[Music] [Maggy Wahba] All right. I think we're going to go ahead and get started. I'm sure folks will join us along the way. But welcome, everyone. Thank you for taking the time to be here. I know it was quite a trek to make it up all the five floors and come to this room, so I'm glad you all were on time. Hopefully, we'll get a few more folks in as well. But thank you for joining us for this discussion on Audible's journey of implementing Adobe Experience Platform on AWS specifically in order to personalize its customer experiences. I'm Maggy Wahba. I focus on Marketing, Analytics, and Personalization for Deloitte Digital, and I also helped lead this AEP implementation, along with a very talented team across Deloitte, Adobe, and Amazon, some of whom I am joined by today.
So with me here, we have Kevin Matthews, who is our lead client partner from Audible and also Senior Director of Data Capture and Digital Analytics. We also have Kenneth Marzin, who leads our global AEP practice for Deloitte Digital, and Tomo Ishigami, who leads the Adobe Alliance for AWS. So very excited to have the three of them here with us today. I know they have a lot of unique experiences and perspectives when it comes to this topic. We should also have some time at the end for open Q&A, so please start thinking of that as we go through, the next 45 minutes or so. So what you can expect today is we'll spend a little bit of time talking through the Audible journey of implementing AEP on AWS. Some of the key learnings and the use cases that we actually prioritized for this implementation, and then also what it means to really harness the power of AEP to personalize the customer experience and some of the business value that you can unlock with AEP. One thing that I'll just note is, we started this journey about a year ago. It's actually been over 12 months. We kicked off in January of 2024 with a great discovery session around use cases and outlining the roadmap. And then just went live with the first set of use cases this past January. So it's been quite a journey, at least 12 months. It doesn't typically take 12 months to implement AEP, but this was a unique situation with Audible being the first customer to actually do AEP on AWS. As you know, that wasn't available before. So there were a lot of intentional pauses in this 12 month journey that you see up here, in order to support some of the product development and the readiness from the Adobe side. One example is when we define the use cases during discovery, we actually shared that with Adobe, and they were able to use that to inform and prioritize the capabilities and features that were then available to us to start our build activities. So this was truly a partnership across Deloitte, Adobe, and AWS working hand in hand for the last year at least, more so, and Kenneth is going to go through that, to bring all of this to life, and exciting. I hope you all heard this yesterday, but this will also be available in GA for all of you, to use in the next few weeks. So I hope you hear something exciting here, that you could take back to your businesses or definitely ask questions about how we implemented this for the first time for Audible. Okay. So with that said, this was a preview into the last 12 months. I do want to hand it off to Kenneth to tell us a little bit more about how this journey even got started. [Kenneth Marzin] Yeah. Thanks, Maggy. So as you all know-- And thanks all for joining, by the way, right after lunch. I appreciate it. You may still be digesting, but excited to be here. And as you all know, AEP has been on available from Adobe since roughly 2019. So it's been a few years. And Deloitte alongside Adobe, were part of implementing it for the first clients in the early days. And one of the things that we've uncovered pretty quickly is that there's a big ask for mostly CIOs, but also some of the marketing teams, on having the ability to have multi clouds, like having the ability to have a choice in the cloud that they are using some of their SaaS platforms are, in order to ensure that they get more benefits from using really one and being in one cloud. And, of course, Adobe had released AEP on Azure, and so it was not yet available on-- It was not available on AWS. And so we got to discussing with Adobe as well with AWS. We started this discussion back in 2022, so that was-- It's taking a minute to get there, but great discussions around like, what would need to be true in order for us to get AEP on AWS? And one of the first thing that we uncovered was we needed to have a customer zero. We needed to have somebody who would be the first customer to get on the platform on AWS. And then in parallel, we were also having discussions with Audible, who were very interested in the platform, and they had some key use cases that they were not able to implement, and Kevin will talk more about those, in a minute, on their existing stack. And so we worked with them to figure out what are some of the key use cases that could be available for them once the platform was on AWS. And that was a catalyst for the negotiation between Adobe and AWS to finally, a deal to put AEP on AWS. So that finally got inked in September 2023, and then that's when we started planning for the implementation for Audible, and the rest of the journey got started. So super excited that it's finally there. Fast forward a few years, and that now it's almost, as you heard from Anil during the Keynote on Tuesday morning, that it's going to be available for GA in April, and for all of other clients that are very interested in staying on the AWS stack, to implement AEP on AWS as well. Yeah. Thank you, Kenneth. And I think there's just so much that went into all of the foundational components of setting up this journey, and I know it was quite an investment across all the teams that were involved. Kevin, I'm curious. I know Amazon to be more of a build first culture, and I think you all have a lot of first party tools. What made you choose to implement AEP and partner with Deloitte? [Kevin Matthews] Yeah. Thanks, Maggy. Thanks, Kenneth. Thanks, Tomo. I know Audible's journey has been about 12 months with AEP, but hearing how many years of development went behind that, behind the scenes is it does a lot of the work for us. So thank you all. For me, my AEP journey, I would say, is about six years old. I was here in Vegas in 2019 when Shantanu and Anil were announcing AEP on Azure, and I just remember thinking, this is an amazing step change from that traditional cookie-based web analytics into a true omnichannel customer profile based analytics. And so we've been looking forward to this for a very long time. But to your question about build versus buy, it is certainly true that Amazon, with our scale, with our unique requirements, with our security requirements we do often have to build things out of necessity because there aren't tools off the shelf that can meet all of our unique requirements.
I think Adobe is one of those examples of where it is an off the shelf solution, but it's also open enough to where we can customize it to fit within our own architecture. And so we're essentially just waiting for it to become available on AWS.
Speaking to some of the limitations of our stack, I'll start by saying that we've-- Have the architecture up here, just so you want to reference. So we've actually had Adobe at Audible for over 10 years. So we've been heavy users of Adobe Analytics, Target for personalization, as well as Audience Manager. But one of the key limitations for us is that our customers engage with us across multiple touchpoints. We have experiences on Amazon. We have Audible web, Audible apps. We engage on third-party platforms. And again, one of the limitations of traditional web analytics is that those are all treated differently, and it's really complicated for us to stitch all those together. So we end up doing a bunch of post processing from an analytics standpoint to look at that end-to-end customer journey. So AEP is a miracle in a sense because it solves for that. It takes all of those touchpoints, stitches them together, creates that unified customer profile, and enables us to see our customers along the journey and personalize it along the same journeys. So you might be wondering why did we wait six years if I was here in 2019 wanting AEP? We are part of Amazon. We're deeply embedded within the AWS ecosystem, and so we wanted to wait for that opportunity to build AEP on AWS. And so when our friends here came to Audible and said, "Hey, do you want to join us on this journey?" We were super excited and definitely couldn't wait to be the customer zero on the B2C side. So yeah. You also spoke to some of the advantages of being customer zero, and I don't take that lightly. We spent a lot of time about a year ago really curating that list of initial use cases that covered the breadth of the tools and capabilities, but also covered many of the surfaces that you see up here.
And so we took that set of use cases, handed it off to the AWS and Adobe engineering team. And as they were building the platform, we were the guideposts. So that really ensured that when the product was ready, all of the tools and capabilities that we needed for our use cases were ready to go. And then second, I have to shout-out to Deloitte. As you mentioned, you were some of the early adopters in implementing AEP with some of the biggest clients for AEP on Azure. So between having that distinct advantage as customer zero plus a really strong implementation partner, there was no question that we were going to partner with you guys as customer zero, so.
Awesome. And the feeling is neutral. I think we set this goalpost of January 31st go live a year ago before really knowing the details of what it would take to implement this for the first time. And the product became available to us in September, and then we started, really, a lot of the build activities between September, to get us to January. And so I just want to echo that in terms of the partnership that it took to get there and to do this for the first time and to figure out this architecture, but also figure out how it incorporates into Audible as a customer zero. So thank you for that. Yeah. Tomo, I do want to hear from you as well. So AEP on Azure has been around for some time. What is really unique about AEP on AWS, and what can companies expect? [Tomo Ishigami] Sure. Thanks, Maggy, for that question, I think the first thing to call out here is because Audible, our friends, our family at within Amazon was the first customer, we were able to have a seat at the table working very closely from a partnership perspective, AWS and Adobe, to ensure that best practices were being used for application development, the right architectures. So ultimately, Audible, as well as all businesses will have a high performance, resilient, and secure platform to be able to drive personalized experiences. So I think that's one of the unique things here is we know with confidence that it's certainly scaling to Audible's business and they're over billions of customer touchpoints. So that's a great test bed that folks in the audience can have that additional level of security to know that what if it's scaling to Audible's business and it's clear enough for Audible's business, then it's going to be a good option for you for your business as well. I think the other thing to call out here is AWS. There's going to be a lot of interoperability advantages. So I think the first thing to call out here is I see customers, many customers building their customer data lakes on AWS. And as you can imagine working within an AWS environment with AEP on AWS presents a lot of advantages in terms of better performance, lower cost in terms of managing that data, as well as security because that data is never exposed to the internet as you're moving it from one AWS environment to another. And then I think the last thing to call out here for the time being is much of Adobe Digital Experience technologies run on AWS. So the interoperability with other products like, Adobe Experience Manager, Managed Services, Adobe Commerce, Target, Adobe Campaign, Marketo, all these other DX products run on AWS as well. So the interoperability amongst your Adobe stack on AWS is going to be very good. So I think those are the main things right now, and I think there's going to be more enhancements and benefits coming forward as the platform matures. Yeah. Absolutely. And personally, I know a lot of our clients are just AWS shops and have really been waiting for this to fit into their tool stack. So I'm excited now that we've done this with Audible and AWS marketing as well as customer zero to take this a bit broadly. So thank you for that.
Kenneth, I know we talked a little bit about our journey at a high level, but can you tell us a little bit more about how Deloitte has been able to partner with Amazon and Adobe, and what's next for this partnership? Yeah. So as I mentioned, once we inked the deal between Amazon and Adobe to put, finally, the platform, AEP on AWS, then we got to planning that customer zero implementation and how we're going to enable that for Audible. So you see here the very high level timeline on how we did that starting with, really, a discovery of what were the pain points. Obviously, we knew at a high level the pain points, and Kevin described some of them, but really dig in onto like, what are some of the challenges and what are some of the use cases and KPIs associated with those use cases in order to really use AEP to add value for Audible. You see here, obviously, creating a unified profile was super important to especially to bring the unknown data with the known data and really have a better view of how a customer moves through the life cycle, for Audible, and that was a key pinpoint that they had. They could not really tie in some of the unknown behaviors to people after they sign in and what they were browsing, etcetera. And so that also led to the next big set of use cases, which was personalization, right? Being able to personalize the experience, even if the customer is not signed in, being able to tie in that customer data or integrate that customer data with Target in order to enable that personalization on the web, was definitely one of the big use case unlock that we could do. And then as I mentioned, the Customer Journey Analytics. So a big piece of this was really fully understanding the journey as the customer was going through not only the web, but also all the other channels, which I think was something that was not really available before. But being able to figure out the behaviors on the different surfaces and stitch them together so that you can see, okay, if a customer came on this surface and they started a title, listened to a title on the surface, what's the next step, like, when they're listening in the car and then maybe going and listening at home. What is some of that experience where we're actually ingested a lot of the listening data into the platform, to the point of like, when they're pausing, resuming, and then obviously, the devices that they're using, they call it surfaces, at any point. So that really helps upscale the understanding of Audible on the full journey end-to-end, which then will be able to allow them to create new audiences and segments that they can activate. So in terms of the design, we looked at those use cases and figured out, "Okay, how do we implement those?" And we figured out, obviously, we need AEP. We need RTCDP in order to have those segments and integrate them with Target. And then we need CJA for that Customer Journey Analytics piece. And then the ability to send audiences from CJA based on the insights that we're gathering back to our RTCDP so that then it can be sent back to Target for personalization on the web. So we spent some time on design. I think Maggy mentioned a little bit, you see this, we started in January and then went live in January. It took 12 months. But we did had to pause in between because as much planning as we could do, we had to wait for Adobe to actually build the product on AWS. And so there was a bit of a gap between some of that design work and the implementation work to let Adobe catch up. Once the product was available, back in September, we were able to resume and sell the implementation. And that actually was relatively fast. I think, it just took three, four months to do the implementation. The main pinpoint here is that, I think two big ones, and two lessons learned, if you will. One was production data and make sure that that's ready as soon as possible.
And that would took a while, and obviously, Amazon being a very, I would say, conservative company for good reasons around privacy and security and ensuring that customer data is handled with extreme care. We had some additional activities that we need to do in order to get there from a production data standpoint. And then, obviously, Adobe was building the product or had-- We're still in the process of building and fixing the product as we went along. So one of the big things we were working on very closely with the Adobe product team is, any issues we found, make sure that we worked hand in hand with them to troubleshoot and resolve as the product was still, I would say, not completely stable at that point as we were going through development.
But I think pretty amazed, actually, at the fact that we still managed to launch on time. We did have some buffer in the timeline because we were expecting some of those things to happen. But I think we were able to take that into account and work with Adobe to move as fast as possible to do it.
And finally do the go live. So launched at the end of January, and then there's some stability that is still being worked on as we speak. There's obviously some things because we didn't get the production data on time. There's some findings that happens quite late that we're going to need to update now, so that some of that is in process.
One other big thing that I'll mention is that, late in the process, we found out that we really needed web SDK in order to plug in some of the data collection and make sure that we get that data for some of the behaviors on the web, into the platform. And that could have happened earlier in the process. And one of the lessons learned is making sure that data collection is a piece that's being really looked at doing discovery and figure out, do we have the right data collection? Do we need more? Do we need web SDK, which allows you to stream data faster into AEP depending on the use case? If you have real-time requirements from a frequency standpoint of the data do you need-- That's some of the considerations for a data collection mechanism and whether you need web SDK. So that happened later in the process, and so we learned that.
And yeah, that's the journey that we had over the last year. Yeah. And maybe there's more to the what's next piece of it, but I also just wanted to point out that these use cases that you have here, those were very foundational use cases that I think are a great starting point for anybody looking to implement this for the first time right around the unified customer profiles, some of the CJA insights and analytics capabilities. So a lot of these are around listening and measurement for Audible specifically and then how those downstream activate personalization. So we actually also walked away with quite a big backlog of additional use cases that we could do in the future as well. Yes. Is there anything else you want to talk about-- That is step one on the journey, and I think we'll cover some of the next steps, later on. Yes. Awesome. On that note of use cases, and for anyone who is an Audible fan out there, Kevin, I'm wondering if you can bring this to life a little bit, around how will AEP help you deliver more personalized customer experiences and why you chose these use cases, maybe one, that sticks out to you and how that comes to life in terms of using AEP? [Kevin Matthews] Yeah. Yeah. Sure. And, Kenneth, you provided so much context on the use cases already, so maybe I'll offer just a slightly different framing of it. So during discovery, we landed with a whole laundry list of use cases, and boiling the ocean is definitely not the right approach in a P0 implementation. So as I mentioned before, how did we narrow that down to ensure that we're covering the right breadth, but also bringing enough data into the platform for our P0 that we can quickly turn on P1, P2 use cases. So we really thought about use cases in terms of three buckets, the first being the data foundation itself, so bringing data in from multiple channels, both online, offline, stitching together that data into customer profiles, adding attribution into the RTCDP, enabling those profiles for downstream activation, etcetera.
So the foundation itself is step one. Step two is analytics and insights, so taking that data within the foundation, using these new customer profiles, and starting to visualize and measure customer journeys in CJA, ultimately with the goal of gaining insight so that you can either improve your marketing performance or we have a lot of product managers who actually use Adobe data. So when they implement a new feature, we add a bunch of instrumentation so that they can visualize how customers engage with it. That's another use case for CJA for us. And then the last bucket is all about segmentation and activation. So whether you want to use the data within the profile itself to add segments and activate, or I think what we're really excited about with CJA is the ability to create journeys, visualize them, measure them, and then find either cohorts of customers who are doing something or in many cases not doing something falling out of a funnel, creating a segment live in CJA, pushing that into RTCDP, so that you can now activate that through Target or one of your own downstream activation systems.
So to bring that all to life, I'll maybe give an example of, let's say, a customer comes to our site for the first time. So they're a prospect. We don't know anything about them. They're not logged in. They don't have a customer ID, and they start browsing around and maybe they have a particular affinity towards sci-fi. So they come to a sci-fi category page and maybe they start clicking into some sci-fi titles, but then they get distracted, and they bounce off the site. Thankfully, along that first journey, with every step of the way, we created a profile in RTCDP. We started adding attribution. So now we know they have some affinity toward sci-fi in this case. So that when they come back in a couple days, we're not just landing them on a blank home page again. There's a lot of ways that we can personalize this to reduce some of that friction. It could be as simple as adding a carousel with some sci-fi titles to the home page. We could land them directly onto a sci-fi category page. Or I think one of our initial use cases is just keeping that last page of the day we're on, so that we can land them directly on the last product and really try to reduce that friction. So, again, the ultimate goal here is to reduce the journey, get customers listening as quickly as possible. And so that's just one of many use cases that we're hoping to go live with our P0 implementation.
- Absolutely. - Yeah. And I love that because that's something you weren't able to do before, and now you will. And we've been talking about measuring the value of being able to do that, right? Like, what does that mean in terms of some of your KPIs as audible and how that will deliver value to you. So I think that's one of the things that we look forward to with AEP as well in terms of the value realization. Yeah. On that note, so we talked a lot about what the journey has been like so far and that this was a first of its kind implementation. So if we could just go around maybe and hear from each of you, what are some of the key learnings or key takeaways for you when it comes to doing this type of work? And maybe we'll start with you, Tomo, so we can give Kevin a chance to catch his breath and then come back to him.
I was more involved in the partnership side. So I think the key thing here is just staying close to the entire build process. Making sure that I'm working closely with the account teams that support Adobe to make sure everything's on track. And then we're gearing up our respective teams to start to coalesce around the additional customers, that may want to start evaluating AEP on AWS. So I think that was a unique situation for us, right? Because it's in advance of a product that's to be released. So I think that's, for now the biggest takeaway.
What about for you? What's the biggest key learning from this journey? Yeah. I think, I covered some of that as I was going through the process and what we went through it. I think, obviously, there's always roadblocks when you're a customer zero. So as Tomo mentioned, staying close to the product team, in order to do that. But what I'll say is maybe for additional clients, right? This should not take 12 months, right? Like, when you're going to implement AEP on AWS and CJA and maybe you're looking at AJO, this will be a lot faster because obviously the product now is there, and it's going to be available on AWS. So that should not last that long. There might still be over the next year or so, some product stability I will say, hiccups.
But by and large, I think that should be resolved over the next few months. So that should be fine. I don't know that that will be a huge challenge. And then back to some of the points I was making, ensuring you understand data collection early on in the process, ensuring you have a good set of use cases, but not boiling the ocean, as we mentioned before not having starting with a small set of use cases that you can then use to test and learn and then slowly scaling up to additional use cases.
And then a few other things that I would mention that Audible has been an awesome partner to work with on that front. But I've seen some of the clients where when you treat this type of project as a very technology-centric project, you can miss sometimes the operational model, change management, and process that you will need to do in parallel of the tech implementation to ensure that once you go live, you can really use the full value of the platform. Because if it's just a piece of technology that you have in your tool stack and nobody's using it or the adoption isn't there, it's wasted money and effort. So making sure that you partner very closely with the marketing team and the business that are going to be the users of the platform, they should be involved from the beginning, from the discovery phase, from use cases. They should be heavily inputted into the use cases, and then having them involved through the process, having them do operating model work in order to make sure they understand what's the new operating model once this platform is live for them, and then what's the change management in order to encourage adoption, ensure that their marketing team and business teams are ready to use the platform once the platform is live. It's probably not going to happen overnight. At go live, there's probably going to be a period of time where you slowly ramp up, and there's different models depending on our clients, some model want to go full. We want to launch to everyone at once, although that's pretty rare. Most of our clients choose to do a COE type model where you have a centralized journey, our analytics and dashboarding team that's going to really touch the platform, and then slowly move to a hub and spoke model where other teams are plugging in with specific resources that are going to be touching the platform. So lots of different options, and obviously, just dependent on clients. I think from Audible, it was more of a COE standpoint, with Kevin's team really focusing on the journey in analytics and working with a different Audible team to bring them the insights that they're gathering from the analytics. It's a model that worked really well for them. And then, yeah, once you have the people, process, and technology figured out, then you're good to go. Then it's about what's next and the roadmap and how do you evolve the platform to continue to add more value to it.
That's great. Thank you, Kenneth. How about you, Kevin? Yeah. I think there's a lot of overlap with what you said.
Again, as a company that had Adobe Analytics for a long time, I think initially we were thinking about this probably in an oversimplified way of CJA being the next generation of Adobe Analytics. And Adobe even in some cases markets it that way in the sense that workspace looks the same.
But that really couldn't be further from the truth. The way you collect data is very different. The way it comes into the platform and it gets manipulated. The way you set up customer profiles and set up the identifiers you're going to use to stitch things together. The way you create data views in CJA, the way-- Everything essentially end to end is different with CJA. So to your point, I think ensuring that you have that change management and operational components baked in is critical, because it's not just the folks working on the project itself that are going to be impacted once it goes live. It's like every user of these tools, whether they're replacing or migrating existing functionality or whether they're being trained on that new functionality with the CDP just don't underestimate that level of effort on the back end of the implementation. - Yeah. - Yeah. Absolutely.
So to round us out here, and hopefully, that's a little bit of a prompt to all of you to think of any questions that you may have. And if you want to start lining up here, we'll take Q&A soon. But just want to hear from each of you one more time, and we'll start back with you, Tomo. We've talked a lot about AEP and for us that was Real-Time CDP. That was Customer Journey Analytics. I don't know everybody's extent of knowledge on the tools and how to use them, but hopefully, this just gave you a little bit of an idea of what it takes to implement that. But from an AEP perspective, what is really the biggest value of AEP, and what does the future of AEP on AWS look like? Sure. So me, right? Yes. We'll start with you. Do you want to click? Yes. It'd be cool. Because the situation was unique and we were involved with Adobe during the build of this product, we also had a head start in some of these really cool integrations and offerings that we're going to bring to market together. So this was just announced yesterday, publicly. Really two cool offerings between the Amazon AWS and Adobe partnership. The first one is Amazon Connect. So for those of you who don't know what Amazon Connect is, it's our omnichannel call center system. And there's a customer profile in it, right? You're capturing all that customer interaction. When you field a call, you field a customer chat. That customer profile data is being integrated with the customer profile in AEP to give, ultimately, businesses a more complete view of the end-to-end customer journey, so that you can drive a better personalized experience on digital as well as customer service channels. With this unified data now, it opens up the opportunity to create AI-powered agents, using Amazon Q in Connect, as well as AEP's AI agents, to drive an even more personalized experience with these agents. So that's one of the first releases. And then the second one's really cool if you want to click over to this, the next one. I think everyone's familiar with Amazon Ads. So Amazon Ads and Adobe is integrated in several areas. So you're an advertiser. What do you want to do? You want to create, you want to run an ad campaign on Amazon Ads. What do you need? You need content. So you can go into either Photoshop or Adobe Express and create content directly for Amazon Ads. With that content, what else do you need? You need an audience segment. Audience segments from AEP can be activated with that content directly into Amazon Ads. The performance insights feedback into AEP via Amazon Marketing Cloud. So that, ultimately, advertisers can manage better return on their ad spend. So these are the two really cool things that are available now, and we anticipate additional joint offerings to come. So really excited. This is really something with the broader Amazon partnership with Adobe that, some of the unique things that we're able to bring to bear to ultimately drive more value for customers using AEP.
Awesome. If anybody has questions for Tomo on that, go find it after. One last thing. So also Adobe will support-- Sorry. AEP to be procured on AWS Marketplace. So if you're not familiar with that, the easy button for that is to engage with the procurement folks that manage your AWS relationship. There's financial advantages to procure Adobe technologies on AWS Marketplace, so. And it helps with your AWS commitment as well. Exactly.
So, Kenneth? Great. Yeah. So to build up on what Tomo was saying, we are also within Deloitte building an offering around Amazon Ads plus integrating with Adobe, and then using AWS Clean Rooms in order to ensure that you can use first-party data for advertising. That's one of the big next unlock, it hasn't really been done yet in the industry the right way. So being able to have all of your first-party data, especially with the lower reliance, I would say, and that cookies apparently are not going completely away, but the lower reliance on third party cookies, and providing a better experience for customers. So we were talking a lot about personalization, right, across channels, ads being one of the channels and being able to more precisely target your audiences on ads using first-party data is really going to help save costs, frankly, on media buys, so you don't have to target your entire audience. You can be much more precise on your targeting and then increase conversion rates because the targeting is more precise again. So folks are going to be more interested in what you have to show them.
And then a few other things that we're working on having agentic. Obviously, you've seen throughout this week that it's becoming a must everywhere. So building agents on top of AEP. So either using Adobe's capabilities that they're developing right now or potentially using Amazon Queue to help overlay on top, imagine being able to task agents to build CJA dashboards based on maybe some of your using it for migrating for analytics, for example, to CJA, or thinking about new dashboards you might be able to create. So that could be very exciting. And then same thing for segments and audiences being able to create those in a more automated fashion, and then use them for personalization is going to really help, and knock a lot of value for that.
And then a few other things that I'll mention is, the fact that the platform is on AWS really does enhance some of those integration. There is performance benefit, as Tomo mentioned very early on in the presentation. There's some performance benefit and security benefit to that. We do have our dual zone solution that helps a lot with that where you can have what we call a zone one in AWS. So something that you build custom on S3 where you bring all of your data, and then you can do things like data hygienes, quality, maybe more sophisticated IDR before you ingest the data into AEP. And the fact that both could be on AWS, will provide good synergies there as well. So, yeah, lots of good opportunities now that this is going to be live, for us to work with our clients on enhancing and providing more value. It's great. And a lot of really good accelerators, like you mentioned as well, as we continue to do this for more clients. Yeah. All right. Kevin, how about you? Yes, from an Audible perspective, we're still very much in a crawl stage, right? We just went live January 31. So continuing to light up those use cases, get folks onboarded, start to really shift that mentality toward a customer-based analytics view, is going to take us some time. So, yeah, we're really excited about all these new things coming, but we'll get there soon. Yeah. But one thing we have been talking about quite a bit this week that is AWS related, is the RTCDP collaboration functionality and the ability for us to potentially use AWS Clean Rooms natively within that product for media activation, which media activation was not one of our initial use cases. So that that might be a fast follow, a big unlock, in a way that we haven't been able to do that today with our current tools. So, yeah, more to come for us, but again, we're still crawling. A lot of work. Yes. There are a lot more use cases for sure. - Yeah. - It's awesome. Awesome. Thank you. I hope you are all a little bit more excited about also going on this journey with AEP on AWS. Wanted to thank Kevin, Kenneth, and Tomo for taking the time to share their perspectives with us today. And thank you all for making it out here. I know it's a packed schedule. We're more than halfway through the week. Everybody has a lot going on, but appreciate you, making the time to be out here and have an engaged conversation. If you have any questions afterwards, feel free to come up to any of us, and I'm sure we're happy to chat, as you're thinking through some of this. But thank you all for coming. Appreciate it.
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