Here's what you'll learn in the webinar
E.ON & diva-e used Adobe Target to implement a personalization campaign to play customized, daily Next Best Action offers to every existing customer.
Highly personalized, pseudonymized offers also in the logged-out area (e.g. up- and x-selling, service offers, bonus campaigns)
CRM-based, daily updated calculation of the most relevant offers & products for each individual customer
Depending on website & position, different offers in different formats (e.g. Hero, Modal)
Real-time configuration (who, what, where, when) on the fly by the business department
Content creation directly in CMS
Evaluation of measures by departments directly in the analytics tool
Web dashboard with automatic test links
Watch online now (German only)
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Transcript of the Webinar: E.ON Next Best Actions
Angela Meyer: Welcome to today's diva-e webinar: E.ON Next Best Actions. Today, you'll learn from our experts how E.ON and diva-e worked together with Adobe Target to implement a personalization campaign to deliver customized, daily Next Best Actions offers to every existing customer. Let's move on to a quick tech check. To the right of your screen is a question box. And just to make sure you see and hear us, it would be great if you could give us a quick signal. That looks good. Yes, they can all hear us. Good, the technology works. Exactly, afterwards you will also receive the presentation and the recording via download. So, let's introduce ourselves: My name is Angela Meyer and I work in the diva-e marketing team and I'm your presenter today. Alyssa and Albert would like to say a few words about you.
Alyssa Ritters: Yes with pleasure, then I'll start. I'm Alyssa Ritters and I'm a web analyst in the data analytics and science team at E.ON, where I focus mainly on onsite testing and personalization.
Albert Wognar: Hello, my name is Albert Wognar. I am an Expert Architect at the Munich site and continue to be the Team Lead for our Global Solutions. And mainly responsible for Adobe Target in our company.
Angela Meyer: Great. Exactly, and our colleague Dominik Bühler from our diva-e sales team is also on board and looks after the Adobe-related topics, and we'll hear more from him later. Then I would say now let's start directly with input and expert tips on how you can implement customer personalization campaigns with Adobe Target. And now let's turn the floor over to Albert.
Albert Wognar: Will you let me know when you see my screen?
Angela Meyer: Yes, it's already-.
Albert Wognar: Wonderful. Hi. Welcome to our webinar. I'd just run through the agenda that we've come up with for today. Then a few words about the tool, talk about our joint work with E.ON with the Adobe Target tool, and then hand the floor over to Alyssa as a follow-up. Let's take a quick look at what we're actually talking about today. Adobe Target. Maybe some of the listeners today know the tool. But certainly not all of them. I will also very briefly explain the context within the Adobe Experience Cloud. In a further step there, I would then already hand over to Alyssa. Let's take a look at the challenge E.ON faced when they approached us about this project, what vision actually developed from the challenge for E.ON, and what task we were given that ultimately resulted in. Then I would explain, try to explain, how we tried to implement and solve this task. Today, we don't want to just, let's say, look at it at a high level and say that we've done it. We really want to show how we did it. I will try my best not to get too technical, but we will already hear one or two technical acronyms maybe. Yes, I hope it is understandable. Then I would turn the ball back over to Alyssa to tell us something about the result, that is, did our solution produce satisfactory results? We would then move into a question and answer session and if time permits, I would then briefly say something about diva-e. And at the very end, which is not on the agenda now, Dominik Bühler would say something about an Upcoming Webinar, i.e. about a very similar, a related topic. And then we'll get started.
About Adobe Target
Adobe Target. Adobe Target is the testing and personalization solution within Adobe Experience Cloud. That means I can use Target, that's sort of the standard case, to customize websites, content so that I can either use that for A B or also multi-variant fixed. Or I play out personalized solutions, meaning I already have certain segments and I want to show them certain content. When we mention Adobe Experience Cloud here, I also want to talk about it very briefly for those who don't know: Adobe Experience Cloud is a suite-on products that, the entire value chain, in terms of planning, creating, playing out, and analyzing digital experiences. We have Adobe Audience Manager as the DMP, as the data management platform, Adobe Analytics as the data analytics suite, Adobe Experience Manager as the CMS and DAM, so we have other features, but those are the two most authoritative ones. Adobe Campaign to play out direct marketing campaigns, so for example newsletters or also social media. We have Media Optimizer, which is designed to plan, place, play out, and also evaluate advertising, or it takes care of that. Also the Magento as an e-commerce platform, Adobe Marketo as a B2B platform, which is for lead nurturing, lead generation, event play out, but also for marketing campaigns targeted at B2B recipient groups. And then the real star of this afternoon I would say Adobe Target.
Within the Experience Cloud, there are then very exciting, sometimes very exciting integration possibilities with the individual products, which then lead to great synergy effects. Whether I transfer segments from Audience Manager or Analytics to Target, which I then use to play out personalization measures, or whether I use Analytics to track a campaign that I have played out with Target in greater depth through the entire panel, or, for example, an Experience Manager with which I transfer content that I have generated within the CMS directly to the solution in order to then use it for personalization measures. There are umpteen other integration possibilities, but that would be a separate webinar. Even though Target is heavily embedded within Experience Cloud, and as I said, we have these synergies that we see, Target is still platform agnostic, so that means I can use Target with any CMS that's on the market. That could be a handwritten website actually. Then I might have to sacrifice a synergy or two, but there's nothing to stop me from using Target as a standalone solution. It has a very strong AI engine, ML some call it, Adobe Sensei, we can also call it IA, which I can use for automated personalization campaigns and product recommendations. That's when we talk about Target Premium as its own licensing model. Target is not API-first developed, I would say, but it's almost. It's a very, very strong API platform that I can use for many purposes, for example, also to play out server-side personalization measures, that's relevant especially where we don't have a web at all that we can manipulate, so no HTML pages, for example, a voice assistant. And finally, Target is consistently the market leader in terms of testing and personalization, both in Forrester Wave and Gartner Magic Quadrant.
We've been developing for over 4 years now, so we're in our fifth project year, developing Target projects together with E.ON and we've really developed a great competence in that time. We are very, very grateful for the customer, because I think we complement each other there, brilliant is maybe a bit much, but we complement each other very, very well. No one is ever satisfied with what we've achieved, as far as we've reached any milestone, or even before we've actually, probably most of the time before we've even mastered it, we're already thinking about the next challenge and as a result, we've implemented relatively many and exciting projects in Adobe Target. We're talking about over 150 campaigns that we've played out by now. We manage the project at E.ON purely on the implementation side, i.e. implementation does not mean getting the tool onto the website, but implementing the campaigns or the tests, the measures that we play out. These are often highly complex from a technical point of view, which means that we are permanently involved in the project with almost one to three FTE developers. The business analyst Alyssa Ritters, who you will meet in a moment, is on the E.ON side and I think we are a very cool sparring team. According to customer statements, every year the licensing and project costs that the tool brings with it are always reflected directly in the form of gains or savings. Savings because a test, for example, can be profitable not only because I can address customers better afterwards or optimize the panel. It can also be the case, for example, that a planned development turns out to be not as successful as initially thought and you simply leave it alone. So the additional savings that you can achieve can also be enormous. In 2019, we won second place in the Adobe Experience Awards for EMEA. We're really proud of that, it's not that easy. And that's what today is all about. Because that was the E.ON Next Best Action campaign and I would now hand over to Alyssa to tell you a little bit about the background of that campaign.
Adobe Target at E.ON
Alyssa Ritters: That's right. Let me know when you guys see my presentation. I just hope now that you guys see something. Exactly (Angela Meyer: Exactly.). As I mentioned earlier, I work at E.ON as a digital analyst in the data analytics team. And I mainly work in the area of onsite testing and personalization. Our MBA measures are one of many projects that we have implemented. But also a project that we are particularly proud of that we would like to share today in this webinar. E.ON is one of the largest energy companies in Germany, nevertheless we also have the difficulty that the energy market is a very competitive market where it is difficult to differentiate ourselves from other market players. Good, digital customer experiences therefore play a very central role for us. However, E.ON also offers more than classic Quality products. We are also active in nine markets for decentralized solutions, such as solar systems, smart homes, and e-mobility.
So on the one hand we have a very broad range of products and services, but this naturally also means that we have very diversified customers who come to us with a wide variety of intentions and needs. On the other hand, we also face the challenge that our website does not offer unlimited space, and our customers will naturally not look at every offer, every product and every communication. That's why, as E.ON, it's naturally all the more important for us to play out the content that's most relevant to each customer directly. For this reason, we as an analytics team focus on creating customer centricity instead of one-size-fits-all by personalizing the customer journey on our website in a data-driven way in order to create the highest possible relevance for the customer. In the area of existing customer communication, Next Best Actions, also known as NBAs for short, are a suitable extension. This is because they make it possible to predict customer needs on the basis of data and then to guide them through our digital customer journey in a more targeted manner with individualized information. Of course, our focus is always on the fact that we are most likely to be able to fulfill the customer's individual needs by targeting these campaigns. The
The foundation for such a Next Best Actions approach actually already existed at E.ON. Because the foundation for the approach is the NBA Engine, which was developed by our BI team. It is responsible, so to speak, for enabling the CM-based calculations and also ensures the data transfer of the right actions for the right customer to all the channels that are then to be played out. I'll give a very brief insight into how that actually works. And, in the first step, the customer selection takes place, here a target group is defined for the campaign we are setting, and this is then converted into selection criteria based on available CM characteristics. In the second step, prioritization takes place. And the goal of this prioritization is to transfer the individual actions in question per user into analytically derived sequences. This prioritization is based on the characteristics of customer-specific parameters, which are available to us in the system.
In the next step, further business rules can be applied in addition to the data-based prioritizations, if required. These are primarily used to bring our business interests into strategic harmony with the customer interests, and then the NBAs are sent to each channel to be executed. It is also important to mention that we do not only execute the NBAs online, but also in various other channels. That means inbound and outbound everywhere. After the NBAs are played out, it is also important for us to present a continuous process by evaluating the customer interactions and reactions to the played-out measures in detail. And then to be able to use these again for optimization or pre-optimization of campaigns. Exactly, and the process, it then repeats itself constantly. Since this NBA agent already existed at E.ON, we wanted to use it to manage online campaigns as well and approached diva-e about three years ago with this project vision. We had very ambitious project goals and many requirements that we approached diva-e with. Firstly, we wanted to play out the MBA campaigns not only in the logged-in area of our website, but across the entire customer journey. That means in the public area of our website as well as during the log-in process and in the customer content itself.
It was also important to us that the content creation can be done by our own content team directly in our CMS. In this case, that is AEM for us. And we also wanted to give both the campaign managers and the content editors a certain degree of freedom in designing the campaigns by providing several different layout formats. Among other things, a Hero Stage or a pop-up. It was also important to us that these could be flexibly expanded in the future. It was also important that not every NBA should be played on every page, in addition to the individual customer approach that we also aim for with the CM, we also wanted to ensure that the context-based approach takes place. Therefore, another item on our list of requirements was that there be flexibility of playout on the page as well. A configuration of who, when, what, how and where is played out should be possible in real time by the business analysts on our company side, without interfering with the running experiment. We also wanted this real-time configuration to be possible without any prior knowledge of programming or Target.
In order for the departments without access to Target to have an overview of which NBAs are currently being played and where, we also requested an automated, web-based overview of the NBAs and the configurations, as well as all playouts including test inch. Likewise a data acquisition of the customer actions in Google Analytics should be ensured, in order to make afterwards also an evaluation of the individual measures possible. Albert will now show us in more detail what these requirements actually look like in terms of technical implementation. So I'll hand over the floor. So screen back again.
Requirements for Adobe Target in technical implementation
Albert Wognar: Do you see it? (Alyssa Ritter: Yes.) Yes. So the backsheet has it in it. You also have to say quite honestly, so it's not now that the first call (laughs) came to us that would have included all of these requirements. I wouldn't have hung up, but I might have run away. That's, that was a narrative process. So of course we had a MWP, a POC, so how do we get to the data, a MWP that we even create the playouts. But it became clear relatively quickly that the specifications would look something like this, and I would say that after a project duration of about three quarters of a year, we were there. I would now like to show in the next step how we implemented the individual tasks. The first step was to identify the right NBAs for the right user. We have already seen the e-on, I would like to briefly introduce the protagonists in this step. We have the e-on NBA engine, we've already seen that.
Then we have the Adobe People Care Service, which was not specifically listed in the overview of the Experience Cloud. The Adobe People Care Service is actually technically a subset of the DMP Audience Manager, is made available free of charge to every Experience Cloud user, even if they only use one product, and on the one hand enables audiences, i.e. segments, to be shared across the Experience Cloud. On the other hand, it also makes it possible to upload so-called customer attributes, i.e., customer data in anonymized form, in order to make them available to the tools and to do something with them. And that's exactly what we're doing with the data that we'll be uploading in a moment. We have Adobe Target, who would be surprised, and we have the e-on existing customer. This is marked with an ID of some kind, a very clear ID, but to look at it a bit more generically, it could be a customer ID, a contract number or even an email address. In any case, a unique identifier. In the first step, the e-on BA site calculates the most relevant NBAs for each customer every day. The data on which this is based is Adobe Campaign segments, Audience Manager segments, but also to a large extent, or probably most importantly, the information from the Customer Relation Management System. Then, once the data has been calculated for each customer, it's uploaded into the people call service as what's called customer attributes. This is a data set that currently has over five million, I won't say how many, but well over five million records. The bottom line is that this is a CSV document where each customer has their hashed customer ID, so we're not uploading any PII, personally identifiable information, but this is the customer ID that has been run through a SHA 256 algorithm and the three most relevant next best actions for that customer. In fact, this document looks a little different. It's a bit simplified here, but it's supposed to be young and readable for today's session, so it's not the actual document, but the information is the same. So here we see such an entry, the hashed ID, which we also remember. We'll see that maybe once or twice more today. 34567 eight times zero and the three most relevant NBAs are a cross-sell topic, a smart home topic, and a billing topic. Is from accounting. Or from billing.
These customer attributes, as I described, are then provided by the People Call Service for the individual solutions in the Experience Cloud for the Target to be available for further segmentations, calculations, etcetera. On the other hand, we have our existing customer with their ID. When the customer logs into the site, the ID is also hashed with the same algorithm. My click here disappeared. And stored as a cookie on the page. The page then transmits the cookie the moment the page is accessed and Adobe Target is loaded, we can pass that cookie to Target through a certain mechanism. So on one side we have the ID in the customer attributes, on the other side we have the cookie, and Target now assigns the IDs. So it looks for the right entry in the dataset and determines the right NBAs for the right user. Step one is finished. In the next step, we need to be able to play out the right content in the right place. So here we go. We have two new protagonists in this Journey. One is the so-called NBA Config.
If we remember the specifications, the requirement was that E.ON should be able to play out the individual NBAs, actually also the creation, the deletion, the pausing, without interfering with the ongoing experiment, that is, when I always say experiment, by the way, that's Target Lingo, and in the final analysis it's another word for campaign. So without interfering with the running experiment, the business analyst should be able to define that, who, how, when, what, where, we then have that arranged so that that's a json file. The data team is deep enough in the subject matter, so to speak, to be able to work directly in the json document. If that hadn't been the case, we would have developed a web interface, a webguy in AIM, for it, but we work directly in the json document. We'll take a closer look at that later, what's actually happening there. We also have the Adobe Experience Manager. That's where the NBA content is created and delivered by the content editors in the completely usual way that content is created, with the four-eyes principle, with the usual workflows, publishing mechanisms. So after the page is loaded, Target evaluates the NBA Config, then fetches the right content from AIM, because it, as I said, we're going to look at this in more detail, fetches the right content for the NBA to be displayed from Adobe Experience Manager, which delivers that as a headless HTML fragment to Target, and the content is displayed in the right place. So we have the right content, in the right place. In addition, this was also a task from the specifications, E.ON uses Google Analytics 360 and wanted to have, so to speak, beyond the evaluation options that Target offers, also an evaluation in their usual bashboards in Google Analytics. Not least because many departments are involved in this campaign. And it would have been a bit difficult to admit them all to Target now, but they already had, they know their way around Google Analytics, they know their bashboards. That's why you should be able to evaluate the success and progress of the campaigns in Google Analytics.
We then implemented this in such a way that the target code, which takes care of all the magic, also transferred the use, so to speak, on the one hand the consumption of the individual NBAs but also then the metrics, that is, for example, the click on the relevant call-to-action, so the success of the campaign, to Google Analytics. We write that in there in the dataLayer, that's, that's an event-based dataLayer and that can then be evaluated by Google Analytics. Now the thing is, we should yes, well that was in the front, we don't want one-size-fits-all content, but we don't want off-the-shelf content either, we want customized content. So until now, we would have displayed one NBA per customer somewhere, that would have been quite fancy, but this goes even fancier. Because what we're really doing, or what we were going to do, was we should do and what's really cool is that we have the most relevant content for the right location. What does that mean? Now if we look again at the data from the people call service above, yes, we provided three NBAs for each customer. That, the background for that is, and Alyssa already alluded to this, is that not every NBA fits on every site. I say, service-oriented theme is maybe more in the log-in area. Perhaps one would like, although everything takes place anonymously, we have seen it, we talk here about no clear data, perhaps one would not like to confront the user on the starting side with a topic that is really service-heavy. And where he also realizes that fits for him quite well. Maybe this is better placed in the service page, a sales topic is maybe better placed on the sales page and some topics should be placed on the homepage. Furthermore, it is also the case that not necessarily every content on every page will be presented in the same way, but we will see it the same way, we can present one and the same NBA on different pages, differently. We'll now bring in a few protagonists from the previous sheet: The NBA Config, Adobe Target and the Experience Manager. And then let's see what exactly happens there.
So you can then practically say right now, okay on the service side I don't want to play out the billing theme within the section as a hero stage, not as a modal. The content is then fetched from Target as an HTML fragment, as headless content, and then placed by Target at the right place on the page. We then have the most relevant NBA at the right location. The same happens for the sales page, again a match follows. In this case we see that it should be a cross sale topic as a modal, location and type on the page are identified, the NBA controller gets the content from Target and plays it again on the page as a modal. For the home page, this is where it gets interesting. If we see that Smart Home theme is qualified as Hero Stage, that Cross Sales theme as Section. Cross Sale is, after all, one of the three, one of the three NBAs for this user. So what happens now? In a first step, the Hero Stage is evaluated, is retrieved by AEM and is placed on the page by Target. And now in a second step, the Cross Sale theme is also fetched, the location on the page is identified, and the content is placed there. What does this mean? We can display both on different pages one and the same NBA or also on the same page one and the same NBA in different types, so once here for example the Cross Sale theme as Modal and once as Hero ,as Section. We can of course, I've actually said that now, and we can display the NBA in different types. That caused a headache that we could implement that, but it worked out. That means that just by changing the NBA Config and creating the content in an Adobe Experience Manager, E.ON can create, modify, or delete experiments in real time, outside of Target and without any programming or Target knowledge. For those, so actually we almost have a Model You Control here, a Model You Control architecture. The Config is the Model, the Experience Manager or the content in the Experience Manager is the You and the Control is the Controller. Yeah, we think it's cool. Now we have already worked through some of the specifications, but not everything. The customer's requirement was to provide a dashboard with an overview of all NBAs. We then developed this for him, which, funnily enough, is also a Target experiment, or we also use Target here to create the dashboard. We read the config that is generated by E.ON and then visualize it in a protected area within E.ON. Where the departments have access to it. This gives the departments an overview of all currently played NBAs as well as suggestions for future NBAs. We could then also use this for QR and QS. We also have to take a look at the content somewhere and that is of course relatively difficult, we can't log in to the site with individual customers to see if everything is working, which is why we have automated generated test links within the dashboard.
The whole thing is structured like this, at the top the user can filter everything either by name, by campaign ID, by NBA ID or also by location of the playout, on which page run which NBAs. On the left in the area, links to the individual HTML fragments are then generated, that is, if the content was commissioned in AEM, you can then also check whether it then also looks the way it should look. And in the right pane, automatically generated testlings are then available for each configured playout. I just have to click on that, and then I can see how my NBA actually behaves on the page. Back again. We'd take a quick look at that live now. If it works. Now everybody should see the dashboard hopefully. Alyssa are you seeing the dashboard?
Alyssa Ritters: Yes, it is displayed.
Albert Wogenar: Very good. So we see here, the, the sorting that I mentioned earlier. I can sort by name of the individual, that's important for the departments, so we work with the NBA IDs, those are our internal IDs, but the department works with names or campaign IDs. But I can also display the individual NBAs by location of playout. We're going to stick with Sort on Campaign ID for now. I would now open the NBA two. NBA two is OKO, which is online communication. So this is about the customer allowing E.ON to communicate with them online rather than by letter in the future. This is of course interesting for E.ON because it is much less time-consuming and not as cost-intensive. Now, for example, I can look at the tested content, let's try that out. I now click on this and come to a page. In fact, this is a normal E.ON page, but we have also hidden the HTML fragments in order to focus on them, but in the end, I see that I have a stage for this NBA measure in AEM, actually in two variants, the sorting is arbitrary, I already mentioned that. An NBA can also have different variances per type. So we see this NBA can look like this or this. We have a section content and what we have here, we'll see it live in a moment, what technically just not here, there I would have to, we haven't implemented that yet. We still have the content here, as a modal, as a pop-up. You can't see it here but we'll see it in action in a moment. Now I need to press another button-.
So that's left on the individual HTML fragments, in a further step I can now click here for example on the test link. Land then on the log-out page of E.ON and see now right here, there you see now here the played out NBA. And so every single NBA can be tested in every single variance. I want to now, if it works, that's because that's always in the log-in area of E.ON, always a bit tricky, but it should work, I've been logged out again. Then here, that same modal For the sake of the environment. So that's exactly the same issue. We are now really testing the playout of the modal here as a test link. Yes, that's it from me. I would now like to take a self-critical look: Have we fulfilled E.ON's order? The first challenge was the sharp, personalized customer approach with the data from the NBA Engine. We implemented this by applying it to the Adobe People Core Service, simply by uploading the data as a customer attribute. And then deploying Target in the next step. The content creation by editors in AEM, we just saw the fragments created. The freedom design in Heroe pop-up, the flexibility in assignment, and also the real-time configuration are all three provided by NBA Config. We also have the web dashboard, no that's Google Analytics. We have, I did before, we have not seen live, but we will see screenshots from the dashboard in a moment, also choppy, and the dashboard we have just seen in action. We found with that, we have completed the job. Now Alyssa will also tell us if she sees it the same way.
Alyssa Ritters: We agree. Only now I would give another insight into the ongoing project. Alyssa Ritters: Exactly. I hope you can see my screen now. First of all, a few more numbers on the current project. At the moment, we actually have 29 NBA campaigns from a wide variety of disciplines. And accordingly also with different business goals running on our website. These can currently be displayed in three layout types. These are currently the Hero Stage, the Grid Section or our PopUP as a modal. It is also worth mentioning at this point that our Config Ball would allow an extension by any number of layout types at any time. In addition, we have an unlimited number of variants in which we can create a campaign. This means that one of our NBA campaigns can be created in 300 different layout types, but also in ten different variants with five different images or five different headlines. The playout of these NBAs currently takes place on nine website environments. However, this can also be expanded at any time.
In fact, all of this is controlled by a single Target Activity with which we have a total of 94 NBA Experiences live in the current constellation. So that's a total of 94 different combinations. Elements of the layout type, the campaign, the variants or even the page that lead to these 94 Experiences. Exactly. Now, as we've mentioned several times in the course of the presentation, at E.ON we use Google Analytics as our central web analytics tool. Accordingly, it was also enormously important for us to create an integration Adobe and Target. Therefore, all news and metrics of the NBA measures are automatically transmitted to Google Analytics. And these then provide the basis for our derivation in the performance of the overall NBA campaigns or also the individual campaigns. In order to enable the departments to independently evaluate their NBA measures, the most important metrics such as views, clicks, click through rate, conversion, or also conversion rate, as can also be seen here on the screen, are provided per campaign in a datastudio. Further individual Depth analyses can then be performed directly in Google Analytics. Exactly. The project online NBA was a very extensive project and took about 90 developer days. The ongoing operation of the project was also relatively extensive. This required the cooperation of several departments and specialist areas in our company. In conclusion, however, it is fair to say that the introduction of online NBAs has added a great deal of value for E.ON, and to illustrate this, I have also included a few of our highlights.
In fact, we can now respond to our customers and their needs in real time by implementing a regular data exchange with our NBA engine and Testing Target. As a result, our existing customers receive about two to five individual offers or messages tailored to them per session. This has also enabled us to significantly increase the relevance of the content we provide on our website. But we also see that this is actually proving its worth. Because in a test, we were able to see that our NBA teasers led to a 400 percent uplift in clicks compared to generic teasers. And you also had a strong impact in Convergence, for example, we were able to record that 20 percent of our smart home closings occurred with an NBA teaser. Exactly. At that point, we're done introducing the project.
Albert Wogenar: Yes, a few words about us. E.ON probably doesn't need any introduction. Most people know it. With us it is not yet so far. Maybe we'll get there one day. But maybe some of you listening today don't know us yet. Therefore, a few words about us as a company. Everyone will know that companies like transactions, i.e. they are interested in sales. It's probably as old as retail itself. The statement "Customers aspire to experiences, not products" is somewhat newer. In fact, it's almost Adobe's crest saying, but it's no less true. For many listening today, it may be taken for granted. I have to be honest, I had a bit of trouble with the statement at first, but I find you understand it much, much better when you negate it. "Customers don't buy products if the experience is bad," or if there is no experience at all. And in this respect, if you think about it like this and especially in the digital area-. How often have we already aborted in the web store, when the login process alone is simply painful, and gone somewhere else. Or when the shopping cart constantly-. No matter. These are often very simple examples. But if you think about it, it's quite clear.
Customers want experiences, customers buy experiences. As diva-e, our DNA is to implement commerce-driven projects and products. We've been doing that for 20 years. The fact that we like experiences is something I hope I have shown today, or hopefully we have shown today with the seminar, with the webinar. Now I'm getting confused all the time. Hopefully we showed that today with the webinar. So from that point of view, we see ourselves as the bracket and Transactions in Experiences and actually see ourselves as the leading Transactional Experience Partner. I would say not only in Germany, but also in all of DACH, so in the German-speaking region. With our portfolio, we can implement the entire value chain, the entire digital value chain with our services and products. Be it strategic, operational or technical consulting, the provision and operation of platforms, technical consulting, ONSCA, but also the development of full cloud applications and finally hosting. We are more than 800 employees at over 10 years, doing the whole thing for over 20 years and have been awarded several times also for it. If we look at it now on the Adobe side, we have over 90 experts in Adobe Experience Cloud with over 15 years of experience. I actually think it's going to be 20 years next year. We don't do any nearshoring or offshoring and we're actually one of the few service providers that develops directly for Adobe. That means we don't just work with the products, we actually co-develop the products to some extent. And we are proud of the fact that, since the beginning of this year, pro!vision from Frankfurt has also been part of our team, and we are proud to be the host of the only AEM developer conference in the world. And with the slide, I would now also hand over to Dominik, because we have another exciting webinar on the topic in May and Dominik would say a few words about this.
Dominik Bühler: Exactly. I'd be very happy to. Thank you very much for the intro. Thank you Alyssa and thank you Albert for taking the time to introduce the category leadership topic around Target. For those of you who found our webinar fun today, the Albert has already indicated, of course, we're always available afterwards to answer questions about the presentation et ceterca. Otherwise, who enjoyed it today, and who is interested in attending our next webinar, we have again a real highlight on 27.5. together with the Hartmut König, the CTO of Adobe. Together we will present again what Albert and Alyssa had already presented to us today. That it is no longer the product alone that is decisive, but rather the experience. Hartmut König will unpack some more insides and together with him, our colleague as system architect Philipp will present a really exciting AEM case, which you will certainly enjoy. And therefore I invite you again to come back to us if you have any questions or of course to watch the webinar on 27.5. Thank you.
Angela Meyer: Thank you Dominik. There was one more question that came in now, and that is:
Are there plans to use it through other touchpoints as well, so for example, email, app, IVR?
Alyssa Ritters: Exactly. So the NBA Agent, so that also delivers to other channels, there online is just one of the channels that the NBA Agent uses. And we play NBAs also inbound or in the call center or also via emails already currently.
Angela Meyer: Okay, great. So that's it then with our content and with our diva-e today to Adobe, Adobe Target. I thank you two, Albert and Alyssa for your interesting tips on how we can also use Adobe Target in our company and also implement personalized, customized Best Actions offers. And thank you guys and have a great afternoon now. Bye. See you next time
Alyssa Ritters: Bye.
Albert Wogenar: Bye.