic results. We've been one year into our contract with Coveo and, you know, for the past 12 months, we've been comparing a year-on-year performance, which was basically a before and after Coveo. And we've seen months where our conversion rates, or most importantly, our transactions, were up to 50% up for people engaging with search, right? So the ROI is definitely there. And, um... Everyone going into their Freedom website can see it right you can now go and search and the search results are fantastic are incredible tailored incredibly tailored to to you not just to your search but also to you trying to understand your intent. And that has been a game changer for us. Recommendations, we also tested them against our previous partner. The results were also astonishing. They blew it of the ballpark. Very, very happy. And that comes to show the power of AI behind tools like this, right? When you move from, you know, algorithms or just logics and you enable a massive amount of data points on a regular basis and to Kevin's point, you give the right data to the LLM to drive those results. The output is definitely there. So we've been very, very happy with that. It's really fascinating because at the moment when people talk about AI, they almost talk about it in this simplistic way of the computers doing the human jobs. But what you're describing there is the AI, the robots call them what you will be able to do things that a human being would never be able to do. They would never been able to sit there and take all of that time. So it's a completely new way. And I was also thought it was fascinating what you said there that it's good for you guys because you're making more money. But it's also better for the customer shopping because they have a more enjoyable experience too. 100%. And also it's a bit of a, it's definitely a journey and a culture shift. You know, some businesses are still willing to manually curate that PLP and the search results and the recommendations. And I think there's always a place for that, depending on the size of your catalog, if you've got hundreds of products, but not thousand. Probably you want to stay there because you just want to, you know your product better than anyone and you know, your customer is better than any one. Hopefully if you're taking that approach. Now for us, it's... We are dealing with volumes that are impossible for a human to manage, right? And that's why the company has adopted this AI first culture where we try things in a safe way and we implement them and we measure, we monitor, and we've seen fantastic results coming from that. So it's a bit of everything to be honest. I think normally people thinks of AI as, you know, ChatGPT, someone asking something and, you know, getting a generated response, but it goes way far, way more, way farther than that. And, and we've seen a fantastic use case behind the scenes to drive our search and recommendations from it. Okay, cool. I'm just going to shift on a little bit now towards kind of marketing. And given that purchases from Freedom are more expensive, generally, say, then say buying clothes, how important is it that the kind of right marketing message lands to the right customer at the right time? Because presumably, this can make a huge difference. Oh, yes, for sure. It is a critical part of the funnel, right? So, you know, funny enough, our GM of marketing shared with us an article this morning, which emphasizes the importance of all channels within the actual funnel. So we've got a... I personally am very proud of the marketing team and the digital marketing team and the work they're doing on socials. There is a lot of, there's a big market there. With us having such a big catalog, discovery becomes critical, right? If you are not feeling that top of the funnel, then over the weeks and months, you will start to see an impact in the bottom of your funnel because you're just not feeding enough people to then convert. So, for us to make sure that we're tailoring the messaging on social media, say Instagram, TikTok, that we have a strong Google presence has proven a great balance in terms of feeding customers through the top of the funnel all the way down to the bottom where we are converting customers to purchase, as well as the work that was done on CRM over the past year when we migrated to Emarsys. It was also a very strategic step for us to continue to build on the post-purchase journeys? And make sure that we are feeding the right audiences to our marketing campaigns as well as to, you know, the digital channels when it comes to feeding the right audiences and getting the right audience in place. Kevin, I could bring you in here now, could you talk a little bit about how technologies are able to improve that? Because it's one of those things where I would imagine if you're serving people the wrong marketing message at the wrong time, then it's having the opposite effect. It's annoying people, it's turning people off. How are you able to make it more targeted and what are the almost different data points you're using with that? Yeah, so inside Emarsys, the tool that Federico and Freedom have just implemented, we can gather all of the information about those customers. So the obvious ones like, you know, their personal information, what they've purchased in the past, both online and in store, how they've used the various touch points, how they have engaged through social, how they've utilized the e-commerce website to drive them into the right segment, into the right group of customers. Sometimes that might be a group of customer of one. Sometimes it might be a much larger group of costumers. And then aligning those segments to the automation journeys. And one of the major advantages with Emarsys is being able to, I guess the power and the flexibility of the tool in the marketer's hands. I've previously worked with some tools in the past where the only way to get anything done is by having some hugely expensive digital expert that builds those journeys. Whereas with Emarsys, it's relatively easy. Even me, I'm a commerce person. Even I can build a marketing journey in Emarsys. And using that tool then drives those segment of customers through, uh, the right journey gives them the right message at the right time. You know, if I have a preference and I engage more when I receive an SMS versus, you know, my mom, when she gets an email from Freedom, she engages through an email, um, that then starts to drive the different way that, uh, each individual customer gets engaged. So I'm more than likely to receive an SMS because I engage through those SMS more. Um, maybe another customer might engage further again through an in-app message or an e-commerce pop-up, so utilizing all of that information then starts to make sure that all of those customers do get the right message at the right time. And it's fascinating because it's like what we said were recommendations. These are almost things that no human being could do, you need to have that next generation technology to do the gazillion calculations and studies that necessary. Yeah, cool. So kind of moving on a little bit now, I'm going to bring both Federico and Kevin in here. And we're going to look at and talk about things like returns and what happens with those because if you are buying, you know, if you're buying clothes, say you buy a t shirt, and it's too or too small. You just, you know, you just send it back. But when you're dealing with more expensive purchases, more bulkier purchases, it's a much bigger deal. And also if you if it becomes if it gets delivered, and there's something wrong with it, you might be a little bit more angry, you might be little bit more, you know, on edge. How important that is it then to a company like Freedom to get that kind of post out engagement, right? And what are some of the challenges that you face? Oh, it is critical. It is absolutely critical. And that's the way you get a customer coming back. Right. I think that's the decision making point on having a one time customer and a loyal customer, right to make sure that your post purchase is is good and on point. So that has been a focus for for the team as well. You know, I think for the smaller items, say for homewares or for dropship products, that's slightly easier because that, you know, an order gets placed, the item gets shipped within 24, 48 hours. The customer in metro areas will receive it within three to four days, no more than that. And so that's pretty easy. We do have an order management system fluent that takes care of, you know, routing the orders to the right store to deliver. That sits nearest to the actual customer delivery address when it comes to homewares. Now it's a completely different ball game when it come to furniture because you need to manage the expectation. Within that range we have products that we stock and products that are made to order, right? So, you know, that's where it is critical for us to stay on top of it. And the team is actively working towards that layer of communication to keep the customer informed of what's happening with that order. In particular, when you are placing an order for a sofa, let's say that is made to order, there is so many critical points in there, starting with the estimated delivery dates that we give you when you are purchasing it, as well as all the delivery updates to keep you informed that the sofa is coming, right? This is a very, most of the times it's a bulky item. That you have to prepare to have delivered in your place. You need to move things around, you need to measure your doors, you need make sure that things fit through. And this was all news to me when I started working here and I was like, right, that's so true. It is a real challenge that you need manage. So the team is actively working on those communications using Emarsys to drive those journeys, as well as making sure that Emarsys has the right data points coming at the right time to trigger those communications. So that experience is spot on. When it comes to returns, again, it's a pretty big range of scenarios where if you have a product that got delivered to you and you can hold it in your hands, you can just come to our stores and return it or you can issue a return for us. If it's a bulky item, then we need to organize that return. So it's all communicated in our end. We're actively working towards serving that information quicker and in a more sophisticated way to our customers. So that's coming later this year as well. That's currently in the kitchen, as I tend to say. But yeah, it is critical and we're actively working towards making sure that that's some constant improvement. It's really fascinating what you said there about, you know, the customer has to prepare a day in their life for this bulky thing to arrive. And also fascinating when you know you maybe you get an update, this is coming in two days, it's definitely coming this morning. That's obviously technology that's serving that up. But it feels like a human is telling you and it's quite reassuring. How important are all those updates and how is technology been able to help deliver them? Because we've all had experiences where you're told it's coming one day, and at the last minute, they change their mind. And like you say, you've rearranged your day, how dare they? How can technology kind of make that process better? Because it's such a big thing to win customers around and get them back in future. Yeah. Oh, both of you, both Sorry, sorry, sorry. Go Kevin, go Kevin. Thanks, Federico. It really is, and so much of it does rely on the order management technology that Federico spoke through fluent. We also have our own technology that's used for managing and orchestrating those orders, and then how they communicate out with, in this case, with Emarsys, the email marketing tool, making sure that they're delivered again at right time through the right channel. But they all rely on, you know, and this is really probably a SAP secret sauce in how we manage the supply chain in the background. Now I am not a supply chain expert, but knowing the timeframes for manufacturing that Federico spoke through, and having all of that information available to deliver to the customer in the email or in the SMS, even communicating out to delivery partners like, might be Australia post for a small item or a larger career company. Having that communication through their channels as well is pretty critical. I think the other part of it is, especially when we talk about returns or even just trying to get updates, one of the recent launches that we had is a conversational AI or AI agent in our e-commerce cloud environment called the service agent and it can be used to ask questions and get updates on past orders or start a return process and those types of things and then if needed connect with a customer service agent to try and work through whatever process needs to happen. But being able to ask really quickly, you know, where's my order or which one do you want, you might show a list of orders, click on the right order and then you get an up-to-date... Uh you know delivery date or expected date from that but yeah you're absolutely right that does rely so much on that information that's boasting both in the customer engagement platform but also for us at SAP in that back end information it doesn't really matter which tool you use in the back end all of that's really required. Tell us a little bit more than he said that almost like the secret sauce is getting all these disparate elements to work together. And then you've got, you know, the website, the technology, the physical product, the journey to somebody's home, things that go wrong, how do you connect all those dots together? Because it's almost like all the things we trusted about here, they were they all kind of relate to one another. Yeah, yeah. So for us at SAP, we launched a new offering at the start of last year called Business Data Cloud. And it's really like a next level data warehouse. But it also lays on what we call intelligent apps. And they're targeted. So there's a retail app coming soon, intelligence app coming soon. And that brings together and allows the business to be able to get access to all of the information. And it's not just, you know, e-commerce transactions or orders or in-store transactions and orders. It's everything else that surrounds that all coming together and the operational data from the supply chain, from their suppliers as to how long things might take and when they're expected either in- store or to be delivered out. But using business data cloud is really the way that that all comes together. I think the other part that's important there and one of the more complicated journeys that Federico spoke through was where something might be delivered. So you buy online, get it delivered, but then return in store. That sounds really easy and many of us have done it, but a lot of the time the point of sale or the system that's used in store isn't necessarily connected to the orders that have transacted online. So having a single source of truth of all orders that even in-store associates can get access to, either through a client telling app or an in-story app that's been built or the point of sale itself. Having all of that information together at one time so you can actually return something in store is certainly more complicated than I originally understood but thankfully we've got some tools to help out with that as well. Okay, and before we move on to the next question, if you are watching this at home, you can submit a question. We're gonna jump to some questions in about 10, 15 minutes. Federico, I'm just gonna go back to you here. More generally, how important is it of using analytics, using all that custom information to make future decisions, say, about which products to sell or promote? Obviously, with your dropship channels, you've got tens of thousands, but how useful is that data? In being able to make decisions as to what is going to connect with customers in the future. Yeah, so that's a key strategic point for us, right? Because as you can imagine, as a retail business, there's only so much assortment you can focus on producing. So the Dropship program also gives us a really good taste of what the market is after. And, you know, certain where the gaps in the freedom assortment relies as well. It informs us on in terms of trends. It's been a very eye-opening journey to see, you, know, where the desire of the market is going, looking at those sales, as well as, you know. Bringing all the customer data together will help us to also understand how we are doing as a retailer for these customers, right? Are we performing well? Are they coming back? Are we giving them the right offering or are we dropping the ball somewhere? You know, things not always go right and we always try our absolute best to get back to those scenarios where things don't go as planned and try to make it up for the customer. And you know so all that information sits within our customer database and it helps us to cut the right segments to to go with the right message and to each customer right to the point we were discussing before. Could you give us some maybe some kind of examples or case studies of that? Is there a time when you as a team looked at that and thought, Oh, this this thing is consistently going wrong. Maybe we can implement a fix. Well, not necessarily a scenario where things go always wrong. But we did identify that there was room for us to communicate more closely with our customers when products are made to order. We also found that there is a lot of contact to our customer service, seeking for information that could potentially become available to the customer online through search or through, you know, to Kevin's point, the interaction with a chat bot or an agent, and speaking of these days terminology. So we're actively working towards you know, filling those gaps, making sure that customers can self-serve more, looking at the data, looking at their level of contact that we get for certain topics. And yes, when it comes to products, we got a product team that is constantly looking at those sales and sourcing the ranges and taking inspiration from multiple touch points, not just necessarily drop ship orders, but looking at whether customers are clicking on certain products, no adding to cart. And we have also discovered that stocking more sofas will help with those sales. Some customers are not ready to wait for the sofa to be made to order. So, you know, looking at our ranges, the business has started stocking more products. So, you know we can deliver software within two to three weeks if that sofa happens to be in stock. So the team is using multiple data touch points to make sure that the whole operation improves based on this information. Kevin, I don't know if you could bring you in here to talk a little bit about the kind of technology under the hood. What Federico was saying there was quite interesting that it's not necessarily about the purchases makes it's maybe the time on the page where people are clicking and looking, how is that able to kind of inform those bigger decisions about what people should be stocking in future or maybe how many things they should make available because presumably when you've got things like made to order, that kind of insight becomes even more important. Yeah, it really does. I think a lot of it is about how that data does come together. So, you know, I spoke quickly about the business data cloud before and that digital service agent. And I think those kinds of tools and technology with the ability to build those intelligence or to get the intelligence on top, when it comes to, you know demand planning and and understanding what to restock and how to replenish. That's actually an extension that we're going to be offering later this year, where using all of that information about what the customer's buying, how they're interacting with the storefront through the e-commerce channel, how the supply chain is being reactive to those things, can then start to bring in some of the really advanced AI-based planning and replenishment. To ensure that stock is made available and restocked as quickly and as efficiently as possible. Working with your partners or suppliers to reorder at the right time, especially for those finished goods. With made to order, I guess it's really about setting the customer's expectation and having a very, very good understanding that this particular product when you're using this variant or material might actually be a 12 week period rather than a six week period. Maybe the leather takes a lot longer to source for the suppliers, therefore the time to make that particular product is a lot long. And again, that comes back to storing some of that information as simply as possible against the product itself or against that variant and always keeping the customer up to date. Federico spoke about it before. Where having it on the product detail page that you know this particular item when it is the brown leather is a 12 week delay rather than an eight week delay and then carrying all of that information through the rest of the journey you know it's no good if we if we know it is going to take eight weeks but Emarsys starts to send emails in four weeks saying your product's nearly here you know that that expectation being reset badly is certainly not what you want. Federico, I'm just going to bring you in here. I think Kevin made a really interesting point. If you've got something made to order. Obviously, it's not ideal, but I imagine it's inevitable that there will be delays in these things. I would imagine that being able to give customers quickly give them information on that almost none of flies a lot of the problems because I think people are less angry if something's been delayed and more angry if they're if they're only told at the last minute. How is important is it to keep people in the loop, give them those updates and make them accurate? And how has technology helped? Because I imagine that's kind of vital of keeping customers on board when you when you have things like labels or troubles. Yes, spot on. So that's at the center of our work in progress. And I think to my point before, it will constantly be work in progress because there's always room to continue to optimize those journeys. I think it starts with our integrations to make sure that the data is coming and flowing from one side to the other efficiently and and most importantly, in a timely way. So when the data comes through, as soon as an update comes into our OMS, we can also push that update to Emarsys is to trigger a message to let the customer know there is a delay, set that expectation or reset that expectation. Give the customer the option to reach out to us so we can talk about it, right? Sometimes customers need to give the feedback that they are not happy about this delay. And you know, that happens. It happened to me with another retailer and I can tell you I wasn't happy when it happened. So, you know we are retailers. We're also customers. So we know how it feels. And, you now, when we put ourselves in our customer's shoes, we... We do try to do what's best for them. And we know how frustrating that could be. And, you know, at times that happens, there are things that are out of our control, but we have to be responsible for it. And, that's the key of what we are working on actively today to make sure that those communications are flowing. Also, we need to make that on the other side, we don't overdo it, right? Because... You don't want to spam a person every second day letting them know it's coming. It's coming, it's like, let me know when it comes, you know, and that's it. So again, it is a balancing act. It's just making sure that we have one single platform firing these updates. You know, at times you get multiple platforms firing updates, talking about the same event and you know that's optimal in my opinion, there are times way. You have to go down that path because there's critical information that you don't want the customer to miss. I think what resonates the most with that is that sometimes you get an email from Australia Post telling you this is coming, and it's coming directly from Australia post and not from the retailer. You still need those emails, right? You still need Australia Post to let you know they're coming and give you that critical information. So we are actively working on mapping all those communications, making sure they are properly orchestrated. And that's the beauty of Emarsys, that it really allows us to orchestrate those communications and constantly work towards optimization when it comes to that. Really fascinating what you said there that you don't want to bombard people with too much, too many updates, it becomes annoying, it comes frustrating, particularly if the message changes. And so a lot of people watching this will be thinking, what's the balance between the human instinct of making a bigger decision, and the kind of the technology making a decision? At what point do you as a team kind of step in and say, you know what, we think this is the optimum amount of updates, or we think, this is what we should stock? How do you balance the information that the data giving you, with what you know from knowing your retailer inside out. Where's that balance lie? Yeah, so it's just opening a little bit behind the curtain there, you know, what you get are events, right? So you get a notification or an update related to a shipment without going too much into the technical realms of it. That's telling you, well, the ETA is this date, or the original ETA was this date and now it has changed to X date, right? Now in between you might not get any events but the in between could potentially be three weeks could potentially two weeks it all depends on what was originally communicated to the customer right so there are two approaches that you know we're planning on taking one is to making sure that when the events happened and come we do communicate them to the as quickly as possible. If there is too much time in between events, to make sure that we still prepare the customer for what's about to happen, right? So that's where, you know, the team is working on those journeys is where, you know we are prepping you for your sofa to arrive, right. So we might ask after you purchase your sofa, we might let you know that it's coming. We might also let you know how to take care of this particular sofa before it arrives. So you're already across how to care for it. When it's about to be delivered to your place, we might send you a communication to let you know how you need to prepare your place. Let's just use the word place for it because you might live in a house, you might live in an apartment, there are different kind of arrangements that you need to make depending on where you live. So all those journeys are currently being designed and we're making sure that the data points are there in the very first place. So this is not a one person job, as you could imagine, it takes a village to get it right. You know, we're actively working towards that, making sure that the right balance is there. It's super subjective, to be honest. Some people might say it's not enough, some people might say about the same topic that it's too much, right? So we need to make sure that everyone's on board and we find the right balance there. Okay, we're just going to shift. We've got some questions have come in. And the first one I want to ask both yourself and Kevin is how do you kind of onboard this technology? How do you implement it? How do you go from the old way of doing things to the new way of doing things? How much time does it take for the data to be collected? Do you kind of press the button immediately and you switch to it? Or is it a gradual process? Talk me through the kind of the moment you you shifted towards a new way doing things. If I could start with you Federico. Yeah, so for us, I think that's the core of what I do at Freedom, bringing those solutions to life. You know, there are many phases to it. There's the discovery phase to pick the right product, the right partner, making sure the requirements are met. And, you know, most importantly these days, they think of what we are releasing into the production website is AI-driven. So that forces us to do very deep testing. We need to make sure that before we ship it to our production environment, which is the website our customers will browse and access and shop from, we need to be sure that everything is ready and working and you know providing the right recommendations so at times it could take you know, a month or even more for us to make sure that it's all ready to go. There's a lot of compliance that goes into play as well. We are very careful when we ship new features to our production environment because it could be massively brand damaging if we ship the wrong feature, if we deploy it back straight away to the production environment. So testing is very, very critical. At times it takes a lot of time. Before the project starts, we know what we're doing. So we do a solid plan to make sure that we understand who does what and when, and we have deadlines to meet. So the team is working towards the deadline, everyone's mission on performance and whatnot. So, you know, sometimes it feels easy when you sit in production, when you go to the website and say, oh, is this what you've done? And you're like, mate, you have no idea how much work went behind that feature. But at the end of the day testing is key and it's critical for us to make sure that it's all signed off before we deploy. Kevin, if I could bring you in here, how do you go from kind of modernizing or changing how a company works? Because someone like Freedom, obviously, they would have had ways of doing things before, that were probably quite advanced that they put a lot of effort in. How do you kind of change things? Because I imagine it's almost like going to a, this might be a madden energy. It's like going into a golfer and changing his swing. How did you, how did you introduce something which is going to be so disruptive? Yeah, you know, we have teams of specialists that work on this particular part. You know, for me, working in a solution advisory role, I work very closely with people like Federico to try and understand what value they'll get out of a particular solution. And then I, you know, then pass it on and work very closely with our customer success team, who are then, you know, their task and their role is to make sure that when... A solution and it could be something like the payment framework, the open payment framework that Federico just adopted last year or could be a brand new commerce implementation at a new customer. They work through with the customer on the onboarding project or the implementation project and a lot of that is around change management, both the change that people saying Federico's team need to go through to start using these tools. And sometimes I may even work with those people to, you know, especially if they weren't involved in the pre-sales journey, understanding how they might use the tool, what value they should be getting out of it. And it's really, you know it's very typical project management work to ensure that the value that I told them that they get is actually gonna become viable in the future. Okay, well, we've got one more question, which I think would be a really good question to end on. And I'm going to open up to both Kevin and Federico. I'll start with you, Kevin. What's the future? What is the future of how technology is going to change customer experience? Because we've really had, say, agentic AI, or whatever you want to call it now for a few years, it's still a very new thing. Where are we going to be in five years? Where are we gonna be in 10 years? What's the potential for this to change customer experience? A big question, a bit of a tricky question here, but I'm going to come to you, Kevin, if you want to do some future gazing, what sort of things developments could we see in the future? Well, look, I wish I was a futurist, but I think I get paid more for that anyway. You know, one of the things I've been working on, you know, for the, for the past month or so, um, is an engagement that we've got with a fairly large retailer here in Australia. Um, and, and we've been looking at the way that without, we have an innovation store, like a physical retail store in our, in a head office in Waldorf in Germany, and that's brought together a lot of the technologies. That we probably will look at using in the future. And the ideal is being able to pick up an item from the shelf, maybe not so much a sofa in Freedom, but maybe the candle. And pick up that candle. There's technology in the store that has identified me. Maybe they've used biometrics, not necessarily my face, but biometrics about me as a person and the device that I've got in my hand. So I've gotten the candle and my phone. But using technology that is available now, not overly widely used, I can pick up that candle and just walk out the door. It will then charge me through some RFID tags or through the technology on the gate. It will charge me though my credit card that is linked to the app and the device. But all keeping ensuring that we don't all of a sudden start losing revenue and the loss prevention mechanism. Is still stuck and those things are real. We've got an innovation lab, like I said, in Germany that allows SAP employees to buy things that they might need throughout their day. So I think that's the ideal for me. I already use, you know, scan and go type apps in some of our large grocery retailers and I love them. But being able to pick up an item and just walk out the door, knowing that all of our privacy concerns are very well treated as well. But making it as seamless as possible to walk out that door, then making sure all of the backend systems do replenish that product, that install people can put it back on the shelf, get notified by all of those things is really critical. That's my vision of the future. Okay, I'm going to bring Federico here. What's your vision of the future? Because again, you said something really interesting earlier, you don't want to almost take the joy out of discovery. So it's about finding that balance. But where do you hope this technology can go? Where do you see the future of this being? Yeah. So it is, again, it's a very, very interesting question, right? A tough one. We don't get to guess the future. I could probably tell you what's happening in the upcoming months. And, you know, personally, I'm very passionate about AI. So I tend to stay on top of everything that's been deployed and, and done by you know, a large spectrum of companies from open AI to the robotics companies to see what's coming, right? Now, I think from my perspective, I need to focus at work because on my free time, I also look into this stuff. But from my respective at work, I tend to focus on how this technology is going to be applied to retail right now. What's coming straight away is agents. Everyone's talking about agents and you see some websites already deploying agents in the form of a chatbot that the way I refer to it's like they give them arms to to do stuff for the user right so in a future I think it's a very near future if it's I think, it's already happening to some retailers you can interact with these agents and you can just say. Show me this product, I want a product that has XYZ capabilities or attributes, add them to my cart, increase the quantity, I wanna pay for it and you can pay for it, right? So, you know, you're not interacting with the website, you are interacting with an that sits on top of the website and that's it all for you right I have no doubt that's really, it is happening. I've seen it happening. And I think it's gonna become more and more popular. Now, what I think is key and critical is for retailers to not get lost into their realm of innovation and keep front of mind who they are and who the customer they serve is. Because, you know, for us, we, again, we have a very varied audience. But you know, if I have to guess how the average 50 years old person is shopping, they might completely ignore the AI agent, right? They might still want to shop the old way. And these tools are not cheap, right, it costs a lot of money to to make one call to the back end to, you know, spend the token and then get the response back generated. It's not easy. I think it looks easy when you interact with it, but when you know what's happening behind the curtains, there's a lot that goes into that. So I think it is critical for businesses to know what's their north star and what's the objective before they embark on implementing AI for the sake of implementing AI. There has to be an ROI behind that and we're very conscious of it. After that, I think people will just buy from LLMs. You might just go into ChatGPT, Claude, whatever LLM of you prefer, and you might just go and say, hey, I need to, I run out of candles. I always buy this particular brand, this particular scent, get me the best one, at the best price I needed by Friday, just shop it, right? So that's going to happen, right? Mostly for reoccurring sales and purchases. Um, so I think it is also critical for us to prepare to, to show and be a preferred retailer for LLMs, uh, the, the ChatGPT, the Claudes of the world, uh because that's coming and it's happening as well. I, I could only focus on what's right in front of us because what's gonna happen next year? Uh, I don't know. There, there are plenty of things that we need to sure that we we keep this coverability and and the capacity to inspire our customers front of mind because we don't want to go straight from A to B. Well, on that future gazing note, it is probably time to bring this webinar to a close. I thought this was an absolutely fascinating chat. I'd like to thank Federico and Kevin for sharing their insights. I'd also like to thank everyone for watching. Thank you again and hopefully we will see you soon. Goodbye.