On-Demand Webinar: Data-driven Marketing at Ravensburger AG

Annabella Pscherer: Once again, welcome to today's diva-e webinar Data-driven Marketing at Ravensburger AG. Today, our experts will use a best practice example to show how marketing activities can be measured, controlled and optimised through digital performance management and with data-based driver models. 
 My name is Annabella Pscherer. I am part of the diva-e marketing team and your moderator for today's webinar. I will now hand over to the speakers Albert Brenner, Florian Weckesser from diva-e and Marko Hein from Ravensburger AG. It's nice that you are all here. I now hand over the broadcasting rights to Florian and wish you all lots of fun and exciting insights during the webinar.

Albert Brenner: Thank you very much Annabella, for the introduction. While Florian takes over the presentation, I'll say hello from my side as well. Nice to have you all here. 
 My name is Albert Brenner. I am one of the co-founders of diva-e and responsible for strategy consulting and data. I'm pleased to be here today with our client Marko Hein, CDO of Ravensburger AG, to talk about data-driven marketing and sales. Before we do that, I would like to hand over to the colleagues who are presenting the webinar with me to also briefly introduce themselves.

Florian Weckesser: A warm welcome from my side as well. My name is Florian Weckesser. I have been working for diva-e in the field of digital strategy consulting for five years now. This is also my focus, i.e. the conception and implementation of digital marketing, sales and service strategies, but also the development of data-based projects to optimise, control and measure the digital performance of companies. And, like my colleagues here as speakers in the webinar, I would like to accompany the presentation and then hand it over directly to Marko Hein from Ravensburger AG.

Marko Hein: Thank you, Florian. Hello to all participants. My name is Marko Hein, from Ravensburger AG. I have been working in digital for 25 years now. I started at Nintendo of Europe, where I was in charge of the online division for 12 years. Back then, in 1994, when the Internet was just taking off and keeping companies busy. 

Since then, I have been relatively active in this field and have often worked in the video games sector for companies such as Bigpoint, THQ or Deutsche Telekom. Before Ravensburger, I worked at LEGO's headquarters. I managed the digital area there and have now been a digital representative at Ravensburger AG for four years and am supporting the digital transformation there.

Albert Brenner: Perfect, great. Thank you very much Marko. Also for taking the time today. You are one of the gurus in the field of entertainment and digitalisation, I would say in Germany, so we are very pleased that you found the time to do the webinar with us today. 

I will briefly introduce what we have planned and then I will hand it over to you again. We have completed the welcome, then the presentation of Ravensburger AG. Above all, exciting: first insights into the digital strategy of Ravensburger AG and how this digital strategy also pays into the corporate strategy. Then also a few words on, let's say, the state of Ravensburger AG, challenges. And then we would talk a little bit about digital performance management, what is that? Defining the term, giving an overview of the whole subject area, and then getting down to the nitty-gritty. What does data-driven digital performance management look like at Ravensburger AG? We will show the model that we have developed and built together. And then Marko will summarise how the topic is used globally at Ravensburger AG. That's the agenda for today. I hope you are also looking forward to it, we certainly are. And we are also looking forward to your questions, so feel free to ask questions in the channel in between. We will collect them later and answer them, so let's get started now. Marko, I'm pleased and I'll hand over to you.

The Ravensburger AG

Marko Hein: First of all, thank you again for the introduction to Albert and Florian. The nice thing about Ravensburger is that you often don't have to imagine it so much. Because many people associate it either with their childhood or, if you have children yourself, with our products. 
 Ravensburger itself has been around for 137 years. It is a company that also comes from Ravensburg, hence the name. It started out as a book publisher and book publishing is still one of our main pillars, where we are the market leader in the children's and young people's book sector. People are certainly familiar with the brands "Why? Why? Warum?" or "Der Leserabe" or also our tiptoi® pen with all the books. Of course, we are also known for our board games. Starting with things like "Kakerlakak", "Scotland Yard", "Das verrückte Labyrinth" or of course one of our biggest areas, the topic of puzzles. Puzzle-2D or Puzzle-3D, where it's all about constructions. We have not only grown organically over the last few years, but have also bought companies. 
 What many people don't realise is that BRIO is now part of our company. Many people may know BRIO from wooden trains. It's a Swedish company based in Malmö. And over the last few years we have also acquired ThinkFun® and Wonder Forge, two American companies. So we are trying to grow both organically and inorganically to further expand our footprint in games and books. We now have almost 2,200 employees, 900 of whom are based in Ravensburg. We also still produce ourselves. So half of our workforce in Ravensburg is manufacturing, that's where our books and games are made. A second location is in Polička, in the Czech Republic. Although we are based in Ravensburg, we now also see ourselves as an international company. We now not only have locations worldwide, such as three in America itself, but are also trying to become more international in terms of product development. Last year we came out with a total turnover of over 500 million, very nice growth. And also this year, although we are now basically having a very tough year in the economy due to Corona, it is affecting us less now. Just rather the opposite. Because we had the lockdown and people are sitting at home, families are of course also looking for employment, which is something we can now do as a games and puzzle supplier, where we can help to bring our products to people, even in times when they have to sit at home. Let's take a brief look at Ravensburger AG itself. 

And then there are always issues where people say, "We have always faced many challenges". It's not even "we always faced many challenges", but we still face many challenges and they are even some of the biggest issues that we have to deal with. For one thing, we have a very heterogeneous target group. So we really start with toddlers, preschoolers with the tiptoi® pen and families. And it's always very grateful when you have a very specific target group to analyse. But at the moment when my target group is very broad and I am active in many countries, it is of course always difficult to set up analyses in such a way that I can cover the whole range. Then, over the years, we have naturally accumulated a very broad landscape in terms of our own touchpoints. We have the Ravensburger website, we have the website for the Spieleland, for our brands. We have social channels for all of these brands and often they are not necessarily aligned with one target direction. That means there is a lot of need for coordination and also a lot of need to really analyse the whole thing in a uniform way. Then, of course, we have relatively little know-how. First of all, we are a very haptic company. We do have an analytics department, but often you also need know-how on the other side, in the direction of the product. Someone who formulates the questions and can then evaluate them for their business. That means that we don't have much analytics here either, as we have now, for example, #00:09:36#. The result is that we often don't have a clear definition: What are our metrics by which we measure our business? What are the KPIs? Here alone is a trick that Albert and I often come up against, the definition between KPIs and metrics. Where often internally it's not really understood, what is the distinction? I think, Albert, you will certainly say something about that? And the result is that we have totally different data silos. Especially when you collect data in different areas and also buy companies that also bring data with them. Then you not only have different data silos, but also different legal conditions under which the data was collected. So there is still a lot of cleaning up to do and a lot of migrating to do in order to create the basis for a clean analytics foundation. Exactly. 

Then the question naturally arises: What goals are we pursuing when we think about the topic of smart data? Smart data is really a conscious term that we have chosen for ourselves, not big data. Big Data always means, "I collect a lot of data, everything that is possible". Instead, we decided to take a truly dedicated approach. To look at "What data do we want to collect, for what purpose and with what background?" That is, with some sense and reason. That means being transparent about the goals we are pursuing and our digital activities in the first place. Often it is not at all obvious to everyone where we are active everywhere, where we perform well, where we perform poorly. That means first of all providing transparency to the management and also to the operative units. How do we operate? The second thing that is totally crucial for us is to better understand our consumer journey. This means that we sometimes catch children at a very early stage and accompany them throughout their entire life cycle until they are adults with our Ravensburger brand. And it is still often the case today that we acquire consumers in different ways and then forget them again. This means that we often have no transparency at all about the life cycle of a customer. So we have to get much better at this and hope to gain more insights in this area through analytics, so that we can of course better control the marketing mix and thus better allocate budgets and resources. What do we need for this? A, that we can collect and evaluate data in a targeted manner, that we understand digital performance on the basis of clear metrics and KPIs in order to make them transparent and measurable for our business areas. 
 And that we can really compare ourselves with our competitors. Because, of course, it's no use saying we're getting better in this area if our competitors are getting better by a factor of two. That means, of course, that we always have to look: Are we really growing or optimising, also in comparison to our competitors, and do we have a competitive advantage at that moment? And also that we better understand the effect of the different channels and can also assign them. Because we now have such a complex digital landscape, with all the social networks we have and websites we have, and some of the things are also interdependent. And understanding the weighting of the individual channels and the mechanisms of action is a very complex field. And here, I think, I'll now pass on to you Albert, without a certain system behind it, which you have to build up, you are, I think, quite lost relatively quickly in the whole topic and I think that is such a handover to your part now.

Albert Brenner: Thank you Marko for the very good insights, not only on the topic of performance management, but also on the strategic outlook and why the topic of KPIs in performance management actually has a strategic role for you. Like Ravensburger AG, many companies are dealing with the topic of digital performance management and one reason for this is to better understand changed customer expectations, changed customer behaviour and, on the basis of this understanding, to control the interactions in a more personalised way and, in particular, to control them in an automated and personalised way across the entire digital marketing mix. And this against the background that ten or fifteen years ago we still had a relatively manageable number of contact points with the end customer as a manufacturer, as a company, and this number of contact points has virtually exploded in the last 15 to 20 years. That means that today I have many possible, different contact points through which end customers interact with me and ultimately I have to synchronise them with each other. And this synchronisation works largely through common data integration. 

These are the typical challenges that make life difficult for those responsible for digital marketing, digital sales and digital service, and we try to address them with an approach like digital performance management. And with that, we also try to-. Perhaps, Florian, very briefly, the three points-. On the one hand, we try to tame data complexity in heterogeneous system infrastructures. This means that I have a lot of data, but it is in different data silos, has a different data structure and ultimately I need a view of the end customer and I get this view by integrating this data. And the measures that I then implement towards the end customer, I want to manage with a uniform and clearly defined and also measurable set of metrics and KPIs, in order to in turn optimally use my limited resources, my limited budgets. That's where, according to my approach, ...#00:16:39# digital performance management helps and we want to take a closer look at that now. Why do I do something like this, such a performance management approach? For one thing, I'm creating a reference model. I am here today in my customer interaction, in my digital customer interaction. How am I developing over time? Am I increasing the level of digital maturity through the measures that I ultimately take? This creates a kind of blueprint that I can then follow and against which I can constantly measure whether I am making progress in my digital development. Secondly, such an approach creates an overall view of all measures. What we often see is that we still have touchpoint managers, a social media manager, a paid advertising media manager and so on, and everyone looks at their touchpoint, everyone looks at their dashboard console. 

What is missing is an overall view of the interaction of the individual customer contact points, of the user's navigation, of this customer journey and how these measures complement and support each other. If I don't have this overall view, then I find it difficult to optimally control and design the entire customer contact point universe in such a way that I optimally achieve customer satisfaction or customer goals on the one hand and, of course, my company goals on the other. What helps are common dashboards, but they also have to be used and used means that I have to analyse the data I see there and ultimately derive measures from it. I have to do this as a team, i.e. across all customer contact points, and this approach also achieves that. 

If we look at it- how does it work? In principle, I have overall business goals in every company and then I have digital marketing, digital sales and so on. And for digital marketing, I have digital customer touchpoints and I can measure them quite well. I can look at various KPIs there and can also optimise them. The objective must be to show the effects of my social media activities and how they can contribute to brand reference or ultimately achieve sales growth via brand reference. This is often the challenge for marketers, for example, to say, "My digital budget or my budget in general has this and this impact on higher-level business goals. The nice thing is that in the digital environment I can measure and track very well and also provide this proof. I provide this proof primarily through dashboards and through presentations of the effects and the figures and also the progress and also the comparison with competitors. 

Typically, we see three levels of types of reporting via dashboards. On the one hand, for top management, there I basically have overarching KPIs, real key performance indicators, to show how I am developing overall in my digital marketing, sales and service activities, how well I am managing to achieve my overarching goals. In middle management, I go much deeper. I want to look at individual channels. I want to look at the performance of individual channels. I will not look at the three, four or five metrics for each social media channel. Instead, I would like to have an overview in middle management of how I am ultimately developing in the individual disciplines, so to speak. The people, the team members, who then really manage the digital campaigns, the digital contact points, the content, the mechanics and the measures operationally, they have to get in at a detailed metrics level, so to speak, which I show in operational dashboards. But there it is important to establish the connection between the operational metrics and the higher-level key performance indicators.

Marko Hein: What's always nice is that even when top management starts at the highest level, it's easy to be tempted to look deeper because you want to understand something. That means that even if you only strive to get a high-level overview in top management, you often get very detailed questions back because you clicked deeper. This means that you also educate the organisation a bit to go into the data in order to be able to understand details. Because if the dashboard is set up really well, it's only two or three clicks away to really dive into the details when a red or green light flashes somewhere. I think that's a very nice way to get a feeling for the topic of digital.

Albert Brenner: And typically, in reality, in many companies I have dashboards on all the individual customer contact points and when it comes to management reporting, then interns, student trainees or operative marketing people sit together and try to put together figures from different systems, which also have different standardisations, different quality levels, to form an overall picture somehow. And that is, of course, relatively time-consuming. The whole thing becomes even more complicated, so to speak, by adding different agencies, PowerPoint and Excel reports. In other words, I have completely different definitions and in the end I never get a real real-time or neartime tracking of my measures. I don't have the ability to analyse root causes, as Marko just said. That is, why do I have a yellow flag here now and can then click through here, so to speak, to see, "Aha, the problem is basically because we're not getting enough traffic from such and such a channel to the next channel." These are all things that I can map very well via integrated dashboards and, above all, automate with a consistent data definition and consistent data quality: 
How do we basically proceed? We identify the relevant digital contact points that are to be included in such integrated performance management. We define the quantitative and qualitative metrics and key performance indicators. We show the interdependencies between metrics and KPIs. 
How do the metrics from the individual customer contact points change overarching company-wide relevant key performance indicators? From this, we ultimately derive a data model that also encodes these interdependencies, so to speak. And then, in the last point, dashboards are developed to support the decision-making process, so to speak, the analysis and decision-making process of the respective responsible persons at the different levels. That is the intelligence that has to go into the dashboard design, so that I can present the right figures in the right aggregation and manner. Well, that's it for my introduction to the topic of digital performance management. Now, of course, we want to take a closer look at how it works in concrete terms. At this point, I would like to hand over to Florian.

Florian Weckesser: Thank you very much. I would now describe in detail exactly what you see here, this process model. How we carried out the individual steps together with Ravensburger in order to achieve the goal of automated business intelligence dashboards. 

In the first step, it was important to first identify all digital customer contact points of Ravensburger AG. As Marko already mentioned at the beginning, the marketing department or even sales and service are on the move in different channels and to create a uniform picture of which channels, i.e. owned, paid and earned, to get, we first proceeded in such a way that we said, "We first have to identify the entire touchpoint and channel landscape to get an exact picture of it."  
Of course, the consumer journey offers a good starting point for 
this, because it also acts internally as a kind of strategic frame of reference that we can ideally use to then assign the touchpoints that Ravensburger currently uses or where users also provide information and content to these phases. So, as I said, in the area of the consumer journey we have initially concentrated on the marketing area, i.e. on everything from awareness to consideration, as shown here on the right. In the area of awareness, the top goal is of course to increase reach, to generate attention for both Ravensburger's products and the brand. 
 Whereas in the engagement phase, the focus is more on interaction with the customer, and this is where the first trigger is set so that the customer decides in favour of Ravensburger. Whereas the consideration phase is used here to provide valuable information and value-creating content so that those interested in the product and brand also convert and then ultimately buy a product in the shop or on Amazon, for example. 
 As a basis for this, it was first important to understand how the consumer journey is fundamentally structured. But an equivalence-based attribution model was also the basis that we carried out in advance, with the aim of matching conversion and target implementation to the different touchpoints, analysing them and then optimising and designing them accordingly. This helped us to determine exactly which digital customer contact points belong to which consumer journey phase in order to develop the driver model in a systematic approach. 

In the second step, it was of course necessary, or is still necessary, to analyse the relevant metrics and KPIs - Albert briefly outlined the difference - per customer contact point. Of course, there are many different metrics per customer channel. In addition, this is of course fed by the different systems that Ravensburger uses. 
 The entire touchpoint landscape has grown somewhat organically. But identifying the 
relevant KPIs and metrics that are important 
for performance management naturally helps to bring it in line with the strategic orientation of marketing, of digital marketing, and also to orient it to the individual consumer journey phases. And also to focus on the channel goals so that you can prioritise which metrics at the lowest level and aggregated KPIs are relevant in the future. We have also included comparative values so that we also get a good significance in these metrics and the performance of each channel. So we compare the performance per channel of Ravensburger in the context with competitor and benchmark companies. 
 This gives us more information: What does the respective performance on the Facebook channel mean in terms of reach or impressions? Or on the website, what does a bounce rate of 40 percent mean? This is how we set it relative to defined competitors and benchmark companies. 
 By using external analysis software systems as well as our internal benchmark at diva-e, we were able to establish good comparative and target values so that the entire performance management of Ravensburger AG for the digital marketing area also has a higher relevance and significance. In the third step, among other things, the identified metrics and KPIs must be brought into a hierarchical structure. After all, we want to depict interdependencies. For example, what is the impact of an activity on social media, on Instagram, on the website? What is the effect of the 
sum of the digital contact points on the ...#00:32:02# -preference, if you now see this as a higher-level marketing goal? 

And for this, it is necessary to bring these identified metrics and KPIs into a structure and then build up the driver model as shown here on the right. 
 On the one hand, we have developed this top-down, i.e. performance, maturity score. This is a value, so to speak. For example, two points out of a maximum of five is the basis for where we want to go. In terms of the dashboards, this is then a board KPI that shows developments, in order to then say on the second level that we take the individual phases of the consumer journey as a reference value and thus form the upper level of the driver tree. And then, of course, the identified metrics flow in bottom-up for each channel, which are aggregated at each further, higher level and are also provided with the respective factor weightings. 
 These factor weightings come into play above all in the data model. So this is where the structure of the basic calculation logic is envisaged. The factor weighting is a relevant component here because it tells us how important a metric or how important a channel is for Ravensburger AG's digital marketing. This is also based on the strategic relevance of a channel, the competitive performance and the importance of reaching target groups and addressing them in a personalised way. With this data model, which is now presented here, we can operationalise the interdependencies that I have just described.

We can also map well for different stakeholders within marketing, i.e. an operational marketing manager for the area of PPC or display advertising. So that he can see at a glance how the performance of individual channels is and can also derive action measures or optimisation potentials based on this, in order to be able to better control the performance in relation to the competition and the target values of Ravensburger. As we mentioned at the beginning, the aim of this model and this procedure for creating the driver model is not only to present it statically in an Excel-based model, but also to map its usability and manageability in Power BI or Microsoft Business Intelligence tools. So that the dashboards can also be made available to different stakeholders and they can always see in a continuous real-time manner how Ravensburger can develop in the digital marketing area on the one hand, but also in the future in all other digital areas, such as sales, such as service, such as for the digital products.  
This will also serve as a basis for us to be able to better measure and control 
all digital activities in a more targeted way. I can see at a higher level how the development is progressing over time. But I can also break it down further and say that I can now look at the performance for a touchpoint, such as social media, shown here on the right, or even further down for a channel such as Facebook, and can identify how my individual activities, which I manage, and campaigns have an effect on the target group, on the channel and ultimately on my performance. I would now like to hand over to Marko, who will explain exactly how useful this digital performance management is and also how it will develop in the future. Because that was the starting point, so to speak, as a reference model for data-driven performance management at Ravensburger AG.

Marko Hein: Thank you Florian. You have explained beautifully what we have achieved over the last year and a half. Of course, it was a long process until the whole thing was finished. But strategically, where do we want to go with it? 

On the one hand, we naturally want to make our entire digital transformation measurable and controllable. Especially in my role or as a digital officer, you naturally have the task of bringing the digital forward and you always feel that progress is being made. But of course, on the other hand, you also have to say how you can make progress measurable and verifiable at all levels where we are digitally on the move. Now, in this example, we have seen more the topic of marketing. But it's just as much about e-commerce, products, and in part also internal mechanisms. So everything that we do digitally as a company can usually be made measurable and it can also be linked together. 
And I think that's where the magic lies in the end, to say, "Okay. If we do something here in marketing, what effect will that have on e-commerce? Or if we get better at consumer service, to what extent does that have an effect on how we sell our products digitally?" That's one thing, that is, measuring our digital progress. 

The other thing, of course, is to increase efficiency and effectiveness. Because of course we want to make more efficient use of our budget, become more effective in how we manage our marketing, how we move our digital business forward. Of course, this can then also be tracked very well and made measurable. Operationally, we tend to say that we want to make it very individual and very flexible for the users. 

What Florian showed was of course a very generic picture of a dashboard. But you can imagine, if you look at our business now, that someone who comes from BRIO and has a very young target group wants to measure completely different competitors than our colleague in the games sector who sells board games or a completely different business segment. That means, of course, that we have to design the dashboard in the end so that it can be put together very individually and, of course, also at country level. Because if we have a colleague in America who perhaps has a completely different composition of social media channels, for whom Twitter is perhaps much more relevant than for us here in Germany, then we must of course also be able to display this in the weighting. 
 Our goal, our dream is to be able to say: People in Italy or in America or our game colleagues have a very individual way of managing their business through such a performance model. We are not there yet. So we'll probably be working on that for the next one or two years. But that would be my goal, where we can say that we can now really design our touchpoints and our marketing activities very individually, based on the individual needs of the respective business operators. So that would be it for the short term. 

 Technology and system infrastructure

If I now look a little bit into the future, what needs to happen or where would we like to go in this area? Of course, we have to set up the topic of technologies and system infrastructure in a future-oriented way. Albert and many of our internal colleagues are also working very intensively on taking another look at the entire technology landscape in order to develop a target picture and to say: 
Where do we want to go? And to get there, which technology landscape do we have to build, with all the tools that go with it, in order to set ourselves up for the future? 

Automation

The second thing that concerns me a little bit is to say, in the long term, how can we automate the whole thing? The whole topic of artificial intelligence is coming up so strongly over the next few years and I think at the moment we have of course built a dashboard, which is more of a snapshot of the current situation. But I think that algorithms will enable us to gain more and more automated insights, which we can then perhaps even use to automate specific marketing activities.

I am firmly convinced that a lot will happen in the next five, six, seven years, so that we will also become very self-sufficient in marketing through algorithms, in order to really automate some things. One challenge that we still have to overcome internally, of course, is to promote data-driven thinking. 
 It doesn't help to just put a dashboard there and say, "Receive, spirit!" We also have to make sure that we take people by the hand and say that a mindset must first be created that data is first there, that you can interpret it and then manage your business. We have to bring a lot of know-how into the organisation. I think these are the main topics and we are in the middle of a journey that we started to work on really intensively one or two years ago. And now, I think, through this whole dashboard issue, you get a sense of where we are on the journey. But I think we still have a long journey ahead of us and I also hope, Albert, that we will be able to walk it together up to a certain point. As I said, this is also an exciting topic that we are working on together.

Albert Brenner: Absolutely and with great pleasure. I think what you said again just now, this outlook-. I believe that the effect of the whole thing should not be underestimated. I do performance management here now in order to optimise marketing, sales, service, digital products and so on in a very concrete strategic-operational way. And of course I can also use such an approach in other areas, in the supply chain, in the other areas of activity of the company, with a similar procedure. I also think it's important once again what you just said last time, this effect and this contribution to the transformation. 
On the digital transformation journey, as we often say, this data-driven thinking is simply a very essential capability of an organisation. Why? Because for potential disruptors from other markets, it is simply a core part of their DNA to think data-driven, to make data-driven decisions, to develop data-driven new products and services. And in this respect, this performance management, which we have in the area of the customer interface marketing, sales and service, what this brings in terms of performance, so to speak, also has a contribution overall to move the organisation more strongly in its digital maturity level.

Marko Hein: What I really like about the driver model is that it can raise many different metrics and activities to a very high level. People are sometimes overwhelmed by everything that is happening in terms of digitalisation. 
 Every day there is a new social media tool, then there is TikTok and this and that. And people do read about it a bit on the internet, but if you're not so deeply involved in the digital world, it's very easy to get overwhelmed by the whole topic. And I think taking away people's fear a little bit and saying, "Hey, you don't have to look at all the metrics and all the channels. We'll give you a high-level overview of our overall company performance", I think that also makes it a bit easier for top management. To say that there is also a view where I get a good overview of the whole digital topic in a relatively quick and simple way. But I can still drill down if I want to.

Florian Weckesser: And especially when I drill down, I can see how my activities in one specific area actually have an impact on another. I can then also break down these organisational silos, which still exist in part in the company. With the contribution I make, which has a direct influence on the service area. And so, in this example, I bring the customer areas closer together in order to communicate and work with each other in a more integrated way. This is also a positive effect of the driver model.