[Music] [Nate Smith] All right. How is everybody? - [Man] Whoo! - Whoo! - [Katie Cipollone] There we go. - That's what I like to hear. Second day you've survived up to this point. Well done. I know these have been some long days. Thank you for coming to our session today. We're very excited to have a little fun this afternoon, okay? So we're going to start walking through some content. We're going to have obviously some giveaways and, hopefully, get you guys out of here maybe even 10 minutes early so you can get some good seats for Sneaks. Does that sound like a plan? Okay. All right. By way of introduction, my name is Nate Smith. I'm Director of Product Marketing for the Adobe Analytics set of solutions, and I am joined by the one and the only. Katie Cipollone. Hi. I'm an Expert Solutions Consultant for Customer Journey Analytics. All right. So if you came here to the 2024 Power Couple session, you are in the right place. Here's what we're going to talk about today. I want to set some expectations right upfront for everybody, before we get into it. So many of you I know are current Customer Journey Analytics customers. And we've had a lot of requests asking us, hey, we've got other stakeholders across the organisation that we really need to help them understand where does CJA fit in the current tech stack? We've got many of you here who are new to Customer Journey Analytics and evaluating, is this actually going to be a fit for our organisation? So we're going to address both of those today.

One thing I do want to mention, we are going to be walking through some demo. We are going to be walking through some technical concepts, but at the end of the day, this session is meant to be more of a strategic type of discussion. So we're going to walk through in that viewpoint, right, from a stat strategy, from a workflow, type of perspective. So that's what we're going to do today.

Here we go. You guys ready? Okay. Katie, why don't you kick us off and take us down memory lane here? Alrighty. So by now we all take web analytics for granted.

I'm sure some of you remember back to the beginning. Maybe you remember when JavaScript revolutionised the industry, and we moved from log files to tag managers. Or maybe you remember the first time we were able to connect marketing campaign data to website behaviour for the first time. The opportunity to actually report on web events connected to specific emails or even search terms back when search terms were actually available. Wink-wink. I remember being able to report on orders from an iPhone for the very first time. The device breakdown and site catalyst, for those of you who go back that far, coupled with the advent of mobile devices that enabled people to shop from their phones was like a watershed moment and so exciting to witness. But now we're evolving to the point where pixels aren't enough, and we need to be able to measure people. And not just digital experiences, but across all channels of interaction. And who knows what will come next? All right. So the reason we take this little trip down memory lane is because a lot of times, analytics, right, it's not important until it is, right? A lot like my help around the house, okay? So that's really what we've mentioned around here, when we think about the beyond. We are in a pretty unique time as we think about customer analytics, right? We've got economic conditions, macro conditions, all sorts of different things that are happening that the C-suite is like, "Okay, analytics is no longer commodity again." And so we're going to talk through a little bit about this, but the expectation that they have that every organisation has, I'm sure you hear this often is we need to go from mass marketing into one-to-one types of personalisation. So if you read some of the analyst articles out there, there's one from IDC. They did a worldwide survey of CEOs and they said the number one consideration for technology investment in 2024 and beyond was for, "improving the customer experience." The very second thing, how are they actually going to deploy that and be successful and be competitive in deploying that customer experience was "with data and analytics" to improve that digital experience.

2024 is the end of time, like I said. I think everyone's very familiar with all this, so I'm not going to dive into this in too much. But it's really a pivot point, right? There's a coalescence of a lot of things that are happening right now in technology. We've got regulatory changes that are happening. The cookies have, in fact, crumbled, right, starting in January, the final push through this year is going on as we speak. Think about the changes in privacy requirements that are happening right now, where you get mandatory consent, consent management changes, and then the customer demands have just exploded since the pandemic causing really just... I guess, allow myself to introduce myself. I'll say explosion twice, explosion in channels, right? The data that comes from all of these different customer channels that organisations have not had to rationalise an action on or even report on before. So while data may be centralised, right, a lot of you probably have data lakes. Right every one of you has a data lake where you have channel data that comes in there. It's not necessarily accessible to those who need it, to those who touch the customer experience. And also, just putting data into a data lake does actually not mean that it is meant for use, right? It's in one place physically, but it's still siloed. You have separate sources, you have separate tables and separate identities that still need to be rationalised. So a question that I would pose to you, a little rhetorical question is, ask anyone in your organisation, how easy it is to access not just data, but insight, right? What would be the answer? And think beyond executive reporting.

So what does this mean? Well, let's start our brave analogy for the day. And I promise it's not going to be any old American football analogy, okay? These challenges mean that it's not easy for organisations to find a repeatable success when it comes to customer engagement today. So it's almost like you're playing a game where you've got the other team that's really stacked with extra players on the field.

So football is, generally speaking, about scoring points to win the game. Do we have any Dallas Cowboys fans in the crowd? Perfect. They're the exception.

I kid. They're the second-best football team in Texas. The players do...

So the players they score, they win by kicking a ball towards an end zone. Business, right, generally speaking is about driving sales to increase revenue. And so you've got business stakeholders that every one of us service in some capacity that are looking for help in being able to court and convert customers. Now in both cases, it's not necessarily the what that is differentiating, but actually the how. How do we go about playing the game, whether it's football or business? So when it comes to customer experience and the kind that really provides repeatable success... That's not changing. That's what's going up and down. That's out of the corner of my eye. I'm like, "What's going on here?" Okay, we're good.

When it comes to repeatable success that how, right, is really important. And so you think about all of the customer data that we have that has brought together lots of new use cases when it comes to customer engagement. It's brought a lot of new data types that need to be used data structures that need to be rationalised and related integrations to really be built to drive sales and marketing and buyer related actions. Now I'm going to quote from, Forrester this time, this was in their 2023 Future Fit Survey. And it said that 67% of business and technology decision makers are in the process of adopting data capabilities to build and improve a complete view of the customer across channels. That was a top priority. Now on the flip side of that, what were the challenges to actually executing on that priority? So the top challenge, according to this survey is being able to take customer data to be able to process it and act on it at the speed needed by operations, business, and customers. And that's because ultimately customer data is special data and it's not just special data because customers are willing to crack open their wallets and give us money, right? Customer data is unique. It's special because of the properties it has. It's more than just traits or rows in a CRM, right? This is data that needs to be sequenced. It's behavioural data. It's event data that ultimately needs to be actioned upon. And so we hear from brands all of the time their current approach is, we need help. It's just not fast enough in what we're trying to do as we engage with customers.

All right, so now I'm going to introduce you to the greatest Power Couple known on planet earth.

You have no idea how hard I've prayed to make sure they stay together till after today.

All right. Now you might assume that I'm talking about Travis Kelce and Taylor Swift. But alas, that is not it. Not alas, but no, is really what it is. What I'm talking about today is your Customer Analytics Stack and Customer Journey Analytics, which will be the greatest power couple you have ever, ever experienced, together they can crush any analysis challenge. All right, so what I want to do is, if you haven't had a chance yet, I think I saw these were getting put on wrists. They might be in your bags here, okay? So go ahead and look in your commemorative tote if you haven't had one yet or gotten in there yet. These are handmade Taylor Swift-style friendship bracelets. And I hope every... There's over 50 Sayings out there. My wife and my daughter, huge Swifties. They saw three concerts this year, okay? So I really need to do well today because I need to pay for that.

That's really what... That's what this is all about.

So they got a bunch of their friends and they handmade all of these bracelets today. So wear them, love them, trade them. They're commemorative and they're off brand, which I love. So I'm going to channel my inner Ben Stiller here. This is handmade quality stuff we're talking about. So I hope you enjoy the shirts as well.

Even if you look like a nightmare, you can look like a daydream. How's that? All right.

So here's how we're going to move through the content today. Our game plan for the session is, we're going to be covering what's going on in "The Playing Field" in the analytics space. We're going to talk about the analytics team, which most of you are on, being able to bring in this outside talent if you will. To help provide value enhancement for the organisation, and then being able to advance the ball, or in other words insights downfield. And then ultimately, the big event, the Super Bowl, we'll talk about pulling it all together.

So with that, let's talk a little bit about the playing field. So when you think about the customer journey, let's look at a generalised customer journey here. Now at the acquisition phase, you're looking at who might be the segments with the highest value in targeting those prospects, right? But these are broad and really expensive brushstrokes as you think about your acquisition budget. Now as customers start engaging with the brand more and more across different channels, it really enables that brand to engage and to collect more data that they can then really inform great personalisation efforts. And ultimately be a lot more robust as we start to serve our customers with the most relevant message at the right time and in the right channel. Now for the brands that consumers have decided to have a relationship, think about the ones that you have a really strong relationship with. What are your expectations with that brand? You expect them to know you. You expect them to know you at a certain point in place in time.

Then it's not that just more data is being generated or is accessible through all of these new channels of customer engagement, it's a requirement by us as brands to be able to get a better handle on data and to be insightful and to reflect our understanding of a customer in their moment, right? That's why you hear so much at the conference this year about data, journeys, and content. That's a really interesting coalescence that really drives customer experience. Now it's like when the game's being played and as you get further down the field to the goal, the pressure's different, right? If I'm closer to that end zone, if it's first down versus fourth down, that pressure is different. And we need to be receptive to that as organisations when we provide experiences to customers. So with that...

Ultimately, if we're not doing this, what happens, right? We go through our processes and we start to have misvisibility. We start to take a long time as we try to draw insight out in our existing processes. And it's a lot like the quarterback dancing around in the pocket looking for an open receiver. You spend too much time, that's latency, and you're going to get sacked.

So what I'd like to do is have Katie walk us through the plays while we're on the playing field. Whoo! - Okay. - All right. So quarterbacks and coaches make decisions in game based on the conditions as they're happening on the field. They choose the play based on who they're playing against, the context of the game, and the status of their players. The playing field and the conditions are always in flux. Likewise, your customer will not always follow a prescribed path. They may start online and end up in store or in branch, or they may respond to an interaction on a mobile device and come back to that same device or another later.

Customer journeys aren't actually something a brand creates.

I'm going to say that again. Customer journeys are not something a brand creates. They are, in fact, created by your customer. That's why we call them customer journeys.

Our brands design the experience that they want their customers to have, but the actual journey itself that a customer takes is all their own. So if it takes marketing three days to get the data in order to determine where a customer is or if it takes two weeks to launch a campaign based on that data, I can promise you you're missing opportunities. I can promise you that your customer is moving.

I've supposed to build that out.

So in this evolving, uncertain, changing world, how can you continue to provide the best experience to the right people if you don't have a complete view of your customer? All right. This was done with Adobe Firefly.

Pretty impressive, isn't it? So funny story. I actually licensed the rights to this meme, right? And three days ago, Adobe Legal said, "You can't do it, unless you get a personal release from Travis Kelce and Andy Reid." I said, "Snap. Let me text Travis." And they bit for a minute, which was funny. So anyway, I had to pull the meme out, but I've got the second best thing. I did a photo realistic rendering in Photoshop because I care about you, my audience. So here we go. So this is the meme that keeps on giving, game time we know can be intense. And this is a question that a lot of you have probably heard around the organisation, what are our customers doing? And this is really where the outside talent can come in and can help.

All right. Katie, I'm going to turn this to you really quick.

All right. The Swift Effect. A few years ago, no one could have imagined Taylor Swift having any impact on football, right? But numbers don't lie, and here are some of them. 2 million, 3 times, 470%, 330 million, and 400%. And this Super Bowl, 448 million impressions worth about $9.6 million a 4-time jump from typical expectations. That's the impact Taylor Swift has had on the NFL and the Chiefs in particular.

Nate and I believe that adding CJA to your business is like adding Taylor Swift to the NFL.

Did you think you needed it? Probably not. Can it amplify your business? Absolutely. So if you take your core competencies and you add a little glitter, what impact could it have on your business? Let's start with where you are today.

We know your data lake is a source of pride. It took time, resources, lots of effort to put together, and I bet the management and maintenance is no joke either.

We know it's a valuable part of your business. It brings all of your organisational data together in one place. Data lakes are great for your specialised resources to conduct deep dive analyses, data modelling, and special projects.

Data lakes also make it easier for those resources to connect and query multiple data sources for standardised business reporting.

But just sending data to a data lake or a centralised repository is like Mahomes throwing a pass to Kelce. It's a necessary part of business. It's table stakes. You can't move forward without it. But to respond to their dynamic experience your customers are having with your brand, you need to be more nimble. If you want to go to the Super Bowl, your whole organisation needs to do more with that data.

While useful for routine business reporting, predefined reports are static. The questions have to be defined ahead of time. Any breakdowns or deeper dives have to be predefined. They have to be thought about in advance. It's like having only one play to run. You'd never imagine your favourite football team running the same play over and over again during a game.

So in order to win, you need options on the field. You need data exploration, not just reports. Your whole team needs to be engaged. And ideally, they all have access to the information they need to make decisions in real-time.

Okay.

All right. Thanks, Katie. So let's talk a little bit about the path to value. When you think about the path to value of data, okay? You're going from data, ultimately, we collect that, right, we store it, we manage it, and then we start to do something to it. We start to give it some shape. We start to give it some meaning through our ETL and the processes that we do there. And ultimately, that's then ready for some type of output, right? That's where the visualisation and the reporting and the data exploration comes into play. What we found is this is table stakes. And ultimately, there's this big gulf. There's this big divide as you go from visualisation reporting of the analytics stack into actually taking the outputs of analytics into activation. That's where a lot of the value lies when it comes to your Customer Analytics Stack. What are we actually doing with the data and the outputs that we have there? Because if you think about the business objectives that you have is the reporting itself only going to, ultimately, going to provide value for the organisation. I'm going to take a hot take here, okay? Go on the record. It's being written down. The reporting, the dashboards and visualisations, unless you're using them for action are actually a waste of time. That's my hot take for the day. Imagine I'm an ESP analyst, I guess.

When we think about being able to ultimately provide business cases and use cases, that stack that you have currently is super valuable, right? When you have business reporting and all sorts of other types of use cases in that regard, but when you think about the optimisation use cases that happen for customer activation, that's really where CJA comes into play. There's a lot of interesting value that comes in. Now one of the things that we've talked about and that is really unique in the space for analytics or customer analytics is around the notion of privacy and governance, okay? Now lots of privacy and governance frameworks are in place today, but think about the profile and the anonymisation, the pseudonymous, say that five times real fast, the pseudonymous profiles that you have access to, right? That is actually a core thing that you have to have as part of your privacy and governance framework. That is what best-in-class means. Being able to have access controls to the data. Who is seeing that? Who is not? Data encryption, right? Table stakes. Consent management, if someone goes and has some consent, to be tracked, how do you make sure that that actually cascades through the entire system? If you do some custom report somewhere, do you have fragments that actually sit around the system? Being able to do audits and assessments, data governance, do you have a framework in place to actually monitor what you're doing with data consistently across the organisation? And then lastly, regulation compliance. This is where this is a tonne of work for organisations to manage and to maintain. When you think about just the stack itself, let alone the ongoing, in perpetuity types of maintenance that need to happen. So when you think about the privacy and the governance that are built into the atomic levels of Customer Journey Analytics, which is being able to go through and again, with the access controls, you can control that at a user level down to a data view where you can actually determine the dimensions and the metrics that are available for view. When you can cascade data governance and have a system that already has privacy regulation built in constantly for the changing things that are happening to GDPR this year, CCPA, Law 25, you name it. This is where a partner can come in and can be very successful to ultimately take a lot of the effort, the overhead that is being sitting on an IT organisation, and being able to unplug that and make that accessible where they can do more things that they're really tasked to do. I remember sitting with a customer once they're a grocer, a large grocer, and they were talking about, we're going to build this incredible stack, we've got all of this stuff that we're doing from an IT perspective. And I looked at them and I said, "But you're a grocer," right? "Why are you doing all this?" And they didn't like that at the time. That wasn't the best response, I guess. They came back nine months later and said, "You're right." This is not our core competency. We need to be able to utilise and to use your software, ultimately, again, as something that's catalytic so that we can focus on the things that make us best-in-class as a business.

Okay.

So when we think about the benefits of the "CJA or Swifty Effect." Think about all of the event data that's being captured today. How is that going into your data lake? How are you actually reporting on that? How are you analysing that in deep detail? It's huge. It could be billions of rows a day that's coming in. And teams, you guys are setting out to expand horizons by exporting digital analytics data feeds into Hadoop or to the Cloud and combine it with other customer data from CRMs. It could be call centre, it could be physical locations, whatever it might be, but ultimately, the sheer size of the digital data and its fast-changing nature and really the unpredictability, that comes inherently, with that data as it starts to update profiles is really difficult to model, and it's even harder to explore with things like SQL and BI tools. So as I mentioned, data science teams, right, they need to be focused more on that data acquisition. The collecting of the data, the bringing, the joining it together, the cleaning of it, and then getting it to a point to make it accessible for users. Now I could talk all day about men's fashions and this, but I'm going to turn it to Katie to actually show you and walk you through what this means.

So the analysis workspace interface with embedded visualisation and query capabilities. Any end user can drag and drop elements on a page for cross-channel analysis that in a traditional reporting environment would be next to impossible to recreate. I can easily pull over page names and metrics like people counts and call centre calls, a distinct data set that would be difficult to connect sequentially in most reporting environments. Because of the attribution capabilities in CJA, I can also configure the calls to a time decay setting of 15 minutes. And by constraining it to the session, I'm essentially building a query via the UI that says, "What are the top pages visited by people within 15 minutes of calling the call centre?" I can then drag over the call reason to get a better understanding of why those calls were made. This use case is great for uncovering pages that disproportionately lead to higher call volumes and identify opportunities to improve the customer online experience, thereby reducing call centre costs. So within about a minute, I can create a connected customer experience analysis that relates two very distinct data sets sequentially. And by applying an attribution window, I can infer cause and effect.

Those same capabilities can be used to compare different attribution windows for marketing performance and to evaluate cross-channel behaviours connected to a dimension like marketing channels. This gives users the option of measuring overall marketing performance based on any attribution, like, first touch, last touch, or even a specific time decay window like we just saw in the last example. And because CJA connects customer data across channels, success measures can include offline events now, store purchases, accounts opened, or funded in branch, store pickups, or agent-supported flight bookings.

The fact that CJA sits on top of the Adobe Experience Platform means that all of the data as Nate mentioned, is housed in an enterprise class environment that includes privacy controls, HIPAA readiness, and the ability to remove data for compliance reasons such as GDPR and CCPA. Again, that environment and its capabilities extends to every solution across the platform, Analysis Workspace, Report Builder, CDP, even the data connectors for Power BI and Tableau. This enables even our largest and most privacy restricted customers the opportunity to connect PII data with confidence in its security.

One of the many tools that CJA provides is the ability to non-destructively massage and manipulate the data to enhance, repair, combine, classify, merge, or otherwise transform in 1,000 different ways to serve the practitioner. The power of this capability changes the game for your end users. For the first time, it puts the power of data views and a full customer journey analysis directly in their hands. In this example, I'm giving you a bit of an inside look at what we do internally to modify our demo environments. With derived fields, I can easily take the page names that we created for retail customers and change them into page names that reflect a website for an airline. Likewise, you can take pages that have been incorrectly named through lack of tagging, or perhaps somebody didn't follow the naming conventions that were defined. Other non-destructive data manipulation examples include case changes, concatenating fields, and replacing values for campaign names or other dimensions. And, of course, CJA provides the same advanced on the fly segmentation capabilities and time series analysis as Adobe Analytics, but this time across channels. So you can answer questions like which products are being viewed online and purchased in store, or how many people searched for flights or hotel rooms online but then called to book directly, or how many people responded to a push notification but didn't book an appointment and then came back offline and did, and when. And once identified, any one of those audiences can be activated directly from the platform. No need to recreate that segment elsewhere. Just pass it along.

All right. So let's talk about this in real life. What does this really mean? When you can take and you can augment and modernise certain aspects of your Customer Analytics Stack. So what we did is we actually contracted with Forrester. I mean, full disclosure, there's a paid engagement with Forrester, right? But what we did is we have them go and survey our customers, the ones that are using Customer Journey Analytics and use this as part of a modern digital transformation within their organisation. So here I pulled out a couple of quotes just, so you guys can see and probably relate to this.

Here, first one, when it came to interviewees and looking at the personalised experience, it was really too laborious to carry out and scale in real-time. That was the current state. The legacy tools, legacy stack couldn't unify and visualise to illustrate the total context of the customer journey. And then lastly here, being able to manage the integration work that's super valuable between legacy systems and marketing solutions required a tonne of maintenance, when it came to IT. So as they looked at the adoption and what that ultimately meant for the organisation, they saw massive increases in the productivity of the analyst. And I think that's really one of the key things that we are really trying to focus on here. There's so much time that goes into ad hoc querying, ad hoc reporting, overhead hell, for lack of a better term within an organisation. And being able to free that up is very palpable in terms of cost savings for your organisation. But beyond that, right, what could it do downstream into the marketer's hands? And we were able to get this back from Forrester and they're like, "Look, the present value of the hours saved per marketer downstream is phenomenal." Like, over $300,000, as far as revenue generation associated with that. You can see the growth here as far as new revenue concerned with the adoption and the ultimate growth that they had as part of the organisation. So back to my hand-drawn photorealistic here, I told you we needed CJA.

But ultimately gaining insight and being able to be efficient, and to be able to provide repeated customer experiences that are valuable, that's something that you're not going to see typically doing standard approaches. And what I mean by that is we need a team. The team comes into two places. So one of the first big challenges for an organisation is to unlock the customer data. There's a lot of data sets that sit on the sidelines. And the current solution, ultimately, for a lot of organisations is just to dump it all into the data lake.

But as I mentioned, it's still not stitched, it still goes in a siloed fashion. And it's not really usable in meaningful ways. So once we take that data and we rationalise that, that gives us past this need to unleash data and be able to get it to other stakeholders that ultimately are going to provide value for it. That's how we really bring the Swift Effect throughout the organisation. If we keep this within a small group, if we keep analysis within a small group, this is beyond the technology, we have to be able to democratise it. I mentioned at the beginning that my wife and my daughter are huge Swifties. And I've noticed a few things about Swifties. First, they're a pretty dedicated subculture of fans. They're very invested and they're also very good at creativity. As a force, they can make even politicians quake in their boots.

And that's really one of the things that we want to draw from a comparison standpoint is you need to be able to leverage that whole organisation. So by democratising access to insight in a controlled way, that's being able to get data into your Swifties hands where you can really start to amplify your reach and then augment your ability to take action. And you can respond appropriately to customer interactions and provide more meaningful experiences as those Swifties, if you will, who touch that customer experience can make data-driven decisions on holistic and up-to-date customer data. Now in terms of data and people, the message, the bottom line message is, don't leave your best players on the sideline.

So, for example... Oops. Let me roll that down.

Think about simple questions, like, how did my last email and SMS campaign impact conversions or impact sign ups? Now basically, if you look over the years, as marketing organisations started to evolve or digital use cases started to evolve, it was clear that older web analytics technologies just weren't built to handle them.

For example, in the example of the SMS and the email. So we've seen many instances where clickstream and behavioural data then gets turned into a data source, into a data warehouse. Now there's some big problems with that for the organisation. First is that you've got basic marketing analytics that are not self-service at all anymore. And you're completely dependent on the data science or the IT or the InfoSec team, ultimately that knows SQL and that can actually produce reports for you and you're not able to actually even get the most basic reports out by yourselves.

One of the main things that CJA was meant to do was to help unlock that. So if you think about all of those basic digital marketing things that have now been taken over, we can now bring that back out into the marketing organisation. The IT team typically loves this because they've spent so much time doing all of these ad hoc queries throughout the organisation. Now you can have the marketing team self-serve again, like they did years ago because of the flexibility, the modern data structures that you can do to manipulate data and to actually answer the questions that might seem basic and routine, but have not been met by web analytics technology.

All right, Katie, can you walk us through a little bit about the flow? So many organisations, yours too, I'm sure, do a great job with their digital initiatives. But when it comes to increasing or accessing insights beyond digital engagement, they have to rely on processes that are lengthy, inefficient, and ultimately expensive. With the focus on customer experience, questions are often asked by leadership wanting to understand the holistic journey and how the channels play together in the customer experience. That task is often placed on the BI team with workflows that aren't built for efficiency and answers in a fast way. Business questions take time, and they require resources to answer. A typical process looks like this. A marketer wants to understand how a specific digital campaign performed offline. So they submit a request to the BI team's cue, and depending on that cue, it could be days or weeks for the team to be able to address it. The BI team writes many rows of SQL. They acquire and transform the data to support that request. Once a sample of that raw data is retrieved, the BI team validates it with the business, and then they export the full dataset by running that query. On top of that dataset, now someone will need to create a visualisation if necessary, which also takes time depending on the complexity of the view, the filters, so forth.

The original requester then spends a fair amount of time going through the data to find out if there are possible audiences to extract for activation, which then need to be identified in another system. If there are any follow-up questions or issues, it can be days before those questions are answered and the cycle continues. This process, as we said, is inefficient. It causes significant delays in being able to react and adjust journeys, and delayed time to insight leads to misspent marketing dollars, decreased ROI, and IT resources that could be better engaged elsewhere.

So we say just put CJA in.

Now that we have the data in a format that's accessible to anyone who needs it. What are we going to do with it? Having access to the data is the first step, but that data doesn't mean much if you can't do anything with it. It's like the coach with the call sheet, sitting at home on a Monday night instead of being on the field. You can't score unless you move the ball. You will need to take action from your analysis, otherwise, you just have a really expensive dashboard. Action means streamlining the path from uncovering audiences in your analysis to sending those audiences directly to activation systems without having to recreate them in other environments before being able to reach the customer, which could take days. And by then, the customer may have moved on. If you don't call the play, nothing happens. You've got to be able to pass the ball, and you've got to be able to pass it quickly. Your customer isn't waiting for you to figure out where they are before they move on. You don't have time to uncover the audience in your reporting tools, try and recreate that audience in every activation system you have, email, social, web, on-site, mobile. By the time you do all of that, your customer will be gone and your pass will be incomplete.

So what are you going to do with all of that data? If you want to make it to the Super Bowl, you have to take a page out of Taylor Swift's playbook. The game has changed. Today's analytics practice is not the same as it was yesterday, the customer identity paradigm. Thank you.

From cookies to customer, from pixels to people, is happening now.

Your customer is not just having a digital experience with your brand, your customer is everywhere you are. You don't want to pass up the opportunity to go to the Super Bowl. Right, Nate? We don't want to pass that opportunity up. So again, I think the big thing that we want to really leave everyone with today is this notion that you have an amazing set of technology and you've got amazing talent at your organisation that is putting that together for analysis. But as we've come into this new world in 2024 and beyond of customer data, first-party data, and new use cases, this is where CJA can come in and be interoperable with that stack to provide the Pink Pixie Dust, if you will, or whatever Taylor Swift calls it to give that effect to the organisation. It's about democratising the data. It's about democratising that out to other people. And if you can do that, we promise we... Well, I better not say that.

That's where you're going to see, like in the customers in our TEI study, a lot of great benefit that comes to being able to take both of those together. And I think that's something that is big in the industry today is being able to understand that did we with our current stack, do we think we needed CJA or do we think we need someone else? Can you get to the Super Bowl with what you've got? Yeah, you guys are awesome, and you guys are amazing. What we're talking about is an effect that helps promote it just like Taylor Swift in the NFL. Ultimately, to give you guys scale in efficiency, operational efficiency, as well as organisationally. So with that, as promised, we're going to get you out about 15 minutes early. If you have any questions, feel free to come up and talk to us, but I want to make sure you guys get good seats at Sneaks. So thank you for your time today. Have a good rest of the Summit.

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