[Music] [Lory Mishra] All right. Welcome to Session 507. Hopefully, you're in the right place. We're going to talk about data collaboration and share a really awesome success story with Alterra, 85SIXTY, and NBCUniversal. And we know we're definitely between you and happy hours and a lot of fun, but I promise it's going to be a great session, and we want to leave you with some actionable next steps so that you can think about data collaboration for your business. Before we get into the content for today, can I get a quick show of hands of who has tried a clean room or a data collaboration solution or is thinking about it? Okay. Okay. Great. Awesome. So the thing to keep in mind is even if you didn't raise your hand today, some form of data collaboration is probably happening at your organization. It could be your partnerships team that does co-marketing with the brand partners that you work with. Maybe it's your media buyers who have direct buying relationships with some of the publishers that you work with. So for the context of today, we're going to focus on data collaboration for marketing and specifically the opportunity for brands to work with publishers to collaborate and drive better results for paid media. So better audience targeting and better measurement after you run a campaign. So we'll work to leave you with a few key takeaways at the end of this session. We're going to talk to you about why data collaboration should be a strategic lever as part of your larger audience strategy. We'll talk to you about the opportunity for data collaboration in the Connected TV space specifically, which is one of the fastest growing channels today. Mike from NBCU is going to cover that. Then Miriam and Kevin are going to come up and talk to you about how they executed a collaboration with NBCUniversal for Alterra and drove business value and drove real business outcomes for a key campaign. And then I mentioned, we'll leave you with some recommendations and ideas if you want to adopt collaboration for your business. So just, to do a quick run of intros, I'm Lory Mishra, Product Marketing for Adobe Real-Time CDP and Real-Time CDP Collaboration. And then I'll let my co-presenters, who I'm really excited to have with me here, behind me here, introduce themselves. [Michael Levin] Hi, everyone. My name is Mike Levin. I'm Vice President of Advanced Products and Activation at NBC. I oversee our suite of audience targeting capabilities and the infrastructure that sits behind it. I've been at NBC this round, I'll get into where I was before for seven years. Prior to that, I worked at a few other companies, but a little bit of trivia. I started as an NBC page. So if anyone is in New York and wants a tour, I don't know that I'm allowed to do it, but I'm happy to help out. Before I know this is my introduction, but I did want to recognize some of the folks in the crowd who helped collaborate and make this possible on the NBC side. So James, Taylor, Stefan, all part of our products group. - So thanks. - Awesome. [Miriam Schachtman] Hi, everyone. I'm Miriam Schachtman, Director of Digital Marketing at Alterra Mountain Company, home of the Ikon Pass. I'm incredibly fortunate to have been with the company since its formation, being able to build my team from the ground up and oversee all the Adobe implementations and use cases. I've worked in the leisure tourism hospitality and travel vertical under the digital umbrella for the entirety of my career, overseeing many a change in technologies. So I couldn't be more excited to share our story with you today.
[Kevin Day] And I'm Kevin Day, the Associate Director of Digital Solutions at 85SIXTY. Been working in advertising for about 18 years now. But for the last eight years, been focused more on the MarTech implementation and utilization both on client and agency side. Awesome. So what you're hearing in our speakers' introductions, hopefully, is what you're going to hear in the session today. You'll hear the Adobe perspective on where things are going and where we believe things should evolve into. Then you'll hear the publisher perspective, in terms of the opportunity to showcase the best audiences and first-party data for advertisers. And then you'll hear the brand and agency perspective in terms of how they can tap into that first-party data to drive better media and drive better outcomes. But before we get into all of that, I'm going to take a quick step back and look at how we got here. So I myself have been in digital marketing in some fashion since 2010 when someone at a party offered me a job building links. So I did that for a long time. And one thing that has been true, and is just truer and true every year is finding, growing, and measuring the impact of the right audiences for our businesses is harder than ever. And it's hard because of some of the reasons that you see on the slide there, right? As an industry, we've been dealing with signal loss in some form or fashion for a few years. We live in the cookie-ish future now, but even though cookies are around and even while they were around in full force, there were never really the best way to reach the right people that you needed to for your business. On top of that, we are dealing with data privacy as a force. That is both an expectation from consumers, right? That the data you have on them is collected with good reason and that it is being used appropriately. And then also from a regulator's perspective, that pressure on businesses is not going away anytime soon. And then lastly, of course, given these forces, it's no surprise that there is a lot of complicated technology promising, but complicated technology that's available to try to help us solve this problem of finding and reaching the right people. And what that really means is especially if you're responsible for MarTech or IT at your organization, is that's maybe more vendors for you to keep track of, more integrations for you to manage, and maintain for your business.
But one of the best things about being in this industry is we're a pretty resilient bunch, right? We come to Adobe Summit every year. We leave with great ideas of better and new ways of doing things. So when we talk to some of our customers at Adobe, Real-Time CDP customers or otherwise. The folks that are ahead of the curve are doing a few things that are really standing out to us as the things to be thinking about, right? If you're trying to figure out like, where do I go from here to make sure I'm talking to the right people? The first trend is not going to be a surprise given it's a CDP session is first-party data. We ran a study last year, and what we learned is that 78% of companies that we surveyed said that they already had a CDP, and over half of them are already using that CDP to activate first-party data. That trend is not, of course, not going to go away anytime soon, right? Because there's no replacement for having a trusted relationship with your customer versus trying to maybe guess who they are and give them the offer that you think that they want. The second trend here related to first-party data is data collaboration, which is what we're going to dig into today. So what is the other great first-party data that your partners have, that your publishers have, that the other brands that you work with have, that you can tap into? In a study that Forrester did a few months ago, what they found is that 59% of organizations are looking to collaborate with other organizations that have more first-party data than they do. And 43% are looking to partner with organizations that have different first-party data than they do. So put simply, who do you know that I know so I can talk to them better because now I have more signals? And who do you know that I don't know that maybe I should get to know, right? So that's the opportunity that we're seeing with data collaboration, first-party data. And then to solve this, there is new technology that's emerging in the form of data clean rooms, which seems like about maybe half the audience has done something with clean rooms in the recent past. So 66% of folks that IAB surveyed a little while ago said that, data and ad professionals said that they have started to adopt clean rooms in some form or fashion to deal with the pressures of privacy regulations and signal loss.
And this makes a lot of sense. Data clean rooms especially for those folks who have tried it, are pretty promising technology, right? Because what they're bringing to marketers and businesses in a marketing context is the promise of privacy-preserving technology, so you can tap into those insights that others have about customers that you want to engage without exposing the underlying customer data to each other. And that, from a business perspective, allows you to unlock things like new insights, helps you build better audiences, helps you think about the right channels to engage your audiences, and start to connect the dots across the customer journey that may be missing because of signal loss.
And just to click into this a little bit further, specifically what they bring to the table is a couple different things. The first is the ability to obfuscate data. So to call yourself a clean room in any form or fashion, you have to be able to provide aggregate insights that don't expose who a individual person is that might be in an audience. So that's table stakes, and that's given. So there's really great privacy-preserving technologies that have evolved over the last few years that many of you may be familiar with that allow data clean room vendors to offer this.
The second is, controlling the movement of data, right? In the last few years, I think we've all heard the term zero data copy, minimizing data movement. It makes a ton of sense from a privacy perspective, right? It doesn't feel great to be shipping one of your most valuable assets in first-party data across systems and worrying about what's happening with that data. So data clean rooms have the ability to reduce the movement of data, assuming both parties are utilizing the same infrastructure.
And the third thing that they bring is protection of your proprietary data, related to the last point that I just made. So if you are, say, a brand and you're working with somebody to run a campaign and you want to run a measurement report, it doesn't feel great to have to ship your entire universe of conversion data or measurement data for a certain period. Ideally, you're only shipping over what you exactly need to, and utilizing that in a clean room. Because, hopefully, when you do ship data over, they're using it the right way, but you don't know, for sure. So clean rooms have evolved to help with that challenge as well.
So this tech is super promising, and we're going to talk to you about how Adobe's thinking about it with Real-Time CDP Collaboration. But in talking to our customers and listening to the market and the surveys and such that we have done, it became clear that while there's a ton of opportunity, it's not all roses. There's a lot of challenges that our customers come across when they're trying to scale data collaboration from a super cool science experiment that's happening in one part of your company to a real part of your holistic customer data strategy. And no shade, by the way, I won the science fair in seventh grade, so love science. So the things that keep coming up for our customers when we talk about what's challenging, why isn't this part of your holistic data strategy? It always starts with-- It's disconnected from everything else I'm doing. I'm often having to spin up a data clean room that sits separately from where I manage the rest of my customer data. So what that means is, A, from a tech perspective, that's annoying. You have to now maintain a totally separate thing. B, from a customer perspective, you're serving your customer a pretty disjointed experience, right? Maybe you're doing some upper funnel acquisition with publishers using a clean room, but maybe the rest of your activation is happening through a CDP. So you lose track of who saw what, at what point, and then what ultimately led them to become a customer of mine. The second thing that is a challenge for a lot of our customer in terms of scaling this is data collaboration today is slow, and it's complicated to use for a marketing use case. So it often requires folks with technical chops who have a lot on their plate, so you might need to know how to write a SQL query, or you might need to know a guy who knows how to write a SQL query to get the insights that you need to run a campaign. And if you think about it from a marketing and our advertising perspective, having to wait a couple of days or maybe weeks to get what you need means you're probably missing out on engaging your audiences in moments that mattered, as part of their journey with you. The third thing that comes up with our customers that gets in the way of scaling this is limited interoperability. And what I mean by that word is, as much as we wish, all companies will never be on the same cloud. Everyone's not going to work with the same data partner. Everyone's not going to work with the same identity partner. That makes sense. There's different options in the market depending on your business objectives. But from a collaboration perspective, what becomes challenging is that incongruous tech stack that two parties might be coming into a collaboration with gets in the way, and ultimately probably means that someone has to move their data, which brings me to my fourth point, is you're opening up maybe some risk of data leakage here, right? Because you're moving data, and you're involving your legal teams, your privacy teams, and security teams, and of course, that delays any interesting marketing and advertising that you might be trying to do.
So this is all of the context that we took into account. This is all of the market feedback at Adobe that we took into account. And last Summit, we announced Real-Time CDP Collaboration, which actually just became generally available in the US market, as of a month ago. So with this solution, what we're bringing to market is a no-code, radically simple, interoperable, and privacy-centric data collaboration solution. This is built right into the Adobe CDP, but the good news is to really pay off that value of interoperability, it doesn't matter if you're not a CDP customer. So if you have your data residing in a data warehouse, in a separate cloud storage environment, we have the ability to accommodate brands, publishers, brands and other brands who want to work with each other to bring their data into a common format and execute business use cases to discover, activate, and measure audiences. So in this environment, what you'll be able to do is execute overlaps, you'll be able to expand that with identity or data partners that you want to work with, activate those audiences to channels like Connected TV, which Mike will talk to you about in a second, retail media networks, eventually DSPs, and then close the loop by measuring the impact of the campaigns that you ran.
And all of this, again, you can't call yourself a collaboration solution if you don't have this, right? All of this is underpinned by a foundation of privacy-centric technology. If you're interested in learning more about that piece, we're in the process of filing patents about how we've innovated on the privacy. I'm happy to talk to you about that afterwards, but what we're doing is moving data into a common format and obfuscating that data to an additional layer that is not available in other clean rooms today.
And like I mentioned, this solution is built right into Real-Time CDP. So as a business, we really think of customer data management as something that needs to include data collaboration as a part of it. It shouldn't sit somewhere else where you lose track of where you're engaging the customer with collaboration and where you're engaging your customer and the rest of them. Tactically, what this means is for Real-Time CDP customers, you have the ability to access the audiences that you've built in that system, and the event and behavioral datasets that many of our customers have in that system, and in just a few clicks, make that available in a collaboration environment, connect with the publishers and partners that you want to work with, and start seeing overlap insights. So I'll show you a couple screens just to give you an idea of what the solution looks like, but before you leave Vegas, if you haven't had the chance, stop by the booth. Our SC or solutions consulting teams have put together a really awesome demo where you can experience the product by itself or even as a part of CDP. So definitely stop by. They also have speakers, Bluetooth speakers because I'm sure everybody needs one more speaker. So let's dig into the capabilities really quickly, right? So the first is the ability to discover and collaborate with partners that you want to work with in a visual catalog. So this is a visual experience where you can read about who the publishers, partners are that are available in the catalog, what channels do they cover, what is the value of the audiences that they're bringing to the market, and where do they best fit into a marketing strategy. And in this catalog, you can discover them, you can connect with them, and we will facilitate that privacy safe handshake that needs to happen between two organizations for collaborations to start.
Then you get to look at the insights. So both parties onboard their audiences, be it from CDP or a data source of their choice. And because of the underlying technology that I was mentioning, we're able to give you overlap insights in real-time. So say you uploaded 10 audiences and the other party uploaded 20, that's a lot of different combinations of overlaps, right? And typically, you're probably writing different SQL queries for each combination. With the tech that we have built, you can literally from a drop-down, select the audience that you want to see, and the audience that the other party has made available, and immediately see the overlap between your universe and their universe. Once you've taken those insights in, we then make activation really simple. So Mike and Miriam are going to talk to you about this in a second, but we have the ability to activate to Connected TV to retail media, and over time we'll be adding more and more places for you to engage your audiences. And then lastly, once you've done all of that, you can measure the impact of the campaigns that you ran with your collaborator in this environment. We're starting you off with essential summary statistics, like reach, frequency, how different placements are performing. And very soon, what we're going to make available is the ability to bring together your behavioral and conversion data, overlay it with the other party's exposure data, and start to look at really interesting outcomes-based attribution for the campaign that you ran. So as you can tell, I'm pretty psyched about this. I work here. Of course, I'm psyched about this. And now I would love to invite Mike to give you his perspective and NBCU's perspective on collaboration in the context of Connected TV. Great. Thank you so much.
So NBCU is helping marketers evolve to the TV of today. And from a product strategy perspective, we believe one of the most beneficial ways to do that is through data collaboration. So if I take a step back from an NBC perspective, data collaboration was really two strategies happening at one time. At one point, it was really about replacing the pixel, right? Making the data more accurate, providing better data back to measurement providers. On the other side, there is the growth and advent of first-party data on our side when Peacock came on board, right? And over time, we have identified that bringing those two concepts under one roof leads to limitless creativity for our clients, for our partners, for our advertisers, and allows us to meet our clients where they are. So whether it's agency platform partnerships integrating directly with agency data, whether it's retail media networks, whether it's a customer data platform like Adobe, or measurement and verification vendors, we're able to extend to these audience and measurement capabilities to a number of different clients. And it really shows the power of data collaboration. I think when you think of a clean room, everyone thinks privacy right away. But for us, it's about getting everyone in under one roof, so to speak, so we can do a lot of cool stuff together.
Some examples of what our feature set within any data collaboration integration or any partner we work with or our own homegrown solutions is allowing the ability to unlock self-serve audience insights, which at a certain point can get very cumbersome and laborious within a data collaboration environment that's more turnkey and automatic. Activation, to Lory's point, being able to get those audiences where they have to go as quickly as possible, and then being able to measure performance within, again, under one roof. So whether that's insights and segmentation, the ability to quickly onboard and activate an audience, and to provide measurement and analytics back. And in a few slides, we'll get into the impact on onboarding and activation. It has significantly turbocharged our ability to get an audience in-house and out the door.
So if I dig a little deeper into the feature set that we focus on or that we strive to make available in any data collaboration product that we build out, it's the ability to see your audience overlapped. Again, these planning activities, happening in real-time and self-serve versus back and forth between us and clients. Audience profiling and the ability to find out the index of your audience. What content does your audience index against? Again, I mentioned onboarding, but that involves matching, right? And we'll see in a few moments, our match rate with Alterra was really, really great through these pipes, using the power of first-party data. And then finally, in the measurement and analytics side, whether that's just basic campaign delivery or reach frequency and attribution.
Really, the goal between NBCU and Adobe is to power in-the-moment Performance Marketing in CTV. We stand at a really, interesting place to do that. From an NBC perspective, that means content, premium content. And what is beneath that or is hidden beneath that is engaged audiences, right? And that's the power of first-party data. And world-class ad tech between NBCU and Adobe partnering together allows us to bring all of this to life.
We believe that CTV is a performance, a full-funnel performance vehicle. Whatever your KPI is, we can help you get there through pipes that we've stood up.
So how does it work at a very high level on our side? A customer visits a brand site or a website or app. That data lives within Adobe. It's then overlapped and pushed into our instance of the CDP. We run overlap functions, we plan, and then we activate a personalized ad campaign across CTV. And then we return those ad exposures back, so you can see performance and potentially optimize your next campaign and spend.
It's driving an always-on audience strategy. Gone are the days of picking an audience, sending it on its way, and then waiting months and months and months to do something again. We are building the way to fully optimize and see the loop close over and over again. It also, again, as I mentioned, gives increased access points to our clients, so meeting them where they are. And it embraces the power of first-party data. We've also, through these channels, have reduced onboarding time, which was once historically three weeks to get a campaign, audience campaign up and running and in and out the door, to just a matter of days. We're starting to see greater adoption of first-party data across the entire ecosystem, which again shows the power of data collaboration. And we're able to allow you to measure your first-party data.
So just to sum up a bit, data collaboration for NBC allows us to deliver our clients these key benefits, whether it's real-time first-party data collaboration, an always-on performance strategy, being able to stay privacy-minded, a personalized ad experience, or full-funnel measurement. And I'll pass it to Miriam and Kevin to go through a little more.
Thanks so much, Mike.
So can you really do this? I mean, we did. For most of you that might not know us, Alterra Mountain Company is a family of 19 iconic year-around mountain destinations that welcomes millions of guests each winter. And the Ikon Pass, the premier ski and snowboard season pass featuring 60 plus destinations worldwide. And it just went on sale for next season.
Compared to a lot of other companies you'll see on the stages here at Summit, we aren't quite what you would call a whale. While we really do try to span our reach, our uphill battle in digital marketing has been and still is vast. Only 4% of the United States skis and even less knows what an Ikon Pass is. So it's really keeping a growth mindset that sets us up for success in our endeavors.
Selling a dream vacation like skiing might really seem like a hook, line, and sinker of a marketing effort, but the precision that goes into this niche market is something that we've been crafting for years.
While it's really easy to see all skiers and snowboarders as the same audience looking for the same experience, when we think of awareness to our customers, it isn't just about ski resorts. It's choosing to take your college friends' trip or your family vacation to an all-inclusive beach resort or on a cruise. And how we find segment, and speak to our customers is really invaluable when we're competing for that share of wallet in leisure and tourism spending. And once folks know they want to take a ski trip, what's next? Do they know where they're going? Maybe they've never even skied before, but they have some kids interested in approaching the sport. That need to drive digital awareness with months of pre-planning and a short sales timing is really where the bulk of that segmentation happens to garner the reach. Now the conversion process takes a true push of each value proposition to ensure users are convinced. Tried and true retail tactics, like sending an abandoned cart email for T-shirts are really efforts we have to look at with a much finer tooth comb. From all of this, we go and we develop our digital architecture. So what does that look like? With the creation of Real-Time CDP some years ago, we stepped in as early adopters, understanding pretty completely what we needed to do to transform our segmentation tech stack. Now working in such detailed segments, knowing the who is at the core of the ownership of audience centralization and creation. We worked meticulously, Kevin and I, to pull the right customer data from all of the sources across our company and unified our first-party data in a way that makes audience building and activation incredibly seamless from all the way from data mapping to activation across channels. Investing that time in our technology is really what enables our digital marketing strategy.
It's things like making data capture and conversion rates actually, a company in priority and even attract OKR allows us to use a compilation of quantitative and qualitative data to define our segments across all of our marketing channels. So much so that we often only build an audience one time for cross-channel usage, especially in our outreach channels like media. Now once we bring them to the website with those carried attributes and strategy in lockstep, we factor in future behavioral models and pull our guests through that personalized journey tailored just for them, all the way from the outreach into the personalization and conversion. However, as I mentioned before, given the seasonality of our business, time is really often a luxury that we don't have, and part of why we're really always on the lookout for additional opportunities here.
So having our key audiences created and mapped out prior to really running any campaigns, we've expanded our use cases to thousands of first-party privacy-centric audience segments, each really meticulously focused on a key value attribute backed up by behavioral value propositions.
These business challenges unique to our industry and model make it so we need to absolutely perfect how and when we speak to each customer. And what leads the nuance to this growth in our space is challenging the established segment playbook and continuously balancing the mix between the known valuable customers and the prospects, thereby making the space to take risks on fine-tuning segmentation targeting to get more sophisticated.
It's really joining these alpha and beta programs with Adobe and always keeping an open mind to what we have to learn about not only our customers, but our prospects is what set us up to succeed in our quest for additional opportunity here in the data collaboration space.
85SIXTY is a close partner with Alterra. We work across each of their mountain destinations. This gives us a unique insight and perspective when we help and support them when it comes to their analytics implementation, how we help support their experience optimization program with Adobe Target, or how we approach the implementation of RTCDP. Like Alterra, we apply this growth mindset to everything we do.
For instance, with our work around paid media, we have these different assumptions and questions, but what's the right answer? There's different ways to approach that.
Do we do direct partnerships, or do we have our team self-manage placements and targeting? With programmatic, you can easily layer in your first-party data. When you go direct, how can you lean into that first-party data more? Based on our research, we might find a partner index as well, but do we have the right target? Is that target or is that media then having an impact on that target with that partner as we expected? You heard Mike talk about the rising of streaming in CTV. Even our Media Mix Models we run with Alterra says we need to buy more CTV. But where does that fully fit in Alterra's Media Mix? Is it a conversion driver? If so, what's the right audience? Is it the renewal audience, the lapsed audience, or is it more prospecting? Now Lory mentioned they introduced collaboration last year, and I was in the session where they introduced it. I was sitting there listening to all of the different features while I was there, and the light bulb went off. I had a use case that I can immediately take advantage of this tool.
With Alterra's core first-party data segments, can we leverage collaboration to determine the effectiveness of CTV to drive both customer retention and acquisition? So you can guarantee right after that presentation, I came up to the stage asking Adobe how we can get Alterra in that beta.
By continuing pestering of Adobe for the last year, it paid off. We got Alterra part of the beta. And we partnered with NBCU to target our high-value Ikon Pass segments, and we're able to measure direct engagements and incremental conversions across each of those segments, both the lapsed, renewal, and our prospecting.
[Girl] Whoa. [Man] Here we go, human. Adventure is everywhere.
My fresh powder is what she really wants, eh? [Woman] But my views are the best. Give her to me. Yeww. [Music] Now that spot was what we ran against our renewal segment, and we had a different creative for each target we ran on the campaign. So now I want to take you through the steps we did throughout the beta, to make this all work and execute. As our audiences were already in CDP, this has allowed us to quickly service them into collaboration. We were able to connect with NBCU and share those same audiences, the renewal, the lapsed, and the prospecting, and see the overlap of each of those individual segments. We ran the campaign for one month at the end of our overall flight. And at the end, NBCUniversal was able to do an incrementality test to determine which one drove the best conversions. And they were able to utilize the conversion data we already had in CDP. So it's a great use of the beta we're testing out.
What that incrementality study showed us is we had 30% lift conversion rate across each of our core audience segments.
Additionally, we had the ability to see who was exposed to the campaign, closing that targeting conversion loop across each of our segments. We had a 30% match rate for each of our segments, but most importantly, it really proved to us that we can utilize CTV as a conversion driver or across the conversion journey for both customer acquisition and customer retention.
As a result, just last week, we launched our second campaign with NBCUniversal using collaboration. [Music] So as Miriam said, this went on sale last week, so make sure you buy your Ikon Pass.
But I'm going to turn it back to Lory because I want to know what I'm going to be pestering her about for the next year to do utilize collaboration even more. Awesome. It's hard to follow that ad even though I'm like very much an inside person. That makes me want to learn how to ski maybe. So Kevin and everybody else, if you're interested in this, we are more than happy to be pestered by people who want to try new things that we're bringing to market. So while you've been at Adobe Summit, you might have seen some of these announcements come through for Real-Time CDP Collaboration. So from a roadmap perspective, here's where we're going with the tool. So if these use cases resonate and you want to start thinking about how you might want to use collaboration for these purposes, come talk to us, come talk to your account team. So first and foremost, we will be launching brand-to-brand collaboration. So say, as an example, there's a airline company and a credit card company, and maybe you want to collaborate to see what your overlaps are, so you can run a loyalty campaign and put some interesting offers out there for that audience, right? So we'll unlock the ability for you to get those audience insights from other brands that you're working with and activate to the agreed upon channels as part of those campaigns. The second is, a really interesting one is we're digging into off-site retail and commerce media use cases, with collaboration and the ability to do measurement there. So this will allow our customers who are running RMNs, commerce media networks to work with brands and do interesting things like maybe run some advice on Connected TV as part of that partnership. The third is, was an announcement yesterday, is an integration with Amazon Marketing Cloud, which is going to set us on the path to unlock more walled garden, clean room integrations as well. So some of you are probably activating to Amazon ads today. What we're doing here is, bringing to market and integration to their clean room, so you can access additional audience insights to plan your buys on Amazon and get additional insights back from a campaign measurement perspective after you run those campaigns.
The fourth is look-alike modeling. So for those of you who are thinking about retargeting is great, but I really want to do prospecting, that is right around the corner. So this is the ability to take a seed audience that you might have and run a look-alike so that you can prospect against your partner's universe of data that they've chosen to make available. So this could be publishers, could be data partners, maybe some of the brands that you want to work with who are open to doing look-alike modeling. And then last but certainly not least, we are available in the US market right now, but we're going to roll out to additional countries. So if you run your businesses in any of these countries, definitely come talk to us. We're starting with Australia, New Zealand, Canada, and select EMEA markets, the rest of this year.
And as we bring these things to market, I just want to sum up the core pillars, the core truths that we're going to stick to as a product, right? And really that is the focus to bring to market something that democratizes data collaboration and helps you make it a true part of your overall audience and customer data management strategy. And we want to do that by bringing to market something that is interoperable, radically simple, and centered on privacy. So first is our focus on bringing MarTech and AdTech closer together. If you are doing your work already in a system and an Adobe system to centralize your audiences and behavioral data, it only makes sense to use that data to unlock more use cases without doing repeat work. The second is the user experience. Our product and design teams spent a lot of effort to build, bespoke user experiences for folks who sell media, folks who buy media, so that they can do the jobs that they need to get done in the experience in a really simple, no-code UI. The third is a solution that is going to be agnostic and interoperable today and for years to come. Because as we know, you are going to work with different data vendors, identity vendors, everyone's going to have a different tech stack. So we're going to continue to focus on making a solution that lets you interoperate regardless of what technology you all are choosing to use. And then lastly, a focus on privacy and innovating from an architecture perspective so that you can collaborate without moving any underlying customer or identity data, keep that data safe, but still get the benefits of things like real-time overlap insights.
So if that sounds interesting to you and you are thinking like, "Where do I get started? I think I'm ready to collaborate." Here's a, arguably overly simplistic summary of what it might take to start, but first and foremost, start by thinking about where data collaboration fits into your overall strategy as a company and where it fits into your overall data strategy. So where does your data live today? What can you do with it? Who do you have to work within your organization to maybe get access to that right data? The second is identify a publisher or a brand partner that you want to work with and establish any legal agreements that need to be established that aren't already in place. I think NBCU would be a good one. Yeah. Yeah. - I thought just throwing it out there. - Yeah. - Take it or leave it. - Yeah.
I love it. So once you've identified a publisher such as NBCUniversal, what you should start thinking about next is defining your key use cases, your campaign objectives, and KPIs. I think Kevin and Miriam are a great example of how to best do that, right? They were very purposeful about not only just setting up their overall data strategy, but identifying a actionable tactical campaign where they could tap into, the great data from NBCUniversal. Fourth, execute the campaign. See how it performs. And I would say, I think the thing that you all talked about having a test and learn mindset is really important. So see what you learn. Maybe it's a success, maybe it's not a success, but even a failure is a lesson in what you can do next time. And then last measure that campaign, optimize the campaign, and repeat with another collaborator.
If you want to dig into this further, again, stop by the booth before you leave Vegas tomorrow. And then I have a couple of sessions I want to recommend as well, that are happening tomorrow. So the first is a session around audience strategy that you might find interesting. If you're thinking like, "I think I need to get my data house in order before I can think about collaboration." I would check that session out. My colleague Josee is presenting there with one of our product leaders, from the audience side of things. They'll also have some really cool, agentic features in their session around audiences. The second is, if you're ready to get hands-on with the solution and test my claim of this being super user-friendly, there is a lab tomorrow morning. So check out the lab. I heard there was one today that was a great success. So get your hands on the product, work with some dummy datasets that we're making available, and see for yourself, if that solution makes sense for you.
All right. Thank you so much for coming to the session, and thanks for giving us your attention. We'll all be available for any questions you all have.
[Music]
