[Music] [Woman] Please welcome Vice President, Consulting Services, Adobe, Suzanne Bordeaux.

[Suzanne Bordeaux] Hello. Hello, everyone. Thank you. I'm Suzanne Bordeaux, and I head up Adobe Consulting Services. And hasn't Summit just been so great so far from Shantanu's keynote to the chance to connect with our peers and customers, exploring the community pavilion? I think the energy has been palpable. Now this is my 11th summit. I know many of you can say something like the same. And I might be a little biased. I think this might be the best one yet. So heading up our services team, I'm so fortunate to have the opportunity to work with brands across industries. And one thing in common is that nearly every brand is grappling with how to effectively use data to drive personalization.

We all understand the power of data, but achieving the results you need at scale and in real time is truly challenging. But the rewards are immense, and it's crucial for delivering exceptional customer experiences. I'm incredibly energized by our work helping Adobe's customers solve these challenges. And I'm so excited to share with you some key insights and learnings drawn from our work together. Let me quickly talk about how this session is going to go and what you can look forward to. First, I'll set the stage by discussing the evolution of data to meet everchanging customers' needs and how brands are succeeding by reaching customers wherever they are through various modes of innovation. Second, I'll dive into the exciting future of data and personalization, showing you how to futureproof your strategy with collaboration and AI. Then we're going to hear from an amazing brand, NBCUniversal, about how they're leveraging data and collaboration to expand and build audiences across the board as well as how they've evolved to personalize experiences in this era of streaming TV. After that, you will hear from my colleague, Sundeep Parsa, who heads up our product strategy for Adobe Experience Platform and Applications. He's going to share exciting innovations in the world of data and generative AI and how they can further accelerate your personalization at scale mission. And finally, we will see data in action with a demo to showcase all the incredible technology Adobe has to enable that mission. Sound good? Alright. Let's jump into it. So data is why we're all here, right? Whether you are the CMO or a practitioner tasked with AB testing, you rely on data. It is the bedrock of your business, and it can make or break you. So when we think about data and personalization, what does good look like? Like many of you, as a consumer myself, I love an experience that's personal to me, and I really know when an experience is not. Even the best brands can struggle sometimes to deliver the right experience at the right time.

I recently went searching for a warm, cozy sweater. I do live in beautiful Connecticut-- go, Huskies-- where one can never have really too many warm clothes. So I began this search in the store wanting to see and feel my options in real life. And while browsing, I received a push notification offering me a coupon. Very tempting, but I wasn't quite ready to purchase, so I decided to wait and keep looking. So what followed after was an email campaign curated to my sweater interests with additional options for me to consider. So the in-store experience had given me confidence in product quality, while the email experience had broadened my options beyond what the store had in stock. Eventually, after probably too much deliberation, I'm happy to report I bought the perfect sweater. Success for me and the retailer. Except not quite. After I purchased, unfortunately, that email campaign continued to hit my inbox. I was inundated with sweater ads and a targeted social campaign. Frankly, it was irritating. Did this brand not realize, not appreciate that I had just made this purchase? See, the problem behind the scenes is that the sale transaction data was not connected to update the customer segment and change the next journey communication. So this is a cautionary tale. The retailer up to that point had done everything right. They used data to personalize my offers, emails, and integrate my offline and online experiences. They convinced me to purchase only then to spoil the fun by sending me offers that were no longer relevant. So what is good personalized experience then? It must be relevant, timely, tailored, and must meet me where and when I want to engage. And the only way to power that type of experience is with the right data foundation. Now just because you have a lot of data and you guys have a lot of data doesn't mean you can deliver a personalized experience. My sweater example really hits this home. In fact, having more data is seldom the answer. You need the right data coupled with a data foundation to deliver those top-tier experiences.

We are seeing our customers mature their data foundation to achieve personalization at any scale. You are on this journey, which started with channel-based personalization, then evolving to omnichannel personalization, very likely using a data warehouse as your source of truth. But to meet modern consumers' expectations, we have to step up and deliver omnichannel personalization with brand initiated and one to one in-the-moment journeys. Ultimately, you want to get to this state of personalization and scale regardless of where you are in the journey today. You need to think about data and personalization and with that your data foundation more strategically. My team and I have worked with Adobe's customers around the globe, and we've gathered some takeaways from brands working on their data and personalization goals. And I'm happy to share what we've learned and show you what that required data foundation should look like.

So in the past, design for mobile or mobile first was the mantra for many companies. The web alone simply wasn't cutting it anymore and mobile was outpacing all channels. And now if we extrapolate, we must say design for omnichannel in the moment experiences instead. This applies to your data foundation as much as it applies to your strategy and your organization.

The key capabilities for a data foundation are an actionable unified profile, providing that single view of the customer which can be acted upon immediately, and a fast path for interactions updating the unified profile, signaling high value customers with the ability to respond to them in the moment. It must have the ability to use signals directly from your enterprise data warehouse to inform the digital experience without the replication of that data.

It must empower marketers to curate audiences as and when they choose without relying on data engineering teams. And finally, it must support unified measurement to understand the behavior of consumers across channels with standardized KPIs.

So as we look at these capabilities, the reality is, there are areas where marketers are struggling.

While it seems obvious to build an actionable unified profile, it's actually really complex. When you bring data together from different channels across different teams, it introduces a sort of language barrier. A single attribute might mean something else within different teams and channels. This requires a single semantical reference guide and standardization of language for an organization. Teams originally were free to operate in the context of a single channel and now they must collaborate with cross channel data.

The next challenge is around creating the fast path, layering on the unified profile. For example, let's say you want to reach out to a potential customer who's walking past your store with a personalized offer. You need to understand that signal of proximity right now because the opportunity to convert might literally be passing you by.

When you're creating data pipelines for this or your business use cases, your pipeline is only as fast as your slowest data. Look very critically at which facets need to be brought together, prioritized, and onboard for speed.

As a mature enterprise, you're operating an enterprise data warehouse. It houses a lot of data related to your business, your customers, their behavior, your business execution. And the use and access of this data is strictly governed. And you need to prevent broad distribution of any sensitive data. However, buried in this data lie valuable signals. For example, in the context of healthcare, to invite a patient for an upcoming flu shot, instead of ingesting full health histories, only create an audience of the eligible patients together with the specific recommended vaccination opportunity and available service locations.

Audiences are the core currency for personalization, and they're defined anywhere and everywhere in your organization. For example, in a brainstorm, you might hear let's target individuals 25 to 35 who streamed the season premiere of Vanderpump Rules on Peacock. So while that definition is clear and available, marketers then may struggle to precisely identify the right data to build that specific audience. Audience curation must be available to marketers directly for rapid iteration without needing to engage data engineering or data science teams.

And when it comes to measurement, KPIs set previously for a specific channel need to be revisited for an omnichannel execution. Teams compete for channel-specific outcomes over those that span across channels. For example, do you optimize for maximum engagement in your email campaign? Or do you measure total uplift of the campaign across channels? Brands are more likely to succeed with scalable personalization when they establish a top-down mandate, incentivizing cross functional teams to collaborate, and choose omnichannel optimization over single channel approaches. And don't lose sight of your business outcomes. Many projects start as a data engineering endeavor where an overabundance of data is brought along out of a sense of FOMO. And this is where a focus on your use cases and business objectives become critical to your success. For example, we want to cross sell to an identified audience with prior purchases and specific expressed recent behavior. Based on this clear scenario, teams then identify data and agree on a common language and KPIs laying that foundation for scalable personalization.

And now there's a plot twist because what I've been describing isn't the final destination. It was once the frontier but has quickly become our present day. Now it's all about data collaboration and integrating innovative gen AI capabilities.

One to one customer journeys are here to stay. No longer a nice to have but the preferred method for your customer interacting with your brand. Customers want to dictate their journey on their terms in the timeframe they prefer. The bar has been raised from having a single view of the customer to having a single understanding of the customer. So to join us here at Summit, you booked a ticket and embarked on a trip, perhaps on Delta. While the engagement during your travel can be personalized to some extent, in this case by the airline, that first-party data by itself provides a pretty limited understanding of your preferences and your plans. With data collaboration in a privacy-centric way, you can leverage third-party data to deliver a higher level of personalization for customers at every stage of the journey. For example, with context on your prior shopping behavior, hobbies, sweater preferences from other brands, the personalization and offers you receive will become much more relevant because of the broader understanding of you as the customer. And shortly, you will hear NBCUniversal demonstrate how they are seeing data collaboration shaping up in the context of media and entertainment.

Lastly, and very importantly, we must consider the impact of AI, emphasized yesterday during main stage and all this week. In the era of AI, we have to rethink digital experiences. As channels grow, customer needs are evolving. The implementation of AI will help to build and deliver experiences at a massive scale. AI is an efficient copilot empowering teams to rapidly sequence data models, optimize segments, and identify what offers will generate the most interest. AI will be infused in everything we touch on today from data engineering, audience curation, collaboration, and it will bring personalization to a new level. I'm so excited to hear Sundeep walk through how this is coming to life in Adobe's product portfolio.

Okay. We've covered a lot so far. But let me summarize. The frontier of the data foundation is expanding with collaboration and generative AI. Investment and integration of these emerging capabilities will be key. And you must keep your organization's role and business objectives in constant focus. When all of this is done right, it can be rocket fuel for your experiences, blasting off to better customer loyalty, higher revenue, and increased ROI. Adobe not only has the solutions to help you with this today but also has the roadmap to face the data challenges of tomorrow.

And now I'm so excited to welcome Ryan McConville from NBCUniversal to the stage. Ryan will bring all of this to life and more, showcasing how he and his team are harnessing the power of their data to personalize experiences at scale. Ryan.

[Ryan McConville] Thank you, Suzanne, and thanks to Adobe for having us here. So my name is Ryan McConville. I run app platforms and operations at NBCUniversal. I'm very excited today to talk about a new partnership that NBC has with Adobe's Real-Time CDP collaboration product. It's helping us evolve as a company beyond our traditional role as a TV company, as primarily a mass market reach vehicle, to one where we can personalize ads at scale for our TV viewers. But before I get into that, just some context setting. I'm sure all of you have heard of NBCUniversal before. But I'll give you a quick overview of the state of the state. We're actually three businesses. We have our TV and streaming business. NBC, the broadcast channel, was founded in 1926. So it's been around for almost 100 years. On top of our broadcast channel, however, we have 12 big cable channels that I'm sure you're familiar with across entertainment, like E!, and Bravo, News, MSNBC, CNBC, sports, like the Golf Channel, and of course, our flagship streaming product, Peacock, which last year was the fastest growing streaming app in the country. Outside of TV and streaming, we also have our films division. That's been around since 1912. It was actually the first major studio founded in the United States. We had a very good year last year. We were number 1 at the box office in 2023. Oppenheimer won seven Oscars, including Best Picture, Best Director, Best Actor, and a bunch more that I don't remember. But even outside of Oppenheimer, we won awards for holdovers, and we had really big global cultural hits with Fast & Furious X and the Super Mario Brothers.

And we use a lot of that IP then to also feed our parks business, which is our third business. And I actually was lucky enough to go to Osaka last year with my seven-year-old, not just to visit the park, but we were there for visiting family. And we were able to visit the park and see the new Super Mario Brothers World, and it is like crazy. You really feel like you're entering another world. And so all of these things sort of work in conjunction with our movies hitting our streaming platforms and then becoming experiences at the park to really create a consumer experience at scale. Now, in the age of Big Tech, I don't know if people think of TV companies as innovative companies, but you have to be pretty innovative to be around for 100 years. And so NBCU had a lot of firsts when it comes to video as a technology platform. It actually had the first live audience TV series with Howdy Doody. I'm not sure anyone here was around watching that in 1947, but maybe. Also, in 1948, we launched the first recurring news program, which is kind of crazy to think about how bludgeoned we are with news that didn't always exist, right? So we're the first to innovate there. In 1956, we innovated around color broadcasting. And in fact, the peacock colors of the peacock come from our innovations in television to bring color to the platform.

Fast forwarding to the modern day, earlier this year, we aired the largest streaming event in streaming largest live event-- Excuse me, in streaming history with the Dolphins chief exclusive game. It was actually the single largest day for Internet usage in US history, and 30% of the internet tuned in to watch the game. So we continue to innovate at scale. And the technology that sits underneath that is quite impressive. And so I encourage you, and I will throughout this presentation, to really rethink what TV of today is because it is much more of a technology driven platform than I think most people maybe think of it as historically. So that lands us at today, we reach 226 million adults monthly. We invest $26 billion annually in premium content. That's the most of any entertainment company in the world. We have the number one TV portfolio in total audience. And we have the largest daily ad supported reach of any video platform, that's including YouTube. So that's quite a lot of power. That power, I think, has been traditionally associated with the TV we experienced growing up, which was first and foremost a mass market vehicle. Right? Everyone gathered around the television with their families, and it was a one feed delivery to everyone in the country. And so the ad experience was everyone saw the same show at the same time, and you saw the same ads. That means my septuagenarian parents that live in Florida would see Pamper ads at the same time as my young family that has kids, and same time as the bachelor that we've captured here is watching television. Obviously, this was a very powerful medium and it's been very successful, but it had sort of downfalls. The ads weren't relevant to everyone. And then for advertisers, there was just a lot of waste, right? Because you had to target a national audience. And that kept certain advertisers and certain advertising budgets sort of disqualified from using television as a medium.

You fast forward to today, and the TV experience is very different. First of all, you can watch, "TV" on lots of different devices. In fact, my TV experience, because I have a two- and a seven-year-old, is largely relegated to watching my iPhone on the couch, while The Wiggles play on a 70-inch television screen in my living room. And I'm sure some of you can relate to that. But TV is now a digitized product, and it's a direct-to-consumer product. And that's a really key point. Because now, as a TV company, we're collecting directly data from subscribers. And that's allowing us to personalize the TV product. I came to NBCU five years ago, and I'd been in ad tech for much of my career. And a lot of my ad tech friends are like, "You're going to a TV company. Why are you doing that?" And I think, well, the answer was, because TV is about to change fundamentally, right? It's transforming into a product that is more personalized using data. It's more akin to your social feed. And I'll kind of prove that to you if it's not already obvious. If I were to come into your home and ask you for your Netflix login, you probably would hesitate before you give it to me. And the reason why is 'cause I can tell a lot about you by what Netflix is recommending to you in your feed. Same is true for any streaming platform, Peacock, HBO Max, Paramount Plus. They're using data to personalize the experience for you from a content perspective and from an advertising perspective. This is fundamental to how TV can benefit marketers in new ways. The ads can now be more relevant for consumers, and there's overall less waste in the marketing spend. So now, all of these individuals who get to watch the content they want to watch when they want to watch it are also seeing ads that are more relevant to them.

This is essentially bringing together two worlds that I think, historically, marketers-- and maybe even today some marketers think of as separate. There's the world of Big Tech. And Big Tech is associated with the use of data, the use of automation, and lower funnel performance. Right? But Big Tech has suffered a bit from a perception of user generated content, not always brand safe content. And it's consumed primarily on the small screen. Then you have the world of big media, which is essentially the flip of that. Right? So it's professionally produced content. Some of the biggest events in the world were home to the Olympics. These are like premier events that draw-- that create cultural moments and draw people in on the biggest screen in the home, these big glossy amazing television screens, like movie screens in your home. But the technology that's been used for targeting and for measurement for marketers has become outdated. Right? It's using panel-based measurement, sampling. It's measuring limited things like reach and frequency. Don't get me wrong, those things are important, but marketers now need more in this era of personalization. And I'll talk more about this Adobe partnership and the specifics of this Adobe partnership in a minute. But it's an example of how that's no longer a tradeoff. We've essentially brought these two worlds together in the TV of today, where you have the best premium content in the world sitting on top of a technology platform that's using first-party data, that's using automation, and that's able to measure performance at a much more granular level.

There's four big changes that I think marketers need to think about when they think about TV and the video platform of today. The first is in audiences. And I talked a little bit about this. In the TV of yesterday, you were limited to broad demographic targeting, so targeting of women 18 to 34 or adults 25 plus. Today, with our audience spine, we have profiles on over 200 million users. Those 200 million users can be connected to your data using privacy enhancing technologies like clean rooms in order to find the precise audience that you're looking for. Those could be recent visitors to your website, as we'll talk about in a second. Those could be people in market for certain products. And you can target just those users without all of the waste. The second is in activation and automation. So on the activation front, you have the manual process of the upfront, where there's a long negotiation with sales reps, the production cycle for commercials is sort of lengthy. We're shortening that process through automation. So our TV platform is now plugged into different DSPs, demand side platforms. So you can buy in an automated way over 30 different DSPs are plugged into Peacock. We also have a self-serve buying platform called Peacock Ad Manager, which starting this year will support credit card payments. So if you're a small business, you can go online, you can punch in your credit card, and you can buy TV ads. We're also making all of our content available in those platforms. So we just announced last week that, for the first time ever, we're democratizing access to the Olympics. That means any business, big or small, can log on and they can bid to have their commercial serve during the Olympics. This is very, very different than anything that's ever been available in the past. The ad experience. In traditional television, the ads have been relatively static. And I think if you ask people growing up if there are too many TV ads, they would probably say, "Yes." With the advent of streaming, we were able to rethink the ad experience completely. So Peacock has the lightest ad load in the entire industry. We never serve more than five minutes of ad per hour of content. That makes not just a better user experience, but the ads stand out more. We actually see in the research that people remember the ads. We actually have a hero ad that is one ad that plays and sort of brings you an entire movie. And those ads, the ad recall on those ads are much, much higher than any other ad format that we have. The ads are also interactive and commerce enabled. So we're starting to see TV transform into a sort of a purchase channel. Right? We saw this with the internet initially. When the internet launched, people said, "Are people going to buy over the internet?" Eventually, obviously, they did. We've seen that with Instagram. Social has become more of a commerce channel where you see things and buy them right away. We're starting to see this behavior in television. You may see QR codes that are attached to ads. I don't know if anyone's... Has anyone ever seen QR codes attached to ads? Yes, show of hands. People are scanning those and they're purchasing directly from the television. So the ad experience has evolved to become more performant. And then finally, measurement.

Everyone heard of the GRP? The GRP was the unit of measurement for television for many, many decades, a gross rating point. It basically said that you reach this many people, 18 to 34 or 25 plus. And that was sort of the primary currency. What we're seeing now with the use of data is that marketers can measure at a much more granular level. So they can tie precise number of app downloads, precise number of checkouts, precise number of website visits to their ad campaigns on television.

So you put these four things together, you have better targeting, you have better, more automated activation that can be done in real time, a better user experience so the ads stand out more and can drive commerce in real time outcomes. And then you can measure that at a granular level that shows performance, not just at the top of the funnel and brand awareness and reach but in the lower funnel.

This transformation in our company has not necessarily been easy. There's been a lot of change management, I think, that has gone on. So one thing, even when I got to the company just almost five years ago, technology, it's not like at Google where, like, product and engineer run the company. Technology, these companies, is almost thought of as IT, right? And so there's been a lot of effort to evolve product and engineering at a TV company to sort of lead actually the sales and product strategy to show that advanced targeting, advanced measurement can actually spur advertising sales.

We had to make big arguments for increased capex. Capital investment in an ad sales division for a long time was like order management systems to process TV orders. And we're sort of saying, "No, we have to invest in clean rooms." And our CFO is like, "What's a clean room?" Right? So there's been a lot of change management in explaining the value of those things. Recruiting. When you look inside a TV company today, you don't just find TV sales reps. You find data scientists, data operations, engineering, product managers. And it's been really exciting to witness that transformation.

And then finally, technology partnerships, which is the reason why we're here today.

We've evolved from this idea of there's vendors that service the TV business to striking technology partnerships that really grow value for our company and for our partners.

And that's exactly what we've done with Adobe. And they've been just amazing partners on this journey. So as I said earlier, we are now integrated with Adobe's Real-Time CDP collaboration product. And I'm going to tell you a little bit about how it works, and then you're going to see a much more expansive demo, I think, in a few minutes.

So if you're a marketer and you're using the CDP Adobe platform, and you have visitors that come to your website, what you'll soon be able to do with this partnership is understand not just that user's first-party behavior on your apps and websites and stores but you'll be able to look up in real time what their media consumption behavior is across NBCUniversal. So for example, if you have a million visitors to your website that come and abandon cart or just come for the first time, you can easily look up and see, wow, 300,000 of them are currently active watching streaming on Peacock. You can also see, you can segment them and find out what their interests are. "Oh, they're sports enthusiasts, or they watch comedy," or they're movie enthusiasts, or they like other genres, which are all available in the Adobe or Adobe AEP instance.

You can segment those customers, and then the idea here is that you can actually trigger personalized journeys. So imagine a world where, as Suzanne actually just went through, someone comes in and looks at a product and maybe they look at it twice and that triggers a text message or an email or maybe they look at it three times and that triggers a personalized TV message, right? These are kind of journeys that have not traditionally been part of the big, broad upfronts of TV planning. You can actually have an always-on CTV strategy that's part of a personalized journey that personalizes the experience for your customer.

So that personalized ad is pushed over to NBCU, and we show that ad to that user. The best part is, though, those ad exposures, that identity level ad exposure, that's built on first-party data is returned into the Adobe platform, and back into the clean room for you to look at and use in your measurement. So you can start to see the ad exposures I did on CTV. Did they drive someone back to the website? Did they drive someone back to purchase? You can start to calculate real return on ad spend. This is much different than the big MMM models that TV has historically done. And it's a whole new way to use CTV and television as a personalized marketing platform.

So the key summaries here that I really want the marketers in the room and the agencies in the room to take away is to not just think about television as a mass marketing vehicle, though it is very, very good at that, but to think of it now with our partnership with Adobe as a place where you can do real-time collaboration around your first party data to learn about your customers, how they consume media, and where you can find them on television.

To think about, just start to consider television as an always-on performance platform, more akin to what you're doing maybe with the social platforms, where it's part of the customer journey that they get served a CTV ad.

The best part about this is that, like, sort of as a fast follower in this space, like TV is not stumbling on some of the same privacy issues that I think hit the Big Tech companies early on. All of this is being done with authenticated first party data, not cookies. So it's futureproofed against privacy sandbox and other things like that. It's all being done using privacy-enhancing technologies like clean rooms. And it's all being done to create this really cool new TV ad experience, where the ads are personalized to you as you watch, and you, the marketer, are getting full funnel measurement.

So incredibly, incredibly exciting.

This beta is now live. We'd love to be testing more. You can also find me on LinkedIn.

And, yeah, we'd love to talk more and continue to learn together. So thank you so much for having me.

Thank you so much, Ryan. That was really, really exciting, both as a marketer and a consumer. So obviously, great story there about how you've partnered with Adobe around data collaboration in a privacy minded way to curate audiences. So I have to ask on behalf of this audience, what's next? What's the next frontier for NBCUniversal? Sure. Are you willing to share a little? - Please? - Yeah. Yes. And the answer to what's next to every question is AI. - Yes. - So... Ding. Correct. But in all seriousness, the demo yesterday with GenStudio was just amazing.

And what was demoed, actually, was the creation of all these personalized Facebook ads. And it kind of is to my point that I said today, I think what we're looking at in terms of the future is, how does AI lower the production costs and personalization of TV ads? Because if you kind of take this use case that we just went over and think about the ability to really showcase different flavors of a high production TV asset to users, imagine the power that you could get with that. I think it would also further democratize access to TV for smaller marketers because of the cost of producing TV commercials potentially comes down. I'd say also just on the AI front, we're employing a lot of AI models to improve the optimization so that we make sure we serve those ads to the people that are most likely to come back and purchase the product. So I think the application of AI will make the whole performance of TV work even better. Very cool. Can't wait to see that come to life as well. Thank you so much. It's been great to have you. - Yeah. Thanks so much. - Great job. Thank you.

So now if that wasn't enough, it's my honor now to introduce and welcome to the stage my colleague, Sundeep Parsa, Head of Adobe Product for Adobe Experience Platform and Applications. Sundeep.

[Sundeep Parsa] Hello, everybody. Ryan, that was an awesome presentation, and a huge fan of Oppenheimer. So hello, everyone. My name is Sundeep, and I'm so glad to be back here at Summit to share with you some of the cool innovations that we have in the world of data and personalization.

Suzanne walked all of us through the opportunity and the requirements to evolve your personalization strategy. And I'm so happy that we not only have a point of view but we also have the technology and the ecosystem to help you get there.

Now let me elaborate on how we're supporting the seven technology imperatives that Suzanne called out, starting with a unified profile backed by a fast lane for data.

Adobe Experience Platform's unique combination of Edge network services, a real-time profile, segmentation, and activation enables you to activate or engage with your customers in the moment and at scale.

We are processing over 5 billion Edge interactions, 17 trillion segment evaluations every single day. And we're delivering over 3 billion real-time offers every year, all in less than 100 milliseconds, 99.9% of the time.

Whoo! Yes. Thank you.

And by the way, we're doing this for customers across multiple industries, helping them reimagine many use cases, such as online interest to conversion, fan engagement in the moment in stadiums and arenas, and bridging physical to digital, like online order and in-store pickup, and making guest experiences memorable when we all have the strips.

Now let's talk about how we're expanding our product portfolio in a few different areas. Starting with unlocking value with your enterprise data, helping you leverage the massive investments you already made to create an enterprise view of the customer, and make it actionable in experienced workflows with minimal movement of data.

Now you also asked us to connect your customer profile in Experience Platform with other types of critical data and business signals. For example, store performance and retail, bookings data in travel and hospitality, portfolio performance data in financial services, and many more.

I'm so pleased that we're announcing federated audience composition in Adobe Experience Platform that's built with this specific mission in mind. It enables you to connect securely with your enterprise data... And I want to say the word again, securely... Through popular cloud data warehouses like Azure, Google, Amazon, Snowflake, Databricks, and also traditional data warehouses like Teradata that might still be running on premise.

With the appropriate access controls and enabling your marketing teams to interact with this data through an intuitive drag and drop interface.

Now the core capabilities of federated audience composition include enriching your customer profile with aggregate signals from all the raw data that's in your warehouse like a booking profile based on the last 90 days of travel history, combine people data with business entity data, like store performance, product performance, etcetera, when you're building your audiences. And to personalize omnichannel communications with relevant data points, like most recent purchases, upcoming subscription renewals, and more.

Now, all of this, you can do without bringing any of this data into Experience Platform. Now you can also control the scope and context within which this data is actioned. As an example, some of the data might only be needed in the context of a specific journey. And when the journey is done, that data view goes away.

Next, let's talk about audiences. Now, we all know that audiences is the core currency that is used in various parts of your marketing ecosystem, including Adobe applications.

Today, audiences are built and managed in multiple places, making it challenging to curate, to govern, and activate those audiences. With audience portal in Experience Platform, you can unify and curate your audiences to support the needs of your entire enterprise.

Now audience portal provides you a single pane of glass through which you can manage fast moving audiences that you need to activate in hundreds of milliseconds. We call them streaming audiences. On demand audiences that are time sensitive and need to be defined and built interactively.

External audiences that are built within your enterprise but need to be unified and governed for experience workflows. And last but not least, third-party audiences that are critical for your acquisition strategy.

Next, let's talk about measurement. Our goal is to drive the shortest possible path from insights to impact with a unified system of measurement.

We are streamlining the workflows between customer journey analytics and applications like Adobe Journey Optimizer to give journey managers the context and the insights that they need.

At the same time, we also provide a single-click launch into customer journey analytics to enable the data analysts that need to do deeper inspection.

We are also releasing expanded functionality in customer journey analytics to support audience analysis and content analysis to drive faster insights to engagement.

Now, once you have a single place to curate all your audiences, you can also collaborate with your partners for audience expansion and reach across paid media channels and emerging channels like connected TV, like Ryan just talked to us about.

Now to that end, we're also announcing Real-Time CDP collaboration, a new data clean room agnostic solution that is expanding and evolving the value of our CDP.

We believe that data collaboration is a necessary component of customer data management in a world without third-party cookies.

Now brands and publishers can better collaborate to discover, reach, and measure the impact of their high value audiences in a privacy minded manner.

Now, Real-Time CDP collaboration will maximize the value and extensibility of your first-party data. It'll work with your existing technology infrastructure. It'll enable you to utilize data and identity partners of your choosing and connect you with top publishers to meet your advertising goals.

It's built for marketers with an intuitive user interface to activate audiences seamlessly.

And with closed loop measurement that goes beyond your ad tech use cases and gives you a full funnel understanding of your marketing investments.

Now, last but not least, let's talk about the role of generative AI to supercharge productivity, to further democratize access and to create time and space for your teams to spur new ideas. As you heard in the keynote yesterday, we talked about our upcoming capability, Adobe Experience Platform AI Assistant that's integrated into our applications to answer questions through an intuitive conversation interface, to automate tasks, to reduce learning curve for your users, to simulate journey outcomes, and to fast-track ideation to activation, and also to generate new audiences and new journeys based on your business goals.

In summary, I want to thank you for your partnership, your collaboration, and your investments. We are on this journey as your technology partner on your personalization at scale mission by making the required investments in our Adobe Experience Platform and applications.

Now I'm a product guy. And I tell my team, the product is the protagonist, not PowerPoint. So let's see some of this innovation in action. And I want to invite Rakhi Patel onto the stage to give us an awesome demo. Rakhi.

[Rakhi Patel] Thank you so much, Sundeep. And before I get started, I wanted to thank both General Motors and NBCUniversal for allowing us to use their brands in today's demo and wanted to let you know that the data you'll see is completely fictitious in order to respect the privacy of their consumers. And with that, ride shotgun with me as I bring Adobe Experience Cloud innovations to life to unlock the power of data as fuel for personalization at scale. - How's that sound? - Rakhi, I have to tell the audience. So Rakhi said, "Let's make this interactive." And I said, "I'm a really bad backseat driver." So in case if I throw her off her game, it's all my fault. So, Rakhi, let's get going. Thank you. Thank you for that disclaimer. So, Sundeep, you talked about multifaceted data as well as fast moving data and how to bring that to action.

Let's take a look at what that could look like as an omnichannel journey with me as the consumer. - Does that work? - Yep. Let's do it. All right, so there's been a lot of volatile weather around the country this year. And I live near the Sierras, and there's been a ton of snow. Silver lining, I can do more snowboarding weekends. But I do need a better SUV to navigate through the mountains. I'm from California. We're not really good at driving through snow. I've heard that the Chevy Trax is pretty cool. I'm going to head to their website and build and price a model. It's less than 25k. Sundeep, I think I can swing that. So I'm going to go ahead and email this quote to myself. That looks compelling.

And I get the email right away with an invitation for a test drive. Now, we all know life happens, and emails get buried. Also, I kind of have snowy mountains on my mind, and this creative looks very sunny. And so perhaps it's just not working for me right now.

All right. So it's a couple days later. I am back home after a really big project in Las Vegas, and I'm looking to binge-watch some TV through my Peacock subscription.

So as I look through the subscription, oh, gosh, I'm going to pause. There's an ad for the Chevy Trax. I forgot to schedule that test drive. I'm going to go ahead and take care of that right now 'cause it snowed about a foot last weekend, so I need to get my act together.

I can see my basic quote right away, and let's check it out to see what the details are. It looks pretty good. Alright, so I'm gonna locate a dealer and find one near me. I'll enter my zip code.

And right away, I'll just go ahead and schedule that test drive. We'll pick a date and time, and we're ready to go. So, Sundeep, as a prospect for General Motors, specifically for the Chevy Trax line, I went from digital to dealership within a matter of days. That's awesome. By the way, as marketing tech provider, I always complete my transactions.

Now that was awesome, right? So many of us in the audience, that's what we do, right, so to create those seamless experiences for the customers that we serve. But you and I know, and we all know, right, there's a lot more complexity, right, if you can appeal the onion, if you look behind the curtain, right? - So let's bring you back into the office. - Okay. Can you play the role of a marketer now? Okay. And show us how AI assistant can be your copilot, right, and supercharge your productivity, and help us build audiences. Absolutely. I'm happy to shift gears from consumer to marketer. And I'm gonna leverage AI assistant to create, navigate, and enrich audiences through Adobe Real-Time CDP.

Now, my team has already built a broad audience of build your own prospects. So we're going to call them BYO, not to be confused with BYOBBTW. And I'm going to enlist an AI assistant to help me find this audience because as you can see, we have thousands of audiences, right? All right. So hopefully, it can find it. And that means I won't be able to... I won't have to sift through a bunch of data myself and do a lot of manual work. And it's going through that data and platform. And voila, it was able to find it right away. And it's already been activated to multiple destinations. That has saved me a ton of time. Now this is great for broad reach, but we want to personalize experiences, right? So it'd be interesting to know who in this broad audience is interested in which type of car model. Let's see if there's a field that exists with a list of car models in GM's portfolio. I could avoid a lot of human error by finding it here versus trying to create it myself.

So again, it's navigating through information in the background and, again, amazing. The field exists. So now I'm going to just go ahead and ask for one more thing, to have the BYO audience filtered by car models.

And within minutes, as it's navigating through the background, creating filters and audiences, Sundeep, dozens of audiences in seconds. - That is cool. - How amazing. Now I've been a data engineer half my life and I've been swimming in data trying to find fields, so that is cool. I want that. So, Rakhi, that was awesome. Hopefully, you all agree with that.

So, Rakhi, now I'm gonna make this a bit more interesting. Sure. Right, so you talked about contextual insights, whatnot, right? And you talked about making enterprise data actionable. Wouldn't it be cool if I bring some of the inventory signals into those audiences? It would be so cool. But please do remember, right, so inventory signals are always a state of flux, right? So can you now bring those signals from the enterprise warehouse into your audiences? Absolutely. And I'm guessing you want to make sure I do that with minimum data movement and copy? I just said that, minimal movement of data. Yes.

All right. So I'm going to go ahead and go to Federated Audience Composition to get that ready. We'll go ahead and start building the audience to enrich. I'll get the process started. I'm going to go ahead and also select the library of BYO audiences I just created. And then we'll start the enrichment process. So here I will now see the data that I'm allowed to have access to enrich information. And, Sundeep, you can also see I don't have any access to the vast amount of data that's stored in GM's data warehouse. My admin made sure that I only have access to the data I need to do my job. All right, so I'm going to go ahead and take care of that and enrich this audience with the dealer information. I'll go ahead and update the audience. And now all of the audiences I just created earlier have been enriched with dealership inventory data. I'm going to go ahead and keep working with my trusty AI assistant to now activate those audiences at scale. And as it's working to do that, it's gonna ask me... Yep. It's gonna ask me to confirm. It wants to make sure. And we will be ready to go. So with that, we were able to now kind of close the loop on our audience strategy for digital to dealership, and that's pretty exciting. Now, that's super cool. And that was a subtle point, right? But I'm sure your admin had to wait through hundreds or thousands of tables in warehouses, right, to just give you the views that you need to get your job done. - So thank you. - Right. By the way, do you have an engineering degree? No. But I'm so glad that our engineers are so good that they made this very intuitive UI for me to use and adapt. And my husband's an engineer, so we already have enough engineers in the family. I don't blame you. I get that too at home, by the way. Okay? So I'm gonna now ask you to switch roles again and be a journey manager, right? So be you built all these amazing audiences that can drive personalized experiences. Can you become a journey manager now and bring these to life in a journey? You also have an AI assistant, right, to work with you. And by the way, Suzanne told me about DJ Diesel. So she's saying let's get ready. Chop-chop. So let's pick email as a channel and bring this to life. That sounds great. And, yeah... I think Rakhi's thinking, "This guy's an obnoxious boss now, pushing me." I don't have any experience in journey management, but I got you. I'll take care of it. I'm at Adobe Journey Optimizer. And here I can see some creative that we've built. And with the volatile weather patterns, we may want to test some different creative, right? So I'm going to use some features from Gen AI to create variants of this specific copy. And it will generate different aspects of copy for me related to winter vibes. All right, so I'll add a prompt to give me some more winter vibes. And then it'll go ahead and generate.

I'll go ahead and select these three variants that were generated and add these treatments. And now my email copy has been generated. Now I also want to update this creative. And I know, Sundeep, you said you were in a hurry. So I'm going to use Firefly. And I'm gonna be a little more blunt, with Firefly, I had bit of a more conversation with my AI assistant. We'll go ahead and generate. And these are some beautiful images that resonate with me, at least much better when I was a consumer. So I'm gonna grab this one, use this content. And now we've created audiences, leveraged data to unlock personalization, and now we have experiences to share with them.

That was super fast. You know what? I almost got a whiplash. You see, I'm still trying. You're doing great. No, seriously, you've done an amazing job. You've covered a lot of ground, data to enterprise data, to audiences, to journeys, right? So now let's bring this full loop. Right? What can you share with us about insights, which we call the flux capacitor, right, of customer journey management? Well, I am so excited to take you back to the future.

So as marketers, we're always looking for ways to access information. And we sort of fast track the context of data to business intelligence or analysis and things like that. But we also need to expedite access to all of that data so we can make decisions quickly. And now, with a tight connectivity across Adobe Experience Platform applications, analysis will become even more interoperable thanks to a unified layer of measurement across these solutions. Here, you'll see that I'm in Journey Optimizer. I can learn more about the audience we just created. And then check this out. I'll open Customer Journey Analytics. It's also taking its time there, and I can see it's the similar report and understand journeys surface through Customer Journey Analytics. In addition, my product managers can get access to a feature called Product Analytics to understand adoption of different features. For example, for the General Motors team, they may want to know a little bit more about... There you go. A little bit more about their mobile app and how they should update their roadmap. So this matrix right here shows a list of different features, and they can understand who uses, for example, remote start or climate control and so on. They can save the insights...

And then use those insights to continue to build their product and optimize. That's awesome, Rakhi. I think you should get a raise. Wait. That was not in my cue card last night. So, Rakhi, you playing games with me? - I don't know who wrote that. - Oh, my god. So this demo became super expensive super fast. So you gotta give us more, Rakhi. - All right. - So what more do you have for us? All right, so I know what you're all potentially thinking. Are we there yet? Almost. I promise. So how powerful would it be if you could understand your customer more holistically, right? For example, comedy fans who are interested in a certain car model.

Now I'm really excited to share that this will be made possible by... Sundeep, any guesses? What? I think I'm in a drinking game with my team members. I've told them you got to say this word 50 times by Wednesday. - Is it RT CDP collaboration? - Yes. - But we say Real-Time CDP. - Real-Time CDP collaboration.

- Thank you. - No problem. So let's go ahead and head to Real-Time CDP collaboration. And this is a clean room application that will enable advertisers and publishers to have a digital handshake in a privacy minded environment all without sharing any underlying customer data. Advertisers will be able to work with premium publishers, such as NBCUniversal, create projects with use cases, such as customer acquisition or retargeting. They can also define their partnership parameters. Perhaps they want to share audience insights, audiences themselves, or measurement.

Within audience insights, we'll be able to run overlap reports with broad audiences or refine them a little bit more. Let's see how the overlap looks with the Chevy Trax audience with the entire NBCUniversal audience. Interesting, right? Half of them may be interested in a Chevy Trax. We can also discover audiences. Here in this example, we see all the content genres from our publisher. And we can take our audience and have that set of genres filtered by that audience and then activate directly in the UI.

So now let's say that the campaign's been around for a while, and we want to see how it performs. And we'll be able to do that via a comprehensive dashboard. So with Real-Time CDP collaboration, you'll be able to discover, reach, and measure audiences in an innovative way in a privacy minded environment and in a revolutionary way to find and attract new customers. And out of the 50 demos that you've probably seen, that one's your favorite, right? - Oh, definitely. That was the best. - Definitely. So I start by talking about fast lane for data and everything that you've shown. It feels like I'm in a carpool lane with data trying to get to my destination faster. - So do I. - Let me try one more time. So thank you. Thank you, Rakhi, for that awesome demo. Please give it up for Rakhi.

So I'm gonna ask...

Please, please try these innovations. Put them to work. Right? So make the data work for you across acquisition, engagement, and retention, all the other use cases. - Rakhi, do you have any parting thoughts? - I do. First, I just want to thank you all for going on that journey with us, and you especially for being a good sport, Sundeep, with being punny with me. I tried to be punny. Yes. And as you're all getting to know Adobe Experience Cloud in these innovations, I hope that you now are feeling more confident to take the wheel. Thank you.

Great job. Thank you.

Wow. Thank you, Rakhi. That was an amazing demo. It's so hard to do the live demos. And that was really, really exciting. Sharing some amazing stuff. And of course, Sundeep, thank you for sharing Adobe's vision and strategy for all things data and personalization. So remember, no matter where you are in your journey toward personalization at scale, you're going to have different opportunities. And as you progress in this journey, you'll get better at personalization, but you'll also find yourself needing more scale and more speed to meet the demands of your customers. At Adobe, I want to emphasize our commitment to partnering with you. Our leading technology combined with our team of dedicated experts is here to support you in implementing and delivering this data foundation to enhance personalization and drive your business growth. Together, we can achieve remarkable results and conquer that next frontier. So thank you for being a part of this journey with us. And please enjoy the rest of this amazing Adobe Summit. Thank you.

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