[Music] [Axel Schaefer] Hello again, at Adobe Summit, and welcome to this session around How Adobe Real-Time CDP Impacts Full Funnel Marketing. My name is Axel Schaefer, and I run the product marketing team for Adobe Experience Platform and Adobe Real-Time CDP in EMEA. I'm very happy to be with you today. I'm looking forward to share some inspiration and maybe some food for thought with you today. At the beginning of every conversation around customer data platforms, there usually is a conversation around the cookieless future or much rather the cookieless now. Normally, there's three themes that are part of these conversations. Number one, the always rising consumer expectations at all points in the journey through the right channels and in real-time. Number two, the dynamic policies and regulations that are forced upon us from the Google Chrome third-party cookie depreciation or from Apple's App Tracking, just to name two. And number three, the need for brand readiness and reimagination that organizations force, not only today, but also coming tomorrow. What does it mean for us as marketers to be able to continue to really sustain in this environment, to be able to continue to do the job that we are asked to do. There's three things I want to highlight. Number one, the shift to durable identifiers based on a very stable first-party data strategy. Number two, the expectation of personalization that is very much based on the actionable and accessible profiles that are created and that power real-time personalization use cases for marketers. And thirdly, not to be underestimated, the need for privacy and governance across different organizational parts and channels that is really essential to be maintained. When organizations think about how they acquire customer, how they maintain customer, and how they increase their customer lifetime value of these customers. Most businesses use a range of technologies to achieve these at the moment. This is about to change. And why do I think so? Well, if you think about how the CDPs have been used until now, they were very much used around your tension, very much used around how organizations can build stronger relationships and direct relationships with their customers as you can see in one of the studies that we have just recently done with our customer base. And also, to be used for increased customer loyalty so again, really very much around the customer lifecycle value and so forth. What we are going to be faced in the future with the change that I just outlined is, to be able to really engage and work with our customers, our potential customers, much early throughout the awareness phase, for example, as well up to conversion point and then going into retention phase that we've been touching on beforehand. In a bit of a different view, you can see here what we have done beforehand, as you can see on the right side here, working with known customer data to grow and retain existing customers, but also adding now early on upper stage funnel elements like finding and acquiring new customers through the awareness and consideration phases. Both of these are driven by actionable profiles for personalization across the customer lifecycle, and they are built on a foundation of really direct consumer relationships and first-party data, as I just mentioned. It all starts, as I mentioned as well, with the customer profile, very much an actionable one. Thinking about personal attributional data, names, loyalty status, for example, as I mentioned, phone numbers or email addresses. On top of that, we can build with behavioral data, such as websites visited, call center interactions, opened email offers as well. Thirdly, we can build on top of that with preferences. For example, with consent by use case, for example, or opt-in programs and offers that we have, or also, such a simple preferences in communication frequency. Lastly, we need to think about how can these audiences that we are creating be segmented into different programs that we do. For example, with upgrade eligibility, cross channel shopping behaviors, or propensity for churn. Now if we convert that, and if we think about that from a more structural perspective, there's three elements that need to go into this to make it really work. Number one is data collection, as I also just referred to, for example, other first-party customer data elements such as CRM systems, email systems, data lakes that you have maybe already existing, but also, as I mentioned, on the previous slide, from behavioral events, from first-party cookies, from device IDs, for example. And very, very importantly, also, through partner data that can be acquired with additional attributes to enrich your datasets. All that needs to be managed in collaboration with the right segmentation, leveraging AI and machine learning, as well as bringing the identities together in the end and based on a patented data governance aspect that Adobe is providing to you. If that is in place, you can very much drive real-time activation into the marketing ecosystem, drive personalization on-site and in-app, and also use the data then again in other customer systems as you can see here. Now this is a very technology-driven view. How CDP technology comes to life is by looking at the use cases that can be driven in real-time. So when we think about how to execute these use cases, there are certain recipes or certain elements of recipes that need to be considered. There's ingredients such as data attributes or behavioral data, as I just mentioned, consent and preferences, or audiences, as I also explained just before. There's other things, like how can they be added, for example, through batch uploads or streaming. And furthermore, there's elements of how broad or how often do I want to refresh this data? Last but not least, it's also an element of how long am I looking at the data that I'm trying to execute on. In order to drive efficient and tangible results, we at Adobe have looked with our customers at a very, very big breadth of use cases and have defined six priority use cases that are usually central to what our customers are looking to do. You can see them here. Number one, reaching prospects who have not engaged with your brand yet. Number two, personalize and remarket to unauthenticated visitors. Number three, building a persistent and additive view of customer behaviors and attributes over time. Number four, using AI and machine learning to build proactively opportunities and reduce churn. Number five, building a real-time experience layer that complements and enhances your digital infrastructure. And number six, control the access and set the policies across your entire enterprise. Let's look at these use cases in a bit more detail. First, reaching prospects who have not engaged with your brand yet. Typically, you want to acquire new customers in the wake of third-party cookie depreciation, or manage partner data and prospect lists to provide greater value with correct governance, or maximize the impact of first-party data. Typical impact from a business perspective is driven through growth despite the limited scale in the market, reducing risk of data misuse and building trust with our customers, or just creating the most personalized and helpful consumer experiences. With our partners like Facebook, we have generated four times higher return on ad spend when using look-alike audiences instead of keyword targeting. Secondly, personalizing remarketing to unauthenticated visitors, which typically surfaces through tie anonymous behaviors to known behaviors in near real-time for on-site and in-app personalization, or having consistent treatments for unauthenticated and authenticated behaviors across online and in-app channels, or delivering targeting campaigns for different cohorts. Typically, business impact is showing through maintaining up-to-date information about what customers really want and need, retargeting across devices in real-time, and of course, respecting our consumers' privacy and personalization practices. For example, a leading financial services company using Adobe Real-Time CDP to deliver better experiences, increased their website engagement by 300% in a really short time. Thirdly, building a persistent and additive view of customer behaviors and attributes over time, for which you usually want to combine multiple data sources into a single set of data to create real-time customer profiles, unifying everything known about a customer in the customer profile and scaled use for digital customer experiences, or stand up one global platform for brand's marketing teams to orchestrate online and offline data. Typical business impact here is driven through the creation of alignment across the organization to always use the most current consumer information in every touchpoint, and then delivering seamless consumer experiences at those as well. According to our Marketing Metrics, the probability of selling to an existing and known customer is up to 14 times higher than the probability that you selling to a new customer, so it's an obvious win-win situation.

Next use case is around AI and ML to build proactively opportunities on the spot and reduce churn, which typically is used to identify lapsed customers before it's too late and the consumer moves on to a competitor, managing segments across channels and ensuring consistent experiences with engaging offers, or creating a loyal customer base that will be becoming repeat customers over time. The business impact here is increasing win-back experiences to customers by delivering personalization or delivering connected messaging across channels to ensure no customer is left behind. For example, another customer of Adobe's, a leading restaurant chain using Real-Time CDP to win-back coffee program subscribers, won back hundreds of customers with 80% efficiency in just one week. Another use case, building real-time experience layers that complement and enhance your digital experience infrastructure is used for the increased marketing friendly use cases, run queries against data to answer questions, having consistency in how cloud infrastructure is integrated with downstream's applications as well, while leveraging connected profiles across different marketers' tools, as well as employing strong governance, which is obviously needed and security. The business impact here is that a CDP tool can be used also by non-technical members of your teams, accessing actionable customer views whenever it's needed by whoever needs that view to be had. And also, internal governance policies that can extend into your MarTech ecosystem and not just within the specialist teams. As a part of the proven value here, the client just sought 20 milliseconds latency from data collection to activation. Another client moved from a 72-hour data refresh cycles to just 14 seconds, so increase incredible efficiency wins on that. As another use case, we're having the control access and set policies across your entire enterprise, which is used to honor consumer privacy across channels, automate enforcement of data governance policies, or manage customer data lifecycle at scale for data hygiene best practices. You need that in order to subject to have and create subject level consent attributes and enforcement of consent at the point of activation, which is really crucial, as well as for data-use governance, data hygiene, and lifecycle management capabilities, not to be underestimated. Last but not least, data isolation and security controls within a single enterprise, for example, by brand or by market from a geography perspective is really, really key to be able to comply with these requirements. Here, for example, Home Depot has enhanced its governance around customer data and the efficiencies, to use and increase or to create an increase of marketing productivity by 50% year-over-year. In order to realize all of these use cases, it needs a few differentiated capabilities that can only be provided by A Natively Connected Foundation like Adobe Experience Platform. Some of these capabilities are, for example, streaming data collection based on prebuilt libraries of data source connectors, streaming APIs, and people and account-based schemas for known and pseudonymous ingestion of B2C data. Or first-party collaboration aspects, which supplementing first-party data with partner data and build on privacy-safe partnerships for acquisition and enrichment without third-party cookies. Third one would be real-time customer profiles and audiences, which are instantly updated customer profiles based on collective behaviors and attributes, including propensity models and insights with Customer AI. Not to be forgotten, patented data governance, which is a framework developed by Adobe with advanced controls for highly regulated industries or geographies to bring together known and pseudonymous data responsibly. And last but not least, open and extensible activation features for people and device-based integrations with various adtech, martech, and IT systems, APIs for custom connections in batch or in real-time.

This is not only what Adobe is saying. Please feel free to also use third-party validation as they're available from Everest Group, Gartner, IDC, or Constellation Research as you can see here now. Beyond that, there's, of course, various customer's examples that we can provide to you quite already across industries now. For example, increase engagement by over 50% from Alterra Mountain Company, cost savings of at least 15% or more from Red Hat, global scale with Coca-Cola, who centralized 98 million customer profiles from more than 100 countries, increased sales that Dick's Sporting Goods is driving, or insights to action with a complex structure of 30 franchises to be compiled through MLB franchise. Last but not least, I would like to recommend another study, which is the Total Economic Impact Study of Adobe Real-Time CDP, specifically to this tool that has been conducted together with Forrester just recently, which shows that a payback into this solution is done in less than 6 months, the ROI can be improved more than 400%, and revenue can be significantly increased as well. So please make sure that you download this study today as it provides you really, really strong insights on how your organization can leverage this tool and can benefit of the capabilities in place. With that, I want to wrap it up and share some key takeaways with you. Number one, as you heard from me beforehand, please make sure you validate your cookieless strategy across your organization. Make sure you prepare, you agree, and you join up your defined goals and plans with other involved parties in your organization. CDPs are natural facilitators for collaboration. Number two, define your use cases based on your business priorities. We went through a few, and as you can see, with the vast possibilities of CDP capabilities in place, agree on a set of priority use cases to start from. But always consider the headspace for growth that needs to be there when you want to advance in those. And thirdly, select your capabilities based on your customers' expectations. Do not compromise on customer experience, for example, with regards to real-time engagement. After all, our customers will be the ones that tell us what they want, and what they want needs to be enabled by technology. With that, I want to thank you for your time. I want to offer you to connect and continue our conversation. Please connect with me on LinkedIn. For now, thank you very much, and enjoy Adobe Summit. [Music]