The first guests in conversation with host Maarten Masschelein are Mauricio Rodrigues and Tiago Andrade from americanas s.a.
With more than 51 million e-commerce customers and 3,500 physical stores, americanas s.a. is Brazil’s leading retail innovation platform with a reputation for exceptional customer service and rapid distribution of products.
In this episode, the conversation is formed around americanas’ approach to data, on which its entire retail offering is built upon, which informs both the company’s ability to recommend and sell the right products to the right people, and its mission to deliver a unified commerce experience for an incredibly diverse customer base across Brazil.
Join Maarten, Mauricio, and Tiago in conversation on innovation, automation, vision, and what makes their worlds go around.
Welcome to the Soda Podcast and welcome to season one of the series In Conversation With. Just like good data helps the world go around, so do good conversations. Your host is Maarten Masschelein, CEO and founder of Soda Data. In this series, Maarten will be in conversation with practitioners, technologists, and change makers who all share a passion in making meaningful connections and rethinking traditional practices. They'll be talking about data, what makes their world go around, and sharing their thoughts, perspective, and ideas that we think will inspire you to be a part of the conversation and be a part of the change. Without further ado, here's your host Maarten Masschelein.
Welcome everyone to the Soda podcast. My name is Maarten, and I'll be your host today, and this is In Conversation With. Today, we're in conversation with Tiago and Mauricio from Americanas. So let's start with introductions. Let's dive in straight away. And let's start with Tiago. Can you maybe introduce yourself very briefly and what makes you a great listen for this podcast?
Hi Maarten. Thanks for having us here. I'm Tiago. I have over ten years working on retail, e-commerce, with a lot of experience leading data and product teams that use information to back up the stakeholder decisions. So I would love to share some of my best knowledge and also learn with you.
Awesome. And thanks for being here. So you're dialing in from Rio de Janeiro. Tell our listeners something about Rio or Brazil that everyone should really know about.
Oh, Rio is amazing. Of course you probably heard about our carnival, but there are a lot of things that we love here. Like the beaches, the weather by itself, the nice place we can go to, listen Samba, drinking a caipirinha, and we are hoping to have you here soon.
I would love to. I've been, I think what to me feels the closest in Europe, that was Lisbon now a couple of times recently. Was amazing, amazing weather, the beaches as well, so I really enjoy that lifestyle. So I hope I'll be there very soon with you guys. So, Tiago, tell us something about your journey and how you got here today.
Well, that's an interesting question. I'm a physicist. My background also, I had a Masters in nuclear technology, focused on science. And after that, I decided to join the entrepreneurship business, trying to in the first steps, build something on my own. So I learned that it's not so easy. I didn't have much experience at that time. And I started applying for what we'd call trainee programs here in Brazil. And I started at Americanas in 2009, if I'm not wrong. Since then I have passed more than twelve years inside Americanas. I had the opportunity to work on very different teams with different scopes. For example, I started working in the sales team. I had the opportunity to lead more than 600 person directly, working in the sales taskforce. I had also the opportunity to lead small teams. Three, four, five people doing some brilliant job. And since 2014, more or less, I started working in technology. So I had a lot of experience developing machine learning system bases to help increase the customer experience, to help reduce costs from the company, et cetera. And for the past five years, I have been working with a brilliant team to develop our data platform and machine learning platform. So this is my day to day, and I have a lot of interesting things to share with you.
I can imagine. What an awesome background. I think it's one thing we have in common. So we're both now in technology and data, but we've both worked extremely closely to the customer. It's a very good experience to have, I think. Now if you look back at the last let's say maybe twelve years that you're now there at Americanas, what will be for you some of those game changing kind of moments during that time?
Well, if we think for the past ten years, could you imagine, for example, in 2007, more or less, fifteen years ago, we didn't have iPhone. We didn't have any kind of smartphone. So I would say that the most game changing was the development of the technology by itself in the past ten years, how it brings democratization, how it brings a globalization of the technology, how you and of course the teams and the companies keep up to date with a lot of different technologies, different ways to solve the same problems. For sure, it was one of the most challenging things we faced in the past time.
That makes sense. Yeah. A lot of things has changed extremely, extremely quickly. So when I first got introduced to Americanas, I almost fell off my chair. I looked at the numbers. I was like, what? This is crazy. Can you maybe tell our listeners because I'm sure there's a couple of listeners that don't know about you guys yet.
Sure. It's a pleasure. Americanas, it's a Brazilian retailer. We have nowadays more than fifty-two million customers, active customers. On our websites, we have more than one hundred and thirty million products, so you can buy anything. We also have more than three thousand five hundred brick and mortar stores, inside all Brazil. So we can guarantee that every customer, every customer's needs, could be matched with one of our stores or one of our online products. And of course, it is safe to say that we are present in the daily lives of any Brazilian.
That's amazing. I'd love to dive a bit into the industry. So we've talked about technology, of course, being a big kind of driver for change in the last ten years. But how would you describe maybe some other key changes or key things that have really impacted the industry as a whole?
The whole industry of retail or e-commerce in Brazil, it's kind of interesting, because if you compare the Brazilian market, for example, with the US market, we are a few years behind them. So we were the first Brazilian company to launch a Marketplace here in Brazil. If I'm not wrong, it was in 2015. And this was one of the things that changed the way we work a lot. Mostly because we increased a lot of the assortment we have for the customers. In the beginning, when we only sold our own products or what we called first-party products, we used to have I would say four hundred thousand SKUs on our websites. As I already mentioned to you guys, we now have more than one hundred and thirty million products on our websites. So it's a very different scale of assortment. And this makes us change every single piece of our entire platform starting from, for example, our search engine. And of course in the last mile, how we can deliver this product the fastest way possible to meet the customer needs. So I would say for the Brazilian market, the launch of the marketplace by itself, which nowadays it's very common. There is a bunch of marketplace in Brazil was one of the most important things that happened and changed the way the customers buy, interact with brands, and et cetera.
Yep. The customer experience, I think you've alluded to it, the customer needs, they've changed drastically, right? And I think data plays a big role in that. So how would you describe the customer needs and the changes there and how that translates back into your world of data?
Well, Americana's purpose is bringing together the best in the world to improve people's lives. So start with that. If you think what a customer needs, it's very different for the same customer in his timeline. For example, if you are a guy who always buys products with free shipping, but sometimes your refrigerator in your home, stop at work. So you can change the way you buy things because of one specific need you had. So understanding all these behavior changes that face every single customer, it's one thing that is very important. If we consider, for example, also the evolution of how people want to receive the product, I would say ten years ago, they were fine to receive the product waiting five days, eight days to receive the product in their home. Today, the people want the product as fast as possible. For example, we have a lot of delivery that we ship to the customer address in only three hours. So this is something that is very, very interesting and how we evolved into this kind of business. And of course, we and everyone won't be able to do this kind of innovation without using data, without understanding the customer patterns, how they buy, what are they expecting, et cetera. So data is the core of this whole platform, this whole ecosystem and these kind of decisions we make on a daily basis.
Makes a lot of sense. And I'm curious, because here in Europe, we have regulation in the industry. And I think regulation for everyone that has personal data customer information, there have been a lot of evolutions around what kind of data we can capture, for how long, how we document usage of data within a company. So everything around GDPR, ultimately. And I'm curious to also learn how that landscape has evolved in Brazil.
Yeah. Cool. Here in Brazil, we have another, I would say, group of laws, which we called LGPD. It's kind of similar to GDPR. So I believe every country or every group of countries, like in Europe, are facing the same issues, the same challenges. So how we can protect the customer, how we can protect its data, and it's not different for us here. I believe LGPD started two and a half years ago. Every company needs to follow a bunch of rules to make sure the data customer is safe. It's in a way no one who can't have access can do it. And of course, guarantee that if a customer wants his data, we can give him all the information we had about his history, his navigation behavior, his orders, et cetera. So it's almost the same. We just changed some letters in the name of the laws.
Fantastic. And so you've been in the industry for, it was twelve years, right? Yeah. You know, what makes the industry for you very fun and exciting?
Well, if you think about retail, I believe it's worldwide behavior. It's always a fast moving industry, because you don't need only to react to your business plan. There's a lot of competition inside this market. So sometimes you need to react as soon as possible, because one of your competitors changed something and make a kind of innovation, so you need to go as fast as possible to make sure your customers will have the same experience, the same need. I would say, not only the environment or the competitors, the market by itself, but also we have a lot of changes on how the people are interacting with the online buying process. So this makes the work very fun, because we need to think of some ways to build the products or to build the applications or websites that work for that person who are doing the first order online. So every single piece of your purchase flow needs to show a lot of trust so it's safe, you can do it. And on the other hand, you have those millennials that buy everything online. So they want to do it fast, with the best experience possible, a smooth flow of navigation, et cetera. So we need to adapt, and we need to think in different perspectives to make sure everyone can feel comfortable using our products. I would say this is the most challenging thing.
So truly fast moving. It's fast moving, not only from the goods that need to flow from the warehouses to the customers, but also in how you need to change your daily operations, I guess, as a retailer. So if you think about innovation is, of course, core in achieving all of that. So what will be the kind of NextGen or new innovative thing that you guys are working on that you can share here?
Oh, this is a great question. There are a lot of things I can't share, because it's not public yet, but I believe there is one that is very interesting. We launched a few weeks ago, our corporate venture capital platform. So for this year, 2022, we are on our way to invest in up to twenty startups. And our idea is, help them to drive organic growth using our entire environment. So we are looking for fintechs, we are looking for logistics, we are looking for tech startups that can address something in our environment which is very, very huge, considering we have a brick and mortar store, we have a lot of online business, we have fintechs, we have logistics platform, et cetera. And all of this business case, it's focus on bringing more open innovation inside the company. So I would say this is a very interesting approach. Again, we are the first Brazilian retailer launching this kind of initiative, and we hope to have a lot of good new business bringing to life inside this venture capital platform.
I love that. I think one of the hardest things as you're starting out with a company, especially if you're a data company, is of course data. And that's something that you guys can fast track for the startup. So that is fantastic. Great. Now, if you go back to your role, your daily role, Tiago, what will be some of the core challenges or maybe the most important challenge that you have to deal with, and how do you go about it? How do you tackle it?
There's a lot of challenging things we can face considering we handle all data initiatives in Americanas. One of the core challenges we have, and I believe every company has, it's democratizing all data initiatives. So how you restructure your team, how you make sure everyone has the training sessions to keep evolving, to keep using data in their daily decisions, and how they can make the decisions data informed. This is very different from what we usually see in the past where someone already has a hypothesis in his mind and is looking to the data to find the answer for that exact hypothesis. So we try to change the way people look into the data, to build a hypothesis during the journey of understanding your data, understanding your behavior, et cetera. So you have, in the end, a very data-informed solution, or a very data-informed discovery, to make sure you are in the right way, which makes sense for us. Understanding the needs of the customer and meeting them. So I believe this is the core challenge we face nowadays.
I love how you describe that, because I've been in a situation like this, where data was used to make a point, and that person already had the point and it was very... like, we didn't truly look at data, build different hypotheses, and test them out. Like, we didn't do that. And, I think changing a culture to that is extremely important. Only then you can truly become data informed or data driven. So that makes a lot of sense. I assume when building out a data innovation platform - because we haven't talked about it much, but we have in our prior conversations - that kind of translates also into some of the core design principles or how you think about innovating with data. Could you talk a bit about that platform that you guys are standing up with or have stood up of course, within the organization?
Yeah. I can share some highlights. I would say I just shared with you from a business perspective what is challenging. From a technical side, I would say, how can you scale your infrastructure? How can you scale your decision process and make sure everyone is using the right data, using the right information during your entire process of discovery and exploratory analysis. So when we think about our IT development ecosystem, for example, we have more than a thousand APIs that generate logs 24/7 the whole year. So how we can make sure we can get all this data flowing, run time into our platform, cleaning it, transforming, and making it available to the systems and to the people to make sure they can move forward with their projects, products, and decisions? So building these ecosystems by itself, in a way that the ecosystem is scalable, trustable, and accessible, it's very, very challenging. And I believe this is one thing the teams we built in the past five years can help all of these efforts to make sure the business can meet their needs. So I believe this is the thing which makes us a good retail innovation platform.
That doesn't sound like an easy feat standing that up. And especially at that scale. I can't even fathom how to go about it. It must be like the nature of it, it must be highly kind of agile and incremental and very fast moving, very dynamic. We've talked about these areas. I'm sure that also requires certain personal traits. So what is it like, maybe more on the personal side? What is it like to work in such an environment?
Yeah, it's challenging. The first step is of course, very, very challenging. I would say keep up to date from what the technology is evolving. The second thing we're always discussing inside with the managing team, how we can build solutions that's not locked to any vendor. This is another thing that we usually discuss. And how we can use the open source concept. Not only the open source softwares, but the concept by itself. Because there are brilliant minds all around the world, it's not only our team, so how can we take advantage of some brilliant minds that are developing software and sharing their knowledge into some new feature or some new product? And we can use this to enrich our data environment, our platform, and make sure we are moving faster. So I believe this is the main topic we would love to discuss. And probably this is the way we got to you.
I find it very fascinating, very fascinating also that this is a core part of your decision making process and that is a discussion point at a very senior level within the organization. I really like that. And it makes a lot of sense. If you need to move fast, you cannot be locked in, because locking in slows you down. Very, very interesting. So, what do you find fascinating at this moment?
This is a very interesting question. I believe we are in the beginning of a new era of the way people interact with technology. So what gets my attention nowadays, it's all discussions, and matters related to Web3, cryptocurrencies, to NFT. I believe in the upcoming years, we will have a very game change around this new market, this new type of trade things online and how people will interact with each other. Since the end of the pandemic, we are facing all companies keeping the home office way of work. So we need to develop new technologies to make sure people can interact in the same way if they were in the same room. So for sure, there's a lot of fascinating things to come in the next coming years.
Fully agree. Do you think that translates also to your fellow data leaders? Do you think this is something that's largely industry agnostic? Or is it not?
Yeah, I believe it will be for everyone, but talking about specific retail, I believe it will be a very fast run to see who will be the first to launch this new way of buying, who will be the first one to launch crypto in the way people use it, your website byproducts, et cetera. So for retail specific, I believe there will be more changes for than other sectors, for example.
Yeah, I think so too. You guys are truly at the frontier of customer experience in the end. I think a lot of other businesses kind of, they follow more, the experience kind of then extends across all other products and services. For example, including software services and other things that consumers are buying. So that makes tons of sense. Let's talk about data teams working together and maybe some stories around that. Possibly war stories. Is there one that pops in your mind?
There's one that we are very proud of. It was few years ago, I would say it's five years ago, during one of the sales season we have in retail—for those who are not familiar with, it's the Black Friday season—so we used to have all kind of the data flowing into our platform, and one of the cloud vendors broke the software we were using into our streaming insert logs to transform it into our business metrics. It was not something related to our way of using the software, it's general. It was broken for the entire world. Everyone who was using that product faced the same issue. And it was almost midnight. And Black Friday season in Brazil, it's very, very famous. People wait until midnight to start buying, because they believe discounts will be available at midnight. So we decided to move as soon as we could to build a redundancy of this ingestion flow. So in other words, we were building the plane during the flight. Exactly like that. This is the most real situation we faced. Me and myself and the team, we holed up for more than thirty-six hours working directly to make sure every single piece of our ecosystem was working properly and we were not losing any data points to help the business make sure. This was one history every person in the team is very proud of. And of course, there is a lot of learning from that. Since that occasion, our entire architecture, it's moodcloud. So nowadays, if we need to switch between one software to another, because any cloud vendor was struggling with some issue, we are talking about five to ten minutes just to change the configurations and redeploy the software. So we learned a lot about that, but it's a history everyone remembers, and we are very proud of.
Wow. Yeah, it must have been a crazy set of days. And it says a lot about the company culture as well, about taking ownership in that moment and about making it work for the customer. So a true customer obsession, I feel in that story, which is really impressive. And also at Soda, we're super happy to have welcomed you guys to the family. We're gonna bring in Mauricio in just a little bit. He's a data manager in your team. But before we do that, could you talk a bit about the team structure that you have in place?
Yeah. I can give an overview. So we have specialized teams. So we have a data ingestion team, we have a data analytics team. Data ingestion, it's already explainable. Data analytics team, it's the team who run the ETL process and make it self serve for everyone else. We have a data visualization team. We also have our data governance who is responsible for how every single piece of the platform works, which software we are using, if it's safe from a cybersecurity perspective, et cetera. We have two more teams. One is software development, which we call tools team. The name it's explainable, also. They build software to scale any process we want to develop. And also we have a community team, because it's not only important to have the technology, the platform running, the data available, if we don't change the way people are using. So we believe the community team is the heart of the entire platform. So this is the way we are organized today. And Mauricio is one of the managers who is in charge of the data ingestion team and the data governance team. Also, he leads the tools team. So he is one of the main guys leading the development on the platform.
Awesome. Mauricio, welcome. It's fantastic to have you here on the show with us. Let's maybe start with an introduction into you and your role. And the key question that comes to my mind is how do you end up in the role of a data manager?
Hi, Maarten. Glad to be here. As I graduated, I already started working with data. I’ve worked with data since I was an intern, right? And I passed through some industries like telecommunications, media, and now retail. And I always enjoyed working with technology itself. But as I moved on with my career, I also found that I love working with people as well. So being a data manager was a natural path in my career, as I can mix those two skills, technical and interpersonal. So that's why I'm here. That's why I chose to be a data manager.
Fantastic. And I'm sure the skills also translate across the industries. Or were there things that were particular in a certain industry?
Well, I usually say that data is the universal language, right? So no matter what industry you are, you have to treat the data almost the same way. You have to understand the business, what your business customers need, and try to bring the data as best as you can. Since the ingestion of the data, through the transformation delivered, you have to treat the data well, because at the end of the day, the business will be run upon the quality of this data. So this is a lesson we learned, that it's the same in every industry I worked in.
That makes a lot of sense. And it was, for me, when I looked at your profile for the first time and saw your area of responsibility, I was like, wow! Mauricio covers everything from both, like, engineering teams to data governance, which is much more about business and people and processes. So it's a very broad spectrum in the end. So I'm really curious to learn, what does your day to day look like?
Well, yes. Indeed, it's a very broad set of responsibilities, but as we have a great team, it also makes our job easier as well. But as Tiago mentioned before, I manage two teams, actually three teams: the data engineering team, the data integration team, who is responsible to create and maintain the data pipelines, ensure that they are all up and running smoothly with 99% of availability, right? And also the governance team who is responsible to make sure the data is well organized, the data is well managed, which means the quality of the data is good, the data is accessible for the business, and also the data is secure. So at the end of the day, we have these teams working together to make sure we deliver the best data, the best information for the business. So our daily job is to ensure that we provide a good background of data to our business customers.
That makes sense. And what does the operating model look like between those different teams? Are there maybe examples of interaction points or how do they work together ultimately?
Yeah, sure. The data ingestion team, the data engineering team, they are focused on the technology part of the business, right? So creating the integration, managing the APIs, making sure that our infrastructure is running okay because the business is 24/7 so they have to make sure that all of our data pipelines are monitored and ready to respond to an incident that may happen. And the data governance on the other side is making sure that this data is being well managed, because we have hundreds to thousands of people in the company using that data. So we want to provide them a well organized and easy to discover data so they can run their jobs frictionless, right? So that's how these teams work together.
Amazing. So you guys have truly adopted fully self-serve and making sure that everyone in the organization can be successful with data while at the same time, of course, making sure you comply with regulations and make sure that everything is done in the right way, which I really enjoy. You mentioned tools, technology, and that you're a big fan. Me as well. I love kind of scavenging on the internet and figuring out what's new, what's happening, and then tinkering with things. It's one of my hobbies. What would be a tool or something that you stumbled upon recently that you'd say, well, that's an interesting one to share?
Well, okay, here at Americanas, we're very proud of having a very talented and skilled team, right? So we usually prefer using open source tools because our team likes to know what's going on under the hood, right? So if you see our data stack, they are mostly based on open source tools like Apache Kafka, Airflow, and other tools and languages. Many times we build our own solutions using languages like Python, Golang. And Soda's a good example, because we came upon Soda because it also has an open source part of the solution, the whole solution, right? So we usually prefer those kinds of tools, right? And hopefully they are all scalable, they are all easy to use, which is important. As we want to scale the use among the company, the tools must be easy. You must be able to create your solutions fast and then open source tools help us to achieve this. Go faster.
Makes sense. I, myself, was a bit newer to open source, like actively, really involved only in the last about six years. And that was a lesson that I've learned as well, that everyone can be much more self-serve and much more successful on their own without having to depend on anyone else is one of the key benefits. So, that's great to hear that's something that you guys have truly embodied within the organization as well. Any kind of areas in technology that excite you right now?
Yes. Yes. We're looking closely to Metaverse for example, which we believe it's going to be a new stream of revenue, maybe. A whole new experience for our customers. Obviously, I believe that there's going to be a lot of data I'll need to work on. So I think this is a very new, promising technology, and we're looking very closely, very careful to that and see how it fits in our business. But for now, I think that's the most we can share, that we are looking forward to implement this technology and see how it can help the business in an overall way.
Fantastic. And indulge me if you will. So, we've recently announced our partnership, and when I read the press release, I had a smile on my face. And, you know, the impact was in all different areas. You've talked about process optimization, revenue or new revenue streams, it touched both the revenue part but also the costs, the risks. So that was really, really exciting to read about. Could you maybe talk a bit about your use of our platform within the organization?
Absolutely. Well, until we found Soda, we had some initiatives on data quality, but it wouldn't scale well. So we found that Soda would provide us this ability to scale to create scans fast. It used to take days to create a scan. With Soda, we can create scans in a few hours. So that's how we found that Soda would help us to monitor all of our data pipelines, because our business runs, as I said, 24/7. The business team literally take decisions based on the data, on real time data, and then we believed and it proved right that Soda would help us to create these monitorings, these other things so we could react fast to any issue, to any incident and guarantee that the team is receiving good data to take their decisions. So this was our first use case to guarantee that our sales data, sales information was going to the business team with good quality. This was the first use case. And then we also are extending that philosophy for other pipelines as well, right? Soda also helped us because of its self-service capability to scale among all the users in the company, because we believe that we should not only concentrate this responsibility in one team because it wouldn't scale well, this team would become the bottleneck of the whole process. But if we can deliver this software to our business analysts, our data analysts, they can by themselves create all of the scans. All of their needs would be fulfilled. And that's why we chose Soda. We found that the features it provided us, the self service capability, and the ease of use was key for us to go in this path, in this direction.
Awesome. Thanks for sharing. Puts another smile on my face. So if we go back to technology and technology decisions, what will be something you guys, or you, more specifically, will never compromise on when selecting new tech?
Okay. I think this solution must be reliable at first. For our business needs, it must be reliable. It has to be also easy to use, as I mentioned, because we believe that we have to scale and use it to give us the capability of automating as well. So automation is very important for us as well. And the availability of this tool must be key for our business as well. I think these are the most important things that we look for. And also it has to integrate well with our ecosystem, right? So obviously it's another key area of requirement we have to select a solution.
Fantastic. You mentioned earlier, you started off with sales, I guess, revenue data or transactional data, I assume, and bringing that to people so they can make reliable decisions. Are there other use cases or areas that you want to share as well that you're currently working on? Maybe different parts of the business?
Yeah, we are implementing the data quality checks, for example, on our machine learning streams, as well. As everybody knows, machine learning relies a lot on data. The models and everything related to machine learning must be trained upon good data, upon good data quality, because poor data quality will in turn create poor machine learning models. So, the machine learning team is also taking advantage of the data quality. They are creating themselves their own scans, making sure that they have the best quality data for their needs, for their training. So this is another stream of use of Soda.
Awesome. There's many examples out there where machine learning models go AWOL and it's of course all because of the data. We often don't have the observability or the understanding of what's really going on with the data. So, it makes a lot of sense that that's a key next use case for you guys. Let's maybe put Tiago on the spot a little bit. What does Tiago give you to really make you successful in your role?
Yeah. Yeah. Tiago shared with us his vision, the objective of the company in a big picture. We discuss the goals. We discuss the details of what we want to achieve. And then he empowers us towards that me and my peers are going to deliver our best. So that's how we work. And I can say it's a very successful relation we have by working this way.
Awesome. And what would be a thing that you give back to him?
Well, I could say that is commitment. We're very committed to deliver. And enthusiasm, why not? I believe that we work with enthusiasm, the job will be done better, the result will be better, better outcomes.
Amazing. I'm sure, Tiago, you would agree.
Oh yeah. Totally agree.
So Mauricio, when you heard that we were doing a podcast and that you guys will be the first team to join this series, was there anything that came to mind immediately that you thought, well, I definitely wanna talk about this or share that story?
Yeah. Yeah, definitely. We always talk about technology, data, technology stacks, but it should also speak about people. Having the best people with us is very key to our business. Right? Nobody does anything alone. So we truly believe that having good people working with you is key to leverage the result of the business. So we are always looking forward to having the best people working with us.
Fantastic. And I'm sure there's some careers page somewhere as well that we should put into the show notes so that people can go and find what those opportunities are. You've talked earlier about some parts of the culture which really stuck to me, like the thirty-six-hour end to end, going figure out, fix things, make sure there's no data loss, make sure everything runs smoothly, and you create a great customer experience. And that I think is something to truly be proud about. Is there something else that you are proud about, both of you maybe, in things that you've achieved with the team over in the last years that you wanna share?
Yeah. I think we have many events here in our business, as Tiago mentioned, Black Friday is one of the most important. And it gives us a very sense of fulfillment, seeing everyone committed to this event. When we are close to an event, everyone is very focused, very excited, really excited to make things happen in the best way we can. And in the end, out of the event, we are always happy with the result. Then we can cheer together and have the mission accomplished. So it's very rewarding to see this atmosphere and see the good outcomes that we achieved with all these people working together in this event, for example.
Yeah. In a more general perspective, I'd also add that we are very proud of our team and of course, in being part of Americanas by itself. The first brick and mortar store was launched in 1929. We are almost a hundred years' history company, and everyone feels very proud to be part of this history of Brazilian people. The digital business was launched in 1999. So that's like more than twenty years ago. And everyone is part of the digital transformation that is running into Brazil. So this makes us very proud of what we are doing.
Yeah. It's a true legacy and one to be extremely proud of. I really enjoyed having you guys here on the show. Before we wrap up, let me ask one final question. What is something that you look forward to? Tiago, let's start with you.
I would say to keep bringing together the best in the world to improve people's life from a business perspective. And from a personal one, of course, I wanna see my baby boy growing and being part of my life.
Awesome. And you, Mauricio?
I hope to keep making a difference in people's lives. In our business, it's very clear that we want to deliver the best to our customers, the best experience and make their life easier.
And what about you, Maarten?
Well, I hope to have, first and foremost, many more conversations like these. It's truly inspiring, and it really gives a great boost and drive to the things that we're doing as a team. And maybe on a lighter note, looking forward to tonight, it's thirty degrees Celsius in Brussels, which is extremely hot for us. So I'll be spending my evening on a rooftop, having a barbecue. Guys, thank you so much for being here today, for sharing all of this. I hope the listeners had a great time as well. I definitely enjoyed it. So thank you very much.
Thank you, Maarten. Have a great day!
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