[Music] [Daniela Canedo Guichard] Hi, everyone. How are you all feeling today? [Man] Good. [Woman] Great. Thank you so much for being here. Thank you so much for being at Adobe Summit. It's the third day. It's the final day. You made it. That's amazing.
Honestly, I'm so happy to have you all here bright and early for this commerce session. I know it's going to be an amazing session. You're going to learn a lot from your peers and really be able to enhance your product. But before we start, did you all have an amazing time, last night at Bash? Did you all enjoy the beautiful F1 venue? It was amazing as an F1 fan. I was really happy to be there. And I kept sending photos to my partner, like, "Yeah, I'm here." So thank you so much for being here. My name is Daniela Canedo. I'm an Adoption Marketing Manager, Supporting Adobe Commerce. And my favorite part of my job is how much I get to collaborate with customers to really bring you the best practices for you to make the most out of your Adobe solution. So without further ado, please welcome Juan Pablo and Francisco. They're both from the Coca-Cola Company, and we're really happy to have them here to be able to present to you how to make the most out of a Data Ecosystem for Personalization Success. So please give them a very warm welcome.
[Francisco Bello] So thank you, Dani, and thank you for all the ones that survived yesterday party. So glad to have you all here. As Dani said, I'm today with Juan Pablo, JP. He is the ecommerce product director for Coca-Cola Company, and I, Francisco, am the Senior Director for Direct to Consumer business of Coca-Cola.
So today we are going to talk about what is our direct to consumer business, just for you to have in mind what we do.
And after that, we are going to go straight forward with Juan Pa, who is the one in charge of telling you how the technology is allowing us to-- [Man] That and where our business-- The business should and must go. So first, we are going to start by showing you a small video.
[Music] [SPEAKING FOREIGN LANGUAGE] [Music] [SPEAKING FOREIGN LANGUAGE] So for the ones who have been in Mexico City before, this commercial represent a bit of the city, a bit of the movement of the city, but also introduced to our Mexican consumers this direct to consumer channel that is available for everyone in the whole Mexican territory. So the name is "en tu gar" for the ones who don't speak Spanish. It means at your home or in your home.
And this huge platform that today we have 80 distribution centers spread all over the Mexican territory in order to serve our consumers. We started as a web page, as a website. Today we prefer to talk about digital ecosystem because we are not only a website, we also have this way for consumer to buy from us through a Chatbot. This is half conversational, half web view. And last year we launched the application for Android and iOS. So today is the consumer, the one who can choose how they want to approach to our ecommerce. And some of them, not all of them, dualize actually. So they buy sometimes from the website, but sometimes from the application.
We offer this next day delivery, so it's a stock-up mission. Today, we are not able to offer a quick commerce solution. So it's a planned purchase mission of a stock-up, that's why we do it that way. And one interesting thing is that we're still offering free delivery. So think about that. We're selling Coca-Cola. That's it. Very, very straightforward business. Our average order ticket is around $20, no more than that. But we manage to have this discipline, to manage the business in a way that we can still offer a free delivery but having a profitable business. Okay? So that's the main challenge of what we do. And we offer the full Coca-Cola portfolio. Of course, Coca-Cola is a big company with over 200 brands. We offer all of them, not 200s, but the ones that are available in Mexico for sale. And on the way, we have some partners to this ship. So today we have partnerships with Heineken, so we sell actual beer through the platform. We have some partnership with Mars, so we sell snacks. With Procter and Gamble, so we sell also the portfolio, a small portfolio of Procter and so on. So we try to complement the proposal that you can find not only the-- You can not only buy the stock-up mission with the Coca-Cola products but you can find other complimentary products that make your life easier.
Some of them are numbers for you to keep in mind. So last year was a great year for this business. We have more than 500 unique buyers all over the year. Each single month, we get 3 million of visit in our sites, in this digital ecosystem that I present to you before. And one interesting thing to highlight is that...
We have two to four peak days each month where we make special promotions. We have something happening in our digital platforms. And on that days, we have been capable of processing over one order per second. Of course, for the ones who are more prone to buy in marketplaces, these big marketplaces like Walmart, like Amazon, this is nothing, this is nothing. But this amount of traffic for a D2C of a CPG company is one of the biggest. So that's where the technology has a role. Our partnership with Adobe, of course, and CINT has allowed us to grow and absorb quickly this traffic, of course, offering a great value proposal to our consumer.
All right. So this is our history. We launched the digital ecosystem 30 months ago.
And we became the biggest digital player for Coca-Cola in Mexico. So that doesn't mean that, for confidentiality, you can imagine who are the blue ones and who are the yellow, orange ones. But we do not sell more than them, of course. We don't sell TVs. We don't sell electronics, but we're actually selling more Coca-Cola products through our own direct-to-consumer business than we do for this third-party relationship what we have with others, all others, digital players in Mexico. Okay? And that was achieved last year. So how have we done it? The first-- Again, this is a very simple business. We sell Coca-Cola. So we're avoiding our consumers, our users, the pain of shopping these very, very bulky products, especially if you thought of a 20 liters jack, for example. The pain of going to a supermarket, putting in your car and so on. And of course, in Mexico, this is very special for Mexico, there is a culture of buying refillable products.
Some of them for sustainability, but most of them for the price.
Refillables products are cheaper than one way products. And we also are solving that pain. 40% of our revenue is from refillable products, and we are avoiding the user, the consumer, to carry this empty bottle to the store in order to refill it. So we go to your home, we take back your empty bottles, and we give you the new ones. Okay? The other part is, of course, focusing on user experience. Simple business requires a simple user journey. So we don't want to make it complex. You go to the site, you find the catalog, you add the products to your cart, and you pay, that's it. Twenty four hours, your products are going to be at your door.
And finally, we are trying to find a way to differentiate our sales, our sell from the other digital players because you can find Coca-Cola products everywhere. Not only online but also in the offline, in the real offline world. So one way we are trying to make this differentiation to happen is that we want to go or create this relationship with our consumers and user that goes beyond the transaction. So we don't want to have only a transactional way of having a relationship with our users. So, for example, during 2024, we have over 30,000 users that want something from us, from a pool of over 100 different experience. What our experience? Very simple experience. For example, Coca-Cola has partnership with movie theaters. So you buy from us, you get free tickets for the movies, for amusement park, but also more sophisticated experience. For example, knowing your favorite artist. So we make this deal with an artist and you can have a meet and greet. Or go into the FIFA World Cup, go into the Olympics. So we leverage the experience of the direct-to-consumer platform, of course, in all the asset that Coca-Cola as a company has to offer to the consumers. And you can find this exclusively in our platform.
But after these 30 months, this journey of 30 months from creating this ecommerce until the numbers that I'm showing to you right now, we realized that a business like Coca-Cola, that is very massive business has many different types of consumers. We can have this one single persona that we target our service. So everyone's, everyone in Mexico buy something from the Coca-Cola Company. The penetration of Coca-Cola Company in Mexico is over 99% because we sell soft drinks, but we sell water, we sell juices, we sell milk. So everyone in over a period of a year has bought something from Coca-Cola Company in Mexico. So the only way to connect in a meaningful way with these very different consumers is by delivering them a customized person like experience. And that's where we are trying to help with the technology.
So we make this very simple framework that we stole from the internet. Nothing fancy. But first, we need to understand our consumers. So this consumer we know they are different. We need to get to know them better. We need a tool to target these consumers based on the knowledge that we have about them. And, of course, we need a way to deliver the message in order to generate this personalized one-to-one relationship with them.
So at the beginning, Juan Pa is going to go deeper into this.
We gather information from all the sources that we have. So we have, of course, the user information. This is the consumer profile, the transaction that they make, the very basic of our ecommerce. But we also have access to other more sophisticated sources of data. For example, interested. We are connected with Meta. We are connected with Google. So I know that you may like football, soccer, music, video games, etcetera.
But we also have some knowledge about the feedback that the user gave to us.
Proper or formal surveys like NPS or when they contact to us because something had happened, but also the silent way of getting feedback from our consumer when they browse through our platform. What products do they look? How much time do they spend in our site? Are they making click in the banners, in the home slider? Are they scrolling down or they are not scrolling down? So we gather all of these formal feedback that they gave to us, but also all these informal feedback. And we gather that in a single platform, that Juan Pa is going to be talking in just three more minutes. So imagine all these sources, information, like Lego bricks. We like ourselves to picture in that way. So we have all these dimensions, some of them summarized in the slide, and we can stack these dimensions like Lego bricks. So we can have very simple segmentations, using just two Lego bricks as an example, but we can stack more Lego bricks.
And these Lego bricks lead us to a hyper segmentation or more sophisticated segmentation with smaller groups that share something that make this smaller group common.
And finally, we need a way to deliver the message. So we gather the information about the user. We have this tool to create this segment, and we need to deliver the message to the very same platform, and these messages can be delivered through digital media, inside the platform with personalization inside the digital platform that we have, the website application on the bot, and of course through our CRM. So that direct messages, direct communication to our consumers.
[Juan Pablo Jurado Martinez] And this is going to be the third time that someone-- Thank you for being here. Again, the first session in the morning, so we're trying to make this session quite dynamic. We're going back and forth on the platform. I don't know how many of you guys are heavy users of Adobe Commerce, AEP, please raise your hand.
For you guys, this is something that you are going to, like, feel familiarize with. But the ones who actually didn't raise your hand, you are going to see how easy is interact with the platform just for the simplicity that Franco was telling you, how you are going to set up a coupon, how you are going to also create an audience, create a journey, how the user activate this coupon inside of our platform to get the benefit and so on. And hopefully, at the end of the meeting, you are going to be eager to actually experiment with this kind of tool because at the end, it's quite easy to use it, right? So coming from the exponential growth that Franco was telling you, imagine that, basically, reaching that level of personalization means that, yeah, we need to consolidate millions of data points, millions of consumers actually leaving out the data. And with that, we have a lot of challenges that we need to face in a very proper way. The first one is going to be the data integrations coming from different sources, different formats, different level of quality. The second one will be handling this massive volume data at a good velocity and at the scale as well.
The third one, for sure, and you are familiarized with this one because at the end, it's at the core when we work with data. And it's ensured that data privacy, the data security, the regulatory compliance just to ensure that we're going to contact our user to actually want to be contacted and in the way the user want to be contacted as well.
The fourth one is, basically, through a really like analytics machine, how we can offer the personalization that the user is seeking in our platforms.
So this is kind of how simplicity looks like. We're going to, like, explain you very briefly the high level architecture in here. But you are going to see that, at the end, like data architecture was thought for the future back in 2023 when we started this work because in 2023, we actually didn't have all the data sources integrated. We just have the transactional data coming from Adobe Commerce, but also the profiling data coming from our CDS or our consumer data platform. With this information, we just need to storage in somewhere, right? In our case, with storage, that information in our real-time CDP, and we transform the data, we create the audiences, we ensure the compliance of the data that we are going to use in the different platform or the destination that we have in the architecture. But also, back in 2023, we also didn't know that we can use basically a lot of the tools that Adobe actually brought to us. And we'll start with the simplicity. We'll start with basically using coupons in Adobe Commerce. But after that, using the same integration, we start to enabling more and more tools depending on the use case. So these two concepts that is going to be basically the use case and the tool is going to help us to understand which tool is going to be the better to be used. And we have the data to actually use the destination in this architecture.
So today, we are going to go through three different platforms. Some use cases in these three different platforms. We're going to go in Adobe Commerce, how we can use the coupons and, actually, how we use the coupons. The second one is going to be Adobe Target. And this is somehow a funny story because you use Target because you want to test, right? But we want to actually test the test. So you are going to see how Target actually help us to, like, approve hypotheses, simple hypotheses such as-- Look, we know that our recommendation is going to work better for the user that are exposed to our recommendation. But I really want to test that. So we start to test a lot of things using Target. And you are going to see some of the hypotheses that we actually worked around using this tool. And the third use case is Adobe Journey. So how we actually are creating some simple journeys just to activate a specific consumer. How we actually create the CRM strategy in the AJO just to actually be sure that we are going to cut the contact, user segment, but excluding all of those users that, at some point, actually are not going to belong to that specific segment because purchase more in the average order value, or because any other variable as well.
So let's just start with a use case of Adobe Commerce. The famous shopping cart price rule. So some general things that you need to consider on this kind of work is that we can offer a special discount in the shopping cart, given a specific condition. The other one is discount is going to be applied automatically on the checkout, and it's going to be displayed just below the subtotal of the checkout.
And the fourth one is going to be that discount rules can be adjusted for a specific promotion by changing some status on a valid date. But when you set a coupon, you must understand that first you need to create the segment that at the end is going to be some conditions on the users. And the rule that at the end is going to come from a commercial perspective because we are going to say, how much discount we want to provide, percentage of discount we want also to provide, how many redemption we want the user to have in a period of time and so on. So with that, let's take a look on this video, that at the end is going to explain very quickly how we, like, create the first rule or the first variable that this shopping cart price rule has that is the segment.
So in the customer section you are going to see that we click on the Customer. We need to normally put a name on the segment. We need also, in this case, to put a description but also to select some sites where we actually want to activate this coupon. We normally work with warehouse, as Francisco was saying, we have a lot of warehouses in Mexico. So sometimes the coupon is just direct for on a specific warehouse.
Then you are going to click on Save, and a lot of more options are displayed on the platform. And in that platform actually you are going to select depending on your data structure, right? We select users that are coming from a website and users that belongs to a specific domain that in this case is the Coca-Cola domain. That this promotion was for an endomarketing purposes as well. And after that, basically we have our segment completely created. But then we need to activate the segment. So for that, let's go for how we activate that kind of segment. So we have three different types of coupons that we are using. The first one, we name it a unique name coupon value for multiple users. And in this, basically configuration you can set a lot of things. You can set a fixed discount, a percentage discount. You can actually also set a specific discount for a category or for a specific product. And that's the way actually we are trying to personalize all of our offers. Try to understand the user that actually buy more water. So let's offer discounts for water purposes, for water purchases purposes, for data specific users. And in this case, we're going to see a specific activation that we have, basically, for a specific user that we want to provide a fixed discount, given the condition that it has the order greater than X or Y amount. So you need to always like have in your mind and you need to put the coupon code. That at the end is the code that the user are going to put into the checkout process. You are going to set up also some of the condition that is, how many redemption we want to have per coupon, how many users we want to also provide in this case? And after that the configuration is set and this is the way that the user can activate basically this coupon. So you are going to see that just right below the subtotal we have the discount complete enabling here. Okay? The second one is, sorry, is basically we want to have multiple coupons for multiple users, multiple purposes, right? The only thing that you need to change in here, you are going to see is that you can enable the auto-generation function inside of the Adobe Commerce. And with that, basically, you are going to make the same configuration of the previous one, but the platform is going to display right on the bottom of the platform, all the codes automatically. And, boom, that's all. You now can activate this, basically, promotion to other channels, such as AJO and so on. But this is the way, basically, that the user also can redeem this coupon in the same way. Okay? And the third one, and is one of the most popular at Coca-Cola, is that we don't want to use a coupon. Actually, we want just to provide a specific discount when the user, in this case, buy a water product. So let's see, basically, how this look like. And it's just a small change that you need to do comparing with the previous configuration. And you just put-- We don't want to use a coupon. So just click on that coupon. Same the same, actually configuration that we saw previously, the same rules and everything. And in this part is when you actually activate the category. You just put, in this case, our category that is the water products. And with that you are saying that, for that segment, we are going to enable the direct discount without using any coupon direct on the checkout. And this is how it looks like for the user.
You see, no coupon, discount below the subtotal. And that will be all for this kind of configuration.
But Adobe Commerce shopping cart price rules actually has pros and a limitation. So we are looking, basically, for working with a broader segmentation using transactional data for a special or big seasonality, and a couple of times at month for instance, Adobe Commerce is a great platform, right? But if we want to automate some activation processes, it made the segmentation a bit more complex and dynamic by using, in this case, profiling data, that is the other data source that I showed on the high level architecture. So we need to combine some Adobe tools because we want to actually have the platform doing the work that actually we were doing manually. And in this case, with the real-time CDP, so we are integrating the profiling data. So you can integrate not only the profiling data, in our case, it's the profiling data but also another kind of data that you have on your data catalog. With AEP, we are basically creating these dynamic audiences. You are going to see how we create an audience very quickly. And using AJO, you are actually automating the triggering. And that's pretty cool because at the end it's something that is constantly moving depending on the consumer behavior. And actually we don't have enough hands to put an army to do this work manually all the time.
So this is the simple use case. And in this case, it's a use case that we have for, let's say, congratulate the person that has the birthday in a specific month.
So let's go to basically AEP. We just put, in this case, the marketing segment. This is Adobe Commerce. So we need to first of all create the coupon because at the end, this is the way we are going to activate from the commercial side of the things. And in this case, we create basically the coupon, all the rules that we saw before, and that will be all. Just make the same configuration. And after that, you're going to see that once we have basically the coupon completely set, we're going to activate in the other platform. Okay.
Great. So then we go to AEP on the Audience section. And we are going to basically create the Audience for this purpose. So in the Audience, the first thing that we normally do is basically bring the data from a specific platform that, in our case, is going to be the website, the chatbot, and also the application. We for sure need to ensure that the user that is going to be contacted have the consent. And we just set the rule of the birthday day to be like a constantly reuse month-by-month. And this is the way, basically, the communication looks like for that user, and where we just are going to see the coupon that I sell on the Adobe Commerce, on the communication, and the communication itself in a email format that we normally send the user at the month of its birthday. And this is how the push notification looks like. It's pretty much the same. It's a shorter communication, but this is the other channel that we normally use to contact the user for this purpose. And this is the way the user actually redeem the coupon for these purposes. At the end, it's going to be the same that you already saw in the previous slides.
In the complex use cases, we are going to see a very quick video. Not that quick, but we were trying to do it quick. That is how actually we enable our CRM strategy or our CRM Point One. That is the name that we provide to the first strategy into basically AEP and AJO. But the most important thing that you are going to see here is, how actually we can work with disclosures before different audiences. Because at the end, we don't want to, like, same communication to the same user because maybe at some point belongs to the different segment, but the platform actually was not able to identify. So that's why we are using the exceptions inside of the AJO. So first, we are going to create the goals segment. So the first thing we actually do is, again, drag and drop our experience that is the platform where the data comes from. We are putting the tree platform. Then we select the country, because you know that N to Y is just for Mexico.
And you can search the country code. Just select the country. And after that, coming from the events, we are going to put the back office data. That in this case, the variables in the order play just to say user with purchase. And with purchase in the last 30 days, just to ensure that actually the audience is going to be creating the right way. And for the goal segment that at the end the user that actually purchase with a high average order value, we just put that the order needs to be higher or greater than 300 pesos, or 280 pesos, sorry, in this case.
We normally, in this CRM strategy, have segment per bottler. So in this case, we need to use this variable. But it could be any other variable or segmentation variable for you.
And with that, normally we just put the description with a naming convention for sure because we have a lot of teams involved on working in the platform. And also we need to put a description because at the end sometimes the name is not self explanatory. So we need to be sure that anyone on the platform or that interact with the platform has the definition and the context of the audience, in case that a specific team wants to use this audience for any other purposes, right? Then let's create a silver segmentation that is basically going to be the same. You are going to see that we are going to follow in the same steps on basically putting the platform from the data it's coming from. We are going to select also the country. After that, we are going to select as well, in our case, the bottler.
But we are creating this audience because we want to show you how we make this inclusion that is going to appear in a few seconds, right after we create the rule for the silver audience. The difference of both segments is that the goal is greater, the amount of the order is greater than 280 and the silver is going to be less than 280. So that's the only difference. But you are going to see, after we select the bottler, that we are going to search our gold audience, just right here.
And we are going to put the exclusion. We're going to say that I don't want actually to have the user with the condition of the gold segment, including the silver. So we are ensuring that, at the end, we're exploring and avoiding the overlapping as much as possible.
So one of the cool things that, actually, this tool has is that in real time, you just can refresh the audience. The platform is, actually, coming from two different concepts to verify that you are creating the segment in the right way, just saying that you have at least data to use but also to calculate the magnitude of the input that you are going to have with this segmentation, using these audiences specifically.
Then we go to the campaign setup. I'm going to go faster on this one. So basically, you are going to see a pre-created campaign that we have in place. But one of the things that I really want to share with you is that when you have the communication, the most important thing is that you need to associate the audience with, basically, the campaign that you are creating for just to ensure that you are going to communicate in the right way on a specific audience.
So I'm going to move faster on this one.
And after that is just enable the audience instead of the journey. So in the journey, you are going to automate the trigger. And for the gold audience, you are going to see that we send the communication. And if the user actually doesn't open the communication, two days after we are going to basically send the other communication. But also, you have a good tool in here that if you want to, like a breakdown, given one condition that you have from the commercial standpoint or just for testing standpoint, you can divide basically the half of the communications.
Given this condition, this is the way actually we are sending this communication to our CRM strategy.
Going faster to the Target, the journey analytics, that's the other case that I shared with you. We want to test two different hypotheses. The first one is if having a recommendation is better than not having any. And the other one is the location, basically, where the recommendation was going to have a better impact for the users. So this is the way the user actually saw the recommendation. I'm going to go faster because at the end this is basically the summary of the three different experiences that we test with Target. We name it the A/B/C testing, 33% each of the segmentation assigned. And we basically saw that the experience be that while displaying the recommendation just above description has a better impact for us, comparing with not having any recommendation or having the recommendation just below the description.
And basically some of the results that we got for this experimentation was, first, that having a recommendation for sure was better than not having anyone. But also because we are saying that, but having a recommendation regardless the location, we got an uplift of 50% plus on the CTR of this recommendation. But also we were seeing that, again, having the recommendation above the product description has a little higher CTR comparing with the recommendation just below.
And just to wrap up and actually provide you some takeaways and also next best for us, we are facing four challenges in the short term, right? The first one is normal that we are going to keep adding more and more data. And as Francisco what explained to you, Coco-Cola has this mixed model between offline and online data. So we are trying to see by having an understanding the online data, we are going to be able to profile better to the offline users and provide some tools to the sales force to actually provide a better recommendation when the sales from the door and present a product offered to a specific household. The other one, for sure, Media. Also, we have an analytics team that all the time are producing more and more analysis, more and more algorithms that we need to figure out how we are going to plug in and use it inside of our platform. And for sure, and this is something that we assigned in some of the sessions during this week is that experimentations. Once we have an experiment completely done, we are going to have a lot of data points to actually, let's say, fulfill some of new experiments or fulfill some of new analysis. So at the end, the output actually becomes a specific input for different purposes, right? The second one is basically enabled multiple personalization use cases. So we are going to basically have the second version of product recommendation. We are seeing some good opportunities to keep evolving this product recommendation that you saw before. The offline product recommendation, the CRM 2.0 that at the end is going to be a more personalization for our user, not just only based on the transactional data, but also using behavioral data, preference, and so on. The offer decisioning, that is one of the good tools that the real-time CDP from Adobe has.
Some use cases such as card abandonment is one of the use cases that we are going to start using, or we have in production actually, two days ago or one day ago that we had that meeting to review that. Third one, at the end, this is something that all the time you are going to face, we need to improve the data catalog. We need to improve also the metadata to ensure that the data that we are using is going to actually enable us to make a lot of use cases. And the other one is the re-consent strategy. That at the end, that this offline channel has a lot of users that, given the condition of the Mexican market, actually don't have an email. So we just have the cell phone. So we need to ensure that this user when we actually want to migrate this user into the online platform, we can actually get the consent, the marketing consent, like implementing this personalization and this strategy for those users and again provide more value to them. And the fourth one is actually how we are going to start using more channels. So the first one is let's keep the eye on the omnichannel approach. But also, the way that we are planning to basically use this is we need to use this AJO Orchestrator or automation to start using WhatsApp. WhatsApp is one of our main channels, but we need to automate a lot of processes that we are doing manually. Also, how we are going to use our application to actually reduce a lot of, let's say, expenditure that we are using in other channels, just using our channel without any additional cost. And the media channels also, how we are going to optimize this consumption.
So this work just could be done because we started to work in a different way. That we have this relationship between client, partner, agency, and so on. So when we started this work, we decided to, like, take off, let's say the legal entities for each one of the team members that we have started to work as a one single team. With the agency, with Adobe, and at the end there was a reason why we start to generate value faster than any other kind of model because at the end we have just one objective, that is enable this data architecture and start offering more personalized experience for our users as well.
And just to close, for sure, I give you a big thank you for being here, but also a big thank you for all the team that was involved from this work, that at the end could be seen as a simple work. At the end, it is a simple work, but we are providing a lot of value for our users but also internally for our different teams that are working with us. So thank you so much for being here. Any question? Happy to address.
Just before we go, a few reminders. Please do rate this session in the Adobe Summit app. Also, Experience League now has personalized profiles, so you can have discovery, build your skills, grow your network, and have our technical access to what your personal needs are. So please feel free to join, use it, and have this app. I see a few pictures, so I'll wait to pass over to the next slide.
Lastly, we're very excited to say we're going to have Adobe Commerce User Groups coming soon, probably within the next month. So this is a great opportunity for you to network with your peers, collectively problem solve, share insights and best practices, and provide ongoing education. So please do join the interest form. I'll reach out to you soon, as soon as these are launched, and it's a great way to learn from your peers and honestly just keep growing with Adobe Commerce.
And lastly but not least, in May, we're going to launch Champion applications. So if you're very passionate about Adobe Commerce and want to keep sharing your best practices and keep growing within this community, please also sign this interest form. If you're interested in one being a champion is, we have a peer-to-peer connection booth downstairs in the Pavilion. So you can talk with Champions from other solutions, hear their experience, and please join. It's an awesome program where you can accelerate your personal brand, create thought leadership opportunities, and share best practices. And we've heard a lot of very positive feedback on this program and how it has enabled them to grow their career. So thank you so much for being here and thank you once again, Francisco, Juan Pablo. That was an amazing presentation.
[Music]
