[Music] [Jacob Winter] Hello. I hope you're having a great Summit. Welcome to Data Doomsday: A Checklist to Survive the Next Generation of Analytics.

My name is Jake Winter. I'm a Principal Lead at Adswerve.

Today, I'll be talking about all of those headlines, the blog posts that you read, the news articles that show up in your LinkedIn feed about, the cookieless future. All of the changes that are affecting our industry, and how sometimes it feels like the sky is falling. It can be really scary reading all of these articles, and I want you to know, one, we're all going through it, and two, we can get through it with a plan. And that's what we're going to discuss today is what can a plan look like, and what is the checklist to get ready for this future? First off, I want to talk a little bit about, how we'll focus mostly on analytics. There are advertising use cases that are affected. We're going to focus a little bit more on the analytics use cases. They're related obviously, but also, how first-party data will be a part of the solution. I know a lot of the headlines also allude to how first-party data can be the cure to what ails you as it relates to the cookieless future. We're going to go a little bit more in-depth into what that means, what first-party data looks like, and how it can help.

So I want to start with the cookieless future. The reality is, is that the cookieless future is not that cookieless. I'd really love if, we got rid of that term altogether.

There will be cookies going forward. They make the web work, and those useful cookies will be staying. And quite honestly, they'll be part of the solution. Those are the first-party cookies that will be set and used for identification. The cookies that are going away are the creepy cookies, like this guy here. He'll be going away with the changes that Chrome is making. These are the third-party cookies. So these are the ones that track you from website to website. These are the ones that, quite honestly, maybe know a little bit too much about you than you want.

And they've been quite honestly, being blocked for years. Going back to as early as 2018 and 2019, Safari and Firefox have already been targeting these third-party cookies and blocking them. A lot of the analytics vendors at that point switched over to using first-party cookies, and then Apple ITP started to target those as well. So even with something like a CNAME, if you're using smetrics.yourcompany.com they're not being blocked, but they're being reduced significantly. So the lifespan of that cookie may be significantly impacted, as short as maybe seven days. And then Chrome is the last holdout. Those are the changes that are going in this year, and those will be the changes that get rid of these the last of these creepy cookies.

What does this maybe look like for you? The removal of those, cookies and the seven-day limits that Apple has put in place probably results in something like this where you see more new visitors showing up on your website and a decrease in returning visitors because that lifespan of the cookie is reduced, and you're not seeing that, longer activity across a greater time period.

So what actually is the cookieless future? There will be cookies in the future like we talked about. What we're really focused on is cross-domain tracking. If you have multiple domains that you've been tracking and using something like an ECID to track them across, after these changes that Chrome will be making this year, about 60% of the market share is Chrome right now. Those use cases across domains won't work anymore. And quite honestly, there isn't a great solution. There is not a fail-safe approach to being able to track across domains because quite honestly, we shouldn't have been doing it to begin with. But there are some actions that we can take to try to mitigate the situation.

And that leads me to the first survival checklist item number one.

Consolidate and reduce domains. And I know a lot have already been doing this, but the use of a sub-domain works if you need to. So like, my.company.com versus mycompany.com Those IDs, if you use sub-domains, will go across and be retained, and you don't have to worry about them being deleted or blocked.

Also, you can work towards preventing proliferation of new domains. So if someone comes up with a new idea, a new campaign, and they're saying they registered a new domain, don't implement on a new domain. Have them just set up a landing page on your existing domain. That'll make it much easier to track, and you'll be able to see the outcomes that are happening. And then lastly, for any, like, mergers or acquisitions, bring it up early and often that domain consolidation should be considered, that you should, as you bring them in, bring those domains into the fold if you can, as early as possible because that'll help measurement.

The next step that can be taken is, develop that unified customer ID strategy. So we're starting to talk a little bit about first-party data here. So the IDs that you use internally will start to become those that you're using to stitch together journeys. So if you don't already have an ID that you can use across your various systems, now is the time to create one and to advocate for one. A few things to keep in mind as you establish the requirements for this, customer ID that goes across your various systems. Make sure it's on all of your domains. This will be kind of how you address some of that missing tracking. If they're authenticated, you'll be able to actually put them back together again. Make sure it's tracked consistently across all of your analytics implementation. Make sure it's in the same eVar. Make sure it's in the same field so that you can easily track them together and always know where it is. And then lastly, make sure that it's on datasets that are outside of your online experience. They're going to be in the future, and we're going to talk about this, how you leverage first-party data. Data that you want to bring in, and it's not necessarily on the website. A lot of times, you'll probably have infrastructure where there's different IDs that identify people on the back end than there are on the front-end. So let's make sure as you're putting together a strategy and advocating for this unified customer ID that it works both on the website, as well as the back end side.

And then our last, survival checklist item of this section is to implement a server-created First Party Device ID. So this is really to address that, reduced cookie lifespan that has started happening with ITP. If you create your own cookies and create them from the server, there's some certain specifications you need to follow. But if you create those on your server, they won't be affected by those reduced timelines. They'd just be like any other cookie that makes your website work. This can allow you to use a lot of the existing cross-product capabilities within Adobe if you utilize their FPID solution. So it does what they call seeding, where it'll pass your ID into their system, and it'll return it as an ECID. So you can use all of the cross-product capabilities. This does require using AEP, Adobe Experience Platform, Web SDK. So you'll want to make that a priority as you move forward is making sure you move over from Web SDK. It's time for app measurement to move on. And then, this also allows you to have better control over your own IDs. So if you're thinking about privacy, which we'll talk about in a moment, having your own IDs gives you more control on how to handle them, what their expiration should be, and how do you actually want to track them over time from a privacy perspective.

So that brings us to the topic of privacy.

Here we're going to focus on how to be proactive when it comes to privacy. It's probably the other thing that shows up in your LinkedIn feed. I know it does mine. New state passing legislation as it relates to privacy. At the time of this recording, there are 12, but there probably are more already, with a number pending at this time. And the reality is this is a trend that will only continue. And ignoring it is not an option anymore, if you aren't already implementing something like consent management tool or thinking about how to implement consent, you need to. It is overdue, taking consumer's privacy into account as we come up with a plan of how to track, needs to be first and foremost, and we need to have kind of a consent-first approach, which brings me to the next checklist item. What you really should be doing going forward is adopting the most strict approach. Think about and work with your counsel, work with your privacy team, and come up with the approach that's, kind of the most strict and can cover the most versions of the languages of the laws that can address all of them and then apply it consistently so that you can have a consistent view of the data that may mean things like having less data. It may impact the amount of data that you can actually track, but it's the right thing to do. And we'll talk about other alternatives and how to still do the work that you did before, despite missing some of the data.

So getting comfortable with incomplete data. This is quite honestly been something that you've probably been dealing with for a long time as well. Like, we were talking about the cookies. Between those cookie restrictions, ad blockers have been affecting us for a long time. And then just not having consent, there's going to be a significant decrease in the amount of data, and that has to be okay. It's going to be a sample that we're working with. The expectation of completeness with analytics and behavioral data is not there anymore. This is also going to affect the detail within the data. So something like the user agent-based dimensions that you see, like, the operating system and browser, those already you probably noticed with Apple, have been reduced. You don't get as fine-grained. They're going to be rolled up at a higher level. And at some point, I don't even know if they'll be there completely. It's something that we can't necessarily rely on going forward. So this has been something that you've been dealing with and will be a reality going forward. So what can you do about it? It seems like, the walls are closing in. It doesn't it? What is the best tact that you can take is, there's going to be other datasets within your organization. There's going to be allies that you can work with, to start to augment this data. If you're working with digital analytics data alone, now is the time. Some of the tools are becoming more friendly to bringing in other data. For example, Adobe Customer Journey Analytics. Now is the time to start laying the foundation if you aren't already using it, to start making the alliances to bring in some of that other data if you aren't already, and work with those teams. A key component of this is getting buy in with those other teams. It can't be a situation where you're going to them and saying, give me your data. That will fail almost every time I've seen it, and it won't foster a relationship. What you want to do is make it mutually beneficial. Make sure that they see the benefits, give them the access to the tools, may help them see the reports, help them explore them as well. That will get the buy in so that this is rising tide that lifts all boats. You want everyone to be participating in this because as other data is brought in and it augments this incomplete data that is gradually becoming more incomplete over time, you can get a better view of the customer. You can get a better view of their journey, and everyone can benefit from that together.

So that brings us to our next section, which is modernizing your analytics ecosystem.

Historically, digital analytics teams often kind of live on an island, away from the rest of the org. Their tools kind of work on their own. You don't have to necessarily worry about interfacing with some of the other analytics teams. They've got their own processes. They've got their data warehouses that they use. And you may pull some data from them like we were talking about earlier where you want to create those better relationships. That is the case on their side now as they're going through their own modernization processes. It's time to start participating and getting a little closer with those teams. Learn a little bit about how their systems work, learn about their migrations that they're going through, and try to participate as much as possible if you aren't.

And quite honestly, some of those things that they're going through are things like, shifts in processes. A lot of teams are going from that ETL, extract, transform, load process to the ELT. They're flipping those around, and that's putting a lot of strain on the amount of transformations that teams are needing to make. There's probably opportunity there where you can work with them, and help them. And especially if they're working with your data, help them understand it better to be a little bit more efficient.

So that brings us to the next checklist item, which is to really focus and capture the events that matter. There's kind of been an inclination within digital analytics and analytics in general to, just because you can capture it to capture it. Instead, let's focus on capturing the right data most of the time instead of all of the data some of the time. Because quite honestly, when we try to capture everything, we end up missing a lot of the things that really matter. We can instead focus those implementations so that we start tracking the metrics and the events those are the ones that really affect the journey. Those kind of key moments of truth that happen along the journey, make sure that you're always capturing those as much as possible, as opposed to trying to get every little click, everything they view, you're going to end up missing some of the things that matter. That might also mean that you think about data in a different way. We often collect data through the front-end, through JavaScript, things like that. If you work with and start building those relationships with either your product teams or other business and analytics teams, you might realize that some of those data already exist in a different form. Some of those events may be tracked through server-side methods. This is a little bit returning to some of the days of analyzing logs. We're going to have to get a little scrappy sometimes, but using other sources that may be server-side, and that may also be some type of, event based server-side tracking that you can work with. If you're using something like a tool like CJA, I mentioned, it's relatively easy to bring in data from AWS, from a cloud solution, to augment. Like we said, we're going to augment our data, to build out the rest of that story, getting creative and using other methods of tracking while still honoring privacy, and using the consent mechanisms that you have implemented, putting together that story and helping augment your data and focus on the events that really matter that affect your journey.

Next, this is really important as it relates to working with the rest of your organization, and this is part of modernization, as well as the days of props and eVars are numbered here...

or in other tools if there's other, like, new variables, or numbered props will be going away, and this is a good thing. Having semantically accurate data helps with protecting it, making sure that it's the privacy policies that you put together that you can actually implement them. If there's a prop that's changing its meaning on a quarterly or yearly basis, some of those policies can be difficult to maintain. This also, I didn't want to get into it too much, but will accelerate some of those generative AI efforts you probably are getting pushed on and asked about. If you have data that's well understood, it's semantically accurate, as much as it's believed that AI can handle all of this unstructured data. It's going to go so much better if you've learned anything from some of these examples and some of these cautionary tales with generative AI. The more understandable it is, the better it's going to perform in these types of models.

Like I said, that governance is going to be easier with these semantic models. So a data model, let's be clear when I say, like, a semantic data model. Adobe has their version of it, which is XDM. This allows you to structure it and name the data as it is so that if you're working with product data, you name it a product price. If you're working with something like health, or appointments, or providers that you're actually naming it the actual appointment as opposed to putting it in an event. These are the types of things that are going to really help lay a foundation for the rest of the data that you're going to use going forward, especially as it gets coming up with data coming from other clouds.

And if you're not necessarily in a place where you can start using XDM, there are steps you can take. One is implementing Web SDK like we talked about earlier and utilizing schemas. And, as well as this is kind of the bare minimum is if you don't have a data layer, making sure that you one, have one, and two, that it starts to, kind of, mimic what you want your data model to look like as you start to actually design those schemas for the future because that is the direction that we will be going. And if you use Web SDK, you can start using those schemas so that you kind of get an idea of what the data will look like going forward.

Speaking of the future and what things will look like going forward, this is me, prognosticating a little bit. But what are some of the things that we can expect? Because we want to prepare for it. We want to know what to look for. I think one thing is, potentially some of these tools, kind of, how CJA works where you can consume and connect data from any cloud, from any source that AEP can connect to, will be kind of cloud-agnostic. They'll allow you to work with the data where it lives. I think another thing that will happen is as opposed to these BI tools that kind of solve everything, they'll look a little bit more along the lines of CJA. So a tool that's maybe more purpose-built, that allows you to use a specific data model that's tailored for something like customer journeys in this case, but it could be other use cases as well. This allows you to, kind of, explore the data more effectively without needing a bunch of SQL developers to prepare data for you. This is especially the case with event data because of the breadth of the data that can contain it.

And then the last thing that I think just to throw in there, it will be probably AI-assisted, rather than replacing your job. I don't think that's going to happen, but there are absolutely use cases, and you've used it already. I know I do, where you can either whether it's code, whether it's quickly chugging through some data, it will allow you to answer some questions quicker and get some work done and be more efficient. And I think a lot of these tools will start to have, some type of AI assistant that can help you process this data more quickly and find the insights. All right, so we're getting into the home stretch here. So some of this was probably hard to take. Some of these changes, we don't necessarily want to do. We've been avoiding them for a long time. Some of these Chrome changes will kind of force the issue this year. But some you should probably have been taking for a while here, especially on the privacy side.

Reality is change is hard. There is potential there though. There are silver linings. There are new ways that we can work that we can probably even do better than we did before by building these relationships, by incorporating this first-party data that we're going to work with these other teams and understand and incorporate and build buy in. This isn't the time to panic. It's time to evolve.

So let's run through our full assembled checklist here. This is what's going to get you through the next generation of analytics.

So first off, we have that, consolidating and reducing domains. We want to reduce those because we won't have that cross-domain tracking anymore. That won't solve all of the problems, so we'll also want to throw in a unified customer ID strategy, encouraging authentication and getting that ID set and getting it consistently set across systems.

Next, we're going to address those ITP and cookie issues by creating our own IDs. This also helps with privacy. We're going to set our own lifespans with those cookies. We're going to set them in a first-party context, and we're going to use that FPID functionality that Adobe has.

Next, is taking the most strict privacy approach. We're going to not create this patchwork of different implementations. Just do what's right. Use our consumers consent, and apply it appropriately and across the board.

Then next, we're going to start to build those alliances, get the buy in from those other teams and data teams across the organization so that we can start augmenting our analytics data so that we can tell that full story despite the fact that we're starting to lose some of the data. We're going to fill it in with other options. Next, we're going to really focus on capturing the events that matter rather than chasing after every little event within the experience we're going to focus on ones that matter and maybe get a little creative with the ones that we do capture. And then lastly, we're going to start using some modern, semantic models and data schemas to help make our data easier to work with, easier to understand, and easier to apply policies to. So I hope you've had a great time in this presentation. I hope I've been great in the chat answering your questions. I'll be hanging around if you want to ask more questions in there. Maybe I'd be curious, if how many I said it a couple times, but how many of these, you're already doing? Give yourself a score. Are you at a two or are you at a six? Are you feeling pretty good about the future? I'd love to hear it. And then anything else that you may be any actions you may be taking within your organization, I'd love to hear it too. I'd love to keep talking with you too. I'm Jake Winter on LinkedIn. Again, I'm with Adswerve, and thank you so much for the time. [Music]