51ºÚÁϲ»´òìÈ

Transcript

Barack Obama will give people another couple of minutes before we get started. While we wait to get started, I just want to mention this is a realtime customer data platform getting started. And although it’s called getting started, this is actually the last webinar of the quarter. There have been a few webinars before and you can access those on Experience Platform. If I remember while the meeting is going, will try and put the your emails to the previous webinars in the chat. Great. I think we can get going. So welcome everyone. As I mentioned, this is real time customer data platform getting started. Just want to make it clear. It is getting started so we only have an hour. And platform is of course a vast product. There are many different pillars that we need to touch here. And so it’s not the intention to go into in-depth detail, but we want to give you an idea of what to concentrate on in the beginning of your CTP journey. As I mentioned, there is a lot of material to explore on experience, leak and during the talks today you will see there are links that we have in this text that points to sections of interest. We will share this deck with you afterwards so you can explore all the all of these links. And of course, this is this is just the beginning. You can then continue exploring inexperience, leak through training, either free or paid for and for any of you who are ultimate success customers, you may meet us in the future in some sort of engagement to discuss more of this material. We are going to cover four topics today. I’ll do a quick introduction to start with. Then my colleague starts is going to give you an overview of Real-Time CDP. The way to use it, what is it? What are its capabilities? He is then going to continue with an overview of organizational readiness how to organize your team, and I will finish to call explaining about data readiness. So how to prepare and actually manage your data. Just to give you a bit of an introduction about who we are. So we are a team of of experts, value experts, architects and strategist. We are part of what’s called the ultimate success organization here, and our team really is there to empower customers to help them drive value realization. We’ve inspired the use of best practices and we help with strategic planning, all sorts of things, planning, including things like new use, case mapping. And of course, this all applies to the whole experience, solutions and platforms and all the apps that it contains. So without further ado, I’m going to hand it over to who is going to start with the RTC type overview. Awesome. Thank you so much. Eves. I appreciate it. I like like he was mentioned. I’ll begin with just a quick overview or not a quick overview, but a high level overview of our CDP kind of going into, you know, why we’re talking about it, you know, the funnel that it exists and as well as some high level capabilities. And then I’ll go into organizational readiness, just talking about how to prepare your team because CDP is so expensive. Just making sure that you and your team have the the tools to be very successful in your implementation and usage of CDP. So without further ado, let’s get into it. So why CDP? So I’m sure that as we all know, personalization has been at the forefront of most brands digital marketing strategies. And CDP really serves as the engine to help execute these strategies. So CDP helps collect data from various online and offline sources and unifies them into customer profiles, both the customer and account level, which then give you and your team better insights into customer behavior, preferences, etc… CDP also has, you know, it’s built its own built in AI, which also kind of serves to serve better insights. We can get into that a little bit later in this presentation, but really the core of CDP is creating unified profiles and then providing better insights. And then once those profiles have been created, they can then be activated across all your branch channels, kind of giving your customers a consistent experience across all parts of your brand that they touch. So really, in essence, CDP is here to serve to simplify personalization and make it easier to deliver high value experiences to your customers. And so here’s kind of the funnel that CDP exists. And so it obviously began to data collection, like I mentioned. So KB has, you know, dozens of prebuilt sources to connect to platform that you can then begin to bring in data from so you know, known customer data, whether it be CRM, email, account association, etc., as well as unknown data, whether that be behavioral events, first party cookies, advertising data, things of that nature. And so as you move down the funnel, then we go into profile management. So once all that data has been collected, you can then unify that data into one. You know, I mean, obviously various, you know, profiles for both people and accounts. So both B2B and B2C are covered by Real-Time CDP and once those profiles have been created, you can then take those profiles and build audiences that can then be activated to, you know, hundreds of destinations, whether that be, you know, your advertising ecosystem, which want to personalize the site, exist within your teams. And so just to, you know, kind of wrap it up Open and Extensible Enterprises give you and your team the flexibility to build and integrate real time customer profiles with internal and external systems to address various use cases that you may be trying to implement on the streaming data collection allows you to bring together customer data, like I mentioned from, you know, online systems as well as offline systems. Trusted profile management gives you a control to govern your data. And 51ºÚÁϲ»´òìÈ has their own data labeling over in a few slides. And then finally, real time activation allows you to activate across various different destinations. CDP has many different people integrations for paid media owned channels, personalization tools, etc… And so getting into the capabilities, there’s three main ones that we’re going to cover unify people. And I can’t I don’t know the resolution pattern, data governance and native cloud integrations all exist across all of these capabilities. So that’s why they’re both on the top and the bottom. And so the three capabilities are shown here are the ones that customers tend to use the most, and these are data collection, audience creation and activation. And so streaming data collection kind of entails CDP having these people data source connectors as well as APIs to bring in data as quickly as these sorts of things can accommodate. And it really supports both people and account based schemas for B2C, B2B and B B2B data management, real time profiles and audiences. Real time profiles allow marketers to create a complete picture of their customer from profile information to account information on from a culmination of data that’s been ingested by CDP and an open and extensible activation, like I mentioned in the previous slide. CDP has dozens of pre-built integrations and connectors that connect to the broader ADTECH and MarTech ecosystems. It’s systems and you know, other systems that your your your brand may be utilizing to really allow you to have the flexibility to activate data and choose which ones you want to send out and activate towards. And then moving into these higher level capabilities, unified people and account identity resolution. This is basically under experience platforms, identity service. And really, it allows you to, you know, match partner IDs and all the data that comes in to really build out these unified profiles. In essence, a patented data governance. So like I mentioned, CDP has data governance capabilities and these can be accessed via the privacy console within CDP. And really the key features are allowing you to apply appropriate data usage labels, Configuring Marketing usage for label data, managing data policies, and enforcing data compliance. We will get into this deeper in a few slides, but just want to, you know, get get our feet wet with this idea of data, data governance. And then finally, native 51ºÚÁϲ»´òìÈ Experience Cloud integrations experience Experience platform can integrate with both 51ºÚÁϲ»´òìÈ products as well as non 51ºÚÁϲ»´òìÈ Solutions. And there’s, you know, hundreds of these to ensure that you know, any common systems, whether that be 51ºÚÁϲ»´òìÈ or not 51ºÚÁϲ»´òìÈ are covered and can be integrated seamlessly to ensure that you know your workflows are not disrupted when CDP is implemented. So moving into capabilities, we start off with sources. So source connectors provide access, like I mentioned to dozens of source sources across 51ºÚÁϲ»´òìÈ applications, advertising, cloud storage, CRM, customer success databases, eCommerce marketing automation, payments and protocols. And this really ensures that customers are able to access any and all data that may be required. So really, it covers a wide breadth of sources that can be integrated with CDP to ensure that any any platforms are being utilized by your brand can be unified into CDP. And so really the key takeaway from this is that source connectors make it much easier to bring disparate data into Real-Time CDP to leverage for both audience creation and activation. And so moving on to the bread and butter of Real-Time CDP, real time profiles, Real time profiles allow marketers to create a complete picture of their customer from profile information to account to account information from a combination of the many different sources that are available for integration. And really, it’s just I think I’d hammer the point home enough, but really just to ensure that everyone understands that real time profiles bring in all this information to both the individual and account level so you really understand the customer and get like a very comprehensive view of, you know, their preferences and their behaviors. And so the key takeaway for this is just that the unified profile is a central promise for any CDP. And it really ensures that you are delivering consistent behaviors across, you know, all the channels that you activate to eventually. And so once your data has been ingested by CDP and once these profiles have been created, segmentation service steps in to really help you build audiences from these profiles for activation. So the segmentation service provides both a user interface and API that allow you to build segments and generate audiences from the data that’s been ingested. And you can choose between attributes of that level data and existing segmentation to design audiences. And you can also estimate segment sizing and choose evaluation configurations depending on need for scale and speed. And so there is the segmentation UI within CDP that’s very intuitive in the sense that you can drag and drop different attributes that you want to segment by or event that you wanna segment by. And it makes it much easier to kind of begin to build out those audiences in order to then activate. And so the key takeaway is just that marketers can access an intuitive and easy to adopt segmentation workspace to build audiences for activation across channels. And finally, destinations. Real time CDP offers 75 plus destination partners in the areas of advertising, analytics, email personalization, survey and voice of customer. Really just the key takeaway is that you can begin to acquire new users and retain or mature existing customers and all channels and environments that your brand touches and utilizes. And so as we leave the funnel, we can kind of view this as kind of overarching capabilities and also exist that cover, you know, all parts of the channel are all part of the capabilities starting from sources to on activation. And that’s data governance. So all the data governance capabilities are real time. CDP, like I mentioned, can be accessed via the privacy console. And just to reiterate, there are various features, but the four main ones are, you know, applying appropriate data usage labels to your data on configuring configuring marketing usage for label data. So once that data has been labeled, you can set data usage restrictions by defining marketing use cases for the data. And this allows you to ensure that any profiles or segments that have been selected for a marketing use case are compliant with your data usage policies. Managing data policies, data usage policies support data compliance with appropriately labeled data. And then finally, just enforcement of data compliance. And so the key takeaway is that 51ºÚÁϲ»´òìÈ’s data governance capabilities are the industry standard for making sure your customer’s data is being managed and used appropriately. And so finally, I just want to get into 51ºÚÁϲ»´òìÈ’s AI slash machine learning capabilities. So Customer AI is a CDP is built in AI that can be used to address use cases for cross-sell and upsell by predicting whether a customer will purchase a product or service, and also help the customer retention by predicting whether that user will churn or not. It also helps to give you better insights into customer data, whether there be anomalies, so on and so forth, as well as giving you insight into, you know, areas where a customer may churn or you know, where they may convert as well. And so really it helps to generate insights at the individual profile level. And so with that, I want to now move on to organizational readiness. So as you can tell, there are, you know, a lot of areas that CDP does cover. And obviously, this is just, you know, the tip of the iceberg. But as we get deeper into it, you’ll understand that, you know, organizing your team is quite necessary in order to have a successful CDP implementation. And really, once you’ve organized your team, you’ll understand and receive better value and insights from CDP. And so starting off, we have this framework. The success framework, these are the four pillars that we’ll begin with. So we’ll start with team alignment. So how to align your team with your CDP vision. Then we’ll get into, you know, building a team, prioritizing use cases, and finally finishing off with the best ways to measure success. So the first step is team alignment. And the way we want you to think about this is how do you begin to build consensus through collaboration? Really, how you organize or how do you rally your organization around your CDP and digital marketing strategies? And so a helpful way to begin is starting off with a problem statement. So I’ve included an example of problem statement here. Third party cookie depreciation impacts our brand’s customer acquisition strategy in order to counteract this, we are investing in a CDP. So this is kind of, you know, an example problem statement that your brand may have. And so once you have this problem statement, the next step is kind of to begin evangelizing this information. So we know that as CDP helps you work more with first party data and also works with second and third party partners as well. And that’s kind of how you’ll address this problem. Even though we have a third party cookie depreciation. So really, you want to let your organization know why you got to CDP and how it’s going to help. So everyone is kind of on board with, you know, the goal and strategy behind why you have CDP. And in this case, it would be to address third party cookie depreciation. Until then, step two is really communicating timelines and team impact. So really, a best practice is to be transparent about what comes next. You know, how will teams change, who will be in charge, What do people’s day to day kind of look like? And this kind of goes hand in hand with us. Step three as well is how our role is going to change, you know, what teams are supporting us, initiative, etc… So really make sure that people understand within your org, you know, what this change is going to entail and really what they can expect. And then finally, step four is if if you do have a long term vision or strategy, you know, make sure that you’re sharing that with the team. And so really the key takeaway from this slide is to communicate, communicate, communicate. When you’re transparent and communicating the goal and vision for CDP that will keep your team informed and reduce any inefficiencies that may come from a lack of communication. And when everyone isn’t in the dark and everyone understands that it’s much easier to rally around and begin to kind of begin working towards the goals that you may have. And so next we’re going to talk about, you know, building the team, what that entails and kind of how that organization looks. And so 51ºÚÁϲ»´òìÈ’s recommended organizational approach is establishing a center of excellence. And so we are responsible for governing the use of of the platform, building an organizational roadmap, tracking progress, measuring results, focusing on enablement and communicating as you thought. The organization both are kind of like high level responsibilities of CEO. But obviously there are much more. And really, there isn’t a necessity to hire more headcount, but really kind of focusing on taking existing team members and carving out some of their day to day to help with their role in the Center of Excellence. And ideally, you want to bring in folks who have a variety of skillsets, whether that be I.T. marketing strategy, troubleshooting, etc… You want to just make sure that everyone has an understanding of and are bringing different skills to the table. I just want to do a quick slide check. Is can everyone see the slide that says the value of Center of Excellence? Okay, cool. Just got confirmation. Awesome. So really, a center of excellence has a lot of value that comes with it. And really the four areas that it addresses are leadership structure. So, you know, you get better alignment on digital strategy. It helps to reduce costs by having clear prioritization of projects and, you know, cultivates an efficient and effective environment. Furthermore, with this prioritization, you get faster time to value and you’re able to understand, you know, exactly what you’re working towards when you’re able to prioritize, as well as having a clear definition of KPIs, so on, so forth. And then also, you know, empowering teams and individuals through enablement. And so still we focus on four key aspects does governance. So ensuring the client invests in the most valuable projects and creates economies of scale from service offerings, support providing a unified, consistent approach and means for alignment on programs across all regional teams, shared learning trainings and certification skill assessments, team building and formalized roles are always that learning is shared. And then finally, measurements. The CEO is able to demonstrate by delivering on valuable resource, on valuable results. And this is done through, you know, educating marketers on how to use success measures to drive project projects. And so really, there are three key teams that are involved in SEOs so that the core team stakeholders and a steering committee or, you know, executive stakeholders. So the core team is typically the team that drives the day to day of the C-suite. They own the project plan and the roadmap and really are the boots on the ground getting stuff done. And they are usually supported by stakeholders and executives who are ensuring that things are headed in the right direction. And typically a core team is not, you know, there’s not a specific number of folks that are involved. But the core team, it really depends on, you know, the organization. But but it usually consists of a product owner of CDP and, you know, representatives from teams across the organization that will be using platform and moving on. The stakeholder team is more so responsible for helping the core team decide what key use cases they should be targeting. They’ll navigate some of the more cross-functional decisions that come with this new collaborative environment and kind of keep things on a straight path and kind of overcome roadblocks. And finally, the executive stakeholders are made up of the folks who own the budget or on the contract, and they are also kind of serving as a North star for the CEO by prioritizing use cases and kind of keeping keeping the team on the right path towards achieving, you know, predefined KPIs and goals. And so what other third step is prioritizing use cases. And this section is pretty straightforward in the sense of the slide kind of showcases the implementation process of CDP. So obviously you begin defining your capabilities, use cases, KPIs and strategy, then move on to designing the system, then building and testing, having a go live and then, you know, measuring value. But really this section really focuses on what comes first. Since you can’t implement a CDP without your use cases. So really you want to take stock of what you’re doing today on our existing processes that are working well and take some of those use cases and bring them forward during the CDP implementation and they can serve as kind of your North Star in terms of, you know what, how are you going to achieve value first and making sure that those use cases are guiding you as you implement. And just really the key takeaway is just to think about use cases first and foremost and make sure that they that there is something in place before you kind of try to jump in because, you know, you can’t you can’t implement everything all at once. You really want to begin eating the elephant one at a time and you don’t want to take it all in at once. And so really, you want to just take a testing mindset. So as as CDP stood up, just test the use case, learn from it and repeat when needed. But it really always comes down to taking action. So making sure you’re taking action and taking tangible steps towards, you know, implementation and, you know, make sure we’re not stagnating. And finally, we wanted to talk about measuring success. And so, you know, really the key step is to begin by defining KPIs and use cases so defined and aligned on KPI as in advance, and then define use cases that aligned to those KPIs. And then as you move along with, you know, implementing CDP and utilizing the system, you know, stop and check along the way if you are, you know, working towards the correct goal. And then also don’t forget about soft metrics such as, you know, are people happy? Are other questions that are coming up? Is their areas of uncertainty really just make sure that you’re checking in with your team as well? And finally, this is kind of how your CDP ment management path will kind of go. So, you know, as you start off, you may have data silos and you know, as you mature within CDP, then you’ll have your online and offline division and you’ll want to bring those different data sources together. Then, you know, there’s another division and then you’ll have, you know, actionable profiles, etc., etc… So just making sure that, you know, as you mature within the system that your KPIs will change and you’re just making sure that those are being communicated to both yourselves and the team. And so with that, I’ll be passing it back to Eve’s to talk more about data readiness Also. Thanks that um, so to start with, if you can go to the first slide, there are many pillars to do this as well. We’ve picked out what what we think the most important ones to start with. And one of those is data accessibility. So what that means is, you know, reviewing your data structure requirements for ingestion and preparing your data. So obviously, very important there is that to you, first of all, very carefully on the stand to help very well understand your your business use case for your data. It’s gonna be very important to identify your primary data sources that should be brought into platform two to address those use cases. Of course. But you should also think about secondary data sources with secondary data sources that could actually also refer to data from other areas in the business. So you may be setting something up for for your, you know, your initial use case, maybe for your business unit or your region or your brand’s secondary data. Sources could then actually refer to other units of the company or other regions or other brands that will be getting on board off of platform as well in the future. So it’s really important when you’re doing your data architecture and your modeling that you keep the whole organization in mind because you want to you really want to end up with a like a a standardized data model that will work across your entire organization. Then what we always advise is to create a high level relationship diagram. So how do these data sources, what what’s the relationship between them? How do they linked together? And then the next step would be to convert that into like a high level entity relationship diagram that is platform centric. So that means you start thinking about your profiles already, you know, how is it how are all these data sources link and and what will be contained in like a full profile. But you also need to think about experience events or all sorts of event data that will need to be brought in to make you to complete those profiles, but also to help you make decisions based on the behavior of your users. That means that for this you need to look at the other entities that connect your data across all these sources. So of course, I’m I’m thinking about things like customer IDs. You’ll have your ECI ID for like web data, which is sort of like the clue of, of course, all the 51ºÚÁϲ»´òìÈ products, but can be loyalty IDs and so on. And important in this is when it comes to IDs, we we work with namespaces idea what’s called Audi namespaces. So you may have different data sources, you may have different data sources where an email address is is the key or the main ID, what data sources or what namespaces then achieve is that even if you have like let’s say three email IDs, each will have their own namespace and so they remain separate and identifiable and and clear what’s what they refer to and that relationship that all of these IDs help. And the way these data sources are eventually merged into one profile that’s, you know, identified in what we call the identity graph. So yeah you’re probably not familiar with that term yet. You will hear that very often because that’s the identity graph is basically or sort of the structure of your your unified profile. Very important then as well is to start thinking about how much data is going to be ingested. As you can see, we think in this deck we’ve included links to relevant areas in experience leak. So at the end of the call we will share the stack with you so you can explore all of these links. Then on the next slide to next slide is about data ingestion, cadence. So what that means is thinking about your use case and how your data is is going to have to be interested in to platform in particular. Is that data going to have to be real time or can you just ingest it as batches best practice there is that unless data really is necessary as real time data is to just ingested this batch. So for example, if you you might have address data and you know, the ability to change address data, that is usually not something real time addresses can change, but once they’re changed, it stay the same. So that’s typically a data source that you would ingest as a batch and not real time. But on the other hand, you might you might be tagging your websites, you might do that with a Web SDK and all of that event data analytics data is streaming data. It might not be real time, but it’s it’s streaming data. We advise it to ingest data that you need in a tool like analytics, for instance. What I’ve historically seen a lot with customers is to just collect anything they think about, you know, just in case they need it at some point. But that’s not a good strategy when it comes to platform, not in the least, you know, because of performance and so on. But it’s really important from the to come up with a really good data model that it’s relevant to your organization and that is the data that you import, you know, don’t sort of soil it with with other data that you may or may not need. The next is to consider data integrity. So what’s the frequency you need to ingest data into to make sure that it’s up to date and that it’s that it remains relevant and accurate. And then you have to start thinking about the formats. This data will be in because, you know, this data might come from your own systems, like a CRM platform or some other platform you may have, you know, you will have to probably process that in in a way so that you can import it into platform. So you need to think about this. My data going to be in Jason or CSP or in any other format and this sort already I mentioned earlier, we have a whole bunch of connectors that you can make use of two standard connectors to for non data sources that you can use to import your data into platform and again, I’ve added a link here to the relevant documentation if you want to go a bit in-depth into all of this and to experience like you’ll be able to follow it using that link. Then the next part is about profile guardrails. So that’s a you’ll review the limits to help model your profile data and optimize performance. So as a prerequisite here, and when you design your platform implementation, which which is done through your data, through the data experts or the data architect and or enterprise architects, you need to, of course, know who is implementing AP and make sure that everyone is aligned on the best practices of the tool. We set default called guardrails when it comes to real time CDP profile data, and there are two types of quality really there. It’s like performance cultivating, which you could see as like a soft limit and performance guardrails or like usage limits that relate to scoping of use cases. When you exceed these performance guardrails, you may experience your platform, degradation or latency. And it’s we need to point out that 51ºÚÁϲ»´òìÈ is not responsible for such performance degradation. So If customers consistently exceed those, you may elect to maybe look at a license again that maybe gets additional capacity to avoid performance issues in the platform. So of course we’re talking about, you know, how many profiles are generated, how much data is important and so on. But we also have system enforced guardrails. So those are you can see or look at those as hard limits. So these are just things that are built into into the tools. So they relate to the UI and the various APIs that you can use on platform. And these limits, your limits that you can’t, you just can’t get run. So it’s like how much imports per minute of data per minute and things like that. So as I mentioned, the limits of the API and again also another important part of this is the concept of data cleanup prior to ingestion. So a common question we get from customer customers is how do I remove profiles that I don’t need anymore? We have a tool for that as part of the PPI, and so you can use that tool to manage in gestation and and reduce profiles and delete datasets. It’s important that you review your contractual limits. So again, you’ll you’ll set up your contract will be set for a certain amount of data sources, for instance, and the amount of profiles you can create. But for that there is a reporting tool where you can look at your license usage. So it’s a dashboard that you can refer to to see how you’re currently using and how you’re using against your your license, its usage. But there are other tools. So there is the experience event expiration, so that in the Experience Platform you can configure expiration times for all experience events that you import in datasets. This lets you automatically remove data from from profiles that is no longer valid to useful to you. There’s no UI for that. So this is something that you you need to configure with. 51ºÚÁϲ»´òìÈ supports. There is also what we call pseudonymous profile data expiration. So like experience event expiration, which is on the dataset level, pseudonymous profile data expiration is on the sandbox level and what pseudonymous profiles or among others is profiles, for instance, where no activity has taken place in a user defined amount of time or where profiles just are not in use or of any use. But it could also be profiles where you have certain only certain identity namespaces like like an ECI. The where you, for instance, don’t have alternative spaces like email or CRM ID or something. They might be marked as pseudonymous data and they might be marked as well for you to do delete if necessary. And then I want to talk a little bit about governance roles. So we’ve mentioned this a little bit already. Know the importance of setting up the right people in your team. We see four big sort of roles apart from the architects, of course, who are more involved in the design stages and, who might get then reintroduced when you use cases are being introduced. But first of all, we see data governance like as a as a concept of you that often this is not automatic and it doesn’t occur in a vacuum. And as we mentioned here, what starts as a role for one individual typically recognized as a data steward, as growing considerably as your data ecosystem is expanded. So data stewards are the main the main people when it comes to ensuring that your data complies with with policies. So data stewards, they’re really at the heart of the data governance, data reviews, datasets. They might supply data samples, they manage the data labeling that sort of mentioned earlier and quickly talk about later. Well, they create a data policy and they apply them to datasets and they usually communicate these policies to you, to the organization. Then obviously you will have data scientists who clean the data and get the insights that are required for the data engineers. They understand all the requirements to build a platform on. And then of course, at the end of the line here you have the marketers. They like the the end point of data governance. That data request the data, the data that Chris, the data from the governance infrastructure created by the data stewards and the scientists and the engineers and of course they do the analysis and so on. As we mentioned here at the bottom of the slides, effective data governance relies on data stewards having all the tools to properly label data that uses usage policies and make sure that your compliance with those policies that can be enforced. On the next slide, I want to talk a little bit about data usage labels. So we have different types of labels that you can apply to your data. And so it’s typically the data steward to apply these best practices to apply this as soon as the data is ingested into the platform. So this helps to categorize data according to sort of policies that apply. We as I mentioned that three main categories, you have contractual data labels, you have what we call identity data labels and sensitive data labels. So all the data you import, you can market stores. All of these categories have many different subcategories in it to effectively label your data and if we go to the next slide, I’ve put a link in here to our full sort of end to end guides on data governance. There are three main steps. So first you start with measure with labeling your data, as we just discussed here, but they stand and defines or helps you to define your usage policies. So with the labels, data labels allow you to categorize data sets and fields according to your governance policies that apply to that data. And labels can be applied at any time, but as I mentioned, it’s best practice to do this as soon as you ingest data into platform that any of your policies or usage policies, they are rules really that describe the kind of marketing actions that you’re allowed to do on that data or that you’ll get restricted from doing. And we have different types of policies. You have data governance policies which restricts data activation and marketing actions that are being performed, performed, and you know, the data usage labels that carry that are carried by the data in question. But There are also consent policies. So what are the profiles that can be activated based on your customer consents, settings and preferences? And then the last step is the policy enforcement. They’re all in, in the whole data lineage. So the timeline or chain, as it were, the data lineage plays a key role in how your policies are enforced. So platform in general terms, data lineage refers to the origin of the set of data and what happens to it, where it moves to over time and in the context of data governance. Lineage enables data usage labels to propagate from from schema to downstream services that that consume this data. So like profiles and destinations. So this allows policies to be evaluated and enforced so that all the all the points throughout the chain in platform. And so when policy police violations occur, whether this is on the audience level or in the destination level, this will of course, bring up errors and then it will tell you to to fix your either your labeling or your policies or of course, remove activation that you were trying to do, because it’s not it’s not allowed. So that’s what’s pretty clear. And the enforcement flaw there is when it comes to consent policies, there is automatic enforcement. But this is for customers who have like health shield or privacy security shield as an adult. And then there is also the control you have over what people can do in platform itself. So you have a rule based access controls depending on the role you have in in platform. But there are also attributes based access controls. So this based on the labels that you’ve put to data, maybe some users of platform are allowed to see certain bits of data, but not others. So it doesn’t just apply to activation in destinations, but also to what users can do in the platform platform itself. This is the end of my section. It took a little bit longer than I had planned for this. We only have 5 minutes, but those are 5 minutes we can use for any Q&A. Are there any questions that people have about any of the subjects we brought up? And as I mentioned earlier, this tech will be shared with you so you can explore all the subjects bits bit more in depth. Of course. I don’t think there are any questions in the chat either. Yeah, but with that, if there are no questions. Thank you so much for attending. Like you mentioned, these slides will be sent to you after this presentation is over. And yeah, thank you so much. This will also be eventually available on Experience league as well. And that’s also where the other webinars this quarter also live. So feel free to check that out when you have the chance as well. But thank you so much and have a good day everyone.