[Music] [Alyssa Espiritu] Hello, and welcome to our session Drive Intelligent Activation and Effective Marketing at Scale with AI in Real-Time CDP. Thank you so much for taking the time to join us today. My name is Alyssa Espiritu. I'm a Sr. Product Marketing Manager for Adobe Real-Time CDP, and I'll have Horia introduce himself. [Horia Galatanu] Hi, everybody. I'm Horia Galatanu. I'm a Director of Product Management in Adobe Experience Platform, specifically focusing on our AI and ML initiatives. Amazing. Before we get started, let's go over some outcomes for this session and maybe what you can expect. So in this session, you'll learn about our powerful out of the box AI capabilities within Real-Time CDP. You'll understand the additional value AI can provide to your day-to-day roles and impact your overall business. But stay tuned as Horia will be showing us an exciting demo within the UI. And no matter where you are in your AI adoption journey, we can help you to get started today.
But first, let's just level set on how AI is changing the way businesses operate. Ultimately, marketers need to do more with less. And you may be experiencing this yourselves within your day-to-day roles. Channels are proliferating, content demand is exploding, data is more fragmented than ever, and budgets are under question, of course. Meanwhile, consumer expectations are continuing to rise. So content teams need to create much more content than they're able to today. Website teams are short on capacity, and audience specialists need to create, sometimes millions of granular segments. So to make this tangible, increasing AI innovations can really amplify the power of human ingenuity and the way that we work. So that's why Adobe has delivered predictive and generative AI across our applications for content, data and journeys, and we are looking forward to our evolution of our tools by bringing agents into the forefront as well.
So by adopting powerful AI capabilities, you'll be able to realize more value from your Real-Time CDP investments. So for example, AI tools will allow you to work much faster to meet the demands of customer experiences. You will be able to minimize workloads among your martech teams be more productive and ultimately scale your marketing efforts. And then lastly, with the help of predictive AI and soon AI agents, you will be able to optimize your audiences and uncover these valuable insights that you may not have been able to recognize before. And you'll see that in the demo that Horia will show you later on.
And so now with all of this buzz and demand for adopting AI tools, you may have received pressure to start applying and using AI in your role or in your organization today. And so yes, it's true with quotes like this. More and more businesses are adopting AI capabilities. But don't be afraid because Adobe is here to help you get started wherever you are in your AI adoption journey. So that's whether you're just starting to play around with predictive AI capabilities, or if you're looking for more advanced AI technology that can help you propel in your day-to-day role and make an impact to your business.
And so we're here to guide you through how AI capabilities can give you a sense of what's available, so you can get started today. We've had predictive AI capabilities within our application, starting even over a decade ago. And here are some of our most popular existing capabilities, really available to everyone who has a license to Real-Time CDP.
Now if you're a B2C organization and you haven't heard of Customer AI, it's an embedded feature in Real-Time CDP that enables marketers to generate these individual level propensity scores for a specific outcome, such as churn or conversion. And you can leverage these propensity scores and propensity models for stronger segmentation and personalization. So here are some use cases. For one, you could leverage customer AI for engagement purposes in your marketing campaigns. By understanding behaviors like the likelihood a customer will perform a specific action when they interact with your brand. You can also predict who is likely to purchase specific products or services and use these high value audiences for targeted campaigns to drive conversion. And then lastly, Customer AI comes in very handy with retention as well. And you can understand which audiences may be likely to churn. And then what you could do is leverage these propensities to reach customers with a personalized call to action, for example.
Another powerful predictive AI capability available to B2C workflows is look-alike audiences. So while Customer AI is used to predict behaviors, look-alike audiences, on the other hand are used for expanding your high-value audiences. So machine learning models create influential factors and similarity graphs with your audiences. And you can identify and create audiences that can target additional customers who are similar to your high-performing or previously converted customers. So for example, you can use look-alike audiences to even identify marketing blind spots by understanding factors that influence certain conversions. You can also find more of your best customers by discovering similar high-value profiles, and then also drive more cross-sells and upsells by targeting the right customers who are most similar to others who have previously converted.
Switching gears a bit, on the other hand, we also have AI capabilities for B2B use cases. So if you're a B2B customer, you can use some of these capabilities to drive sales from account-based marketing. We have lead to account matching, where you can discover buying groups by automatically matching lead profiles to the right accounts. We also have predictive lead and account scoring, and you could use it to advance through your sales stages by predicting the likelihood that certain accounts will convert. And ultimately these capabilities allow you to engage with potential leads from target accounts much sooner in your sales cycle and help you prioritize accounts to maximize return on investment. So these were just a quick overview on our predictive AI capabilities that are available for you today to take advantage of.
Now let's switch gears and talk about additional GenAI tools that build upon our predictive models. And we'll also get a sneak peek into additional capabilities powered by AI agents that we will be releasing later on.
Now first, to boost practitioner productivity, we launched AI Assistant, and you might have heard of it about a year ago. If you're just learning about our AI capabilities, AI Assistant is a valuable and easy tool to use to get started today. So it's a very conversational interface. It's a conversational tool powered by GenAI, and it allows you to learn about product capabilities to deepen your product knowledge and skills. So for example, you can ask AI Assistant, "How do I get started with look-alike audiences? Or how do I get started with Customer AI today I want to learn more?" Second, you can also interact with AI Assistant to uncover valuable insights into your audience data and business objects. And you'll also see that in the demo that Horia will show you as well.
Lastly, AI Assistant can also help you create and iterate on content. And so since we've launched AI Assistant, we've seen great business impact and value. Its help streamline operations, saving valuable time for our customers, and really empowers our users to make data-driven decisions and run more targeted campaigns. This year, we're also working to evolve our AI capabilities to also include audience agents. And agents are intelligent operators that will be able to interpret goals, create plans, and take actions across Experience Platform applications. So in the future, these agents will act autonomously, and be able to take actions on behalf of the people that they're working with and working for.
And so with that, let's actually see this all in action in a demo. And I'm going to kick it off to Horia.
Hi, I'm Horia and I'm a marketer at a big retail company. My primary focus is on audiences. And as a result my days are very busy. I have a lot of things to do. The good news is that since I've been using AI Assistant for Adobe Experience Platform, I've been a lot more productive, and this has given me time to work on creative new ways to use our data and our audiences. So let me show you a few moments of my day and how AI Assistant is helping me. Now the first thing I want to do in the morning is just look at my audiences and figure out if something has happened in the last period or not. So in the past, that used to be a very tedious process involving a lot of manual work. Now I can just ask AI Assistant.
I'm going to ask it to show me the audiences with the size change compared to a 14-day average, and sort them by current size 'cause I really want to look at the big audiences that I have. It's giving me this nice table here. It explains to me how the results have been provided, which is very important 'cause I've always double-check this and I can look at this big table and at a glance, everything still seems to be working fine, which is great. And in the future, Adobe is telling me that this will be something that I don't even need to ask anymore, something that the system will do on my behalf and it will notify me if something has gone wrong. Talk about offloading work. That's going to be a game changer. Now one of the things I also have on my morning to-do list is look at this recent website visitor audience. Now that's an audience that we will be using more and more. And it's the primary audience for a new upcoming campaign that we have. So I want to look at historical trends for it and figure out if it varies a lot or what are the trends. So I'm going to ask you to show me a historical average size in the last six months. Great. AI Assistant gave me this, the details that I was looking for. So I can see there's an upward trend. By the way, I can download this in the CSV file and play around with it in Excel, but this is pretty good. I have a good idea of what it has done in the past. Now before I go to my meeting with my colleagues to tell them about this, I know that the AI Assistant also has a new capability that would allow me to forecast this, the audience size as well, so I can have not only a past view, but a future view as well. I'm going to ask AI Assistant for this information as well.
Great. It's giving me a quick answer. I can again open up this table and see that it is predicting a slight increase in the audience. I can see where the forecast date is. And I've also see the forecast range. So it can tells me how confident it is in this prediction. Now this is great. Now before I wrap up my morning task, there's one last thing that I want to do. We have a new problem in the department, and that is managing communication fatigue. Some users have been getting too many messages, and it's not a great experience for them. And the problem with fatigue comes down to audience targeting with the same users being used in multiple audiences. Now I know that a lot of messages are going out for the social media engagers. And I'm curious for the recent website visitor's audience, what's the overlap between the two of them? Can AI Assistant help me with this? Okay, great. It has given me the answer that I was looking for.
I can see that the overlap is actually very significant. So this would be something that I need to tell my team about. And we'll need to adjust how we think about this campaign and going forward.
Now that I've handled my urgent work items in the morning, there's one thing I want to look at which is creating highly targeted audiences. I know that the AI Assistant has some new capabilities here, helping me create the machine learning model that can identify users that I'm really interested in. So let me use this for the next campaign. And that campaign is really trying to sell some Smart TVs. I don't have a model for it, and the data science team is busy for the next three months, so let me see if I can help. So I'm just going to ask it, "Hey, help me build an audience of 100,000 profiles for selling Smart TVs over the next 30 days." Great. It's telling me that it does. It can help me with it. And it's giving me a high-level plan that involves identifying the data that's going to be used, training a predictive model based on this, and then finally creating an audience that will use the model. This looks great. So I'm going to let it proceed. So please proceed...
With the plan.
Okay, great. It has managed to successfully train a model. It's telling me about the time frame. It's telling me the sample size that it used. And a lot of other few interesting details. Now I'm fairly technical, so I can use this information and at a glance I can understand that this model seems to have a good predictive power. So this gives me confidence that I can use this to actually create the audience that I want. So yes, please. Proceed with building the audience that I want.
Fantastic. It has given me the audience that I was looking for. It's telling me that it has, the audience size is 100,000 profiles, as I wanted. It has a conversion rate of about 3,100 profiles, which is better than I was expecting. So this is actually pretty good. And it's telling me that it has high confidence in the model. And I do have high confidence in this. But still, I would like to understand a bit more. How did you come up with this? I want to ask you to give you a bit more information about how we came up with this. So it's telling me about the input data that it used. It's telling me about the confidence rationale that we discussed before. And very interestingly, it tells me about the key factors that were influencing the prediction, which includes people who were on that product page but did not make a purchase, people with multiple purchases, and people who just visited my website in the last 90 days. This is absolutely great. I don't need more details.
This is really been great. And this is going to be a game changer for me in terms of working with audiences. I know that when I use a highly targeted audience, not only do I improve my campaign results, but I also reduce message fatigue, and I was limited in the amount of times I could do that. But now I can apply this much more widely, and it's going to have a huge impact into how I run my business.
Well, I hope this shows you, when I was mentioning at the beginning that the AI Assistant is making me more productive and allowing me time to creatively think why I said that. I can't believe how much I accomplished today. Not only did I manage my day-to-day tasks, but I've also created a new, highly optimized audience. And this is just the beginning. AI Assistant really allows me to free up my time so I can focus on reducing fatigue, uncover valuable insights, and deliver standout personalized experiences. And this is all happening in a fast and easy way that I wasn't able to do before. I'm so excited about this, and I can't wait to see what they're going to come up with next.
Now that you've seen how AI Assistant works, here are some examples of how this combination of predictive AI, generative AI, and agents will benefit you and your teams. First, you can optimize your audience strategies by uncovering new and valuable audience insights, and these insights will allow you to identify marketing opportunities that drive more effective campaigns. Second, with these tools, we can work much faster and have additional capacity to focus on strategic and creative initiatives like the opportunities I was referencing before. And not only that, but AI agents, as Alyssa was mentioning, will act as a force multiplier for you and your teams and help you proactively manage and operate your audiences, and this allows you to unlock a new level of scale for your personalization efforts. And all of this has been built with trust, privacy and verifiability in mind to ensure responsible handling and the appropriate safeguards with customer data, so that you can deploy this at scale across all your teams.
But don't take our word for it. Since we launched the AI Assistant, our customers have started seeing value across multiple teams and use cases when interacting with this tool. Just look at these numbers. We've seen tremendous improvement with productivity and efficiency for users across data, audience, and journey management use cases. So much time has been saved for managing schemas, uncovering audience insights, and managing journey inventory. And this is just the beginning. So with that, I'll give it back to Alyssa to close out the rest of the presentation. Amazing. Thank you, Horia, for the awesome demo. And it's exciting to see those value metrics come to life as well. And so as we wrap up, I encourage you to start implementing these AI capabilities in your roles, if you haven't already because now is the time. Our AI models and capabilities are built to expand upon one another as use cases are continuously evolving. And since every organization's data models are specific to their business, you will get better long-term results and compounded value the sooner you start running AI models against your business data. So by using our predictive and generative AI tools available to you today, you can one, master your product skills, increase productivity across the organization, including in your own role, discover new and valuable insights from your audience data, and ultimately work much faster to scale personalization efforts.
Lastly, please check out some of these resources to learn how to get started with AI Assistant today. Or if you're interested in joining our feedback program as we shape the future of our AI tools. So check out these QR codes. We have a lot of very helpful and comprehensive information online as well on Experience League if you want to learn more about our AI tools today. So thank you so much for joining us, and we hope you have a great rest of your day. [Music]
