[Music] [Greg Collison] Good morning. It's a time to get the show on the road.

Welcome, again, to a day two of Adobe Summit. On behalf of Adobe, thanks for joining us in Vegas this week. And selfishly, I would just like to say thank you for setting that alarm a little externally to join us here for this session. My name is Greg Collison. I'm one of the product leaders here within an Adobe DX, and I'm joined by my colleague Alyssa from our product marketing team. And today, we're going to introduce you to this big new idea of ours around experienced led customer acquisition. So to give you just a quick roadmap of what we're going to do today, we're going to start with the big idea, right? What is experienced led customer acquisition, why is it important and why now? Then we're going to try to break that down into use cases that are actionable. We're going to try to bring it to life with a demo, and we're going to wrap with a set of product announcements that are all related to how we can help marketers with this customer acquisition idea. Okay. So if we start with a bit of a definition, right? What do we mean when we talk about customer acquisition? For us, that term is really all about how marketers win new customers and ultimately grow their business. And I think it's pretty safe to say that we'd all agree that that concept of winning new customers is mission critical for every enterprise marketer today, right? We want to be really good and having a repeatable efficient process for winning new customers over and over and over again. But there might be some of you in the room they're wondering, hey, why is Adobe talking about this in 2024? I mean, haven't marketers always been focused on winning new customers, and that's absolutely true. The one thing that we would just kind of assert at this point though is that we do believe that digital marketing is undergoing a period of dramatic transformation, right? Yesterday, Shantanu talked about tectonic shifts in the industry and in the tech. And I kind of agree with him, not just because he runs the company, but I think he's right. And so we believe that what got us here won't get us there, that the old models for acquiring new customers won't translate into the new world. And so we believe marketers need to reinvent, rethink how they go about customer acquisition and really focus on delivering amazing experiences for their customers in an end-to-end way, starting at advertising all the way through to on-site experiences, to really jump into that new world of what we're calling experience led customer acquisition. So that's why we're here. That's why we're talking about this.

And I think it's important to start with a little bit of context, right? Where are we today? And again if you're a part of any elements of customer acquisition. I think you'd agree with me when I say, look, customer acquisition today is hard. It's always been hard. And if you look just around the corner, there's a bunch of headwinds coming at us that are going to make it harder. And I think it's important to talk a little bit about these challenges because this is sort of what we're up against, right? So if I kind of talk through these one at a time, we all know that third party cookies are going away. Admittedly, there has been a lot of starting and stopping on this topic, but Chrome assures us that they are committed to their plan to deprecate third party cookies throughout 2024, right? And as you all know, cookies have really served a sort of the global identity layer for the open Internet. So when they go away, we are all going to have to rethink the way we do the things we do around targeting personalization and measurement, right? That's challenge number one. Challenge number two, we know that Walled Gardens continue to expand, right? Google and Medic continue to grow. Amazon, TikTok and the streamers are here to stay. And while this explosion of content has been really, really good for marketers, right? It's created new ways for us to engage with our customers. They have created some complexities, right? It's really hard to deliver an integrated campaign across Walled Gardens. It's really hard to do holistic measurement when you're buying across a bunch of Walled Gardens. And so these are just challenges that we as marketers have to contend with. Number three, we know that advertising technology and marketing technologies are very often disconnected. And it's not even just the technologies. It's the teams and orchestrates everything. And as a result, the experiences that we deliver to our customers are often disjointed, right? The experience a customer sees in an ad is very different than the experience they receive when they come to your website. And that level of disjointed experience hurts your efforts to acquire new customers.

And last but not least, we know that content production or creative production has been really manual today. If you're part of the main stage presentation yesterday, there's a ton of talk around this. And to me, the big implication here when I talk to customers is that when marketers don't have enough creative, they can't do things like personalization and experimentation across the entire customer journey, which makes it hard to give customers the right experience at the right time. So this is what we're struggling with, right? When we think about how to do customer acquisition, right? And when we look ahead to what the future of customer acquisition could be. We think it's much more than just driving generic site traffic. We think marketers are going to have to invest to build new capabilities to win in the new world. And those capabilities are things like the ability to optimize marketing spend across this fragmented media landscape in more real time for dynamic adjustments. We think it's building new muscles around creative experimentation in paid media using paid media as a test bed for what creatives resonate with each part of your audience.

It means connecting your on-site experiences with the advertising touchpoints that came before, so you really are delivering a consistent experience to your customers throughout the journey. It's finding new ways to retarget your customers, because spoiler alert, most of that is powered by cookies today. So if that's a vital tactic for you, kind reinventing how you go about reengaging with customers that come to your site and then leave. And last but not least measurement. Measurement is the foundation for what we want to do here and really being able to identify the impact of your audience of your creative and your media towards those business objectives. So this is what we want to help marketers build and grow into. And we think it's an important opportunity because for marketers that built these new capabilities. They'll be able to move from the old model of customer acquisition, which was largely focused on optimizing cost and hyper targeting audiences to what we're calling this new model of experience led customer acquisition. And we think this transition is really important because not only are the legacy model's hard and getting harder. But I think you could even argue they're far from perfect, right? If you think about it, after a brand reaches tens of thousands of potential customers with their message and market through advertising. That brand will probably win less than five new customers, which is a pretty low conversion rate when you think about it end to end, right? And so rather than focus on eking out another 2 or 3% of incremental cost savings from a media budget, we think there's a bigger opportunity, right? The opportunity is to think about delivering amazing experiences, so at every step in the journey you're maximizing engagement and ultimately conversions across that entire process to dramatically increase kind of the number of customers you win, right? So that's the big opportunity. It's not 2 to 3% cost savings. It's two to three times the number of customers you win through these efforts, right? That's the big idea. That's what we're trying to help customers unlock. And if you're sitting there thinking, well, that sounds great, but how do we do it? Right? Because maybe it sounds hard. I think the first thing I'll say is, Adobe is here to help, Adobe can help with these efforts. You heard Shantanu talk yesterday about the fact that we've launched a new set of tools to help marketers harness the power of Generative AI and not just in the playground, but taking it into production, right? To help you build more creatives faster in an automated way. You obviously know that Adobe has tools and technology to help deliver personalized experiences and deliver experimentation at scale across the entire customer journey, starting in advertising all the way through to on-site experiences. And you probably know that Adobe has a ton of tools to help you measure the impact of all of these efforts. So you know what is working and what is not working. And I get excited to be part of Adobe because this is a really big vision. And honestly, I think Adobe is the only tech partner in the world with portfolio that's big enough and broad enough to help marketers solve for customer acquisition across all of these dimensions.

And part of our secret sauce, part of how we make this happen is the idea that all of our products are natively connected, right? You heard on main stage all of this effort to build the Adobe Experience Platform is this sort of hub to connect all of the different products. And this really matters because what it allows marketers to do is seamlessly go from planning to activation to measurement and back again, which means that marketers can conduct rapid experiments across their audience, their creative and their media. And those experiments really matter because that allows marketers to first discover, but then more importantly deliver the best experience for each customer at every interaction in the journey, right? So that is the big idea, right? That is something that we get really excited about. I hope that gets you excited. And again, maybe even a little curious, right? How does that actually work? And so for that, we'll dig into the details here. Again, planning is that first step in the process. Within planning, we're really going to try to help marketers get their arms around on a couple of big things, one, budget, two, audiences and three, creatives. So from a budget perspective, again, we've got this fragmented media landscape. Planning today is typically like a blend of art and science, some technology, some services. We want to help make that more programmatic. So that you can get more real time budget allocation recommendations. And again, the key there is really finding the optimal allocation across all of your publishers and networks nearby. Within an audience, we have tools to help brands collect augment, extend, and activate first party audiences, which is obviously foundational for what you want to do in customer acquisition. And then, again, we've talked a little bit about this idea of accelerating creative production. But just in case, that still feels a little buzz wordy, to me what this means is you all can continue to get hero assets from your creative agency. But wouldn't it be nice if you could use technology to build a tailored version of that hero asset for each one of your customer segments. Or even better, one if you built three variants for each segment or five variants for each segment so that you could actually experiment. And find out which of those assets is really resonating with those different customer segments. That's what we mean when we say helping marketers accelerate on brand, creative velocity, right, creative that matches your brand guidelines, but build them faster, so you can do more personalization, more experimentation. That's what we mean for planning. Right now we know what the marketer wants to do.

When we talk about activation, again, there's a couple of different pieces of this puzzle, the first is paid media. And again, in paid media, we'll continue to do all of the important things that marketers are used to using today, right, audience targeting cost optimization. We're not getting rid of any of those things, but we're going to add to it, right? We're going to add this notion of creative experimentation. So now paid media becomes this test bed where you get to discover which asset resonates with which customer type. And that can not only help you boost engagement with your ads, but also inform the downstream interactions you have with your customers. And those downstream interactions would happen online, right? So the next big step here is making sure that we are continuing to personalize on-site experiences, but not in isolation, right? In connection to with the knowledge of, what resonated with that customer and their advertising experience. So that journey is connected. It's cohesive. It's consistent, all with the spirit of maximizing conversions for you. And then last but not least, again, customers will come to your site, and they will leave your site. That is part of how it works. And for those customers, most marketers want to reengage. They want to keep that conversation going. So having tactics and strategies that can do that for both authenticated and unauthenticated audiences, which is a really important distinction in the cookieless world. And this is how we execute the plan.

And then last but not least, measurement. And again, lots of tools and techniques here, but one that's really important is this idea of de-duplicating conversions across Walled Gardens. So you have a true sense of contribution, and then intelligence help understand the impact of your audience and you're creative on those conversions. And again, the insights at the measurement layer, this is what informs the next side of experiments for the campaign, right? So you can start to see how this loop can repeat and repeat, right? Incrementally, improving the way you deploy budgets, the way you target audiences and the way you build creatives, to constantly improve the experience for customers, the engagement with your brand and ultimately results for your business. So that's the big idea, right? We said we would start with the big idea. And again, to recap, it just means we believe that marketers are going to have to rethink and reinvent how they do customer acquisition, and that experiences are really going to be a central part of doing that well in the new world. So, that said, I'm a practical person I know that big ideas can be hard to implement. They just feel too big, or they span multiple teams, or you don't know where to start. You can't do everything all at once. All of that is completely fair. And so at this point, in the presentation, we want to try to make this a little bit more practical. We want to make this a little bit more bite size and so we're going to do this in two ways. First, I'm going to talk about a couple of use cases. And then we're going to have list to come up and do a demo to bring it to life. So, hopefully, we're going to move out of the stratosphere, right, that 30,000-foot idea and make it a little bit more digestible, practical, actionable. So use cases. I'm going to go through five use cases. They're each going to feel a little bit like this. The first use case is around optimizing media spend across channels and publishers. And this is really focused on solving two big pain points in the industry. The first is that marketers need a clear view of which channels and publishers are delivering the most value. And while that sounds like a really easy thing to do, I can assure you it's not, largely because each publisher tends to report their data in a silo. And so that means, if two publishers showed an ad to the same individual who ends up converting, both publishers will count a conversion for that. And so if all you do is ingest and aggregate data from those publishers, you'll see two conversions, but you know there was really only one. Now imagine that happens over and over and over again across your media by and think get pretty messy pretty fast. So the good news here is that Adobe Mix Modeler has intelligence to help de-duplicate conversions across those Walled Gardens. And give marketers a true sense of contribution for each. The other thing that Mix Modeler can help within in this use case is it can simulate the ROI of those different publishers at different budget levels to find that point of diminishing returns for each publisher, and ultimately then recommend a budget allocation that makes the most sense drives the best outcomes across the whole portfolio. And it can do this in real time. So this doesn't have to be an annual planning process or a every six-month planning process, right? You can kind of use this to inform in flight adjustments, which is a really powerful concept back to this idea of experimentation. And if there's anybody in this room that says man that sounds complicated, why does that matter? To me, the simple answer is, better allocation means better ROI, which is something I think we could all get excited about. Okay. Use case number two, this is all about reaching new prospects. And, again, I'm probably stating the obvious. But today, prospecting is relatively easy. Mainly because all online traffic can be tied back to a third-party cookie, which means you can use cookies to build audiences and then retarget those in programmatic media. All of that gets harder without the third-party cookie. So our associate brands are going to have to rethink how they do prospecting in this new world. The good news is, we saw this coming. This is not a surprise, so the real-time CDP has already built capabilities to help advertisers and marketers navigate this change. Mainly, two big things here. One, the support for what we call partner data, which is a way for brands to use partner data to sort of matching their first party data sets or augment the first party data sets to enable prospecting use cases. The other big thing that the real-time CDP has launched and announced this week is what they're calling real-time data collaboration, which is the way that brands and publishers can match audience in a privacy safe way. With some lookalike capabilities, so brands can prospect into premium publisher audience segments, pretty powerful concept, all of which obviously become super important post cookie. And so the idea here is we want to help marketers continue to find those high value prospects and bring them to sight.

Use case number three. We've talked about this a little bit but personalizing those on-site experiences. And again, you might get tired of me saying this. But today, a lot of how we personalize is through cookies. And so again, we sort need to reinvent because if we don't change the way we personalize, the vast majority of site traffic that marketers see will be anonymous. And when your audience is anonymous, it's really hard to personalize. And when you can't personalize, it's hard to maximize engagement and conversions, and acquire new customers, right? So it's really important we rethink this. Again, we've got some interesting capabilities with Adobe. You can use things like first party cookies, ECIDs, partner data to help you personalize across both known and unknown customers. We also have Adobe Target that can help marketers automate experimentation and personalization of those experiences. So lots of good stuff here. Again, to keep experiences relevant, engagement high, and maximize conversions on sight.

Two more, we're almost done. Fourth use case is all about retargeting. As we said at the top, for most marketers, retargeting is a really vital tactic within the customer journey, right? It's very normal and natural that this high propensity high value audience comes to your site. But they leave before they convert or sign up, right? And so as a marketer, you want to find a way to reengage with those customers. You want to keep the conversation going and you want to nurture the relationship.

Again, a lot of this is powered by cookies today. And so I think what you should hear for me is we need to reinvent, we need to rethink how we do it. And it's going to get a little bit more complicated. And today, all site traffic you can kind of treat the same, right? Because you can use cookies for all of it. That the big concept I'd love to kind of leave you with today is that, retargeting the future will be a little bit more complicated. You'll need to think about your authenticated audiences and have a strategy and identity strategy for how you approach your authenticated audiences. And you'll lead a different identity solution for any unauthenticated site traffic. And it's kind of ironic but based on what I've seen a lot of the headlines, and the PR is kind of sucked up by all the strategies to solve authenticated. But for most brands, 90%, 95% of traffic is unauthenticated. So having a really clear plan for how you're going to retarget on authenticated site traffic is super important. Again, we can help with that. And again, getting this right means that you can keep that conversation going. It doesn't end when someone leaves your site, which again is important for that customer acquisition idea.

And last but not least, we have measurement. And again, I think there's a bunch of capabilities within Adobe to help with measurement. We've got Analytics and CJA for all of the on-site activity. That notion of real-time data collaboration also supports measurement, right? So matching the brand data and the updated figure out of the exposed audience who converted. That's a really powerful concept. But the thing I want to highlight here is what Neil called out on main stage yesterday, which was this new category of analytics that we're launching around content analytics. And Content Analytics is a really big deal because, to date, the level of insights and analytics around your content, I think has been pretty limited, right? Maybe it's limited to a channel or a publisher. And when you get it, it's often reflective of the overall creative, right? The entire creative all the choices that went into that creative. But what we're doing now is launching AI, again, not as a buzz word, as a practical tool to almost decompose an asset and identify the main elements of the asset. So the subject is it the main subject an image of a child or of a pet? The background, is it a red background? Is it a blue background? Is it, what are the tones? Is it warm? Is it cool? And then score or discover the impact of each of those elements on the engagement within your audience. So does your audience respond to pictures of kids or pictures of pets? That's really interesting. And so not only can you then make sure you're delivering more budget and more impressions to the experiences that drive the most engagement. But you can also get smarter about how you want to build the next set of assets, right? So you can incrementally learn about what creative really resonates with your customers. The other cool thing that we can do with this technology is stuff like detect fatigue. So there was a comment yesterday on main stage about the fact that, you worked so hard to build these creative assets. And you don't even have enough of them. But as soon as you deploy them, the half life is a week. Right after a week, people are already getting tired of seeing that creative. Wouldn't it be nice if your technology could automatically kind of measure your baseline, detect fatigue right when that engagement starts to fall off and generate a new batch of variance based on all these smart insights and learning and deploy them for you. So that you can avoid having stale creative in market. That is what Content Analytics unlocks for marketers. And again, the idea is if we can keep that content fresh, we can keep engagement high, as a means of really trying to increase conversions throughout that journey. So, that's the last use case I'm going to talk about I guess maybe I'll just, on this page, two big takeaways, right? One, if any part of this presentation has been exciting, right? If you're sort of buying into this idea that we need to rethink customer acquisition. I guess something here, the first takeaways, we're here to help, right? We've got a bunch of capabilities that are available today. The second thing I'll call out on this slide is you don't have to do it all at once. These are intentionally designed to be modular, right? Which means you can spot one idea that seems interesting. One problem we're solving, one opportunity that makes sense for your business, your team, your customers, and you can start there, right? So intentionally modular. It's a big idea. But you can tackle it in pieces if you have interest. And the last thing I'll talk about before we bring this to life in a demo is just one quick slide to sort of demonstrate that we're making progress on this. So it's not just an idea. It's not just a set of use cases. It's actually technology that's live, and more than just technology, it's helping customers achieve better performance, right? So a couple examples just to highlight. We've got customers that are using these GenAI tools, GenStudio to automate the production of email content. And when they've done that, they've seen higher click through rates. We've worked with customers who have used Mix Modeler to do this optimizing of budget allocation across the fragmented media landscape. And when they do, they've seen higher ROI from their media budgets. And we've got customers who worked really hard to deliver personalized ads and also connect those ad experiences to the on-site experiences. And when they do that, they see higher engagement, both on the ads and on-site. So again, hopefully, a bit of a proof point to say these are not just ideas, these are real solutions that deliver real value, which is the whole reason why we're here, right, we're all trying to get better. So with that, I'll introduce Alyssa to come up and do a demo and kind of bring this to life for us. Thank you. [Alyssa] Cool.

Thanks, Greg. Hi, everyone. 8 AM on Wednesday in Vegas, right? So thank you so much for coming out and spending time with us. As Greg mentioned, I'm going to be going over a demo on how you can kind of see this all come to life. I'm actually going to go over a couple things. And so I'll show you how marketers can plan campaigns to maximize their ROI, reach new high value customers, test personalized experiences, and then measure the impact of these campaigns. And so we're going to start our campaign planning here in an Adobe Workfront. In Adobe Workfront, we can see all the different campaigns that we are currently running. For this demo, I'm going to go over a fictitious athletic apparel brand called Luma, and let's say they're running their 30-day test campaign. For their new Luma Kicks running shoes. So I can take some of the guess work out of my campaign planning, right? As a marketer, there's a lot of things that I need to fill in, and this just takes so much time to fill in all these information. But instead, what I can do is I can actually import a brief directly from PowerPoint or Microsoft Word directly into the UI. And what's happening is that AI is scanning this document, and you can see it automatically populated the information from my brief to all these fields. So for my campaign, I can see my key messages, my goals of my campaign, channels, products, my strategy for my campaign, but what's also interesting in what you'll see throughout this demo is this target audience's piece. And so as Greg mentioned, we're talking about how important first party cookies are, how important it's to get smart with the type of data that you're going to utilize to reach your audiences. So remember these audiences for this demo. We are going to want to reach millennial women and high propensity frequent shoppers for this new kicks running shoes campaign. But what's really cool here is that I can see my budget as well. And I can understand where I want to allocate my spend for this budget. But I want to be smart with that, right. I don't want to just put my money where I think is cool. I actually want to make sure that this is going to provide me with the best returns. So in order to do so, I'm going to go into Mix Modeler over here. And as Greg mentioned, Mix Modeler allows organizations to plan and measure that impact of their channels, and which channels are providing the best ROI. And so here, I can see the spend per channel and my budget over time. And going into models, I can see conversion, digital sales and how that relates to the spend on various channels over some quarters, I can see the spend per channel. Well, what's really interesting is if I want to plan my campaign in the right way, I want to better understand which channels are garnering the most return. So we have connected TV, and we have paid social, and we see that these are actually performing better than other channels. So this can give me a better idea of how I want to continue with my campaign, right? All right. Let's take it a step further then. Let's get even smarter. As you saw earlier, we input the brief. Here, we can compare how we're going to spend our budget in two different plan side by side. The plan on the left is a fully AI automated plan. Whereas the plan on the right is something that I customize, I applied some restrictions to and what happens is and Mix Modeler in this planning feature, it can take my allocated budget for this campaign. And it can populate maybe where I want to spend my money based on historic performance and ROI of each channel. And so looking at this, it seems like that fully AI automated plan is actually providing better forecasted ROI for me. So this gives me an idea of, okay, maybe I can spend a little less money on paid search, maybe heavy up and connected to TV. That way you can garner more returns, right? All right. So you've seen us plan our campaign. Now we know where we're going to spend our budget. The next piece now is to figure out how are we going to reach our audiences and who are we going to reach for this campaign? Here in Adobe real-time CDP, you can ingest data from anywhere into a centralized system for profile and audience creation, and then you can activate it on multiple channels. And as Greg mentioned, partner data is going to be very important for a new strategies for customer acquisition, right? And so with partner data support, I can ingest manage and then activate durable identifiers provided by trusted identity partners. For this instance, Axiom, for example. So let's see what that looks like for our prospect audiences. Here's a list of some audiences that I received from my identity partner. These are probably audiences that we don't own today, but we feel like they would be a great fit for company and our brand, and we want to reach them on our channels. But as per brief as you remember, we actually wanted to target millennial women for our campaign. I can see the description of how I got this audience. We saw that Axiom provided me with these attributes. We see how big this audience is. But what's also important is we know where we're going to activate this audience, right? We're going to reach millennial women in these following destinations. And so with Adobe advertising, I can reach this demographic on my off-site ads, or with Adobe Target, I can reach them on-site as well for better personalization. But what's also as important is I need to utilize my first party audiences and my first party data as well. So I'm going to go into my audiences, and what's really cool here is that with customer AI, it can actually create propensity scores on profiles and audiences. For instance, high propensity to buy, high propensity to churn, low propensity to buy even. And so this happens because customer AI is able to gather data on behavioral factors or influential events. And so in this example, I can see a list of my audiences that I've applied propensity models and scores too. And so as per our brief, you probably remembered, we wanted to reach high propensity frequent shoppers as well for my campaign, right? And you're probably thinking great. Let's do it. Let's start your campaign. But customer acquisition is a little bit more complex than that. As per brief, we also wanted to reach customers on Connected TV as well because that's where consumers are spending a lot of their time, right? So how do we reach customers on all these emerging channels? Well, coming later this year is Adobe real-time CDP collaboration. And what's really cool about this is that this is a brand-new application that allows brands and advertisers like Luma, myself to collaborate with premium publishers to discover reach and then measure new high value customers. So in this example, I can see that I'm actually connected with NBC Universal. And we have a ton of projects going on right now but let me look into the Luma Kicks campaign project specifically. What's awesome and what's brand new that we can do here now is we can actually see how my overlapping audience fits with NBCU's overlapping audience. But what's even better is that I can ingest my first party data, my high propensity frequent shoppers that you saw earlier, and I can see the breakdown the overlap of that as well. So I can get even more granular with my targeting and make sure that I can reach audiences that are relevant to my brand. Who might have interest in my brand, right? On NBCU's properties. So what happens is when I activate this. What's really cool too is that I can see all the various segments and categories with overlapping identities that I have with NBCU. I can see reality TV fans like myself. Golf fans, action fans, and I can choose any of these audiences that I want to activate for my campaign. So let me actually activate reality TV fans. Maybe I'll target someone who a millennial woman who likes bravo like myself. Who knows? So let's see a summary of what we just did in collaboration. We activate our first party audiences with NBCU's properties, and we saw an overlap with reality TV fans, and now we can reach these customers on NBCU's channels and properties. Right. Is everyone still with me so far? Are we good? Awesome. Love the head nodding.

So far you saw how we planned my campaign. We've allocated my budget. We've identified the customers that we want to reach for my campaign, the next step now, one of my favorite parts actually is to the creation piece, the content piece. Super fun. So here's content hub in Adobe GenStudio. You can find all your assets in one place in one repository and any marketer can go in here and find branded approved assets. I can look on the search bar, but what's really cool is with these features and these filters I can get even more granular with my search. I can search for the Luma Kicks campaign specifically. And here we can see all the various variations of branded approved assets that can be generated with Adobe Firefly. But as a noncreative and a marketer like myself, I can actually go in here and edit it directly in Adobe Express within GenStudio. So I can add a text. Maybe I want to add a cute little cheeky hashtag. Souls for your soul. Maybe I want to change the color as well. I think that hashtag's probably too big, so maybe I want to change the font size. And there you go. I can easily remix an asset, but what's actually really important here is that I didn't just add a hashtag. I made sure I stayed within brand guidelines. Because you can populate branding templates directly in Adobe Express. So I know I'm staying consistent with my fonts. I'm staying consistent with my colors as well. I can save this as a version. And now I actually want to use this for my campaign. All right. And now, we've created our assets. We know that audiences we want to target. So let's see how this is performing on our ads. Remember our first party data are high propensity frequent shoppers. They're seeing all these variations of assets and content directly in their social media on their ads. But what's really cool here is that Adobe Advertising is also quantifying the performance of these assets, and then it can shift the best performing asset to these customers. And the same thing can also happen on Connected TV as well. But what's also important is not only using ads to drive traffic to your site. What's as important is actually getting customers to convert once they're on your site, right? And you need to do that with personalization, and it does not stop. So here I'll show you an example of two different audiences. The one on the left is the millennial women prospecting audience. The one on the right is a known audience for to us. My first party data. And you can see that they're seeing two different personalized pieces of content. What's really cool is, and this is the hard part that some organizations are actually struggling with. How do you still personalize a site if you have an unknown visitor. So let's say we don't know this customer when they visited our site. They haven't authenticated. We don't have them as a profile. But like I mentioned earlier, we need to utilize, we need to get pretty crafty with this. We can utilize partner ID. And durable partner identifiers and partner recognition API where we know that this is actually something that Axiom has as a segment. We see their partner ID. We see that they are an outdoor explorer and they're part of this segment. So what we can do is with this partner recognition API, we can still personalize this visitor's experience and provide her or him with a personalized banner of maybe some shoes that might be interesting to them based on the segment that they're are part of. Great. The one on the right, for instance, is a customer that we do know. But let's say they haven't authenticated on our site in this session yet. We can still personalize them because we know that they have an Experienced Cloud ID. With this Experience Cloud ID, we know that they're tied to this person Sam Rose, who is a part of all these different segments. We know he's a runner. He bought from us in the past. He's a loyal customer. He buys online and in store, probably has a shopping addiction like me, great. So we can actually personalize his experience and provide a coupon code for a pair of shoes that maybe he is most likely to buy. All right. And so measurement is extremely important, right? We want to measure how our campaign is performing, but we want to get very specific and granular with the insights that we want to measure. And so with content analysis powered by Customer Journey Analytics coming later this year, I can actually see how elements of an asset is performing and customer affinities to that asset. And I don't mean just talking about asset number one versus asset number two. I actually mean that attributes behind an asset. So with AI and machine learning, it's able to detect all the different attributes and metadata within an asset and create that profile. So maybe I can see for instance that warmer tones are generating higher conversion rates and return than cool tones. And the interesting thing about this is that I can use that information and make sure that my on-site imagery matches my off-site as an imagery as well, and that also creates more consistent experience for our shoppers.

All right. And then I'm going to end here in Adobe Mix Modeler. And this is actually where we started when we planned our campaign. But this is really important to actually understand. How are we tracking against our budget? How are we tracking against our allocation spend? And where are we right now with our campaign in terms of generating returns in our ROI. So we see that we're on pace with our budget, that's great. We can see how we can compare our actual spend versus what we planned to spend. But we can also understand, okay, how are my channels performing right now? Am I getting any return on them? So for instance, here, we can see that paid social is performing as well as we expected. But maybe Connected TV is actually performing just a little bit better than I thought. And in the middle of my campaign, what can do is I can take this information back to my marketing team and say, maybe we take a little bit of our budget out of, let's say, paid search and heavy up on channels that are actually working for us. And so there you have it. This is an example of how Adobe solutions are connected together in this end-to-end workflow. Addresses multiple use cases for customer acquisition. And then your organizations are able to pick and choose which use cases are relevant for your business from planning campaigns to testing personalized content, and then measuring in a multifaceted way. All right. Thank you so much. So I'm going to kick it back off to Greg to finish this off for our product announcements. Thank you.

Thanks, Alyssa. That was great. Maybe it's the product person in me, but I love seeing product more than I love seeing slides. So that was awesome. So I'm just going to spend maybe five minutes quickly to recap some relevant product innovations that are supporting the use cases we talked about. And again, spoiler alert, we've already talked about some of these capabilities, right? So they're not going to feel totally new, but I just want to kind of underline or sort of emphasize some of the new innovations so that if you're already using these products, you're aware of the sort of the good stuff that's come in your way that you can take advantage of if you already have real-time CDP, Adobe Advertising or any of the other solutions. So first, we've talked a lot about Mix Modeler. And, hopefully, we've done a good job explaining that it can help with a couple of things, right? It can help with holistic measurement. And it can help with holistic planning, kind of getting those budget allocations right and even doing that in a more real time way than the current planning process. So the big news around Mix Modeler, not surprisingly, we've got teams that are constantly working to make those models smarter, And one of the big, kind of unlocks that the team is launching this week is what we're calling, see the market factors which means that now these planning and measurement tools will be able to isolate the impact of external factors, like big macroeconomic events or promotional events and try to decouple that from the impact of the actual budget audience and creative decisions. So you get a cleaner view of how those controllable factors are influencing outcomes, right? So kind of think of this as an even smarter, better version of Mix Modeler, because the teams are constantly improving the intelligence behind those capabilities. Next, we've talked a lot about, real time data collaboration as part of the real-time CDP. Alyssa did an amazing job, I think showing this in product. So I feel silly following that. But again, hopefully, it's clear. This is sort of that data collaboration workflow where brands and publishers can share data in a privacy safe way to power things like targeting and measurement, right? Because both of those parts of the equation really, really matter. And the idea being that once you sort of find the overlap of audience, you can then do lookalikes to expand to a bigger pool in the published ecosystem for targeting, or you can use it to sort of match the exposed users to the converted users to understand the impact or the outcomes of measuring on those premium publisher environments. So again, we think this will be a really big deal, especially as cookies begin to deprecate. And brands and marketers are looking for more ways to activate against their valuable first party data.

They might be cheering for us. It's hard to say. But just remember, that whole idea of data collaboration is very powerful. But again, it's largely limited to authenticated data, and it's largely limited to those premium publishers. So for everything else, we also want to help marketers find strategies to achieve their goals. So this is where Adobe Advertising can help, and we've got a bunch of great capabilities there. So Adobe Advertising is already integrated with the leading, authenticated ID vendors like RampID and UID. The big announcement for Adobe Advertising this week is we are also launching an integration with the industry's leading probabilistic ID, which is ID 5, and that can really help unlock this retargeting use case for unauthenticated site traffic. And again, I already said this a little bit, but I think this use case of retargeting unauthenticated has been a little-- Hasn't gotten a lot of attention. And so a lot-- When I have one on one meetings with customers, this is a use case that really resonates. So the team wanted to make sure there's a solid solution in place for those unauthenticated visitors. And again, that's the ID 5 integration within the Adobe Advertising system. And then last but not least, again, I love how Alyssa brought this up, but this notion of Content Analytics is new for us. We think it's a nice complement, everything we can do with our analytics CJA tools, data collaboration tools, but this graphic probably does a better job than what I can do. But again, there's a lot going on in each ad or each experience. It's not one thing. It's 10 different things. It's the subject. It's the background. It's the tone. And being able to understand or discover the impact of each element in driving engagement with the different types of audience is really, really important. And it's not only important as a means of delivering the best experience to each customer, but it's also really important in informing the next set of creatives that you and your team built. So this is a big unlock and really foundational for that notion of rapid experimentation, of creative paid media and on-site, right? So Content Analytics is a really big deal for us. So those are four big innovations that are all going to support customer acquisition in a big way. And I will just recap with this, right? We're getting very, very close to the end. I think if all of this has felt like a bit of a blur, I'm going to try to summarize like this, right? We really do think that now is the time to rethink and reinvent the way in which you acquire new customers in light of all of the changes and challenges coming our way. Right now is the time. We think that getting customer acquisition right, largely depends on our ability to deliver amazing customer experiences, not in one part of the journey or another part of the journey, but across the entire journey, right? That's the goal, right? So that you don't have big points or drop offs as you think about that entire journey. We really do believe that getting this right is critical for business growth, right? We started by saying winning new customers is the way we drive business growth on a repeatable basis. That's what we're trying to help brands unlock. And, of course, we're here to help. So if any part of this conversation has been interesting, exciting, got you curious. Feel free to grab me or Alyssa or anybody else from Adobe. I think we've got a couple minutes, so some of us will stick around but otherwise, we're free to give you 10 minutes to find your next session or just to sit and decompress. [Music]