“Using Data as the Basis for Communication in Marketing”—with Burkhardt Gasber

Recorded in German—English translation of the original conversation.

Intro

Maria-Lena Matysik: Hello and welcome to a new episode of Analytics Sprechstunde!

In this episode, my guest is Burkhardt Gasber. Burkhardt comes from performance marketing and online sales and has been working in data-driven roles since 2005—first as interim CMO … today, Burkhardt deliberately operates in the “translation space” between operational marketing and management.

He helps teams structure data, focus on what really matters and turn the flood of information into a real basis for decisions. His focus is not on tools but on structured communication about data.

Burkhardt has worked in large corporations, mid-sized companies, family businesses and start-ups—often in phases of upheaval: when leadership positions couldn’t be filled, in crisis situations, when building teams or in pre-merger phases.

In this episode, we talk about the different perspectives and ways of looking at data that exist within the same company, how we can reconnect data with hands-on expertise as well as knowledge of target audiences and context—and what the best starting point, the best data preparation and the right focus are for that.

Let’s go!

Interview

Maria-Lena Matysik: Hi Burkhardt 🙂 Welcome to my virtual podcast studio. I’m really glad we’re talking today.

Burkhardt Gasber: Yes, I’m glad we’re talking too. We had already exchanged ideas once and realized that this might be a really interesting topic for this podcast. That’s why I’m also proud to be part of this podcast today.

Maria-Lena Matysik: The pleasure is all mine! Then I’ll just jump right in: What role does data play for you in your day-to-day work, in your role today? How would you describe it?

Burkhardt Gasber: In the marketing business—and especially in online marketing, where I primarily operate—data naturally plays an essential role. There are many tools that keep producing new reports and new dashboards. That has practically exploded in recent years and is exploding again right now with AI, because there you also have the opportunity to analyze data once more and get another opinion.

So for me, over the past few years, data has not primarily been a reporting instrument and not primarily meant to be housed in dashboards. Rather, for me data is actually a communication medium that you have to engage with.

The issue isn’t a lack of analysis or anything like that. The challenge is actually finding a common denominator in the data and figuring out the shared story in it. That’s really, really important. And that doesn’t happen on some data boards or in some PowerPoints, but in real work with data.

I sat in meetings like that for a long time, and, as I just mentioned, different conclusions were always drawn there. The problem was rarely that data was missing. The problem was the shared direction—a commitment about the data, or rather about how you look at data. Because everyone has their own approach. Some immediately open their Excel spreadsheet and do the math themselves; others don’t engage with it much. People are at different levels.

Since I realized that direction is the issue, I’ve defined my role differently. I stopped trying to report even better. That’s what you reflexively start with: Somehow there needs to be a second level in the report to bring this or that person on board. You keep trying to refine it further, add a third level to the Power BI dashboard so people can click there too. But nobody does that—usage is really low. When you then look at it together in meetings, people often lean back and say, “Yes, a nice show of data—he’ll know which way to go.”

But that was never my approach. I wanted to get at precisely the knowledge people have about the data and the opinions that exist there. After all, there’s also a lot of experience. The whole marketing world doesn’t consist only of data—you have to know that too—but also of experiences, technical hiccups and so on. And that’s never taken into account in a condensed, aggregated version.

Bringing structure to the communication about data and providing direction so that you’re able to act again—that’s what it’s about. Because it’s often like this: You walk out of the meeting and don’t really know what we’re actually going to do now. Sometimes I’m actually brought in just for that. There are huge BI structures, huge data structures, everything is already prepared, great reports. And then people say, “You have to help us make decisions here. How are we supposed to …?” On the left we have attribution models, on the right awareness studies as well, then data from Google Analytics too, and then someone voluntarily built a Power BI dashboard on top of that. You really have a very, very fragmented landscape. Bringing it all to a common denominator once and providing direction so that you know exactly: This is the next step, this is what we’ve learned—and putting that on a foundation, that was really my best practice.

Maria-Lena Matysik: If I sum that up, the challenge isn’t that data is missing at all—it’s developing a shared view of the data. In other words, a shared direction: What are the numbers really telling us? And what do we concretely derive from them in order to be able to act?

Burkhardt Gasber: Yes, exactly, wonderfully summed up. I think that’s the summary of everything I just said. That’s exactly it: finding the common denominator. And that’s basically what I do, completely unscientifically: finding a level somewhere where we can all look at data in a relaxed way, evaluate it in a relaxed way and say in a relaxed way: Okay, we did this and that there.

Maria-Lena Matysik: You said there are different perspectives that all have to be brought to a common denominator. Can you explain that a bit more? What kinds of perspectives on the data are there, and in what way do they lack a common denominator?

Burkhardt Gasber: To structure this a bit: If you imagine it as a pyramid, the data gets condensed more and more as it moves up toward management. That in itself is already an issue. The numbers that arrive at the top are mostly data from BI or ERP systems. They reach management in condensed form—online is then one line, and it says something like 10.5K. And at the extreme, at the very bottom, you have all the campaign data, viewed operationally: campaigns, CPCs, target audiences, data and information from market research, all kinds of things. And there you have three decimal places, to put it a bit more pointedly.

In between, you often have tactics, usually at the team-lead level. That’s where the channels are discussed: Which channel do we give more weight to, where do we allocate the budgets? Those are decisions that no automated system and no AI can really take off your hands yet—because then you’d be giving away responsibility. Of course there are software and SaaS tools, I know, you can load everything into them, and then there’s a supposed attribution and supposed decisions. But still, in the company there’s always this level that decides: Where do which budgets go? How do we do it? How do we measure it? And so on.

That’s the pyramid you move within. That means: At the bottom, you have three decimal places. At the tactical level, you drop the three decimal places, and then you’re already left of the decimal point. And at the top, just a K is written after the thousands, so to speak. But the story as a whole has to fit together. You can’t decouple a campaign from the ERP data; that doesn’t work. That’s always management’s question. There’s the negative case: Things go down—then you start explaining why they’re going down. You’re always in this explanatory stance. Or when things go especially well, you also have to explain: Where is the success coming from? And then it’s really good to have a common denominator that management can understand too. Because often what happens then …

Maria-Lena Matysik: From my perspective, it does make sense that the people responsible for the channels look at different numbers and draw different conclusions than management further up the pyramid. So where does a problem arise from the different perspectives?

Burkhardt Gasber: I wouldn’t see it as negatively at all; rather, it’s in the nature of things when management runs into the operational level. I’m deliberately putting this in very neutral terms—I know there are always people behind it—but described at this level, it’s a communication problem.

Management has strategic decisions, the company’s course, personnel and all kinds of things to deal with. And then there’s a meeting about explaining a success. I’ll assume the positive case here: Online did very well last month—what happened? Then there’s a meeting with the operational level or the team-lead level. And then it very quickly goes way too deep and way too granular—and then people’s eyes glaze over. That’s a psychological issue in management. I was in management for a long time, and I know exactly: By the third twist, you’ve simply lost me. That’s simply too much. It’s not wrong; it’s all correct and correctly structured. For me it’s still somewhat understandable, because of course I’m in this business. But for many in management, it’s a closed book. And then you think: Yes, sure, it all sounds plausible—but there’s no understanding.

That’s just not enough to be able to decide quickly: There’s a business opportunity here, there’s a bigger opportunity, we could actually scale again here. This commercial, business-oriented thinking is then often missing in these operations. Everything that’s been done is shown—in a great many numbers, data, facts, reports and derivations, all really super clean and also very competently done. But with this kind of communication, you don’t get through.

So it’s always a communication problem. Sometimes, of course, it’s also a bit tactical, sometimes also a bit of a lack of knowledge. Those points exist too, but actually rarely—more rarely than you’d think. Display, for example, is very typical: Something gets derived so that there’s continued investment in media, because it doesn’t immediately bring in sales and so on. That exists, of course; there’s tactics involved too. But it’s a communication issue. People simply fall asleep in the meetings—to put it a bit more pointedly. You simply lose them. They can no longer concentrate on all the details being delivered to them. And that’s a challenge.

Maria-Lena Matysik: You say it’s mainly a communication problem. What’s the reason for that, in your view—why does communication so often not work? Why does a problem arise there?

Burkhardt Gasber: Exactly, that’s simply the psychology of communication. You have different target audiences. If you’re down in analytics or in the broad data, you often don’t have that much to do with executive boards or management, who then suddenly take an interest in your topic—because something went really well or because this digital focus is becoming more and more important. Then suddenly you enter a different world; you mustn’t underestimate that. That’s psychology too. From a management perspective, you think, “I’m just talking to this person; I’m a completely normal guy.” But from the analyst’s perspective, it means, “He wants to see something really special from me.” That’s pure psychology—how I talk about data. That’s exactly what we’re talking about right now. And in my opinion, that’s simply not properly taken into account.

Everything just gets crammed into these slides—I know them all. Everything once more here, once more there. “Oh, that was interesting too.” “We also had a hiccup there, and this is how we saved it.” Everything presented in data. And that’s how you lose people. And if it’s then presented somewhat nervously—what sticks in the end? Then people think: Okay, that’s a bit nerdy, they’ll figure it out somehow. Trust is often definitely there, but no real mutual understanding.

And that way you don’t bring in more budget or more trust. It actually happens very subtly: People think, okay, I don’t see a real business opportunity there—so I’ll keep dealing with the familiar, with the usual sales channels and so on. And you don’t really get in there and don’t get any real support. Unless there are people who are real fans of these topics and are deeper into the data. But that’s rarely the case.

Maria-Lena Matysik: So how do you go about tackling this and improving communication with the data and about the data in a marketing team?

Burkhardt Gasber: Over the years, I’ve developed a very, very clear approach. I’ve now reflected on it more deeply in my remote situation: What’s the difference between the teams I led and the teams I experience today when I come in somewhere? And it’s actually creating a certain visibility in the data. In other words, finding a format in which you can talk about data so that you get an eye for the stories—and not just your own. If I’m responsible for a channel like paid search or email, unfortunately I usually only look at it in a silo. So it’s about creating a format and visibility that work across the board.

Then it’s very important to establish focus. Not everything is equally important—not the bounce rate and another KPI here and something else there. You often have a pretty broad view of lots of KPIs, especially relative KPIs. I leave those out completely at the beginning when I look at the data with the teams. I don’t look at a CR or a CTR or any other data first; instead, I first focus on the so-called North Star Metric. That’s always the very first thing I do. Depending on the business, that might be revenue, units sold or new customers—it can be all kinds of things. For me, that’s the direction to start with. Focusing on that first—really easy, really simple.

And then looking at how this data develops, specifically at a granular level in the channels and per day. That’s a very simple thing I lay out first. We have, for example, five or six channels or people responsible for these topics—sometimes there are only two who then handle several channels. Then we simply look at the trend of these individual numbers. At the beginning, maybe two or three: starting with the North Star and then two or three more below it. And then you look at it with the people to see: This is how it develops over time.

That sounds very mundane, but surprisingly it’s very rarely done—really looking at a longer time series. The numbers sometimes go up, sometimes down, there were certain peaks and so on. Then you see it like a map you’re looking at. And that makes a lot of things easier, because you leave out all the clutter around it completely—this noise of lots of data you come across in dashboards. There you get asked questions and then have to go here and there again. I take that out completely and create a space in which you clarify the context.

For example, by seeing on individual days: Okay, there was a particular peak there. “Yes, there was a PR campaign; the boss gave an interview here and there.” Then I think: Okay, that had an impact on the visitors and on everything else. Clarifying this context is a really exciting thing. If you simply look at the absolute data in a time series—that’s basically the secret. Really having the courage to focus on the core topics again and to simply look at absolute data in a time series.

And if you combine that with visual options as well—I like to do that with heatmaps, quite simply per channel over a time series—then you see: One channel is going up there, suddenly the new-customer numbers are going up, and oddly enough on the same day in three other channels too, even though it was an email. Then you see connections, you see individual stories. You can do reverse engineering. I always look at the data this way myself first, then ask questions and say, “So what was up on March 17? What happened there? All the channels are showing red.” And if you happen to have the IT guy in the meeting, he tells you, “I didn’t even know that had such an impact—we had a two-hour server outage then.” Then you have real experiences that everyone takes away. The head of IT takes that away too: You can actually see it in the data.

Maria-Lena Matysik: Communication is super important! So what communication stages are companies at when you come in? Do you already find these meeting routines and communication channels in place, or do they first have to be established when you come in?

Burkhardt Gasber: Nope, that has to be established first. Usually these are two worlds. The requirements sometimes move toward “even more data” or “implement even more tools” and so on. And of course there are difficult communication situations there. Everyone has their prejudices. I’ve also heard from IT, “That’s all nonsense; we can do that ourselves.” Then they develop their own ideas—I’ve experienced all kinds of things there. You really have to feel your way forward. Of course, at the beginning it’s not as simple as I just pictured it. They’re really two worlds. You rarely have IT people or BI people at the table. And that actually has to be established proactively over time. But that’s also a task of a leader: to build these bridges and heal old rifts. That’s a challenge then.

Maria-Lena Matysik: If we do all of this the way you describe: What’s the positive output?

Burkhardt Gasber: Of course, everything is in flux. It all happens in day-to-day business, amid the day-to-day hustle—I’ve left all of that out just now. It’s not a point where you say: Now we’ve made it. Rather, it’s always evolving. Communication, too, is always a process of development.

But it’s a success when I notice: People are talking to each other, they’re more able to act and can even make their own decisions again—even if that sometimes seems impossible today. You always have to ask, “We have the data now—have you decided yet?” Often decisions are still pushed upward. For me, it was always important that the guardrails are set correctly. When the guardrails are set correctly and you have a shared perspective on the story and the data, you also enable individual team members to decide for themselves again and say, “I can raise budgets a bit more there, I can take a bit more of a risk there”—in quotation marks.

When a team as a whole is more able to act, and as a result also talks to each other in a more motivated way and, despite all the pressure from the numbers, also laughs together sometimes—I actually pay attention to that. It’s sometimes really disconcerting for people from other departments who come in and say, “You’ve just had such a success” or rather “You’re under so much pressure—how can you be so relaxed with each other?” It’s actually perceived that way. And that’s what then creates success in the team.

Beyond all the attribution models and data that are imposed on us from outside, for me it’s still essential in the online business that people work well together, are able to act and are motivated. Not everyone has to like everyone; that’s not what I mean. It’s not a good-mood parade. But at this level it definitely also enables disagreements—sometimes things have to be cleared up—but overall you then have life in the team. I often see that there’s no real life there. Everyone has their own agenda, their own way of doing things and so on. If you manage that, then that’s success for me. And business success actually follows from that. That’s essential for me, and that’s what I’ve always measured success by—to this day.

Maria-Lena Matysik: Would you say that by carrying out this process, the culture and the way data is handled change—and that, in the end, this is independent of the leader?

Burkhardt Gasber: Yes, that’s how it is. That’s the wish—not always 100 percent fulfilled, but that’s exactly it: the culture, the data culture, the way data is handled and also removing the inhibitions about engaging with data. I think I mentioned this at the start: There are many people who had their access to numbers literally trained out of them through their schooling or bad math grades. Those are actually still traumas from the past. That’s never admitted, it’s never talked about either—I just see it.

There are those who can handle data quite well, those who are deep into it or even dig themselves in too deep, and those who are hesitant to show something because there’s someone there who’s even more competent. That has to be balanced out. As I said: simplify access to data, simplify the view of the data. That’s a question of culture. And that’s how data literacy grows in the team too. Then everyone has their role, too. Everyone knows: He or she can help me prepare my data better. It’s more of a fear-free situation rather than a judgmental one—along the lines of: My numbers in my channel aren’t that good right now, or I have smaller numbers than the SEA channel and therefore have less say. There are so many psychological things at play, and that’s a cultural question that has to be solved.

Maria-Lena Matysik: That was the perfect closing statement. Thank you!

Burkhardt Gasber: Yes, you’re very welcome, that was fun. There’s nothing to add to that. And as I said at the beginning: I’m very glad and happy to have this conversation here with you. It was really fun.

Outro

Maria-Lena Matysik: I found it really exciting to hear again in the interview with Burkhardt—and this also matches my own experience—that most companies and teams don’t lack data. What many are missing is an open conversation sparked by data: What do we see in the data? And what does it tell us? (Although “us” can mean very different things: What does it tell me? What does it tell you? …) Data is a communication catalyst.

And I found it really exciting to hear how Burkhardt swears by overlaid time series and heatmaps across all channels to find conspicuous data and then use it as a starting point for conversations.

And with that, we’ve already reached the end of the episode. Feel free to follow me on LinkedIn, and if you have feedback or comments on the episode, or suggestions and ideas for future episodes—feel free to write to me!