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Transcript

Hello, everyone. Thanks for joining. We’ll be getting started in just a couple of minutes. Today’s session will be focused on context experiment with the AI Assistant content accelerator within AJO and how it relates to ÃÛ¶¹ÊÓƵ Target led by my colleague, Nicolas Mariel. We are going just to wait a couple of minutes more to let people come in and then we’ll get started. Okay. We’ll wait for one minute more and then we’ll start the session focused on content experiment with the AI Assistant content accelerator in AJO and how it relates to ÃÛ¶¹ÊÓƵ Target. Let’s get started on this topic. Hello, everybody. Good morning. Good afternoon. Good evening. Welcome. Thank you for joining today’s session. Today’s session is focused on context experiment with the AI Assistant content accelerator in AJO and how it relates to ÃÛ¶¹ÊÓƵ Target. My name is Rodrigo Aratia. I work in ÃÛ¶¹ÊÓƵ’s ultimate success as the principal architect. We focus today in helping customers to get as much value as possible from ÃÛ¶¹ÊÓƵ products. I’m going to go ahead and keep up our session today. First and foremost, thank you for your time and attendance today. Just to note that this session is being recorded and the link to the recording will be sent to everyone who registered. This live webinar is in a listen only format, but it’s very much intended to be interactive as we go through our content in today’s session. Feel free to serve any questions in the chat and Q&A pod. I will try to answer them on the fly, but if I need the presenter’s help in the end, we will have a Q&A session at the end. Our team will answer as possible here. And in addition, we have time to discuss some questions at the end. Note that if there are any questions that we don’t get during the session, please take note and follow up. We will be sharing our survey at the end of the presentation. That’s with a lot of your participation and to help to shape our future sessions. So I want to take the time and if we go to the next slide, we will be showing the rest of the webinars that we will have during next month in Q1. Especially interest for today’s attendees, ÃÛ¶¹ÊÓƵ Target Engineering Insights led by Target Engineering, where there will be a sneak preview on the new features and roadmap for ÃÛ¶¹ÊÓƵ Target. So I’m joined today by our presenters, Nicolas Mariel, his Senior Solution CSM and Ultimate Success, Ray Collector and promoter of the famous Target and Top-Ups event all around EMEA. And now we get started and hand over to Rico. Thank you very much, Rodrigo. Muchas gracias. Hello, Elie. Also for me and welcome to everyone. I’m Senior Customer Success Manager. Yes, and it’s my pleasure to present to you content experiment with the AI Assistant Content Accelerator and how it relates. ÃÛ¶¹ÊÓƵ Target. So let’s get started. Have a little agenda for you. Small intro. We will look at the AI content accelerator and then explore how that relates and how that works together with the content experiment. And we will bridge over to Target and see what AI capabilities are around here and what might come cover some use cases. And I have a recap table and then also highlight some resources. And like Rodrigo said, hopefully also and pretty sure have some time for Q&A. So keep your questions ready again. Put them in a chat or in the port. And we’re here to answer those. So let’s go. This short intro, I was actually not sure if I should do this because it’s so obvious that AI is everywhere. The AI landscape is just rapidly evolving. There is not a single day that passes where we hear something new from AI companies and AI happening here and there and everywhere. And of course, ÃÛ¶¹ÊÓƵ is your best partner with our AI investments like Firefly and all kinds of AI assistants and things like this. But don’t believe us. Take it from the surveys you see here, for example, 89 percent believe that AI will help them better personalize customer experience. So that’s a really, really strong indication, a strong number that marketing managers and customer experience leaders really believe that there is a missing gap between personalization at scale and how to tackle this. And AI is here now to tackle this gap and to help us to personalize at scale. There are other numbers here, 42 percent marketing application to have the most promise in the organization. And then the last number, I think it’s maybe very interesting because here it points to 2026, which is already almost there. It’s just one year away. So this is around AI driven features that will be more and more embedded across business technology and different features and functions in all kinds of solutions that you use. And that’s exactly what we have here in this webinar, where we will highlight AI and more specifically, Gen AI technologies that is embedded in features and different solutions. So very strong numbers. And even without those numbers, I’m sure that you are aware that we hear AI all the way and it’s here to stay. I don’t think that this is just a trend. Of course, things go up and down as well in that landscape. But this is very strong indicators for an AI driven future. Right. OK, let’s drive now into more specifically. Now, if you want to do personalization at scale experimentation, of course, you need content. Content is still crucial. Content is still king. And whether for AI testing or multivariate testing, personalization, all kinds of different contexts for different content, for different context, for different touch points, for different devices. You heard probably also the word content velocity. So we never needed as much content as today in all kinds of formats and variations and so on. So, however, creating and generating this content at scale in different formats for different devices, in different contexts, that can be challenging. Right. And even time consuming. And finally, also expensive. And this is exactly where the AI assistant content accelerator is relatively new or something that we released last year, end of last year in Q4. Where the AI content accelerator, it’s a long word, yes, but it helps you exactly this. You’d have content velocity on one hand side and content accelerator will help you here in an AI power assistant to help you to generate, like it says, text and images. We will see this in more details. Now, something that already existed in AGO is content experiment. And like it says, you can experiment with content. This allows you to measure and optimize performance for your different variations or treatments, like they call it, A-B testing, click through rates and so on, opening rates. These are things that you can measure. Now, if you bring those two together, which is optional, like the arrow indicates here, you actually can have this kind of making, producing, generating content on one hand side and then, OK, now let’s test it and you should test it. We would really recommend that you leverage those better together features in AGO and by the way, also in campaign V8. But let’s dive deeper into the first of them in AI assistant content accelerator. Meet AI assistant content accelerator. It’s a long word. Not easy for me. Behind that is powered by Microsoft Azure, OpenAI and ÃÛ¶¹ÊÓƵ Firefly. And it offers really three types of content for different touch points or for different channels, if you like. So three types of content. They are text, images, HTML. So these are available. You can generate text, image or HTML for push notifications. Right. Inside AGO for SMS, you can generate different text, images, HTML and for emails as well. We will see some examples can generate an HTML email and inside that HTML email you can generate and touch and edit and refine and tweak and tune the different textures and images. And then also for web page generation is possible as well. How does that work? The whole generation, I’m sure you’re familiar at this stage with prompt based text and image generation. Every one of you, I guess, has already had the pleasure to do some prompting or some chatting and create medicine that whether with ÃÛ¶¹ÊÓƵ Firefly or other tools. So it’s prompt based text and image generation. And these can then optionally and that’s the beauty and that’s the key also bit here being used and A B tested and bring them to the next level. Because how do you know if that content and text and image actually performs? You might like it, but your client or your customers might not like it. Okay, let’s go to the next content experiment. So content experiment again is if you like the experimentation component inside ÃÛ¶¹ÊÓƵ Journey Optimizer and Campaign V8. And again, allows you to optimize your campaigns. And you see here a very simple workflow. It’s sort of simplified. But of course, initially you would create your campaign and then use AI Assistant Content Accelerator to generate different variants of text, different variants of images, then you would browse and select and see which of those variants are the right ones you want. We will see a little recorded movie that go through that process, more or less. And then you will preview, fine tune and so on. And then in number three, you will go to that step where you say, okay, do you want fries with that? Do you want to experiment this? Now that you generate it, do you actually want to experiment those variations? You see here very small two HTML, emailed side by side. We will see that in a moment in a bigger screen. This is where you decide, okay, I want to experiment on those variations. And then of course, you configure and you launch or activate this experiment. So let’s look this a bit closer. So here we do a zoom in of the step three that we just talked about. So this is an example of a use case where we generate an HTML through the accelerator. And now we want to AB test that HTML email. So you see here, maybe it’s not so easy to read, but the subject line here says, explore exclusive marine adventures at Luminary sort. That’s the subject line for the left or the version A if you like. And on the right hand side, you have discover exclusive marina adventure at Luminary sort. So there’s only one different wording here on the subject line, but the pre header is also different. And as you can see, probably more easily, the three, four, four different images are also different. So you might want to check out which of those image will generate more feedback, more engagement, more opening rates, more click through rates for your Luma result in the Maldives. Right. And that you do here by selecting those. And then at the top, you have this little slider, enable experimentation. So that’s it. And then you have another step to activate this. But you can see that from production from generating subject line pre header, and those images, and then to experimentation, we have this inbuilt workflow, thanks to generative AI. Let’s go to another use case. So here we go. Also, still an email and we’re looking at email variations in terms of text. We will look at this video twice because it or three times because it’s quite fast. Here we have different variations of text. And here we call power linguistics, we have a lot of different options to refine the different text elements. Of course, we first selected and then we do a preview, we select the variation, we hit the refresh button. We go on elaborate, we have different kinds of elaborations here, we can summarize, rephrase, use simple language, or we can also change the tone, which is the second case here, where you can change the tone to something that is more humorous, or more empathetic, more exciting, more friendly. So the different tones, the different elaborations. And you can also even change your communication strategy. That’s the last one here at the bottom, which is not being highlighted in that video. But change your communication strategy is a third component of what I call power linguistics, where you can go deeper into, I want a communication strategy that is around urgency, or around formal fear of missing out, or around social change. Scarcity, all these kinds of cognitive biases, if you like, or exclusivity, right? Or gamification, informative, educational insight, these are all communication strategies, and refinement, and that you can use for all your different text elements in that way. And there are pre prompts and pre built things here, but it’s very, very powerful. Of course, we know that younger generations, they might suffer a profit from formal fear of missing out. So your hypothesis could be, okay, for that segment for that population for the younger ones, I want to get them to my bank accounts to open a bank account, for example, to say something, and I’m going to change my communication strategy to a formal based communication strategy or something like that. So you have a tons of way to explore and to experiment and to exploit, I hope, with those power linguistics with those features that will help you to have a better communication. Now the next use case is not around text, but it’s around image. And here, we will again, look at this video several times, it will rotate. Here the use case, the scenario is, we want to have an image reference. So we talked to our brand and compliant team, and they have given the okay, they have given the approval for a specific image that comes from our corporate design center, we have received that image, and we’re going to go ahead and upload that image here. So here, upload the image that is corporate approved. Now we have the prompt for that image. And we can fine tune the color tone, and the lightning and maybe also the width, if it’s, you know, one column, two columns, or which size, different aspects ratios can be selected here, then it will generate, in this case, we see different variables. And again, you would select them the variation, you can do some more tweaking some settings, and then you have an AI generated image through Firefly inside a geo inside the email designer. And this image is now corporate ready if you like, of course, we will check back with the corporate department with our style guides and CI guidelines and see okay, here we have a generated image that is based on an image reference. Is that good to go? Can I use this? And then again, we can do also experimentation on that, like we’ve seen before, with this little slider at the top, we could then go into experimentation and test different images if we are not really sure. Should I take this one? Should I take that one? What do you see? So I would encourage you always to test because that brings just much more insights and can really make the difference. Okay, what does this have to do with ÃÛ¶¹ÊÓƵ Target? Well, ÃÛ¶¹ÊÓƵ Target, as you know, is our one stop optimization solution. That’s where you can experiment a B testing, multivariate testing, testing, copy UI images, all kinds of designs, layouts. You know, this is really your full blown optimization and experimentation platform. You also of course, personalize eyes. So you do different different treatments, different recipes, different orders, different experiences, that’s the right word, different experiences, different experiences for different people, experience targeting, auto target. So we have now also a lot of AI, well, that has been been around for a while, AI and machine learning components. Of course, you’re familiar to auto target, auto allocate and these kinds of things. So again, your one stop testing and personalization platform, A B testing, multivariate testing. I’m sure many of you are familiar with this experience targeting and here’s some AI already existing. Functionality automated personalization, auto target recommendations. But what is in the pipeline for 2025? That’s the exciting news. And that’s where it links back to AGO and the content accelerator. So let’s look what’s in the pipeline. I’m just going to highlight two of them. And because they are relevant for what we are covering in this webinar. However, there are many others, experimentation, speed adoption, search filter, like you see here, these are things that are coming, extending the recommendations possibilities into more use cases, there will be specific insights and homepage where you can get more insights of overall performance of your target activities. But I will focus on Gen AI. If you’re more interested in this in more detail, there’s a webinar that Rodrigo mentioned on the 25th of February, that will go into sneak peeks with the engineering team, the target engineering team who will cover this in much more detail. So if you’re interested in that, please be interested in that. That may be down. So AI assistant. So AI assistant is something that has already been around in some of other solutions, which is a chat based AI assistant, that’s named where you can you see it on the right hand side. And it typically in the solutions appears on the right hand side, you can switch that on and switch that off. It’s this little what do you call this this little bubble, the stars, and then you can just ask anything. Like you see some example, why can’t I access this dashboard, which attributes have been used in segments? What’s the difference between auto target and auto allocate? What’s the difference between experience targeting and auto targeting? So the typical questions maybe around targeted you might want to ask how much traffic or how much conversions do I need to run recommendations? You might have all kinds of almost trivial questions around the product. And how to use and how to adopt faster, all the features and functions that exist in this case in ÃÛ¶¹ÊÓƵ target. So that is coming to ÃÛ¶¹ÊÓƵ target very soon. And of course, it will accelerate your workflow. You get a better understanding, you have like co pilot actually here to help you and to troubleshoot problems and to understand also, for example, reporting, quite often you have questions reporting how to read that report, can you help me in this and so on. So that’s coming. And some of you again, might be familiar with an AI assistant from some other ÃÛ¶¹ÊÓƵ solutions. And then the hottest I would say and I think this is the coolest because again, content is still king. And one and I am a power user and a long term veteran of target. And one of the biggest challenges indeed, is where do you get the content? Where do you get text? Where do you get the different images? And if you do really large A B test or even multivariate test, you can run easily or with automated personalization, you run easily in a lot I’m talking about 200 different elements of content. So text, buttons, borders, different lines, different styles, different main pictures, you easily run into these kinds of I need 2000 or 200 different elements. So here, welcome content accelerator, this is something in a similar fashion that I just show you for a geo in a similar fashion, maybe not 100% the same, as we’ve seen, but basically the same power for new features prompt driven simplicity like is here, context aware, creation, okay, brand asset integration, we just saw showed you that we can upload a brand from the company guidelines or upload this and use this as a reference image. So these kinds of things will be coming to the visual experience composer inside ÃÛ¶¹ÊÓƵ target. So the VEC, where exactly it will sit, we will see. I’m really excited also and curious to see how that rolls out. Okay, so stay tuned for this. And again, if you’re interested in more, there is this webinar coming up. Now, let’s talk a bit about use cases. Well, typically, we just talked about target. So typical use cases for target, of course, is web and deep web personalization and experimentation on the web, whether this is one to one automated personalization, or content for multiple pages, automated targeting, category affinity, single page application, client or server side, this is all breadth and depth. This is your playground with ÃÛ¶¹ÊÓƵ target. We can do all kinds of different things very sophisticated, very large and all kinds of stuff. Of course, you can also web and mobile and apps, you can do quite some stuff. And then recommendations, maybe the hottest underrated feature, and I wouldn’t really call it a feature, I would really call this the solution in the solution, or the product and the product recommendation with over 40 different criteria. So algorithms, people who looked at the product, this looked also that people who bought this bought also that most viewed, most bought top sellers, and so on people who read this article also have interest in that article. It’s not only for ecommerce, it’s not only for product, it can also be in the media world can be all kinds of things, all kinds of rule, automation catalogs, very, very, very powerful. So if you haven’t checked this out, this is worth going the extra mile, and then product features rollout. In apps or in other scenarios, you might do some feature flagging that is also typical things that you could do with ÃÛ¶¹ÊÓƵ target. There are many more, but just to keep it simple. Now, if you look at ÃÛ¶¹ÊÓƵ journey optimizer, we’ve seen the content accelerator, but what are typical use cases. So here we are more in an orchestration scenario. So orchestration, omni channel, cross channel. So we are talking about the keywords here, really, omni channel, orchestrate, real time, these are the areas and touchpoints and journeys. These are really the sort of taxonomy. That is necessary or that makes sense here in the use cases for ÃÛ¶¹ÊÓƵ journey optimizer. So across different bio lifecycle orchestration, different touchpoint with the SMS, push notifications, emails, all these kinds of things. So also embedded like you see here in email, SMS, I just talked about push notifications, all these kinds of different touchpoints with your clients, with your customer, with the known clients. I mean, if you have a customer, number, right, so here we are more in a known customer scenario, lifecycle, managing lifecycle campaigns, campaign fatigue, things like this. And then also combining the offline world and the online work, the physical and the non-physical, the digital experiences. So for example, in some sensitive scenarios, thinking about banking or financing, you might start some onboarding or some process of opening or doing some transaction online. But in order really to execute this, you have then to go offline to a point of sale and show your passport or something like this to do really to execute finer details. So these kinds of combined offline online are also typical or quite often scenarios for ÃÛ¶¹ÊÓƵ journey optimizer and mobile engagement, of course. Some scenarios where both could work together. So again, you start, for example, on a mobile device and then you jump from the mobile device to the web, outside of the app to the web. This could be scenarios. It could be several, we have two scenarios here, but there could be several use cases that can help to combine those two. And we really have also more details on this where we have, I think we have some kind of better together story around if you have ÃÛ¶¹ÊÓƵ journey optimizer and ÃÛ¶¹ÊÓƵ target, how can you leverage them together, offer content design optimization. There are several scenarios here that can help in those two. Okay, to resume a bit or to put them a bit to put them a bit side by side. Okay, the engagement and the scope for target is, like we mentioned, mobile web API’s as well. On the other hand, on the journey optimizer side, we have, like we mentioned before, much more those touch points, where we have more information about the visitor, which are typically clients than email SMS push direct mail. Also we have mobile and in-app messaging. So it’s a more granular and more closer relationship journey optimizer than maybe we target. Some unique capabilities here maybe, well, I mentioned it, product and content recommendations. So the recommendations engine, the full blown engine, which I call the solution in the solution on device integration. And then again, typically anonymous visitors would be the ones that visit here. Not always, but typically you, of course, you have all the people who log in, but this would be more something that is a bit distinct in terms of compared to journey optimizer, where we’re looking more at typically known visitors. Okay, right. So let’s recap a bit. I tried to put all of this in a table. So now this table, there is a caveat to it, if you like. So here, what we tried to do is look, what are the features and capabilities of target? So we mentioned here on the list one to 14, and how do they compare with this combined power combination of using content accelerator and content experiment? So if you look at the figure, AI based tech generation, image generation with Firefly, HTML generation, we looked at an HTML generation, I showed you side by side and then how you can use that in experiment. So this is available in AGO in this combined approach with content accelerator and experiment in AGO. This is not yet available in ÃÛ¶¹ÊÓƵ, it was in a roadmap. So believe you will see this very soon or hear very soon something about this. So however, if you go beyond 45678910, and down there, you see that this is really where target has everything green and everything. Yes. So here, whether it’s multivariate testing, auto allocate auto target, automated preservation, experience, and recommendations, solution solution, and so on. These are where we see really the width and the breadth of this full blown optimization platform that target target represents. So this table is a bit to contrast and also to help you a bit. Okay, there is a certain overlap here and there. Yes. But it should also help you a bit to position where and when to use what. Okay. And with that, I come to almost the last slide, we have also some resources that’s more for reference, when we send out slides, there is of course, some presentation, there is an interactive playground, we have some press releases, we have some blog posts, so you can go deeper into those stuff. There is also stuff for target, of course, target overview key concept. This is stuff that you will get as well those links and you can go then deeper into exploration of those different features and functions that we mentioned here. And with that, this is my last slide, we are coming to questions. I’m aware that I went quite fast through this. But on the other hand, we have now time for questions, if there are any questions, and I’m going to stop and switch over to Rodrigo here. Thank you. Thank you, Nico. We have already started the poll as well. So please leave out your comments and let us know so we can get current and better for the future. Okay. And there are no questions for now. If there’s something just comment in the chat or not. So in the meantime, I have one question, Nico. And is that is AI content accelerator in AJO for free? Yeah, that’s a very legitimate and good question. And the answer as quite often is it depends. So yes, to a certain extent, it’s free, but you cannot abuse and generate billions of pictures. So to a certain volume, you know a bit more about it. Perfect. One more question. Is there a better together story between AI content, existing accelerator in AJO and ÃÛ¶¹ÊÓƵ Target? Or is it pretty much same thing? No, I think we have actually somewhere webinar or something, a slight take on this better get to story. There are quite some scenarios I highlighted two of them. Because that was not the main focus here, but we have some more details on this and maybe you can add the links to the resources. Okay. So it seems we have not many other questions. So we can close out the meeting. Thank you very much, everyone for your time. We hope this has been really helpful. And thank you for your time. Thank you, Nicolas, for your next presentation. Thank you, Rodrigo. Thank you, everyone. See you soon. Thank you. Bye bye. Bye bye.