Adobe Real-time CDP - Use Case Mapping to Solution Capabilities

Transcript

All right, great. Again, I’m just saying, join today with my co-presenter here, Ben Joseph. So let’s talk about the high level agenda today. So we’ll be talking about what is our CDB again at a higher level and what are some of the purpose driven use cases related to it. We’ll talk about prioritization of these use cases and the fundamentals. Hotels, business value and towards the end will move towards how these CDP features and capabilities they align with these use cases. So this particular slide will serve as a brief refresher for the issues that our CDP is able to tackle. And what this approach is also address a blend of industry and organizational hurdles from a customer perspective. It can call it confronts the issues related to segregated marketing tools, scattered data origins and overall shifting governance regulations. This is data governance I’m talking about and equally crucial former external or industry viewpoint. It’ll tackle the ongoing shift with the deprecation of third party cookies that BFC will be talking about impacting use cases that have long depended on them for approximately two decades now. These use cases they’ll include paid media retargeting, prospecting, personalization and audience suppression strategies. So RTC, CDP, it addresses the challenges within this particular architecture diagram, and its function is very similar to a DMP audience manager, for example, and it encompasses the data ingestion audience management and overall data output structures, except it goes far beyond that. And in its overall infrastructure and capabilities. I’m talking, I’m comparing audience manager or any DMP to our DCD, and it enables the use of more resilient first party data identifiers, including NPI, data, advanced identity management and any segmentation capabilities. Moreover, it incorporates evolving AI functionalities that enhance audience creation capabilities. Now, when we’re thinking about how RTC, CDP can help solve challenges within your own business, one of the first places we tend to look is use cases. But it’s likely that there’s no surprise that our CDP use cases. They can be very extensive. So if you’ve seen versions of our Use case libraries, you’ll know that they can vary by RBC to be version industry or even the customer goals and overall strategy. So one one of the first fundamental steps is ensuring that RTC, CDP, it’s set up for success and establishing and prioritizing your own use case. Those that will not only be achievable and measurable, but also drive your own business forward. Now, how we go about selecting these proper use cases as a pace as opposed to boiling the ocean with what CDP can do. So while this slide, we’ll talk about what helps us evaluate and decide which use case is more relevant to us. Now, understanding the potential of CDP in terms of use cases is very crucial for us to be able to grasp its capabilities and possibilities. It’s essential that we align this understanding with your strategic priorities, goals and cables. Distinguishing between use cases and capabilities is a key here because on the right hand side you’ll find supplementary details and links for further escalation. And it’s about mapping out these use cases, ensuring they align with your marketing tactics and overarching business objectives. They should directly contribute to your bottom line goals, and it’s important that the use cases are measurable with specific outcomes. And keep in mind. Now begin this by familiarizing yourself the various use case that RTC DB can address. Then you can align them with your business objectives. Prioritized those that are pertinent to your strategy, clearly differentiating between the use cases and capabilities, and more importantly, establish a direct correlation between definitions of these use cases. And like I said, your bottom line goals. Secondly, evaluate those specific KPIs and make sure the use cases they align with the specific metrics that are both achievable and time based. You can make sure that you have the right technology to support and execute these use cases, and then some might happen outside of Adobe technology as well, such as some downstream paid media activation. So you ensure that there’s an under understanding of that level of effort and the additional costs. Also, more importantly, confirm that you have the right people and the processes in place to make sure these use cases come to life. Some of them might require some cross-functional teams or even outside partners and working in close collaboration of each other to make this happen. Last but not least, make sure the use cases they fall in line with your own company complaints, standards and policies. Evaluating your use case against these elements will overall help you to hone in on not just a few due parties, but bring to the market? So you go through these exercises and let’s say we identify five use cases to execute with already CDP. Now we can start focusing on how we’ll do this with all solution capabilities almost there, but not, not quite yet. So as a way of bridging gap between use case selection and capability mapping, we always recommend to take step between which generally encompasses and taking your selected use case and considering where they fall into the marketing funnel. This will then allow you to start thinking about various components that will be very important to you to put your use cases in motion and in addition to that, the solution capabilities we’ll talk about shortly. So we’ll use an example here of your standard marketing funnel where you have awareness prospecting of new customers to the top retention and finally, upsell cross-sell to your current customers at the bottom and then the various forms of overall engagements in the middle. So like I said, we’re using example here of different components. You’ll want to consider when creating strategy and overall or on your use cases, we’re going to use a general example of a retailer trying to sell jeans so we can we can call them brand. And that first starts off with considering some specific audience definitions. Now, who is the audience you know that’s looking to that we’re looking to reach and engage with across our various use cases can be clearly defined. Them can clearly define the cohorts that fulfills the use case. Once we had that, we will then want to think about what data sources actually make up your audience. Now, maybe a partner data helps fulfill Legion at the top of the funnel, while CRM data or logging data will define your current customers and identifying these sources helps ensure you if you have proper data needed to build up your use cases. Now, once we have that, we can then start to think about various tactics and or strategies that we want to leverage that align with your use cases that you’ve selected. Do your objectives, do they call for retargeting or any upsell or cross-sell or maybe any frequency management? And then do you also have idea of the technology involved or solutions? And we’ll use that to execute each of these use cases. Do we have that? Maybe the CDP is near the top of the funnel and, and then an email provided towards the bottom for activation? We also need to know we have our actual delivery methodologies for these use cases, maybe some walled gardens or the publishers for media activation, some mobile or some as push for any retention based use cases. And then keep in mind then some of these elements they might have been known to known from the get go, and then that’s perfectly fine. But the intention is that before you start jumping into the weeds with our BCP CDP capabilities, you’re thinking about your holistic strategy and architecture and how everything will ultimately play to get use cases. All right. And for today’s example, we’ll obviously want to ground ourselves in a sample use case when we start thinking about functionality and we’ll select, let’s say, these three use cases that align with our retail example that I mentioned, the jeans and the brand and having the goal of basically selling jeans. Now these use cases, they can be pretty straightforward. They’re very common among the all our CDP customers, at least as retail customers. And we’re looking at prospecting a use case. And then with the goal of finding net new users without the third party cookies, we’ll look into, we’ll look at re-engagement of these use cases. We want to retarget the users we have that they have abandoned a conversion before the purchase which is a very common use case abandoned cart use case. And we will also look at the evolving lifetime value that will focus on personalization, how to convert their own customer to purchase a new complementary product. The upsell cross-sell stuff that we talked about. And as you can see, this is obviously a simplified example, right? So we’re aligning our defined use cases to the various phases of the marketing funnel that we mentioned at the beginning. All right. So now that we have identified our use cases, determine their placement in with our marketing funnel and outlined how they will connect with specific audience or solutions and furthermore delivery methods, now we are ready to dive into the capability mapping. This will entail ensuring that we harness the appropriate RB CDP functionalities to be able to execute our use cases effectively and achieve those business goals. To the initial step. It is basically to familiarize yourself with our CDP capabilities, which are which you can see on the mark invert out towards the left of the screen. It is very essential and important that we understand where the various functions reside within the core pillars of authorities. CTP And one of the example for that would be say, data mapping or schemas correspond to data in while destination services align with the data out in activation. This sort of takes us back to that architectural icon that we saw in the very beginning of our CDP. On being data sources, being on the left already, CDP being in the middle for segmentation activation, and then finally the data out or the activation part for connectors or extensions towards the right. It’s very crucial to understand in graphs not only what the capabilities entail, our CDP capability is, I mean, and their intended functions, but also their desired outcomes. What is the final use of these capabilities? What are we getting out of them? And this understanding, it’s very important for aligning each function with with our use cases that we have selected and prioritized. So for example, customer air, right? It’s designed to generate a cohort of users or profiles with a specific propensity to convert or churn. Now it will help us aligning the function with, again, our objectives, effectively our business goals. It’s also very important to note that this is an exhaustive list that we’re showcasing here on Sorry, this is not an exhaustive search that we show giving your it’s it does list a lot of the major RTC capabilities, but there are many more and they’ll matter depending on how complex or straightforward your use cases. And we also always encourage our customers to leverage some of the learning materials on the right or further education or individual functions that you may have. All right. So once you have that firm understanding of what the major capabilities can do, you can then get into the process of solution capability mapping. Now, basically it means once you have identified as you use case, this was this will generally happen on the marketing and the business side, well they identify use case. Now you’ll need to get a better understanding of what RTC CDP capabilities can actually enable this use case. And we have already reviewed let’s say we already reviewed our use cases and you have grounded yourself with what definitions and intended outcomes are can then start with number two in the flow. If you see on the diagram on the right side, there’s number two, this one right here. So you can start with that to consider which features are going to be leveraged to execute or use cases from there on onwards, you can begin to consider how exactly are these CDP capabilities can be utilized in different ways. And it’s very crucial, important to understand the strategic applications for which they will be leveraged. Now, once you’re beginning to utilize the functions in the right and the meaningful ways and start seeing results, you can also start to look at the ways to expand the maturity, right? So almost like a coral walk, run model, I would even say crawl, walk, run, fly model. And these can include at least the running. And the flying part can include tactics like AML or overall automation or creating some testing strategy right within our CDP and other activation solutions connected. And finally, we’ll want to ensure that we’re trying to use cases to to the correct capability is for those specific outcomes and measurement plans. And then we’ll also go to all these steps in more detail. But let’s start with number two, right? The one we just highlighted and where we think about the actual mapping process. All right. So and what this mapping process entails, it helps you figure out which capabilities are going to align with which use cases out of all the ones that you have prioritized. Now, obviously, there are many ways you can map, diagram, you can map and diagram this out, but we’re showing a very simplified version on how some of the major features can align with the example use cases that you have selected. Now you’ll notice that some of these capabilities are evergreen, meaning they live across every use case at all times. So that’s what this this mapping diagram shows now is a feature like, let’s say, data collection that we talked about or in the schemas or real time profiles. So they’ll be capabilities that will be spanning across all of these. Now, some of the other features, on the other hand, will only be used across one or two use cases, for example, partner data, right, for prospecting and re-engagement. So you’ll just need those in the in the beginning phases. Once you have them converted, you might not even need that data anymore. And the composition canvas is used for evolving lifetime value. Now keep in mind that it’s completely normal, and I would say very much expected to have multiple features and they’ll overlap across all these use cases and different phases of the funnel. And you can you can structure this in whatever way that works best for your workflows, your use case, and you can leave out a lot of, I would say, always on capabilities that are more rooted in the setup overall, set up an infrastructure and if it’s easier only focus on one or more of those audience management capabilities. Now, in fact, for the sake of our examples, we are only going to focus on the post data ingestion capabilities today as we begin to talk about how we need to do this or how it’s done. So now let’s hone into the practical aspect of leveraging already CDP functionalities and features and address them. Address the requirement for our use cases that we have selected. Now, I will begin with some straightforward approach for audience segmentation, right? Focusing on that 1 to 1 static retargeting. This will include defining our audiences based on specific actions that they take on our website and devising them in a general strategy for the audience building and messaging that is tailored for these actions. The the objective is basically to illustrate how we can not only create these audience segments right directly aligning for each, directly aligning them for each use case. For example, I would say the mid funnel audience that are based on any downstream people is actions like browsing of genes or different colors or sizes, but also develop a comprehensive funnel strategy that’s aiming and guiding the same user through through the entire purchase journey. Now this basically serves an example for leveraging some basic segmentation capabilities and rest assured, good progress, right in sophistication and encompass each of these use cases ever formulated. Now, our next capability will focus on the idea of audience prospecting. So so for reaching out net new users, for example, like those who have never interacted with our brand or the brand A for the jeans and also keeping in mind this is all done without the use of third party cookies. So obviously this is directly aligning to our first use case. So as our example was, the next step is how we understand on applying this in real life. And after educating ourselves on the features, we know that this this works by allowing the ingestion of prospecting lists from outside partners, right? And these lists, they come from strategic and some operational conversations that you’ll be having directly with the partners of your choice. So there you’ll focus on procuring a specific audience that you want and aligning on things like, let’s say, cost or ingestion, frequency, etc… So those are some of the things that you want to keep in mind when you’re looking at getting that partner of your choice involved with the data. So in our example, we are basically attempting to reach new users that we have never seen before, but also some that may have interest in buying jeans. So our scenario, we’re working with a third party partner and procuring those prospecting lists for fashion enthusiast, for example, and prospective jeans purchasers right now from there already CDP, it has now pre-built schemas, right? So for these prospective audiences and we allow that for proper ingestion of all these audiences into the schemas are just hard to keep. Eventually. All right. So the next capability we’ll look at is an expansion of the former that we just discussed and the same concept of ingesting the partner data. But instead of using it to find new users, you’re leveraging it to enrich our existing profiles of users that we already have in our ecosystem. And a scenario like this will show how it’s applicable to our mid funnel use case that was basically targeting users that we already know about. And the idea here is to leverage partners to provide the additional attributes on the data that we already have. So we have a more complete view of our customers that the goal is eventually to make that 360 view of a customer in our in our GCP for activation. This will obviously help with more granular personalization and allow us to create very appropriate and niche messaging that will resonate with our customers a lot better. Right? It’s a lot more relevant for the customer. So there are a lot more chances that it will lead into the less of the related offers that you’re sending or any related messaging that you’ve seen. So a few examples that can be applied here is, let’s say maybe we have known site visitors that are interested in certain type of jeans, but the partner data now allow us to know that the users, you know, let’s say gender or age for a better targeting for them. So let’s say a female with a certain age range, you want to show them what’s the, you know, supposedly the fashion you recommend those products. And then through different data sets, you know, maybe we know that through search data that the user is searching for a competitor’s jeans in another brand. Now, this can also inform you some specific messages and targeting tactics. Now segment match. It’s another capability that we could actually apply to to offer use cases, re-engagement and evolving lifetime value. So what this feature does is it would facilitate the data share between two RB CDP customers to build up that profile trait and across overlapped profiles, and is very similar to leveraging the partner data for the profile enrichment. Basically what we just talked about. But in this case it’s a second party data exchange where the data, the sharing, it’ll mutually benefit both customers. And just because it’s second party, right, there’s no added cost these. So in our engagement example, let’s say we’re seeing the data with a retailer who sells specific vintage t shirts and with the knowledge of our in-market jeans customers, we are also being in in market for the vintage t shirt. So now we can create custom creative that showcases the attire pairing attire pairing of the combination of the jeans and t shirt that will better resonate with our customers. Right. So let’s pretend that our Deuce brand is also selling jackets. Now we have a recent jacket purchaser in a recent t shirt purchaser So maybe now we decide that we can cross sell them specific jacket types and that will pair well with a t shirt and jeans with all those new purchases. All right, now let’s get into step four of the flow and we’re going to start basically increasing the maturity of our features of use cases and creating more personalized experiences for our users. And so far, we’ve talked about basic use cases of prospective prospective customers, conversion from customer to some cross-sell. Right now maturing a little bit more. And then now we’ll start to look at some more advanced ways you can create these segments. But in real time CDP and how these can align with your use cases. So we can also leverage boolean logic right within our CDP to include multiple attributes or events. And maybe we want to target a user who has used viewed the jeans and the sizes and the colors. So recency and frequency levers can be utilized to determine the prospective prospective customer value. Now maybe we want to target someone who’s viewed the jeans five times last seven days, and a user like this will of course be more likely to be reached with a more aggressive retargeting strategy. Now we can look at these customized attributes and account values in this example that we’re showing that what it looks like across the evolving lifetime value use case and let’s say, for example, a user that has spent between 100 to $200 in the last 12 months on jeans, and we know that this is a segment we can now attempt to cross-sell the jeans to. So basically mixing a few more attributes and putting some Boolean logic between them and creating the custom custom attributes and leveraging the custom attributes to create these segments. We can also look at the aggregate or account functions, right? So the ability to say something like total average order across all the products is minimum 300. So you can use that as a it’s a complex logic, but you can use the aggregate tongue functions to put that in place to create that segment. And now we know that this is a frequent shopper, a high spender that could cohort and that cohort should then be managed as such. All right. So there are also different types of these advanced segments that can be leveraged as well, sequential segmentation. And like I said, it’s a very advanced one. So people generally shouldn’t start with this. But when you’re, let’s say up in the maturity curve, you can definitely start using the sequential segmentation and it’ll start taking into account that six tens of events in your audience building and audience segmentation, but also help align this to our re-engagement use case, right? So let’s say maybe after running a path to conversion report, we create an audience for prospecting, jeans, buyer used colors, and then jeans type and then virtually dry out. So that’s, that’s a complex, you know, segment and it’s also sequential segment like the events are happening in a sequence. Another example is dynamic segmentation allows us to use the variables to build the rule, to build the rule logic and dynamically express relationships. So aligning this to the same use case, we could create dynamic segments for the type of jeans, a user or a particular type of jeans that uses private browsing. So if there’s less than 20 different types of jeans that are creating 20 segments or 20 versions of activated, etc., we can only create one. And that can serve purpose for all these because it’s dynamic. All right. So this is a good one again, for an advanced capability. But let’s explore customer air. It’s the final feature on our list that we were discussing today. But it’s it’s an email enabled capability that also helps with creation for, say, propensity models indicating a user’s likelihood to convert or even churn in some cases. Right. So in line with our reengagement use case, we might utilize this capability or propensity score to ensure and assess a user’s or a customer’s inclination to either purchase the jean right post that virtual dry on that we talked about, or we could then target the users with the highest likelihood scores through high frequency and retargeting efforts. So this capability it extends to retention and involving lifetime value strategies. For example, we could generate propensity models for any recent gene buyers with high likelihood of purchasing a jacket right next, because we talked about that example, right, Windows T-shirts and jackets. So that can be also enabled using this capability once we have this propensity model in place. And similarly, we could also tailor these messaging for the user, even surpassing a certain propensity propensity score. Furthermore, this tool, it proves super valuable for churn prevention as well. So for example, we could calculate any churn scores for current owners and identify those with any highest likelihood of not making another purchase. Right. So it could test both purpose. You can increase the spend on targeting segments that are the propensity score is where they are likely to purchase more. You can also decrease the ad spend on some of those segments and cohorts that are less likely to make another purchase. So now you can target them either with special offers, right, aimed at either retaining their pat patronage or at at some point some. You just also have to learn to let go. Right. We know that no matter how much ad spend you’re spending on our own channels and the customers aren’t coming back, it is better to move on. I know customers generally don’t like to hear that, but at a certain point, as you have to decide to move on. And lastly, we will want to make sure that we include a value map. And what a value map is. It will start looking at our use cases, capabilities that align with your goals. There, your prospective value, and any other related KPIs that you that you might have. And this particular example, it it demonstrates that based on the different use cases we put picked up. So I’ll talk about one the middle example, the re-engagement right out of the funnel, the middle example. So the capability self is advanced segmentation or segment match or that part partner data enrichment we talked about. So our goal should be how responsibly and intelligently we are able to reengage these customers who have abandoned a conversion even before completing it. Now, what’s the value? The value is basically we have better site engagement and then we have improved content that enables better site engagement. We have increased our conversion metrics, could be, you know, number of orders, revenue, what you have it. And then we also have improved segmentation accuracy and lead scoring. Now how do we measure these those are the example KPIs, right? We’ll will measure it by the visits or the interactions on the web, overall conversions, any any trial signups or the number of overall product purchases or signups. Right. No major orders or revenue overall. So this is a very real world example, right? That’s why I want to share that. So that was the content. And we can now get into the companies and for anything that was, let’s say, unanswered during the webinar in the chat, we can get into that now. And while we do that, I’ll also drop in a couple of questions as a poll, right? This will help us better this program for future. So I will stop sharing and I will go to the Q&A pod. Guys, thank you so much. That was great. So throughout the webinar, it looks like we’ve only had one question in the Q&A tab. We’re happy to you know, I know we have some time here, so we’re happy to answer any questions and any follow ups that anybody might add. But yeah, so far I’m not seeing anything new. Okay. I will launch the the poll now as well. And while somebody else, if they’re thinking do anything, leave any questions, feel free. I’ll also launch another poll question. This will be basically if there is any other topics that you would like to see us cover any any future sessions, Is everybody able to see the second question? Ben, are you. Oh, yeah, I see it. It wasn’t refreshing on my end. Now it is, yeah. So recordings of this presentation will be sent around. So yes, you guys will have available, you guys will have content and recording available. I see a lot of, uh, well capabilities or CDP capabilities, more of them explained. Okay, great. I’m going to go back to the Q&A part and see if there is anything or in the chat. Yeah. This is great feedback in terms of additional topics. So it looks like many of these are feature function capability related. So definitely something that we can take back and figure out what roadmap plan looks like to get some of these capabilities on the calendar in the future. But this is a really good list right here. Okay. I’m going to give one more minute. And if you don’t have any more questions, we can give people 15 minutes back. And meanwhile, I just also wanted to thank all of you for taking the time and joining the session today. We also hope to have your company again for any future webinars that we will have. And thanks again and then have a great day. Okay, Ben, do you have anything else? If not, I can close the session officially. Yeah, nothing else on my end. Thank you so much AS. Thank you guys and for joining. See you soon. Bye.