Adobe Experience Platform Agents for improved marketing efficiency and better business outcomes

Transcript

Hello, and welcome to Experience League Live, Adobe’s practitioner focused webinar, where we try to have a little fun. I’m Daniel Wright, Senior Technical Marketing Engineer. And today’s episode, AEP Agents for Improved Marketing Efficiency and Better Business Outcomes.

There’s been a lot of interest in our recent episodes on AI agents, and today’s episode is not going to disappoint. We have two really fantastic guests. I’m so excited for this episode. I even rolled the lint off of my Experience League Live t-shirt. Thank you.

Our first guest is from a family where everybody is a software engineer. Please welcome Senior Vice President of Engineering Anjul Bhambri.

Welcome Anjul. And our second guest is from a family where everybody is a dentist. Fortunately for us, she broke the mold. Please welcome Director of Experience Cloud Evangelism, Gina Casagrande.

So Anjul, how does this happen in a family? Everybody being a software engineer. Is this genetic? Is it by accident? Or was this due to some, dare I say, parental programming? It’s certainly not genetic. So it’s accidental.

And my husband and I, we met when we went to the School of Engineering in India. And then I guess our daughter took after us because, you know, as engineers, you’re always trained to be self-reliant, right? Nobody in the house helps each other because it’s like, you can do this yourself. So I guess that’s how she got trained from the beginning. And then, yes, she went on the same path. That’s great. And I bet, you know, having kids, especially when they get to be teenagers, they like to challenge you. And, you know, maybe it’s good having a child who’s challenging you on technology trends.

Certainly, and certainly these days, right? With AI and she’s a software engineer in a practicing software, right? So now it’s like, hey, I don’t have to write all this code by myself. I have, you know, she has CLOD and Codex and Gemini and, you know, you name it.

Gina, your fun fact made me wonder, what if all of us were like the Casagrandes and took just two minutes twice a day to not only think about our dental hygiene, but also our loved ones. And the thing you told me, you told me that your niece is also your personal dentist, your niece.

We talk a lot about interest in digital marketing, but this is at a whole other level, not only because it’s a, but also you have entrusted someone from a younger generation with your medical care. And that is a big moment in life when you take that step. We need to do more to celebrate these generational transitions.

Anyway, so let’s get started.

So during the show, you’re encouraged to ask questions in the comments. Adobe team members will be there to answer and some questions might be saved for the end of the show. Gina has a demo that she’ll share later and Anjul, let’s start with you. So to set the stage for everyone, can you walk us through how technology has evolved to bring us to AI agents? Thank you, Daniel. I mean, I think everyone would agree that this has been quite a journey and, you know, just stepping back and looking at, you know, how we got here, there have obviously been many transitions in this quest for intelligence. And I love to use the framework from Andrey Karpathy, you know, one of the most respected voices in the eye that I’m going to use. And this framework actually breaks us down into three phases.

First is what he refers to as software 1.0, which is the rule based error, where we wrote, you know, logic by hand, all the if this, then that.

This is, you know, it’s been a pretty powerful framework. But, you know, we would all agree it’s been it’s, you know, rule based is always very rigid, and you really have to know exactly what you’re looking for, and then write the code.

Then really came software 2.0, which is the machine learning era. And instead of programming rules, we train the models on data. So systems could, you know, predict, classify, detect patterns. Again, a major leap, but still largely analytical is what everybody would agree. And now we are in software 3.0, you know, which is really the generative era, where models can understand they can produce, they can produce language, they can produce images, code, video.

And they interact in ways that we’ve all seen feels natural, it feels pretty human.

And I would say the leap happened, really, Daniel, and you know, all of us in the audience shifts, right? There’s a massive data, the powerful compute, and, of course, the breakthrough in neural architectures, which really, you know, brought us to foundation models. And of course, the key is that they don’t just generate content, they also generate instructions. And so when you combine instruction generation with the ability to execute those instructions, that’s when you get agents. So agents haven’t been a sudden disruption, they are kind of like the next logical step, right? And so we’ve seen the evolution from rule based to machine learning, to generative systems that can reason act. And it’s really the shift from, you know, automation to autonomy. And here we all use we’ve been using, you know, Chad GPT, Gemini, coding agents.

Now, OpenClaw as a personal assistant, right, has been another breakthrough. And they’re just many innovations that are coming out every day. And of course, they are having an impact across disciplines, right, like engineering, right, but coding agents across even like HR, finance, legal, marketing, and I think it’s just going to continue.

And how is Adobe bringing these innovations for brands, marketing teams and driving impact today? Yeah, you know, at Adobe, we see the shift as it’s more than opportunity and, you know, a capability, right? Because as technology creators, and as innovators in the creative and marketing space, we play that both of those roles. And we are bringing intelligence into our software or applications by infusing these generative AI capabilities into existing applications. And, you know, what we sometimes call as a co pilot model.

So that’s, you know, exactly what we’ve done with Adobe AI assistant.

And we have embedded this AI assistant across our marketing and customer experience applications like experience platform, our CDP, our campaign management applications like journey optimizer, analytics, experience manager work front.

And the AI system really helps the marketing practitioners, you know, generate insights, content, automate workflows, right within the application, as well as across the applications that they already use.

We’ve also reimagined the user experience, right. So in addition to your typical modes of interactions, which has been through, you know, mouse clicks, and keyboard taps and screens, AI assistant really allows you to talk to the system.

Go through a, you know, natural language interface, which I think will serve as the predominant interaction mode. And then behind the scenes there, the AI assistant is powered by AI agent orchestrator, which manages the coordination across multiple AI agents across the LLMs and the tools.

Now, some of these agents are built by us. And some of the agents could be built by, you know, the audience that we have today, which is like our customers, our partners, and our purpose built agents will enable you to generate content, audiences, journeys, experiments, like tons of experiments, experiment with, you know, and analyze the performance of these, and then help you optimize.

So, you know, when you look at all of this, we’ve really built an open ecosystem, right, that our customers and partners, they can bring in their own agents, whether it’s for booking support, ecommerce, you know, whatever else, you know, they need for, for these engaging customer, you know, consumer journeys of, you know, they, it’s an open system, and in their own agents, you know, they work seamlessly with Adobe’s AI agents.

And, you know, the other aspect is that all these agents collectively and their work can show up in different surfaces, with Adobe’s AI assistant just being one of those. So the, you know, the conversation experience will now span context and generate output, from Adobe, as well as, you know, your own tech or customers own tech.

So it’s a, it’s a, you know, fully extensible.

It’s an ecosystem enabling deep customization, interoperability.

And, you know, I think I’ve talked enough, I really want now, you know, our audience to really see a live demo of how Adobe’s internal marketing team is putting these agents to work to deliver these, you know, end to end use cases, all the way from intent to execution to insight. So maybe we should bring on Gina at this point.

Great. Well, thank you, Anjul. And as Anjul said, Adobe is enabling enterprises to effectively combine creativity, marketing and AI to deliver personalized, connected digital experiences in real time. And Adobe Experience Platform agents amplify human potential every step of the way. But don’t just take my word for it. You can all try it yourself today. Let’s jump in and I’ll show you. So when I log into Adobe Experience Cloud, I now see that I have access to Experience Platform agents through our AI assistant. It’s amazing. And let’s try it out. Now, I’m going to play the role of a marketer at Adobe.com. And I’m brought directly into this immersive AI assistant conversational interface where I can see some of the out of the box prompts to get me started. And here in this prompt library, I can even filter by some of these goal category, the application or role. So it’s really tailored based on the underlying applications and capabilities that I have access to today. Since I’m a marketer at Adobe working on our spring refresh campaign for Firefly, I first want to understand events from last month so I can have an understanding of how engaged our customers are currently. I can simply trend events straight from here using this out of the box suggested prompts.

And very cool. I don’t have to ask a business analyst for this data, which could take days to get back to me with the data I need is surfaced right here for me in this visualization and it’s instantaneous. I love it. I can see I have a task right here, a notification, and it looks like I asked to update the Firefly homepage with the springtime feel.

I typically go to another application to get more context on this task, but I can simply ask AI assistant to pull up the project summary from here. So I’ll ask to give a summary of the spring refresh project.

And here we go. Behind the scenes, agent orchestrator coordinates the right AI agents to get this work done. And I can see all of the context for this campaign project, including the delivery date, the key messages, channels, and targeted audience. And I can also see my task in the next steps. So I’ll be refreshing the Firefly page for spring and then driving traffic to it with an email campaign.

Okay, great. So let’s quickly preview what the existing page looks like. And here we are on this Firefly landing page. Yeah. Could definitely use some springtime feel, especially as we’re going to be springing forward next week.

Okay. So now that we have the plan, let’s go ahead and start by reviewing existing content to see what can be reused. So here I’m going to ask AI assistant to find assets tagged as spring background in the last 12 months in the Firefly folder.

And now AI is surfacing the highest performing assets, helping to maximize my existing content library while keeping the production costs low, which is really important for me as a marketer with flat budgets these days. And these are all great options, but I’m really digging on this one. So next, what I want to do is update the Firefly landing page with this asset. And again, guess what? I can do it from here as well. So here I’m going to prompt on Adobe Firefly, update the Firefly background image, and then I also am going to prompt it to rewrite some of the headlines with the spring theme.

And amazing. So here we can see the reasoning is complete and updates have been made. Image has been updated and the headlines have been rewritten. Ready to update the, to take a look. Let’s go ahead and preview this page. Amazing. I love it. We have that beautiful image, spring background, and here we see these, these headlines have been created using generative AI based on my simple prompt to rewrite those headlines here. This is amazing. And once it’s ready, I can actually send this back for review and approval, and then deploy these changes with the help of agents to ensure everything is brand compliant and modernized. And I can also create a few different variants of this Firefly page using different assets.

Maybe I select a couple of those that we had in our repository and I can leverage AI to quickly understand what works and what version we should proceed with. So I’m able to go from planning to production, to delivery at an unprecedented speed, all without sacrificing brand voice or the quality of my content. And that’s the power of an optimized content supply chain with Adobe.

So now that we have our new refresh page, I need to drive customer engagement using a new campaign. And luckily, guess what? I can do that from here too. So I want to target customers who haven’t logged in for a while and send them an email or a push notification, driving them to this content. Now I can do this today simply by adding my prompt. And I’m going to sneak peek an upcoming innovation where I can take this picture I snapped during a team brainstorming session and then add that image here and the AI assistant to provide further context on my journey.

All right, let’s enter this prompt.

And so this is powerful because I don’t need to be an expert on all the products to do this. I can use natural language and images to portray what I want. An agent orchestrator is invoking the right agent to carry out the jobs. We see it building the audience and the journey it’s defining, validating and creating it for me. And here I can see this re-engagement journey created for us in just moments. And this is super impressive. I can review it here. And if I want to make some changes, I can change that conversationally through this AI assistant, or I can also save it and then later make tweaks in the application directly.

Okay, so now I have my journey created and I love that I’m guided to what I can do next. Some out of the box prompts to get me going. I need to add content for the different channels on my journey as AI assistant is guiding me to here, so I’ll select that.

And here it’s actually guiding me again. It’s recommending marketing email as the first step since it drives the highest engagement, and this is a game changer. It knows what performs best at this stage, and it remembers the context of the campaign from my previous interactions. So it’s populated these content guidelines for me. I’ll select to generate content for the marketing email action.

Okay. And now I’m simply just going to provide the purpose of this message and action I want the audience to take. And what’s great is it’s even providing guidance on the best way to frame my prompt. So let’s go ahead and say we will get them in the background. We updated Firefly page to align with our spring refresh campaign. And our goal is to attract unengaged users to our page. And within moments, it’s generating that content for my email based on our spring refresh campaign, and I can save the, see, you know, these different variants of content, and I can even, you know, save these now and then review them later and make updates in the application, or again, I could do that here as well. So we’ll go ahead and save that content.

And again, we can experiment and test and see, you know, once we’ve run this journey, what’s performed best. Now let’s say we’ve actually deployed this and my campaign has been running for a few days, I can come back to AI assistant to help me understand how it’s performing and I can see my previous conversations here for context, or I can even start a new conversation here. I’m going to say analyze journey, re-engage inactive users for profile dropout.

And here I can see that it’s doing the reasoning and then it’s actually coming back to me with an analysis of where the audience is dropping off and even providing recommendations on how I might improve the fallout. This is so powerful. This is the power of Adobe experience platform, AI assistant and agent orchestrator coming together to deliver an end to end customer experience orchestration. It’s a single immersive conversational interface delivering seamless orchestration across workflow planning, audiences, journeys, content, and analysis, just like Anjal said. And you know what I love is that it’s available for everyone to start using. So get started today. Back to you, Daniel. Yeah, that was great. Thank you. Thanks. I love just, you know, I’ve worked with so many customers and my time at Adobe and a lot of customers, they can get very deep with some of our products, but only a couple of products that they’ll specialize in. So the ability to do simple tasks and products that they’re not familiar with the interface, that’s really amazing. Like, you know, I spent a long time on using Target, consulting on Target, and it’s always best practice to start with, you know, what are my top performing pages and where are people dropping off on my website? So the ability to just get that data out of CGA without having to learn everything about that interface is just so powerful and great for marketers.

I agree. I’m just super excited about the fact that I can actually get data, build audiences, generate a journey, create content conversationally through this interface. It’s super powerful and it’s going to actually increase productivity for those of you who are marketers using our technology today. We’re hearing great stories and use cases.

Every time I see a demo, there’s this new, cool functionality being added. The image upload to the journey translation was amazing. Yeah, that’s very exciting.

Yeah, and Daniel, you would agree, this was just a glimpse of what the AI system can do.

Yeah, absolutely. Yeah, we only had five minutes for the demo. I wish I could go longer. I could show so many more capabilities. It is so powerful. That is so true. I mean, there’s always a lot more that the assistant helps you with. You know, like Gina was saying, improving productivity of your teams by giving them, you know, Gina showed some aspects, but it really gives them the how to, right? Anything that they need to do in the product, the how to, they just have to ask the assistant. So you get all the how tos when people need it. You know, the help provides with debugging and fixing workflows, you know, because we saw, we showed all the happy path here. There are also times when, you know, happy path. So and that’s when you need help with debugging, fixing workflows, other than just automating workflows.

So a big, you know, as you start using it, you will see the improvement in productivity, which really drives the, you know, agility and delivering significant savings in time.

And I don’t know, Daniel, if we should unpack a little bit of, you know, the engineer, in mean saying, should I unpack a little bit of, you know, what was happening behind the scenes? Yeah. Yeah. So at a high level, there are two things that are happening behind the scenes, right? The agents that you saw in action, they’ve all been, they have been provided and are being provided context to data, which could live in Adobe experience platform or the applications of Adobe. But it could also be brought from, you know, MCP servers, and, and from, you know, enterprise sources, other enterprise sources, it could be your warehouses and data lakes and anywhere where the context you think is relevant for driving customer engagements, you can bring in the, in the, and provide that context to these agents, you could also the agents could talk to other agents via a to a protocols, and that’s how they could also learn. And so the models that are underlying the agents, they’re really trained on, you know, the customer’s data per brand, with no intermingling of brands data. And typically, we get asked, right, which models do we support? So we support the GPT family, you know, the cloud family, as well as some open source models. And, you know, another sort of thing that typically comes up is that, can customers they ask that, can we bring our own models? And yes, you’re not locked in, you can bring your own model as well. And, you know, another piece of work that obviously happens other than providing context is, there’s a lot of verification of the output that we do. And we build verification checks in the agents. But we also expose that to the practitioners, so they can do their own verification, or really have a clear explanation of, you know, what we’ve done. And, you know, yeah, another aspect is that, you know, agents can show up in different surface areas. AI assistant is just one of them. So you know, what what Gina showed today is just one of the surfaces with where these agents could show up. But if you use, you know, cloud or chat GPT or Microsoft’s co-pilot, you can also use our agents there as well. So that, you know, I just wanted to because we couldn’t show everything. So I wanted to share that. It sounds like a great future episode of Experience League Live, Anjul. Can you share some examples of how businesses are adopting this across their marketing workflows? Sure, you know, so, you know, early on, we worked with almost like, you know, 300 customers as our design partners. And now we have around, you know, 1000 customers using AI assistant. And, you know, some of the marquee customers are like Wegmans, AAA Northeast, Marriott, American Express, Home Depot, CBS, Cisco, Hershey’s, Lenovo, Merkle, Bamboo HR. So you can see it’s across all different industry verticals. And really, what we see is that the marketers are using the AI assistant as their digital teammate. And that’s where we are seeing measurable business results, right? Higher engagement, you know, Wegmans, they saw a 3x higher engagement rate using AI powered audiences for, you know, some of their mobile campaigns that they launched.

Precise targeting, and like AAA Northeast, they saw 165% increase in car rentals, while targeting just a fraction of their prior audience sizes. So it’s improved conversion with smaller, smarter audiences. And, you know, a really important shift that we are also seeing is that the customer experiences are obviously becoming conversational, right? Context aware. So we are also seeing brands use our conversational experience, whether it is on their websites, or on WhatsApp, or any in app conversation that the brand is having with the consumer. Not only are they using our tech for the conversation aspect, but the agents behind the scenes that power these conversations are context aware, they’re grounded in real enterprise data. And it’s an omni channel experience. So you know, we have brands that are, you know, they can bring together the interaction that they’ve had with a consumer that comes to their website and is having this conversation experience, but can tie to all the past interactions that they’ve had with them, be it via email, be it via, you know, in app or, you know, on the website. So it’s truly, it’s conversational, but tying it to omni channel experiences. And really, what we hear from customers is that this isn’t, it’s not experimentation anymore. This is all, you know, enterprise grade execution where things have, things are today. So things are happening. So what’s your suggestion? What’s that? I said happening very fast.

Yeah. And so for customers, folks in our audience who are just getting started or thinking about getting started, what’s your suggested call to action so they can start seeing value with these tools? Yeah, I mean, you know, we launched AI Assistant almost three years ago. So all our customers that are using Adobe’s applications, you have the AI Assistant available. You know, my request would be if not already, please start using it. It’s simple to use like Gina showed. And it really enable you to scale your teams. And you’ll see the improved productivity, not just by running campaigns or automating the workflows, but you can do a lot more experimentation. And this experimentation would span, you know, with content experimentation with who is the, who is the content being shown to? And, you know, on which surface on which channel, and and we provide insights, right? Like if which content is resonating versus not. So this is all based on like experimentation could always be on with measurement. So you know, which experiments to double down on. So this will definitely give velocity. And I would, it would be, you know, like I said, we started this with a few hundred design partners, we’ve expanded this now to 1000s of users that are using it. So really, we are all on this journey together. And we want to work with you as you use it, we want your feedback.

You know, we want to keep striving to achieve, you know, perfection here. So I know our teams, our product and engineering teams have created a distribution list, where you can provide us, you know, feedback and, and we’ll continue to improve this with you. So we’ll iterate and improve with you. But please get started. Yeah, and those sample props in the interface make it so easy to just start trying things out and thinking about what’s going to work for you and your workflow and be most useful. Yeah, and Daniel, actually, Andra, probably you could speak to some of the innovation there where we’re actually building it so that it’s customized based to your brand, your needs. So that’s something that’s going to be really coming soon and very compelling for people to start using.

Yeah. And, and, you know, all these conversational experiences like which the brands can expose to their consumers are all, you know, trained on your brand guidelines, and comply with everything that you know, the brands provide. So it’s not, it’s not going to generate or, you know, any content that doesn’t adhere to your guidelines. And we always have human in the loop, right? So all the approvals and everything before anything surfaces to the consumers will always be approved by the different roles and you know, however, things are set up in a brand.

Yeah, and I think that’s great. Like Data Insights agent, you know, you’re just pulling data. So it’s kind of a passive process. There’s not, you know, any harm that can come from, you know, pulling that info. But with something like, you know, creating a journey, it’s very easy for somebody to start creating a journey. But it’s so it’s great that then there’s that split in the workflow. So, so anybody with, you know, access and with some permissions to create journeys can get things started. But then you can pass it, pass that project off to a co worker who is, you know, knows the full picture of what Journey Optimizer is doing and can complete that marketing plan and, and get it live. I think that that is a good, good approach to being responsible with it with these capabilities. Yeah, I’m seeing some of the questions and these in the chat. Daniel should be just try just bring up at least I don’t know, we have time to answer all of them. But I at least I want to make sure we answer some of them. So yeah, there’s a question around somebody is asking that they’re in the process of standing up Adobe omni channel tech stack. And they want to know when does it make sense to adopt Gen AI? I would say that, you know, it’s a great question. And, you know, if you’re, if you are standing up the omni channel tech stack now, absolutely, please get started as you’re standing up the tech stack, because all the capabilities that Gina showed what I just talked about, it’s all available to you. And, you know, if you have the luxury of doing this from day one, it’ll be just an awesome experience for your team. And, and, you know, that way, you just get the whole, you know, the stack built with kind of like that Gen AI first mindset. Even amongst the users of the of this tech stack, you know, once you’re done setting it up, so I don’t think there’s any need to hold back there. I don’t know, Gina, you work with a lot of customers. Anything you want to add to that? No, I think you’re absolutely right. Just get started. And you’ll see how powerful it is. You know, Anjal, one of the things that I think is kind of fun, maybe, if you want to talk about, I don’t know if you if you can say anything, but we know that Adobe Summit is coming up. Is there anything that you can speak to on what we’re going to be talking about there? Anything you can hint at? Or is it top secret? You know, there’s more capabilities and stay tuned. Be sure to join us there. I would say that right. We’ve shared a lot today. You know, Adobe Summit is still, you know, almost like four or five weeks away. So, you know, it’ll be great if, if, you know, our lovely audience here could, you know, get their hands on on the AI assistant. And we’ll all be there, our product engineering teams will be there. And we would just love for you to also join and give us feedback there. I, my, you know, I have a lot of gratitude for how much feedback we have received from our, you know, users. And that is really what is helping us make improvements and really make sure that this is ready for your enterprise workflows, right? Because enterprise data is not going to sit on the internet, right? Enterprise data sits inside the enterprises. And so we need to, you know, us collaborating together to, to ground these agents in your data, in your metadata, in your workflows, and ensuring that these are really your digital teammates for the enterprise that that you are a part of, right? So that’s the customization we provide. But it’s not, you know, it’s all done together by the partnership.

Anjula, another question came in specifically for you. How do you personally stay up to date on everything that is happening in the world of AI? I think it’s both reading as well as, you know, you have to stay very hands on. And I’m, you know, as a consumer, I use a lot of this tech, right, that is available. So without naming, you know, my, my favorite applications, but, but, you know, whether we are all now reliant on whether it be Gemini, whether it be Chad GPT, whether it be Claude, right, perplexity, you know, everyone has their favorite, but, you know, this is like, you know, I’m using them for everything. And, you know, even so just experimenting is one aspect, but usage is another. And then of course, you know, reading and then if you can’t read everything, you know, these, these, all these tools do a great job summarizing. So now we can consume a lot of content, if you can’t read it end to end, because the summarizations that they do is great. And, yeah, so, but immersive experience, I think is the best that, you know, you have to have to be using these tools to really know even what works and where things actually sometimes even encoding agents, you know, sometimes you get very productive, and then you reach a level where things are not as you’re not as productive, right. So just know where it works, where it doesn’t wear things actually, you know, kind of taper off or fall off, and where you need to do more work than sometimes the agent, you know, having that understanding is super important, because otherwise, you know, you don’t know what to expect from your teams as well, right. Yeah, I create a lot of video scripts as part of my job. And, you know, they say with writers, one of the hardest parts is starting with that blank page. But you can very easily get stuff on the page. It may not, you may not keep very much of it at the end, but you immediately can move into that editor mode of, oh, you know, what this came up with is, you know, what the AI came up with, I don’t like. I don’t like it, because it should be like this, and you’re already further along than if you had started with that, that blank page. I think so. I think Daniel, like, you know, sometimes because these agents will generate, they will also hallucinate. So I think having like, you know, especially like you said, right, while writing maybe, you know, even code, right, or product specifications, one has to have a lot of clarity in, in specifications, and they have to be very detailed with the guardrails, right? Otherwise, you know, if it’s all very open ended, you can, you can end up with a lot of messy stuff, and it gets difficult to clean up, because, you know, the more that it generates, then, you know, then there’s more work for you. So even, even in documents, doing it section by section, is more important than just saying, hey, generate the whole document, because, you know, they generate something and you think, oh, I kind of like these two things there. Whereas if you go section by section, you can keep correcting as you go along.

And I wanted to say about Summit too, hopefully a lot of, a lot of you can join us there in person. But I wanted to remind everyone that also, if you can’t, there are a lot of online sessions. So you can, you can watch a lot of the main stage presentations where for a lot of new cool stuff will be, will be shown links on Experience League, and you, you do need to register, but then you’ll be eligible for all of the online sessions. And a lot of content will be available, will be recorded and then be available to you after Summit. So yeah.

Cool. Well, we’d like to wrap up these episodes of Experience League Live with a little, well, first of all, before I get into that, thank you so much Anjul and Gina for Adobes’ Gentic capabilities. And I look forward to having you both back on the show at some point and look forward to seeing everything that you’re going to share at Summit. Yeah, thank you. And a big shout out to our customers as well for joining us. Thank you. Yeah, agreed. Thank you so much for having us and hope to see you all at Summit.

Great. So we like to end every episode with what we call an unrelated cool tip, which has nothing to do with spring, which was a theme that Gina brought up in her demo. So the cool tip, if you want to help our birds and pollinators and have some outdoor space, it can be as small as single pot. Grow some plants that are native to your region. An extra bonus, native plants, they’re typically perennial, drought resistant, and don’t need much maintenance. Thank you so much.

Thank you. Thank you.