[Music] [Kimberly Leung] I'm a Product Manager at Adobe. And I focus on using AI to help marketers execute, plan, and measure their marketing investments. Recently, we just launched Mix Modeler, which helps marketers be able to measure the effectiveness of their media and then also to be able to help them to optimize their ROI. Today, I'm super ecstatic that we have Manuel Neto here, who is a thought leader in marketing and analytics from Capri Holdings. He's the Vice President of Global Analytics, and he'll be here to talk to us about his strategy in Capri and then how marketers can better equip themselves to be able to future proof their marketing strategy.

Thank you so much, Manny. [Manuel Neto] Hey, I paid her to say all the nice things about me by the way. So I'm Manuel Neto, I go by Manny, unless you're really mad at me. Then, yes, go ahead. Start with Manuel, so I can see how that relationship's going to go. I'm very pleased to be here, collaborating with this brilliant person by my side, all the content that Adobe has supported through-- And that's it. That's the end of our speech.

Well, actually, I don't need that to keep talking in the meantime. So the name of the session is actually Retail Therapy, which is one of the biggest reasons why I accepted this invitation. So particularly, there's a lot of relatability of the word therapy itself, the word therapy at work. You may be in a Zoom Call at times, and someone very intelligent says something, but the intelligence is not recognizing this planet just yet, so you mute yourself and you go scream. When in a meeting, there you just want to leave and potentially go to the bathroom and scream, all very important therapy moments. In this room, if as we go through the content, if there is relatability to that content they need to scream. You can go to the back of the room, do some scream. We're going to offer some words of support, some words of love, then we're going to come back, we're just going to pretend it never happened. I may scream a few, in fact. As part of the word therapy, we're going to ask you guys to participate. So the participation will come in the shape of raise your hand for some simple questions as well as more elaborate questions. Please participate, please engage, please talk to us. So I don't look sad up here, and it becomes a fun and dynamic conversation. Do not be mean, do not ask hard questions. I was married to an actor for 10 years. I will pass out on this floor, and I'll make it look very realistic. There's going to be ambulance involved, it's going to be ugly. So ask questions, engage, but do not be mean. And before I pass back to her, look at that. Look at me back there, photoshopped, back on the thing. Before I go there, I want to try out some of the reactions, you ask, you guys to participate by a simple raise of hands. This is one of those very few moments in this session that it's okay to lie. So if you-- Just lie. It's okay sometimes in life to do that. So raise your hand if you're excited about this session.

Some of you did not lie. That's okay. I appreciate the honesty. I'm going to try again. I'm going to shift the question a little bit. So it's going to be more life related. This one you should definitely lie. So how these big hero movies are actually changing the actors? If everything fails in analytics for me, I'm going to sign up to be the new Superman in the new movies. Normally it's a Clark Kent kind of look. So raise your hand if you feel I would suit the role as a handsome guy who could go ahead and play the role. Nice. Some of you do not raise your hands. We're going to talk after this conversation, but okay. So thank you for joining and I'll pass back to you. Thank you, Manny. So we're here today to talk about planning and measurement. And I think we can all agree that having an effective planning and measurement process is integral to having a successful marketing business and a successful brand. However, marketing, planning, and measurement is hard. It has historically been hard for several reasons. Some reasons here that I've listed and there's more than this, but some of them are that data typically is scattered around different systems and platforms, right? There's just so many platforms where consumers are interacting with and that data across these platforms is really hard to collect into one place for a comprehensive view. Oftentimes, the data that comes out of these platforms have varying granularities, quality, and it is not consistent. Other aspects are, it's very manual and time consuming historically to setup the data into a view and then also being able to get reporting out of it, that is actionable, which then results, unfortunately, into organizations, not being able to make data driven decisions, wasting resources, and then having difficulty to align with the different stakeholders in the organization. I think this has been shown in many, many surveys and many research that, the most difficult thing for marketers right now is to be able to prove ROI with analytics. So, Manny, what have been the top challenges for your marketing organization? And can you tell me more about how you're thinking about prioritizing them? I can. I'm going to seek for help from someone from the audience first. Who is comfortable to help me understand the top two challenges before I build on top of it? Raise your hand if you'd like to answer that question first.

No? Am I going to have to volunteer someone? I have coworkers in the room that I may have to actually bring up.

So-- Okay. So we are actually on a last touch attribution channel today. What that creates for us is an inability to understand and unpack the entire consumer audience, which by consequence is creating, is doing a disservice to main KPIs, such as the return of investment KPIs, as well as the conversion KPIs. So in addition to that, it's creating a lag during site. So because we are, consciously, part of the last touch for now, which hopefully, if I don't mix model, we're going to change that reality. We also sometimes misattribute where the audience is actually engaging the most and where they're participating the most. So what's really creating is a self-fulfilling prophecy where we are aware of our limitations from a data perspective as it stands today. That is creating, doing a disservice to metrics are important for the marketing alignment and the marketing optimizations, and then by consequence, creating a lag for us to change that dynamic and optimize against it. That's changing. There's more to come, but for now, yes. I would also-- So the number one that they see on that slide is basically that. It becomes harder for us to then showcase that the ROI is actually working, and a combo of limitation of our attribution model as well as limitations of technology that we're working to develop. It's creating challenging times to have that ROI analytics. Also if my boss is watching, I want to say that inability to implement my ideas is a big thing that's been happening this day. So that's been something I want to put that. But also, because of our last touch model, we are struggling to make long-term decision-making process. So it's very short term focused and lacking that ability to expand into more long-term visibility. Gotcha. So there are a couple of challenges that you've discussed. Here's another survey I have around Forrester. And one of, like, the priorities of, I think CMOs across the business, what they're trying to solve. So for you, what would be the top priority? I would say, yep, those are exactly the ones. I would say the inconsistency level amongst data sources because what started happening is, because of the model that we sit today, a lot of the groups, rightfully so, went ahead to create their own solutions. So by consequence, that creates a lot of, sometimes, single source of truth. And I'm not saying they're wrong, nor they're right, but I'm saying is that creating fragmented decision making. So it's developing that inconsistency on the decision as well as inconsistency of the quality when you bring all of those sources together.

Connects well, if too many unconnected data sources as well as the inability to link insights to specific customer. So that's a combo that we're seeing from the lack of the multi-touch, medium mix, modeling attribution, but also from the previously advances that we continue to see coming, particularly to North America. And then because people are driving some of their own decisions, their own technology, it's creating conflicting analysis when you have too many models. And, again, I'm not saying they're wrong. I'm just saying that they are individually true. So when you bring that truth together to demote for different sources, it creates that conflict automatically. That totally makes sense. And I can see that besides all this, even market challenges are not easy for us to solve. Like, all the privacy changes have really accelerated signal loss recently and all the changes across Apple and ITP, Google, and Privacy Sandbox. You can see how a consumer journey is now barely trackable, right, at a user level, where, now we have to think about new solutions to be able to deal with this. So, Manny, what do you think about the current kind of market? And then what do you think would be the future of privacy? Yes. Let me ask the audience for a simple raise of hands. Who here works with marketing? You're making decisions on a marketing level perspective. Awesome. So how many of you are losing sleep or concern about any previous rules impacting you? I love, I haven't even finished the question, so people are like, okay, we can go in the corner and cry together if we need to. So in similar fashion, so I should start by saying, as a global role, I've had an advantage to look at our global markets where the privacy rules such as EMEA, the European markets and potentially the Asian markets, they have been more structured and strict for a longer time. So in those markets, for example, there are instances where we are losing visibility up to 50% of the audience. So imagine 50% of the time you're not really able to tell the trackability and the efficiency of some of those journeys that we're getting through a website. So what it has enabled us to do, however, is also create a road map of understanding impact overtime by leveraging these learnings from the European market and trying to see how that's going to happen, particularly as the US start embracing some of those. What is going to happen for us, we already are doing is, the inability or the more difficult times to create that one-on-one interaction in measurement, as well as the trackability of that measurement, right? So it's limiting our ability to journey, which by consequence is going to impact a lot of the conversion metrics as well as the ROI kind of metrics. All metrics are finance and our CFOs. And basically, when you're looking for budgetary approvals, that's still what they're going to be focusing on. So it is limiting us. We are going to be talking a little bit about how we're changing some of that, but in short, we are losing a lot of trackability with the advantage of looking at the European markets and Asian markets to learn what they suffer potentially two or three years ago. Gotcha. And so I think I have kind of a shameless plug here, but mix modeler has been thinking about this. And we started with this problem as the forefront of what we're trying to solve when we were developing the product. And when we were doing research with our customers, I think we know that from the past, typically, most of the digital marketing was trackable, right? And then there's, like, maybe 50% or less of the spent that is in offline channels or offline stores that's not trackable, that did require MMM. But now given the progress of cookie deprecation, this is looking more like a lot of the marketing spend that is through Walled Gardens is now also not trackable. And maybe 35% of marketing spend can still use maybe multi-touch attribution to quantify those kind of marketing investments, but then the rest of it needs to lean on marketing mix modeling techniques or maybe, like, renewed techniques of marketing mix modeling.

Furthermore, we've only had maybe, like Chrome is like 1% deprecated in terms of cookies. But by the end of this year, it'll be 100%. And I think what we're seeing probably is that, maybe only first-party channels will be able to be measured with multi-touch attribution, and then the lion's share of media will have to use some kind of technology or AI that looks at aggregate data, like marketing mix modeling, to be able to figure out the contributions. So this is all the research and kind of user research and, that we've done in mix modeler that we've-- But then I was wondering, Manny, if you can give us an example of the implications that have happened in Capri and your various brands like Jimmy Choo's, Michael Kors. What has those implications been with that cookie deprecation? Yes. I should also use a time here to say, we were one of the very first ones to be able to be part of the pilot, and it's been absolutely fantastic. So thank you to the Adobe team. They did not tell me to say that, by the way I'm saying this out of full will. And then we've been joining. We're partnering really closely for the mix modeler. So it's going exactly that. It's-- We are very aware of the-- We're actually in an even worse scenario as it stands today because we are in a last touch attribution. So we can't even see this beautiful universe until we partner really closely to have this Adobe Mix Modeler in house. And our goal is to, how can we start enabling-- Something's happening with microphone. Enabling all of these signals to essentially come together and start already preparing for what's about to get a little bit more difficult, from a scenario of tracking. So we are also already thinking through what's the fiscal as well as financial impact of those deprecations, but then augmenting those deprecations by launching a new technology for us, like the media mix modeling and the MT, we're actually embracing the mix modeler as well as, bringing a customer centric approach. So for example, in the country that we know we're losing 50% visibility, we want to make sure that, that visibility does not translate into visibility of, loss of revenue. So a year ago, in partnership with enhancing our, literally technology as well as our modeling through mix modeler, we also launched what is called a Research Lab. So Research Lab is started in North America. We spoke to 30,000 segmented audiences, talking to consumers and bringing the consumer to the center of that, participating in the products development, in the campaigns and whatnot. And we expanded to nine countries. And by end of month, we're going to be in 12 countries. And the goal is that, as some of these countries are losing some of trackability, we're augmenting with mix modeler, we're augmenting with MTA, we're also bringing the consumer to ask them, hey, if you could launch products A versus products B, which one would you go with? If you could buy product a bag blue versus bag yellow, which one would you buy? And then incorporating that in our part of development from products all the way into production. Gotcha. And while balancing that, how are you thinking about being able to still demonstrate ROI while keeping the customer in the center of your focus? - I'm hoping this helps. - Yeah. No. So we shifting some of those KPIs because moving from last touch attribution to a medium mix modeler, multi-attribution is huge, but it's really starting to look at the journey not in isolation or as a one single point and how are those audiences connecting across throughout, but also bringing that qualitative feedback back. That makes a lot of sense.

So we know that besides marketing touchpoints and investments, there's also, like, business factors that typically impact a business outcome.

Mix Modeler is coming out with a new feature that will help marketers understand the impact of business factors on their outcomes as well as being able to just have an out of the box easy UI to be able to select factors that impact your specific business vertical and for you to upload kind of projected factors into planning, scenario planning, and forecasting, so you can get more insights into the future. So I guess, Manny, for Capri or your different brands and your different regions, what are the key factors that impact your business? You all stopped buying luxury bags. What happened, guys? So, yes. So there was a big shift, in the industry for us, particularly post COVID, as we started competing not only with our main competitors from a luxury perspective, but also, we started competing for experiences in general. So the consumer mindset for us shifted from, hey, I can spend x amount in this luxury item, this luxury bag, brand agnostic from Versace, Michael Kors, or Jimmy Choo, or I can also go on a trip. So they started valuing experiences differently, which automatically created a whole new universe of competition for us beyond just our direct competitors of luxury industry. So we have been taking care of that as well. We have been through personalization and understanding. What are the experiences that the consumer and our targeted audience started shifting towards? So that instead of considering them, suddenly a whole new world of competition, can we partner with them? Can we offer a joint experience? Or can we bring elements of that experience to the journey of our consumers? So if I know now that my consumer loves Facebook, they love to travel to beaches and they're all blue waters and they love blue bags, can I personalize when they land on my page to replicate some of that experience, so that they feel welcomed, they feel talked to, and the time to purchase, the time to funnel diminishes? The economy also is impacting us quite significantly. So in the luxury industry in general, there's been a decline across every single brand of double digits. So we are actually in a good spot, but it is actually happening, the luxury industry in general. So it's kind of two opportunities there. One is the experiences themselves, the consumer shift in their mindset, but also the economy as it stands today. This is one of the things I'm most excited about because a lot of these things that I have to bring in my work routine is leverage a lot of external elements to say, hey, here's in addition to this dip, which it is caused by potentially a lack of interest on our products and here's our opportunity to change that. I also have to consistently bring in, but here's how the industry looks like. So it's very common to have slides that are followed by, here's the industry trends, here are the business fact-- Look at me trying to adapt the words already. Business factors that are particularly potentially contributing in addition to what else we can change, and we can move. Gotcha. That makes a lot of sense. I guess switching gears to a more kind of strategic aspect, I would love to, like, understand better from your perspective, like, how you're leading your team and your organization.

What is the North Star process that you're trying to get to? Yes. So we actually have a slide. It's not as cute as her slides because this was the one I made. So that you can see the dip in quality because it's me. It's still very cute. Everyone. So I'm going to be talking for a second, so bear with me. But yeah. So what I try to do here is consolidate the things that have been successful with Capri in particular, but also in previous lives experiences. So the one that I start with is the alignment amongst leaders, and I particularly chose the word start with on purpose. But do you have alignment across all the leadership level of, hey, we need to move this technology. We need to move to this new approach. We need to change the methodology of the way we've been looking at things. And I say this as I'm living this at the moment. The company has been doing large distribution for as long as it existed. So to get the buy in that will require significant change. Hey, we're looking to things now from a mix modeler, from a mix modeler perspective, as well as an MTA perspective, that's automatically going to shift KPIs. It's automatically going to shift attribution. It's automatically going to shift budget and the return of and conversion as well as metrics. So getting that high level alignment of leadership and helping them understand what that's going to mean in the months to come or years to come, depending on how you are in your data literacy journey, has been very important. I did say I start with the leadership planning because what I'm very lucky with is that, when I joined Capri, I-- It was very tangible to feel how hungry everybody was for data. So once the leaders were aligned and it was easy, honestly, to get everybody on board. It was creating a roadmap to cascade that information down to the most junior level. Because sometimes, and that was a mistake I committed early in my career. I thought that's because leaders were aligned, it was everything was fine. That's not reality. Sometimes the leaders are not the power users of that information or the power, the people who are actually extracting those discoveries. So creating alignment that is, yes, starts leadership, so there's no conflicting priorities or conflicting understanding and then cascading that down to the most junior level has been crucial. What it has translated for us, we are an Adobe partner, as you know. We use Adobe analytics. We have over 6,500 reports that are created by users in our platforms. So it shows the power of, really, that people are going in. And I say 6,500, you may be asking, my God, there's five of the same. Actually, no. We do a purge every year. We just kicked off their process where we actually eliminate our repulses that are duplicative, and we actually also purge the people who haven't access Adobe Analytics in the last five months. So it is active reports that people are utilizing across the organization, across all three brands, which shows the power of-- Once you're aligned on having a goal, of having a data center, of changing the universe, and people are embracing it, make sure it's cascading across all levels. I use the word being ready a lot here, because it leads me to the enablement of a data culture. And that has been the hugest learn for me, particularly with Capri. So data culture, is both challenging but very rewarding. So discoveries are great. And if your teams are empowered to make those discoveries, what it ultimately means is that your teams, your peers, your colleagues, they will be finding things that are going to be game changing but very uncomfortable. So there is a sentence that I've been, I've read in a book once and I've been very attached to it, but basically goes like, the power of a discovery is only as valuable as the action that it drives. And the action that sometimes it drives, also need, is going to face resistance, is going to face acceptance. So how do you minimize that resistance, and how do you increase that acceptance? And as humans, we are much more towards the resistance. And sometimes a discovery, an insight, it will lead to a change, and we're going to be not wanting that change. If it changes processes, it's natural behavior to just not want that change. So data culture is changing that behavior, is welcoming more of the hang-on. You're challenging the blue versus yellow bag. So I've been buying a blue bag for the last six months, but the new insight's showing me that the yellow is the way to go. And that insight's coming from data. Are you ready to make that change, that you need to move the yellow bag? Is the culture feeling safe enough to challenge regardless of level that they're feeling empowered, they're feeling safe to go to their bosses, to their peers and say, hey, I think the yellow bag would make more sense based on the accurate data that I'm being receiving because it is clean, it is giving that power to them. So data culture really comes to-- Do they understand to how to drive the focus? Do they understand how to create that safe environment where any of us and all of us are feeling safe enough to leverage data to drive that change? And change is not seen as, this big monster, but rather an opportunity that could be a competitive edge. It could be the differential that's driving you further ahead. It could be what's driving that innovation for you. And what I've found a lot is that, that data culture change is a huge enabler of the powerful information that we may unlock. Otherwise, the analytics teams like myself and your peers, they may come in and bring all these tools of this technology. But if no one is leveraging the actions and the insights, the stories that discovers the technology is driving, it's not going to make a difference. And sometimes, what happens with this data culture is-- If you're enabling that correctly, if you're enabling the alignment, if you're creating process that are driving that change, you are then creating parallel process, which is, I call it democratization of intelligence as well as empowerment to drive actionability and they can happen in parallel. I purposely chose the word intelligence because, everybody, and I was again lucky, but everybody at Capri was very data, they embrace data, which is good and bad. So, but data is just a bunch of numbers together, that if you don't extract that discovery, that insight, that intelligence out of it, you're also going to have multiple levels of interpretation. So whilst making sure that everybody has access to the level of information that they need, the way they need, with the relevant topic that they need. So I'm going to feed my planning team, my creative team, my marketing team, my commerce team, who's in the room, they're amazing, shout out to them. Actually different levels of data with different slices of data. So I'm democratizing access to that information. But in addition to that, I also need to make sure that across all these teams, if I'm truly enabling data culture, I need to democratize intelligence. For some time, the discovery that may come from marketing, we should go for the yellow bags or the blue bag. They will not only impact marketing. For marketing, should be able to drive that change. My ecommerce team has to say, okay, I need to change my entire digital landscape to reflect the yellow bag. In addition to that, I also need to make sure that, the production is changing the buying of the material to now produce more of the yellow bags. And so that cascade down. So by creating a datacenter, by making it accessible, make it easy, you don't need to have analyst title today to interpret data. I think that's aspects of a lot of the new roles or the roles there are today. But you're helping create the accessibility in addition to, also making it relevant and making it easy and helping by creating the intelligence that the organization, the company would be governed by. Last but not least, and again they can happen sometimes in parallel, is the empowerment to drive actionability. I think I was saying earlier that the power of a discovery, it can just go as far as the resistance or the action that it drives. If you find something amazing, I discovered the yellow bag does not sell as much more than the blue bag, but you're not driving that actionability to actually stop building the blue bag or selling the blue bag, it goes nowhere. And sometimes what happens with big corporations in particular is that, to drive that change from the blue bag approach, the yellow bag approach, it could take months. So you're going to have to talk to my planning team, to my buying team. So the actionability empowerment is very weak. And that was something that we had to reevaluate within Capri is, are we ready to be able to drive the actionability of Fino process? And our discoveries actually show that some of the processes were taken, even though we had tangible, real, accurate data, our actionability timeframe was taking three to six months to execute. Three to six months of continue to build a blue bag, that, I'm using quotation marks in the air just for the people who are recording. Continue to build a blue bag that is not selling is basically saying, I'm aware that this bag is not selling. I know that I'm losing money on this bag, but I'll continue to build it because my process takes too long to shift the yellow bag that the data is showing me. So the empowerment of directionability is actually, are we ready to absorb real-time data? Are we ready to be driving that change across the organization? And how many of you here hear the word real-time data? Raise your hands if real-time data has been sent the last month in your roles, right. And I always question back, like, is your company ready? Are your teams ready to drive real-time action? Because if you're not ready to drive real-time actionability, then real-time data is just more data that becomes more and more information in your hands that is not being derived upon. So-- And most importantly-- So in addition to having the right power to drive that change and, like, three months or six months of our own org taking to drive decision, that's wild. Imagine bringing that to market. We lost the opportunity. The accountability of using information. So the enablement of a data culture will essentially also include that, hey, the accountability of leveraging information is not only with Manny's team, right, the data guy. Everybody should be leveraging that information. But, and I realized that they will be using that information more when they feel empowered, and they're also held accountable. And I'm not saying, go point, your hands and say, did you use data? No. But you can ask, have you validated this approach? Have you considered if we go this different direction? So it became a lot of, a question and learn opportunity. We partnered with a lot of teams to drive A/B tests as well to literally start asking those questions of them. Hey, you have this information. What happens if you try this other one? And let's go back to data. Do we have data? Do we don't? We're bringing fillings of data. So this has worked quite well thus far. Gotcha. I think a lot of customers I've talked to, they've had challenges with kind of getting buy-in from leadership. So in your case, how did-- Would you be able to share an example of how you got buy-in with your peers and the leadership team that you're in? Some of my bosses are still locked in my basement at this stage.

- Okay. - No. So, I think it's-- With Capri in particular, it was twofold. One, it was easy enough that people were hungry for that information. So the resistance to the buy-in was not as big. And for particular brands, yes. But it was the-- Here's how much further we could go if we were to do these changes. So particularly moving from a last touch attribution to a media mix modeling, attribution model and bringing this innovative technology. We're launching heat maps. We're launching, research lab. We launched research labs. It was a lot of new things to bring to them. And, in every single aspect of the new innovations that we brought, I call innovation role, there's, like five major projects where Adobe mix model sits in one of them. It was ensuring that they understood the impact financially, organizationally, and also go talk to every single team before even reaching to them. So before I go talk to my CEO, who I report to, go talk to all my partners at ecommerce and marketing, at planning, and, like, hey, what does it unlock for you? Get that insights of, it's going to help you do this, create their road show of opportunity, and then bring it to my bosses and say, here's an addition to the financial value that the models can elaborate for us, the new technology. Here's also how the organization can move forward much faster. You're gaining efficiencies here and there. And it has worked. And they're also in the basement. That is okay.

So I guess, I am very kind of curious. How do you see mix modeler and, I guess, AI and technology in general would play a role in your North Star process? I'm going to talk about-- Oops. So I think the next slide shows some of that. Yes. So what it has enabled us to do. Again, we've been very lucky to be part of the early stages of a couple of opportunities with Mix Modeler and it's already developing that, centralized universe that leaders are able to go in and see the opportunity. So the ability to centralize information and enhance and literally transform our company from last touch into media mix modeling and multi-touch. That in itself is huge. In addition to that, it has created that unified place that they can go in, and they can also extract the level of information they need. So it has created the empowerment to drive the alignment between leaders because they can see the results and it's tangible in their hands. It has stopped my enabler of a data culture because by creating that empowerment that came for the alignment, it's also giving the democratization and the enablement of a data culture. They're going really close together because any team is able to go in and develop their own models and get validation on those models and then come back to us and say, how can I partner with you to create that intelligence on top of it? So for us, it was crucial because it's a perfect brilliance between the technology meets the expertise. And just so you guys know, we have our, we RFP'd over 12 partners that could, even though Adobe was our partner. There were over 12 RFPs that we put out there to essentially partner with us. It's a huge transformational change for three brands, iconic brands to go for last touch to multi touch. And we selected few and few, and few and then essentially partner with you guys to make this happen. So, and it has enabled that culture of change of transformation because we're not, we are doing our best democratizing information which your tool, your technology has enabled. And again we keep forgetting sometimes that organizations with actualability will go nowhere. So the scenario plan-- There is a scenario planning. Maybe I'm spilling some of the beans, but there is a very cool scenario plan that allow us to also go in and look into here's what could happen if you did this or if you do that, if you move the budget here, if you move the budget that. And for us, that also has been very transformation. So it's helping us drive that actionability empowerment. I will say, I'll be talking, after this speak too because I've been on a lot of sessions, and I also want to start using some of your Helper AI. Yes, very exciting. And again, very lucky to be part of this journey with you guys. - So thank you for that. - Yeah. We're honored to have you and your team working with us as well. It's been a great learning experience and also being able to just develop hand-in-hand with your team. So I would love to kind of, I guess, ask you, Manny, for, like, the key takeaways here for the audience here. What is the key to future proofing and being successful in measurement? Sure. First of them is vote for me if I ever decide to become an actor in a superhero movie. But-- So I think 10, 15 years ago, there was a buzzword, which is, we need big data, we need big data, and we got lots of data. So often at Capri in particular, our opportunity wasn't or challenge, whatever word you prefer. It wasn't that we didn't have the data. It was that we had too much data that was either organized or was not structured correctly or was living in isolation. So the evolution of, if you do have that lots of data, find that single source of truth, find the location where it's going to be democratized, everyone is going to have access to, but you develop, you're moving from just a bunch of data, different systems, and you're creating intelligence on top of it. So evolving particularly of Capri, from here's data to here's intelligence, an intelligence that's accessible for everybody, intelligence that's easy and relevant, because if you're creative, potentially you don't worry as much as the planning team. You have access to that as well, but your focus would be creative. So make it democratized, make it relevant, and make it intelligent. So help create that intelligence in top, on top of your data. The leadership alignment, again, I think it shouldn't be news for any of us. Make sure that the leaders are onboard with that, avoiding that conflict. But most important, that enablement of-- The alignment happening at the top is also happening all across. The importance of an insight coming from a junior person is as equal and as big as the importance of an insight coming from a VP. It just really matters on how you're challenging that and how you're embracing that and how you're driving change and actionability on top of that. So when you have the data culture, that safe environment, everybody has access to the data, correct, clean, accurate, then if I find out that yelling matters more, or my junior person, the insight's the same. So how you create that safe environment that enable that changes, most importantly, you're acting on top of that change. And then the technology. So in similar fashion, when everyone was talking about big data, a lot of technology boom happened. And today, there is a lot of technology out there, which is fantastic. You have options, but make sure that you don't get overwhelmed by an ad tech stack. So not ashamed to say that we had 77 partners when I joined. A lot of them doing duplicative work, some of which were on P&Ls that were never used in the last two years. So doing a cleanup of some of that was part of the process, and selecting the ones where-- And it could be what I call Frank's Time Approach, where some of the partners will offer X, the other will be better at Z, that's okay. But knowing who your right partners are, of course, I had to put the plug of mix modeler idea. That was my choice by the way to add it there. So they're coming together not only as technology providers. There are a lot of great companies out there. They're coming together as partners. I actually eliminate the word vendor from my vocabulary a lot. I use the word partners because we're all trying to do good money, do good work, and do fantastic things together. So partners are my favorite word. So having those right partners with the right tools, not only technology, there are tools on top of the technology, has been key for us. I told you we did a humongous transformational event and it's all launched in the same time, so that has been crucial for us. And then, reactive decision making, part of it driven by how we were setup, part of it driven by the lack of the culture that enables the decision-making process being much faster. So I always like to finish with, make sure you are, you're not your own enemy, that you have all the right tools, you have the alignment, you have the right partners, but you have decision paralysis or actionability paralysis because your own company takes six months to make a change between, potentially, the blue to the yellow. So how can you make sure that you're driving actionability, you're empowering every single person to drive actionability, and you're doing that timely, so that you're not losing your biggest competitive advantage? I should say if you're competing against Versace, Dimitri, and Michael Kors, yes, you can lose your competitive advantage, no problem. But if you're doing, just you're taking keeping that on top of mind. Gotcha. Well, thank you so much. - Thank you. - For going through this with us. [Music]