Krithika: Hi! Welcome to a brand new episode of the retail podcast by Vue.ai. In case you're new here, I'm your host, Krithika Anand. Our podcast highlights innovators who are creating significant shifts in the retail sector. We showcase tech specialists, committed business owners, business leaders who contribute their views to the dynamic world of retail. Today, we're delving into the future of customer service and experience, exploring how AI is shaping the landscape with Shamas Aziz, a seasoned leader with over two decades of experience at companies like the Matches fashion, Selfridges, Net-A-Porter, Ocado and many more. Shamas. We're very excited to learn more about your perspectives, insights, and future plans. Welcome to the retail podcast by Vue.ai. Shamas Aziz: Hey Krithika, thanks for having me today. Krithika: Pleasure's mine, Shamas. All right, so let's jump right in. Um, can you tell us about your journey in the customer service industry, from your early roles to your position at Matches right now? Shamas Aziz: Well, let's start, um, 22, 23 years ago, uh, I fell into call centers, traditional call centers by accident. Um, I'd left college. I was for my first full time role, and, uh, I lived in a town called Enfield, which some people will know, based in North London. And one of the biggest employers in that town was a very large high street bank, a 400-seat call center, uh, which was split down the middle. Half of it was telephone picking up the phone, and the other half was an admin back-office type. Krithika: Hmm. Shamas Aziz: Uh, area. And so, I joined the call center, as did potentially every other household in, in the area. Um, and a few weeks and months into that, I decided to stay. And I guess I never looked back. And, um, over the years, whistle stop tour, uh, I just continued to sort of work my way around the call center as a team leader, as a trainer. I moved on to doing induction training. I did outbound training, inbound training, and then from there into Ops management, there was an opportunity that presented itself to take over a call center, an in-house call center, and then through that opportunity in life, that particular call center for Ocado.com, uh amazing grocery company, slash tech company, slash IP company, or whatever else they're calling themselves today. I really had the environment and the opportunity to experiment, and that enabled me to just sort of do a little bit of everything from systems, processes, people. Daily operations, tactical projects, even thinking about strategy and where it would go. And so that sort of took me halfway through this sort of 22, 23-year career that I've been talking about. And then from there, all the roles after that started to have a strategic angle to them and were at quite a senior level for a number of wonderful businesses and um, circa ten years ago ended up somehow in luxury fashion. Don't ask me to explain that part. I'm just going to say, preparation meets opportunity. And, uh, I joined Net-A-Porter, and this was around the time when the UK's merger was taking place. And so, there's a weird and wonderful world, and I was able to come along with good basic hygiene, customer service, call center operations and techniques and then able to apply them at scale. And this then took me on a roller coaster journey, which over the last number of years took me through Selfridges, both the wonderful department store that it is and the .com side of the business, the digital side of the business, which has a global footprint. Last year, in October 2023, I was made redundant along with a number of people. As we're seeing out in the industry, that redundancy seems to be the thing right now. Well, almost every year it's been the thing, I guess. And so following redundancy in October 23rd, I set up the thecxway, which is my own customer service consultancy, and it was an opportunity for me to get out there and speak to different people, different brands, and one of the first and most fun contracts I was able to win is Matches Fashion, where I'm currently an interim customer experience specialist, and this involves looking at multiple projects, working with the operation. But my focus is more tactical operating model and strategic projects. Krithika: Oh, wow. Shamas Aziz: That's a good whistle stop tour. Krithika: Absolutely. You know, that's incredible. And congratulations on thecxway. I can't wait to see the kind of things that you're going to be doing with it. Shamas Aziz: Thank you so much. Um, I'm going to be really transparent and open here and say I'm also excited to see what I'm going to do with that. So, given that a lot of my roles have always been strategic, I've always anchored them back to the business, to the business mission, to the business vision, to the business values. But now it's my own thing. So, I need to come up with that mission, vision and values too, and then anchor what I want to do. And so, it's a work in progress, and I'll figure it out as I go along. Um, but I'm in a great industry. I'm working with great people who allow me to come along with my knowledge and allow me to figure things out. And so together, I'm excited for what the future holds. But I won't pretend that it's fully mapped out. Krithika: Right, and I'm sure it's going to be a great. Shamas Aziz: Thank you. Krithika: Also, you know, I recently happened to read one of the articles that he had written. Um, and I found it super interesting, and this one really stuck with me. You opened it with a Wayne Gretzky quote that read, I skate to where the puck is going to be, not where it has been. Um, how does this philosophy align with your vision for the future of customer service? Shamas Aziz: Yeah, it's one of those great sorts of I want to call it a movie quote, but this is the actual real quote from the great hockey player himself. Um, it kind of aligned with everything I've ever been doing over the years. And the first time I heard the quote, I was like, oh my God, that was written for me. And of course it wasn't, but it's written for many people. What particularly resonated with me is that through customer service, through call centers, over the years, we've always mostly have been on the reactive end of the customer journey. So, there's always, I guess, a query, a complaint or a problem, and that's generated a contact. And then we've reacted to it. And I've always over the years felt that's the wrong end of the customer service journey, or it's at least not the most value adding end. And so, I've always thought about how to set up a department that could help feed back into the business and not just be reactive. So, starting to be more proactive. And that's where this quote kicks in. It sort of says, let's predict what's going to happen before it happens. And almost in a minority report type way, which is another thing that I talk about in one of those articles, the future of customer service is we know through our experience what customers typically are going through and where there might be bumps in the road, or why don't we get there first and try and eliminate them if we can. And so this quote I felt, was able to sum all of that up together in just a couple of sentences, but it resonated well. And it's applicable, I think, across any department, industry, role, vertical. Um, yeah. So it was just, you know, that moving from a proactive to a reactive and even in those articles I start to talk about predictive. And that's where this quote works. Krithika: Wow. That's actually a very fascinating perspective, Shamas. And, you know, drawing inspiration from, um, Wayne Gretzky's philosophy does add a unique touch to your vision. And in fact, I've been wanting to sort of ask you this, but you, um, touched upon this point about, um, shifting the customer service strategy from reactive to proactive to predictive approach. Um, I find this quite intriguing myself. And, um, so tell me this. How do you bring about such a shift within an organization and what key considerations are involved in making this transition? Shamas Aziz: It is a great question. I think the short version is budget meets expectation. Um, and sometimes, you know, those two things don't always align, I guess, particularly in the last couple of years following the pandemic, following the economic downturn, following just everything that's going on, I guess in the economy in the world, that it's become quite difficult to have the ambition and expectation to deliver the best possible customer experience when I guess the balance sheet isn't necessarily backing that up. And so if you've got the budget, the expectation is already there. Every exec I've ever spoken to will always say, put the customer at the heart of the business, and then you get to the P&L and to the budget sheet and you're like, okay, let's try and put them mostly at the heart of the business. And, um, and so I think sometimes there's a potential for compromise, and I understand things cost money. And so, for me, you know, the things the considerations that are in place isn't just the cost, but it's the, the value add, and the demonstration of that value add. And typically, my approach that is twofold is taking the data that's there, but being careful that it doesn't just become about the spreadsheet. That's number one. Have you got your data and are you feeding that into the business. Number two though, which I think is a lot more powerful, is twofold. It's customer stories. And how can you bring those to life and share those back into the business? They resonate harder, in my view, than a spreadsheet can. And so whether that's a customer tweet that you've received, that you feed back into the business, or whether you open up your call center to your exec, to your senior managers, to anybody that wants to come. I almost think that anybody that joins your business and depending on your type of business as part of induction, there should be a day in the call center where they put a headset on and they get to listen to what customers are saying, what customers are feeling, and that storytelling coming to life in real time. The impact of one phone call in five minutes is going to be much broader, much wider than it ever will for me writing multiple emails, multiple spreadsheets, multiple pivot tables. And so I think culturally you can move the needle via stories. And I think if you've got the data to back it up, that always adds a little bit of credibility. I think potentially because you have data from your customers. And so take your data, take your stories, open up your call center if you can, and let people in. And in return, when you come along and say, hey, we want to move to the predictive end of the customer journey, people will already start to join the dots before you need to help them. And so I think that would be my approach. And it's usually how I like to work. Krithika: Hmm. That's really interesting. Um, in fact, you know, um, when I planned this conversation with you, the one thing that I really wanted to ask you is all things data, right? Data is so important today, and with so much focus on customer service and experience comes a need to deal with the plethora of data. Um, it could be based on customer needs. Like you rightly pointed out, the preferences and everything that one should rightfully know about the shoppers to keep them happy and make them come back for more. And I think it's in somewhat it's safe to say that as much as customers and trends, um, impact service plans data has done its fair share to um businesses have an abundance of data today, and however, the data is often unorganized, stuck with different segments and sections of the business, and they don't really talk to each other or interact with each other. So, um, how can a business benefit from data, especially from customer service point of view, and how does that feed into the larger goals of the organization? Shamas Aziz: It's quite tricky, actually, and I think you've flagged a couple of interesting and key points that make it that little bit harder. There's the saying, um, analysis paralysis. And so sometimes you spend far too much time with data, and you end up not making any decisions because sometimes it's safer not to. It's safer to allow status quo to take place and play out and not rock the boat, not come along and say, I think the data is saying this. So now we should do that. Um, however, there's also the danger that it's a little bit less creative in that approach where you just sit and look through the data and try and understand what it's saying. There's also another saying that you could get the data to tell the story that you want. And so, I think there's a balance between trying to enable change by using the data, whether it's structured or unstructured, and whether you have an insights team or you don't. There's an opportunity, and I think I favor the world of experimentation. It's a leaf out of the Lean Startup book by Eric Reece. The idea that you roughly know your direction of travel, you have a hypothesis, and you do an experiment. You then review and you tweak the next one. And so, I think use the data that you have, whether it's structured or unstructured, the amount that you can get from it and run an experiment, take some of that and figure out how to interact with your marketing team or your trading team, or your IT team. And then review and then think about your next steps. Having said all of that, I do think it's important to build for the future and well, hopefully today rather than in the future. But have a think about how to get your data into the right place in a way that it can be used better, and think about what needs to talk to what. So if you have different data streams, are they all going to one repository that can be queried? And um, when they get there, what type of ways are you grouping that information? Are you using tags. Are you using classification? How valuable are they? How easy are they to get to. And if you can get to them, how easy is it to drill down if you need to? Are you looking at themes that are higher level? Um, so if I give you an example, let's say delivery within e-commerce as a theme, um, or if you need to drill down into that, which delivery partner specifically is causing contact to come through. So now you've gone from a high level into the nitty gritty. So thinking about how your data is structured, it's never too late. It's never too late to start to build for the future and start to bring bits of information in. I guess you need access to somebody that understands how those systems talk to each other. So typically for me, that would be to go to an architect and work with them and figure out what are all the different repositories, how do they connect with each other? Where does that data go? How can we access it? And then I also think it's going to the philosophers of this world and trying to figure out what questions do we want this data to answer, so that it's not just always binary ones and zeros, black or white. You sometimes want to uncover that gray so you can see the nuances in something that you could go after, which may or may not be a competitive advantage or difference for your business. So, I've thrown lots of different words around, but I think the idea is take what you have and get started, and along the way build your systems and processes to become more granular when you need it. Krithika: You know. Absolutely. I agree, um, I find I think that, you know, businesses today have a robust data set and more often than not, they're they don't know what to do with it. And especially when it comes to, you know, customer success or customer experience, I feel like putting the pieces together, like you said, you know, putting the puzzle together, because that's exactly how I imagine, you know, broken data pieces. And it's important for companies to put them together and sort of make sense of it, to be able to serve the shoppers better and reap more out of it. And I think it's safe to assume that data is the backbone of many business strategies today. Speaking of data, companies emerged with strong technical expertise and scale at exponential rates. However, the more structured DNA of legacy companies that are rooted in familiar practices built across decades still prevail. The technical debt, which I think we've already spoken about in our previous conversations. The technical debt of legacy businesses will prove tedious in implementing change today. How do you tackle that and stay ahead of the curve and, you know, bring in fresh, technologically sound ideas into the system? Shamas Aziz: Yeah, it's very interesting trying to figure out this particular puzzle almost feels like one level up from a 2D puzzle. Maybe potentially we talk about the Rubik's Cube. So we're moving into this 3D, 4D world where, uh, you think you figured out one side of the cube and you turn it upside down, you're like, ah. And so I think when it comes to technical debt, um, yes, you could try and figure that out, but I'd rather not try to figure that out. I think that's where you go find the right expert that you can speak to. So the architects of this world, the system architects, the data team, the IT team, go to them, sell them the vision and where you're trying to get to and then figure out together with them how you can work with this technical debt. So whether that's a middle layer for a messaging system through APIs, um, any new sort of technology that you want to bring in usually will also have its own reporting in isolation. And I know I've just spent the last few minutes talking about bringing your data into one place, but until you get there, you can access some of that reporting within the native platform that you've just bought in. And so I think get help from your data and IT teams on how to work with technical debt. Don't let that stop you from taking view of what data you've now started to uncover the new data through the new system, and so you can start to get some progress again. You can start to experiment. Um, but I think what you need to try and do is always think about the customer and the use case, and not let the system approach stop you getting to where you're trying to go to. And so it's that sort of Rubik's Cube and, you know, getting to a place where as you solve one problem, you're potentially creating another one. But if you keep going, eventually you'll get really good at spinning that cube around and just matching the colors on all sides. And you could argue that will never, ever match all the colors on every side as new technologies emerge, as new ways of working emerge. But that's quite exciting. There's an interesting place to be and an interesting place to work where as you figure it out, you know, the goalposts move again. And so that, in my view, will keep the industry fresh. It will keep it interesting. Um, lots of career opportunities and progression and pivots. Um, so I hope that helps answer how not to get stuck behind technical debt, how to accept the reality of it, go get the right type of help. But in my mind, if you're a customer service customer experience professional, that's what you need to advocate for and spend time doing that. You don't need to know everything, you just need to know somebody else that does. And so find out who your team is. Assemble them together, Avengers Assemble, um, and then figure out which enemy you're going after and fight. Krithika: Absolutely. And that's a great way to put it right. Um, with that being said, I want to touch upon something and, you know, look at the broader landscape and, um, talk about digital transformation and how it is reshaping customer service and the impact that it has had on this function so far. Um, digital transformation in specific is an undeniable part of the business model today. Um, regardless of the industry, organization size, etc., and um, organizations are using to enhance customer experience and efficiencies across the board. How does this impact the customer service space? Um, why don't you give us a few examples? Shamas Aziz: Yeah, this is always quite interesting to me. So I always find that digital transformation typically starts somewhere else in the business, usually within the IT side of the business, or if there's a digital or customer division, it might start there. However, over the last sort of ten, maybe 15 years, the contact center has become a place where, um, there's lots of marketing and sales teams that are working to leverage, um, the teams, the peoples and the systems there to deliver. And so with that, it's now not unusual to seek investment, get investment, and use digital transformation techniques to move your contact center forward and help work with your business. So I think some of the credit of that goes to the sales and business development community, who have identified a new customer in the call center and the contact center teams to go and sell to them. And some of that actually just comes from customer necessity with their feedback, how they have interacted with brands and whether they've been satisfied or not. At the other end of that, business leaders have had to figure out how to respond and figure out, well, how do we get a bit quicker? How do we join up systems so that we can answer these questions in a better way and go after some of the golden metrics within the call center world, such as first contact resolution. If a customer calls and wants to know where their order is, is that information readily available to the team member who can then share it instantly with the customer? Could you go one better and make that self-serve and available in an easy and digestible way? Um, not all customers will self-serve, but there'll be some out there, so could you service them? And so I think digital transformation examples that I would call out would be especially coming from an e-commerce background myself around the delivery space. So trying to find out where your order is and figuring out how to get that information across in a really nice, clean way. So I think Amazon do a great job when it comes to talking about what stop the driver is. You have a little map, you can see little van. Um, and also you get notifications pushed to you, which is helpful versus, you know, before the customer comes looking for it. The information is there proactively or in the returns space. I think there's a lot of opportunity for digital transformation to take place there, connected with the call center, enabling customers to do easy returns. You do sort of wonder a little bit why the return is taking place, and whether you can tackle some of those questions during the buying journey. So things like product information, size and fit. Are you able to surface that in a better way? That enables customer to make the right purchase the first time, and not have to worry about doing a return? Or if you are going to do a return and you have a returns journey, how to make sure that that doesn't cripple your business and take you off focus of why you were there in the first place. You were there in the first place to drive a customer experience and perhaps sell a product or service. But now we're focusing on the returns journey, which feels like the wrong end of the stick. And so I think, these are two sort of ripe spaces. There are a lot of innovators in this space, and in some cases it's less innovation and it's more basic hygiene around just being able to track really well in an easy way across the multitude of carriers that are out there. And then globally, bringing in, you know, things like Customs and Excise and some of these other really complicated, unsexy things that take place within the customer journey that just makes it a little bit harder to do a great job. Um, so these are very tangible digital transformation pieces, perhaps too narrow with focus. But I think if you can start solving for some of the repetitive use cases, you can build space for yourself to step back and look across the landscape and figure out how to actually transform the customer experience. Krithika: And, um, how do you think AI is changing this landscape? Shamas Aziz: AI is the new favorite child. Um, yeah. There's also a lot of money in it. And, you know, there's a lot of external use cases that are not specifically commerce or business driven. So take YouTube as an example. People have come up with weird and wonderful ways to use AI to do weird and wonderful things. And so again, with the very well-developed sales and business development community and the founders out there who have seen an opportunity to take AI and bring it over into the business landscape, there's absolutely an opportunity. I think we're still figuring things out, though. A lot of it seems to be focused around productivity, cost, um, insight, repetition, how to tackle these very tangible parts of a business case, or a return-on-investment case that would enable you to bring AI in. Um, and as we figure this out, I think we'll get back into the customer experience customer journey enhancement space with AI. And I'm sure there's many founders out there who are already doing that, but perhaps they are still stuck behind the might and the dollars of the other companies that are pushing this productivity agenda. I don't think productivity is the right part to go after, in my view. I think it's the easier part because it's ones and zeros. Again, you could quite quickly figure out what percentages you can drive through increasing productivity. But I think, you know, keeping a lens and a foot inside the customer experience space, we need to do better, and we need to figure out more creative ways that AI can play a part. And I'm excited to see where that goes over the next few years. Krithika: You know, I think AI is completely found its way in through customer experience and especially in the e-commerce strategy. Right. Um, with AI, businesses can take more organizational and holistic approach to customer experience. And this is something that we specialize in at Vue.ai, day in and day out. And, uh, businesses and enterprises of today come to us to ask for solutions which can help them to improve their customer experience strategy. And we're very, very happy to be collaborating with so many of these businesses to sort of help them realize their potential and provide them the kind of solutions that they're looking for. But having said that, going back to a point that we discussed before starting this conversation is that customers often prefer humans over AI in interactions. How do you see this perception evolving, and what strategies can businesses employ to gain customer trust in AI powered customer service? Shamas Aziz: The customer trust. There's absolutely a piece around just time, as the technology gets better and more efficient and is delivering the right answer in the right time frame, trust will start to build. I think always pair it with transparency and data security. So data security really simple. Keep it secure. I say it simple. All my data security friends are pinging my inbox right now telling me it's not simple. What I mean is the request is simple. We need to keep data secure. Um, but the other side of building trust is the transparency piece. So I think it's fine to name your AI bot technology, whatever it is, but just be clear that that's exactly what it is and be willing to use some level of language and or journey that makes it easy to come out of that loop. So if you've put a journey in front of a customer, make it easy. If you've made it hard and you want customers to jump through hoops to get through it, you're just delaying that trust, um, from landing. And so think about 1 or 2 use cases that you can automate really, really, really well. Put that in. But then always give the customer an out, enable them to come out and over time figure out how to slowly pick off the use case and improve it. And what systems does it need to connect to to make it a better journey. So if we take an example of a return, if a customer wants to do a return, can you automatically generate a returns label so that it's printed off and sent to somebody? That's probably a good way of doing that, but you might not necessarily have all the systems talking to each other. So how do you pick that off step by step and start to improve that journey? So transparency and trust will come as the technology improves. But you have to make sure that you're being transparent throughout that process and have a bit of patience. Don't worry about trying to get it up and running to fully automate and deflect. And I hate that word deflect. By the way, that's used quite a lot in the AI space. I don't really want to deflect customers, I'd rather just resolve their issues. And so I think we might need to change our language a little bit, but have some patience. Don't worry about trying to get the automation rate so high so early, because you might be creating a terrible customer journey which is eroding your trust that you've mentioned earlier. And so it's a fine balance. Probably another jigsaw puzzle, or perhaps not a jigsaw puzzle, but a set of scales where as you move one thing on one side, the other side moves. And so you just have to keep experimenting. And I would say do it slowly. Krithika: Well, that's very well put. I feel like trust and transparency can go a long way in building that kind of relationship that you want to have with your shoppers. And about trust and transparency are very essential for any businesses to run today. And um, having said that, I. Right. So, um, moving on to my final question. Um, what are some of the challenges that come with implementing, um, the changes that we've spoken about earlier? Right. Um, while businesses may not want to experiment and push the boundaries on innovation, how would you tackle that? Shamas Aziz: Um, this is the million dollar or million pound question. Let's be a bit more on point with our currencies. Um, I'm based in the UK. That's why I'm talking about pounds. Um, I think it's almost too easy. And I mentioned this earlier to allow the status quo to play out. And sometimes you've got the cultural shift required, but also within the current economy and climate, trying to get funding to drive change through a new system, a new process and new technology. A new partner isn't always as straightforward. And so there's an element of figuring out whether you're looking for wholesale transformation or change. And of course, that might be a harder message to get through versus picking off through the customer journey. A couple of nuanced and interesting focus points that you can pull out in isolation and enable a business to safely experiment on a segment. And then that way, it feels a little bit more what's the word I'm looking for protected so that you can have a go at experimenting on a smaller scale, look at the results and over time, build your confidence. And so when times are, when times are tough and we don't have access to the funding or to the cultural appetite to deliver big change, can we do it in smaller steps and smaller changes to build up towards those bigger ones? And so it's the power of the 1%. How many times can we do a 1% change that through time can add up to that wholesale change? That would be my advice. Pick off a couple of journeys and nuanced points. Experiment with those safely, build trust and confidence and enable your culture to move forward slowly, step by step. Krithika: Fantastic. And I think that was a fascinating glimpse into the future of customer service, artificial intelligence and customer experience with you. Um, thank you for sharing your forward thinking strategies. But now it's time to jump into another section, um, of the podcast. Um, Shamas so, now that we know about your thoughts on customer experience, we'd love to know a little bit more about you. So here's a quick rapid fire. Are you ready for this? Shamas Aziz: I'm not very rapid. I'm probably a bit more fire, but I'll give it a go. Krithika: Awesome. Here we go. So, if you could only listen to one song for the rest of your life, what would it be? Shamas Aziz: Oh, wow. I don't listen to any music. Um, so let's go with podcast. Um, and that's probably a better way of doing things. I would listen to my friends podcast. It's called Get Out of Rap by Martin Teasdale. Please check it out. Krithika: So, absolutely. If you had a time machine, would you go to the past or the future? Shamas Aziz: Um, that's always a tricky question without taking it into a weird space. But, uh, if it was a time machine and it was something that we were able to do, I'd go back to the past and I'd want to go and spend time with those who are no longer here. Krithika: Right. Favorite movie or TV show? Shamas Aziz: Um, I was thinking about this recently, actually, because a few different people had asked me, um, so my favorite movie I would say is inception. Um, Leonardo DiCaprio. It's a bit odd. It got the cogs turning. Um, I watch it multiple times over the years, and, uh, I always enjoy it every single time I watch it. Krithika: Lovely. Um. If you could master any skill instantly, what would it be? Shamas Aziz: Um, probably cage fighting. Um, I used to train many years ago, and, uh, it was always fun. It was always challenging. Um, it always was a great equalizer to anything that was going on in life. Um, an opportunity to just think about you and the person in front of you. And so, um, if I was able to just learn that again and master it, um, in a different way, that's something I'd probably download and install. Krithika: Nice. Um, dream superpower. Invisibility or ability to fly? Shamas Aziz: Oh, wow. Um. Let's go with flying. Earliest memories of Superman and watching him whilst I was growing up. Um, so let's go with flying. Krithika: Mhm. That's nice. So if you could switch jobs for a day with someone in a completely different field, who would it be? Shamas Aziz: Uh, I would probably want to be a teacher. Um, so, yeah, I think that's probably a scary concept. Um, having to find a way to get my point across in a different way, but actually more likely than trying to get a point across, it's having the right questions and set of questions to unlock the potential of somebody else. And so I think it's an amazing job that teachers do. Um, and it's one that's equally scary and interesting to me. So, if I could switch for a day, it would be that role. Krithika: Lovely. Early bird or a night owl? Shamas Aziz: Uh, both, which doesn't really work too well. Um, but, yeah, I am bit of both, uh, Night Owl, and then I get up early, too. Krithika: Great. All right. And that's the end of the rapid-fire section. Thank you so much for taking the time out to speak with us. It was truly insightful, and there's a lot to take away from this conversation. Once again, thank you for joining us. Shamas Aziz: It was wonderful spending time with you guys today. I hope you found something useful. If you'd like to interact with me, you can find me on LinkedIn. Krithika: Great! Stay tuned for more engaging discussions on the retail podcast by Vue.ai. For now, this is your host, Krithika Anand. Bye.