Now I'd like to introduce your first presenter for today's session, Jen Zik, Principal Digital Strategy Group, Media, Entertainment, and Communications with Adobe. Jen, you now have the floor.
All right. Thanks, Anu. And hi, everyone. Thanks so much for joining us. Good morning, good afternoon, and most importantly, happy first day of summer. So we have some really great content to share with you today. I'm just so excited. And like Anu said, I'm Jen Zik. I'm with the Digital Strategy Group here at Adobe. I started my career actually as a classically trained data-driven marketer, always knowing the benefits of having data drive your marketing strategy. And really, the past 15 years of my career, I spent in sports and live entertainment successfully bringing marketing technology to probably hundreds of professional sports teams and venues globally. So like I said, just excited to share the great content that we have lined up for you today. And I'm really happy to be joined by Andre, Vice President of Technology at Publicis Sapient. Andre, thanks for being here with us. I'll turn it over to you to give yourself a quick intro.
Thank you, Jen. Good afternoon, everyone, or good morning. Andre Ingberts, VP of Technology at Publicis Sapient. I've been working for more than 15 years on marketing technology, including work on Adobe content management and email marketing platforms, and also working on customer data platforms to enable personalization. Looking forward to this presentation.
Great. Thanks, Andre. Okay, so jumping right in, here's a little bit of a snapshot of what we're going to cover today. First, we'll talk a little bit about how audience and fan experiences are shifting, especially post-pandemic, and just take that macro viewpoint and use that as a way to set up why personalization is a priority now more than ever. And to get a little bit more into the tactical execution and to help you take action on that personalization strategy, we'll focus a little bit on zero-party data and why that's important and how you can start to capture it. And then ultimately, we'll cover some strategies and tactics for activating that data for results and loyalty with your customers and fans. And we will start with a fun slide. Oh, my goodness, no words. That rarely happens. But I have this slide up here because, actually, this deck, or a portion of the deck, mostly the slides that I'll cover, were initially presented at the MIT Sloan Sports Analytics Conference earlier this year. And to get things started, I took a quick poll of the audience to see who was a little bit more left-brain dominant versus right-brain dominant. And as a quick reminder, the left brain tends to be a little bit more analytical, strategic, maybe sees things black and white. And then the right side of the brain is a little bit more creative and passionate and maybe more vivid and full of colors. So you can imagine what that poll result looked like with the audience of folks at MIT. But really, I think the majority of us, as data-driven marketers and data-driven business people, we spend so much time, really an increasing amount of time, collecting data, centralizing data, normalizing it, analyzing it, and modeling it. And this presentation is really meant to serve as a reminder to zoom out. And don't forget to think like your customers, think like your fans, really reverse the binoculars there and tap into your own humanness. So throughout this deck, you'll see a combination of really good strategic points catering to that left side of the brain and then some creative reminders trying to tap into that right side a little bit more. And to continue to set the stage, you may have heard that at least our positioning at Adobe is that people buy experiences, not products. So experiences really have the power to engage, connect, inspire, convert, support, retain. And what I say in sports, like I said, this deck was originally presented at a sports conference, is that while the win or loss record on the court or the field is certainly important, there's so much more that goes into that overall experience. I mean, experiences are all-encompassing. There's a lot that leads up to that actual event or that purchase. And then in many cases, these experiences, they live on in our memories for a really long time. Like I said, this is certainly the case in sports and live entertainment, but it's certainly relevant across industries when I think about new car day, automotive. There's a lot of experiences when it comes to viewership and streaming and watching TV, especially with family and friends. And then, yeah, like I said, new car day and across sub-industries. So we'll definitely keep this in mind as we go through the presentation. And as customer expectations accelerate, as customers become more digitally savvy, as technology provides just new ways to experiencing things, these customer experiences, they need to evolve. So what we say in sports when we try to think about, okay, what do these customer experiences need to look like, well, that varies, right? In the case of live entertainment, it varies and looks differently for the fan that attends in person than the fan who's maybe watching from home or the fan that lives to tailgate, as you're seeing in the visual here, versus the fan that really lives for that sweet experience. And sometimes that's both. So the big question is, how do we identify, reach, communicate, and deliver experiences to every fan or every customer in a way that matters most to them? And, of course, the answer is personalization at scale. I mean, this really is the future of customer experiences, delivering the right experience to every customer via the right channel in real time. And, you know, that's going to be the core strategy and one of the key topics of today. And at Adobe, we're breaking personalization at scale down into three pillars to help it be a little bit more manageable. So this first pillar, you see data and insights, that's where we're really going to focus today on the importance of data. And we'll talk about how to grow the size and depth of your database. And I'll mention quickly that second pillar around content or content supply chain, especially as I hear more and more brands thinking about new ways to reach younger and more diverse audiences, short form content specifically is becoming more and more important and getting content to market quickly. And then ultimately, we're all after that highly personalized, highly engaging fan or customer journey. But we can't activate on those personalized journeys without data. So that brings us back to that first pillar where we will focus. And to continue talking about the importance of personalization, I'm going to turn it over to Andre.
Thank you, Jen. So Forrester defines personalization from the customer perspective versus the brand perspective. So personalization is an experience that uses customer data and understanding to frame, guide, extend and enhance interactions based on that person's history, preference, context and intent. And we mean by that that personalization should deliver value that contributes to the customer experience. And effective personalization requires a deep understanding of a customer. Many brands base personalization on historically poor customer profiles, but it is also critical to consider the current interaction and the customer's intent as the context for personalization. So we have seen on work that we have done between Sapient and Adobe a lot of success for our clients working with personalization and working with their customer data platform. For instance, with a retailer of outdoor footwear, we have seen sales growth and five point margin increase after investing in customer segment-based marketing. We have seen also 15 to 20 percent lift in average revenue per order through personalization in early implementation at a fashion retailer and five to seven percent projected increase in total revenue for a pharmacy store chain by enabling customer journeys on a customer engagement platform. And for a large quick service restaurant chain, we've seen 14 percent growth year over year, partly driven by a strong digital engagement with personalized and in-context offers and loyalty rewards. So how do we personalize essentially? In order to design for personalization, we look at moments in the customer journey because we want to influence the customer through the entire engagement lifecycle. We look for opportunities to personalize every possible touchpoint along their journey from inspiration to the purchase and then on the post-purchase experience. So here what you are looking at is an illustrative journey of a customer conversion where we leverage data along the way, so first, second or third party data to personalize messaging, content, recommendations and offers on different channels to be able to influence conversion, get a larger order size. We have an opportunity to upsell or cross-sell. So building personalization and achieving multi-channel data driven personalization of a customer journey is a tall order, of course, and we go after six objectives or six components for doing that. The first two are customer and prospect recognition where we capture as much data as possible from customer touchpoints, so both offline and online to create a rich customer profile. We then unify the identity of a customer from any place they connect with a brand so we can build a rich single view of a customer and understand where customers are in their journey. So one and two are the fundamentals of personalization. Three, four, five and six are more advanced capabilities like with a rich customer profile and identification of a customer across all touchpoints, we're able to understand when is the best time to initiate an interaction with customers and what the best interaction is for a given moment is derived from automated decisioning and that's what we call the next best action. With four orchestration, we apply next best actions, decisions essentially to multi-step journeys to create engaging customer experiences that evolve with the customer behavior. With five, since we have the same data and insights accessible to all marketing activations across all channels, we're able to maintain consistency in customer messaging across all channels. And then finally with six, successful personalization will come from the optimization of a user of each channel to achieve more frequent interactions that are highly relevant and effective in influencing the customer. So this obviously comes with some challenges and we, personalizing an entireIf there's not, it's going to be really hard to be as successful as you can be. From there, it helps to map out the ideal customer journey. So I said a little earlier, you can't execute successfully on a personalized journey without data, but what you can have is the vision. So I do recommend choosing one or two of your organizational objectives, thinking about how that can also help the fan or your customer, and just mapping out all the steps that can help you get there along the fan journey. And this is, again, just a sample, kind of a hodgepodge of some things that we see pretty commonly among our sports and live entertainment clients. But once you have this ideal customer journey mapped out, you can begin to see where the data you have fits in and can help augment or personalize this journey. And then you could also see where maybe you're missing some data or where some new data can help make this journey more successful. So from there, once you understand or have a better comprehension of what data you need, you can start to think about how you can go about collecting that data tactically. And I list some common data collection tactics here. And you'll see that most of these have been around for a really long time. So this is back to basics. But what I will also say is that a lot of our brands have not revisited these tactics in a while. So technology has certainly improved a lot over the years. And a lot of folks have not revisited, for instance, their registration or preference center, where you can spend a little bit more time humanizing that page, being a little bit more clear around subscriptions, collecting more of that explicit preference data from your customers or fans. Same thing with welcome programs. A lot of them are one touch when really they should be multi-touch. And take advantage of that really prime opportunity when customers are new to file or they make that first purchase or they just sign up to set the tone for your relationship with them and get to know them. So that multi-touch welcome campaign is also a really great example. Certainly ongoing surveys and quizzes, not only in email but on your website and social channels. A lot of our sports clients and others, for that matter, partner with companies like Jebit that do a really great job making a lot of the data collection a little bit more engaging. And certainly progressive profiling has also been around for a while. That's one way to do it too. But when you start asking for data from your customers and fans, it all comes down to a value exchange. Give your customers a reason to engage with you. And by the way, make it fun, right? And make it resonate depending on where they are in the customer lifecycle or what they're trying to do. So a lot of our brands always think that the value exchange has to be a discount. But research shows that a lot of customers and fans just want a better recommendation. So keep that in mind. Certainly saving money and time is another big benefit. But others just want to unlock new benefits or have a more frictionless experience or be entertained or be tested and quizzed or learn something new. So there's a lot of ways to play around with that and test that value positioning. So I encourage this piece especially as a great test and learn opportunity.
And just a real quick, very linear example, super basic, but something that we see in sports and live is, for instance, a league can collect someone's favorite team, right? And then that data, wherever it's collected on any sort of web-based property, can automatically feed into a real-time CDP and then be activated on in a personalized way next click. So like I said, if a league wants to collect favorite team, then on next click, you could take the fan to that favorite team's ticketing page or merch page or homepage or whatever you want to do without a durable identifier. So you don't even need an email or anything like that. So this is a very linear example. But of course, there's so many more possibilities when you consider multi-channel, highly orchestrated, one-to-one fan journeys. So with that, to go a little deeper on the technology behind what makes this all possible, I'm going to turn it back to Andre to cover customer data platforms.
Thank you, Jen. So Jen just talked about many ways to create engaging user experiences, which are personalized with a rich profile. Let's get into what a customer data platform is and how it works to support personalization. So the first step with a customer data platform is to collect customer data. A CDP collects customer impressions across touchpoints that are extremely great and invaluable assets for brands. And the data that results from these touchpoints can be very diverse. All the data we collect to build a customer profile is organized around several dimensions that you see here on the outer ring, demographic, transactionals, experience, interaction, behavioral. And as we move into inner rings, we can essentially drill down into each of these dimensions with a rich set of data categories. So, for instance, for the transaction dimension, we capture all the details. We capture clickstream data that led to the completion of a transaction, payment history that comes from both physical and digital channels. So as we look and collect that customer data, we want also to unify it. We want to stitch that data to track the growth of a profile that starts with the unknown state of a customer on the left, who leaves a first-party cookie after a visit, and then hopefully, progressively interacts with the brand and creates behavior data. Once that customer registers, we have addressable PII data, and we can engage the customer to collect a lot more behavioral and transactional data from both a zero-party voluntary and first-party standpoint. The CDP platform itself, if we look at the definition, is really a data platform that combines the ability to know the customer by creating a unified customer profile from multiple data sources, then engage with customer through many activation platforms with relevant personalized insight and then orchestrating next best actions for the customer's preferred channels, both batch in real time, and thirdly, measure results of campaign of any activation so you can create more effective personalization campaigns. From a very high-level technology standpoint, a CDP is organized as a data pipeline here that you can see from left to right to organize the data, capture first the data, organize it, enrich the data, and bring the data into a shape that can be used by activation application on the right side. So the pipeline starts on the left with the acquisition of the data, zero first-party data, and get to the point where you know that the latest data is available for the next stage. And the next stage is about cleaning up the data, organizing the data so that you end up with a trusted and complete data set ready for processing. And where you want to go next is creating what's called a C360 data repository where you perform identity resolution, various enrichment of a customer data for identity resolution, potentially getting the help of third-party data partners, and then also creating business views to really get to the point where the data is ready for an analyst and for a data scientist, which takes us to the next layer, the analytics layer, where these analysts and data scientists will be able to create insights and prediction then available to the final layer, the top layer of a CDP, which is the orchestration layer, where you can execute segmentation, decisioning, recommendations, optimize all of this through test and learn, and then integrate the data with loyalty platforms, offers, commerce, product merchandising, campaigns, content, advertising, and so on. So where this takes us is being able to create highly personalized experiences. And these highly personalized experiences, if they're well done and they're rich, gets you to create a deep relationship with a customer and increase the customer loyalty without necessarily having a loyalty program. Loyalty at the end of the day is an outcome, not just a program. And as you personalize content, offers, product presentation, recommendations, or even customer services, you essentially increase the value exchange between your company and the fan. And visitors have a feeling that they are getting value, that you have a share of a mind with them, they have a feeling that you understand them, and you also drive up the convenience of doing business with them in a very compelling way. And these factors combined increase the loyalty to the brand, which is buying frequency and buying purchase amount, and as a result, increasing the customer loyalty for some form of virtual loyalty program, loyalty marketing.
Yes, thank you, Andre. I'm so glad that you presented loyalty this way, because I think a lot of brands think that they need to have a loyalty program, but really that's not the end goal. The end goal is to leverage data and personalization in a way that drives retention and that customer lifetime value and loyalty, and you don't necessarily need any sort of formalized program in the back ends there. And you also have increasing buying frequency as an example, and this is a goal that we see a lot in live sports, for instance, trying to increase the average number of tickets that a fan buys per season, right? So I think that's a great example leading to retention and loyalty. And just looking at our media clients and especially subscription services, retention is really important right now because we all know that a lot of audiences sign up for subscriptions just to maybe watch one show and then they churn or they drop the subscription where there's a real opportunity for these streaming companies and media companies to better understand their audiences and not only what they've watched already, that's a good example of first-party data, but to collect more zero-party data to understand their audience preferences and maybe where they're going or where they would like to go and what interests them and leverage that combined first- and zero-party data to serve up better recommendations that will drive viewership and therefore hopefully retain those audiences leading to increased customer lifetime value and loyalty. So just a great summation or, again, I love this slide, how it ties everything together. So thank you for