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Transcript

Hello and good afternoon. My name is Axel Schaeffer and I head up product marketing for ÃÛ¶¹ÊÓƵ’s Digital Experience Data Solutions. I want to welcome you to today’s Skill Builder online event and specifically to the Data and Insights track. I have the pleasure to start us off with a keynote in just a few seconds. However, before that, I’d like to look at you of the agenda of what we have in stock for you this afternoon together. So as I said, I’ll start off in a couple of minutes, hopefully, and then we’ll have three different slots with each two choices of specific content, as you can see here that you can choose from. Shikhan, Ramit and Wilson will start off. Again, you’ll have the choice between those two because they’re running at the same time. I will come back to that and I come back to the agenda on a lot of specific topics, a lot of specific touch points that you can see here at the end of my presentation so you can have another look. Before that, however, I want to hit us off with something that’s fairly high level and maybe known to all of you. However, I’ve got a small update for you in stock. As you all know, experience is the number one factor for making decisions on a purchase nowadays. And we have before talked about the experience being more important than the product. However, up to following a recent study from Forrester, even now the experience has overtaken price in the competition of the most important aspect of this. As you can see from revenue growth to customer retention, to average order value, the importance of the experience is really accelerating and exceeding all the other factors that they are. Now, what does it tell us? It tells us that the time is right for personalization at scale. And I’ll let you know what I mean with that in just a second. There’s three aspects that are coming to that. One is customer behaviors are changing. However, what’s remaining is they’re asking us, they’re really expecting us to engage with them in an authentic, meaningful and personalized way. That’s really the core of every customer interaction, if we are really honest with each other. But the importance again, doing this on digital channels is increasing, increasing, increasing. With all the data that we have in stock, it’s really important not only you have the data and collect the data, but really to make sure that we can gain value from it as well. Last but not least, with all the possibilities that technology is providing to us, it’s really important that we make use of AI and machine learning to make that part of our day-to-day interaction with our customers. So really, in this world, post-COVID, post-pandemic, where we’re really happy to see each other again, we need to acknowledge that still most of the interactions are digital and we need to be prepared to have these conversations across channels. But a lot of these channels will still remain and be digital. Now, I talked about personalization at scale without telling you what I really meant with it. Personalization, as you can see on the left side here, is delivering a personalized experience to the right customer and the right channel. Now, what we have to be ready for is being able to do that not only to one customer, to every customer, on every channel and in real time. That is a major step forward for most organizations and requires a serious consideration, not only from an organizational, but also from a technology standpoint. Now, in order to make that a bit more visible or visual for you, I want to look at it a bit more detailed. So what that means, it’s really about orchestrating those singular moments in a cohesive journey that meets the ongoing and progressive needs of the customer. So being aware that the customer will dictate every journey that he takes, just mentioned about all possible channels at any given time and in real time, we have to provide a context that is based on his behavior, but also on our end, on our business objectives and provides the best experience that meets and connects both. You can see that, for example, you can look at a promotional email on your mobile, go to a mobile website, download an app. But somewhere in between, you may have already looked at a store offer or something else on an outlet as well. So it’s really a lot of different options that this can come together with. And I want to not under emphasize the complexity that is behind it. Talking about complexity, it takes a lot to make personalization at scale happen. Don’t get me wrong. You can just see a few of these elements here, personalization at scale in the middle. And what we’re talking about, what I’m going to focus in a second on, data and insights right next to it. So there’s a few aspects that we need to consider. And if you’ve got time and if you’re interested, take the time and look on demand offerings after this afternoon and check out one of the other areas, for example, around customer journeys or content as well. As I said, we will go along with the aspect of data and insights for now, which is really looking at three essential parts from personalization at scale, specifically in data and insights. Those are around analytics, profiles, data governance, and also around activation. So what is it that you need from data and insights, from a data perspective to make personalization at scale happen? It’s number one. That’s not a new one. Bringing together data, but not only from online sources, but really from all relevant sources that are available to us. Second one, and even more important in these times of very sincere privacy laws and so forth, governance and compliance with the regulations that are in place across countries, if you are active in different countries, for example. The third one is looking beyond the analytic stages. Really, how can we then integrate analytics, customer data platforms, and personalization, which is pretty much around what we’re talking in this track and in this keynote, and make them come together? Lastly, how can we optimize customer journeys to make sure that once we’ve taken all that effort to understand the customer, we can also exercise the best possible and most impactful journey with him? Now, all that said, you will not be surprised when I come back to you and say, around 50% of the companies manage their customer data still through individual applications. Hence, everything I’ve said until now is still very difficult. Why is that? Why is that an aspect that organizations maintain? Why is that a perception that customers also still get from us, that one piece does not fit to the other? Well, it’s pretty much around making sure that we are, in the end, paying attention to our customers. So what I want to say with this is, can we really find a way of not only focusing our IT infrastructure, but ourselves as an organization around the customers more and more? How can we align ourselves, for example, along customer journeys, not only around our products? So really be honest with yourselves. Think about it, how reality looks in your organization. How close are you to this imperative? Are you really there yet? Probably, we all have a small way to go. Now, if you’re looking into making that happen, I want to ask you or ask you to ask yourselves a couple of things. When you think about understanding the customer, can you inspect your business at different grains? Is it possible to understand the data across channels? Secondly, in your organization, do the people designing experiences, not necessarily only the analysts, have the necessary insights? How can the data be shared within the organization? And thirdly, how far are you in designing a customer profile? How are you collecting your data? How are you bringing together behavioral with other kinds of data and make sure that on a historical basis, you can update and you can react to that in a real-time manner? Those are essential questions, and I want to leave them with you for this session and even beyond. I hope that gives you some triggers and some inspiration there. Now, if you’re looking into how this would come together from a tool perspective, which I think is the other aspect that I touched on, this is how it looks in a more traditional sense of the technology word. We have SQL queries, which are fairly slow. We have a bunch of BI tools, which are not necessarily giving you the real-time customer focus that you have. And you put all that in a data lake from which you then have to pull the reservoir data. In more visual terms, beforehand, look at the SQL script that looks like the left of the screen here. What we’re looking to and what we really want to promote, not only from an ÃÛ¶¹ÊÓƵ perspective, but promote from a customer perspective is a way where we can easily understand them, as you can see on the right side. Bring customers in a digestible and a visual way that we can really track them, that we can really understand them, that can really make sense of what they’re doing with us. So that said, I want to go a little bit deeper. I want to show you some of our innovations that we have along these technology changes of the world. I’m going to start with what we call supercharged attribution. Making sure that with our tool that is called Customer Journey Analytics, that we see as the future of analytics, we can bring together different paths of the customers. I mentioned before, we need to be able to really understand different journeys, make sure that the journeys are connected and the real insights and actions can be driven from them across all channels and with a campaign or an initiative or a purchase impact. So a lot of information that we can bring together here and analytics, specifically Customer Journey Analytics, brings together the most powerful attribution models to bring brands into position to really refining their advertising, really making sure that the spending from a marketing perspective is optimized in a way that is most powerful for them. Secondly, I want to really understand and want to bring together the understanding of different channels and how they cause an effective relationship between the different interactions that you might otherwise only have seen separately on each of those channels by itself. So as you can see here, CJA provides experimentation panels that enable customers like you, like your teams, to test content, to make sure that you can try these channels out, you can provide different scenarios, and you can see how that would impact then, for example, your email, your in-app, in-store or call center interactions down the funnel. So really important to see what if I would change one element in the customer journey, how would that impact the other pieces. Now, enough said about Customer Journey Analytics, I don’t want to limit my presentation this afternoon to that. I want to summarize, however, the benefits that you would get. So Customer Journey Analytics provides you with a position to see a customer journey context to really understand where the customer came from in a single reporting view. Second one, it will make insights available to everyone. I mentioned the democratization, the availability of data, and the people designing the experiences beforehand. So really making sure that with the simplicity and with the visual appeal that we provide with CJA, we can make decisions faster and make them based on the most complete data that’s possible. Third one, and then again, I refer back to what I said earlier about machine learning and AI. Customer Journey Analytics brings the AI ability to normal people like yourselves, possibly, and definitely me. That really helps us unlocking insights that we would otherwise not be able to have and to understand. The fourth one is really around the visualization here that I touched on already. But what really probably brings the biggest change to you is really making sure that we can provide this across different data channels. So while previous products that you might have owned from ÃÛ¶¹ÊÓƵ side, from an analytics side, and focused very much on the digital channels, Customer Journey Analytics makes it possible to really go all in, to really go from one channel that’s purely offline to another one that’s most digital that it gets. And we’re even open to other channels that may or may not appear in the future. And for the advanced guys amongst yourselves, even greater control of your data manipulation possibilities. So really, if you want to do something with the data, the possibilities with Workspace in platform are really, really enhanced. That’s definitely something to explore once you’re on that very advanced level as well. That said, you’re not alone. You definitely have good company. We have more than 100 customers on CGA already and actually more than 2,000 customers that are using analytics and CGA together at this moment. So that number will change over the year as we are building up CGA to be more and more available and the functionality to be on parity with analytics as it’s been existing beforehand, plus the new functionality, of course. But we have gotten quite a head start and I want to share rather than talking about it myself forever, I want to share two quotes from our customers with you. One is from Fredrik Werner, a fairly close colleague or business contact of mine now, not colleague, but good customer. We’ve been working with him for a few years from DHL and he is really all in, not only in analytics, but also customer journey analytics and he believes, having seen both solutions, that customer journey analytics is truly the future of more advanced analytics. So if you have possibly, if you’re following Fredrik, very active on Twitter, make sure you can connect with him, that you contact him and ask him all the questions that you may have beyond this session today. I hope that hopefully I can spark a little bit of interest or inspiration for you, but make sure that you ping Fredrik. He will be the best person to talk about it from a customer perspective. I got one more and that’s from another customer from Europe here, which is from NetWest, head of analytics there. They had the challenge of reducing the support calls they have into their call centers and only within a few hours, they were able to actually identify five funnel journey issues that were making the journeys that they have provided so far, very inefficient and made them result in unnecessary call center interactions, unnecessary call center calls, and have put them in a position now where they can actually not only save a significant amount of annual support calls, you can see it here, it’s 187,000 calls that they are not doing on a year by year basis. I think that’s quite a big number, but they’ve also been able to have a substantial increase of potential sales. So making sure that they have better understanding of the customers, what they would like to have, and really can benefit and double down on that. So a two-sided improvement there. So really a lot of good things that can be said. Now, I focused and with a good reason, a lot around the customer journey analytics aspect of things. However, in today’s session, I want to not hide with a couple of other innovations that we have created and that I want to at least make it a small mark with you. For example, the stuff that we do in ÃÛ¶¹ÊÓƵ Analytics, we have increased the possibilities to add your own context, to have your own commentary functions within analytics, and bring that into aspects like the mobile app that we have released just recently. Again, it has won actually some very well-respected prizes with it. So really check out what we have done there. There’s a lot of stuff that you can put in place that makes it much more impactful for yourselves, in terms of democratizing your data, also for your colleagues that actually consume the information that you provide. Next, I’ve also had, and I touched on it a little bit beforehand, to look into ÃÛ¶¹ÊÓƵ Target. For example, making sure that the possibilities that you have within ÃÛ¶¹ÊÓƵ Target in combination, for example, with CJA is enhanced as well. So a very, very tight look into how can you make sure that the potential results that you get from certain tests, from certain variations that you do within Target can then be reflected in analytics in CJA and simulated there as well. Last but not least, I’m coming to the activation of the data in ÃÛ¶¹ÊÓƵ’s real-time CDP product that we’re also pushing. We really want to make sure that you guys have a good understanding of it as well. At this point, all the information from analytics, but also from a personalization perspective, come together in the way that we can bring these omnichannel insights, as we say here, together into the relevant segments, personalize those relevant segments, and activate them in any channel across the different customer segments. Now, all that is probably quite a lot to consume at one point. My colleagues, in a few minutes, will hit into a smaller batch of different specific topics. However, if you want to know more, feel free to ask questions in the chat, feel free to follow up with us, and feel free to request another session with me or my colleagues as well. With that, and as I promised you at the beginning of the session, we’re coming back to the session agenda for this afternoon, as we just had the first session about trends and innovation with myself. We’ll have next two options for you to choose from, one of which is analytics and target applications for mobile maps, with my colleague Ashika Ramji. The other one is ÃÛ¶¹ÊÓƵ Web SDK benefits and exclusive features with my colleague, Will Wilson. There will be two more slots, and colleagues will introduce those hopefully as well. However, if you want, make a screenshot now so you get a good overview of what’s up and coming for you later on in the session. With that, I thank you for your attention, and I want to leave that with hopefully another few questions that I can attend to in the chat. Thank you. . . . . . . . . . . . . . . . . . . .