Christoph, Customer Success Manager, has started as a trainee with us and will soon begin his dual master's degree. For an interview, he briefly got rid of his double screens and the balloons of his birthday colleague.
So, hello Christoph. You know our interview series is about the .companion staff and what they're up to. We'll start with a difficult thought experiment.
Imagine your grandma invites you over for coffee and cake and she asks you, "Boy, what exactly is your job? What do you actually do, every day, with this Internet?"
Christoph: Oh, that's difficult, think about it for a minute - silent for almost a minute .
So, I would tell her that I check what companies are reporting on the Internet and in all kinds of social media, and how people react to it, whether they think it's good or not. I do that especially when the companies are doing their advertising and campaigns.
I get the data on these communications from the companies and do mathematical evaluations that tell what went well and what didn't go so well. To do that, I have a pretty fancy dashboard, my baby, that's unique to us. The dashboard generates colorful charts or automatic texts, and I look at them together with those who are behind this communication in the company. We discuss the results, evaluate them together and then draw conclusions together.
Your grandma will then surely ask: What's that for?
Exactly, that's the crux of the matter. It's always about communicating better and doing more with the same money. To do that, I have to talk to my customers about the statistics and interpret them. But what exactly is "good" and how to get "better" really just depends on the customer, their goals and their situation.
One client, for example, wants to strengthen his brand more. He may simply want to reach more people with the same resources. The other would rather have people engage better with the content a company provides on the web or social media. Yes, and the next one, he wants to engage in dialogue with everyone who is connected to him. And then there are those who simply want to sell after they post or advertise. Depending on the goal, I weight the data differently in the dashboard and then we see what the result is.
How can your grandma imagine your environment in concrete terms? Do you work at a workbench, like in a workshop?
In a way, yes. Most of the time, I'm at the machines. But when I talk to customers, it's via video conferencing.
How do your machines work?
Well, first they get the data and then they process it. It's mostly simple mathematical calculations, but sometimes also complex video indices that are updated en masse, with every new operation. You set your filters, depending on the question you have. The results then tell us, for example, which topics did best last month or which videos were the most attractive.
That sounds simple. Can't many people do that? What is so special about it?
That I answer these questions across multiple platforms, and not just for the website, for example, or for YouTube. I can answer them for entire campaigns, or for a theme that I've played on completely different channels. I can filter and summarize as I want, that's what's special. And if I want to know why an overall result was so good, I can get into the details and end up finding, for example, the one video post on Instagram that made the whole theme go through the roof.
I can also tell my customers which advertising bookings on which advertising platform - with a target mix that was primarily focused on engagement and conversion - brought the most. Not even Google has such a complete view. And that's because we evaluate in a uniform way.
Evaluating key figures uniformly - how do you do that?
By sitting down and looking at what the interfaces for exporting data give me and what I can use to compare with other platforms. The platforms use similar key figures and data, you just have to find them.
What platforms are we talking about?
Well, simply everything that is digital. Texts, photos and videos in blogs, stores, Facebook, Twitter, LinkedIn, Search, banners, Chinese platforms, newsletters ... it doesn't matter. Anything that goes out on the Internet, I can get into my machine.
So, if I understand this correctly, you're making sure that data is pulled from these platforms and analyzed in a way that it's comparable?
Correct.
And you enjoy that?
Yes, a lot of fun, actually. The beauty of it is that I have the overarching perspective. I see all the platforms of the companies and campaigns side by side. I benchmark that and can see, for example, that all customers have a top performance in engagement over the same period of time. This is then due to the platform and not the customers or content. I could see something like that at LinkedIn, for example, who changed their metric definitions for reach over quite a while. Engagement rates went up all over the place, yet they only made internal changes. That was an artifact, there was no better communication.
Interesting, the clients and their agencies knew that, didn't they?
Some did, but most didn't. There was quite a hello, especially among those who had placed ads. There are so many changes on the sides of the platforms. KPIs are calculated completely differently than before. Then, in the latest export, data columns that were previously available suddenly disappear. Or data and KPIs are added that did not exist before. The platforms and their changes keep us on our toes.
How many changes per month do you observe?
So, there are big ones and small ones. I would say there are major changes every quarter on at least one of the platforms. But in addition to these planned changes, there are also technical errors on the platforms all the time.
Technical errors with the platforms?
Yes, absolutely, Facebook and Twitter also make mistakes, just like everyone else. But I do wonder why, since they are giants. But they also have a lot of manual processes in their own IT, that's how I explain it. And anyone who has manual processes also has management problems - welcome to the club! (laughs)
And how do you deal with their mistakes? They do a lot of work, don't they?
For this we have our own little helpers, which I help to build. Scripts and bots that we develop ourselves and that detect changes and errors. They check automatically and are so nice that they write us emails if something is wrong. But you have to have developed a routine for that beforehand. We therefore have to organize ourselves well and do this continuously.
The tools you use to control the quality of the platform data, what is that exactly?
These are simple scripts, short programs that we write in different languages and that are used sometimes here and sometimes there. Sometimes on a database, sometimes directly in PowerBI, our dashboard software, sometimes in between, in our data science lab. These algorithms give us feedback that certain data is missing, or that a measurement is not plausible, or that the same content has been posted twice with different IDs.
How many channels do you actually have in the system?
At the moment I compare more than 100 channels, most of them on 6 platforms.
Do you actually work in a team?
Of course. I have people in Data Supply who get data. Then there are also bots that fetch data, but that first have to be built and then maintained by our developers. And finally, there are colleagues in my position, Success Manager. We look at each other's results and, as a first step, check the technical quality of our customers' communication and marketing. After all, we have to translate the results into our customers' everyday lives.
And how do your results get to the customer?
Customers can navigate through the results themselves in the dashboard. But they can and should also call me if there are questions or if they have special evaluation requests. There are also regular meetings where we interpret and discuss the results with the team at the customer's site. That's actually the most important thing. After all, we have this saying, "Data only talks when you talk about it." That's true enough. I know the data, but I don't always know why it is the way it is. But the customer knows, with his project knowledge, also called domain knowledge. For example, the customer knows in detail what he has bought on, what campaigns he is running and what themes he is playing with what goal. There's a bunch of background and I can't know them all. We bring that together in conversation and that's how we learn why it is, how it is, and how to do it better.
And where is the journey going, what's next?
The next step goes beyond social media and the evaluation of one's own media performance. What comes next is the evaluation of the impact of one's own communication. We have already included the conversion to target actions on the website, but what comes next is the evaluation of the media response. Have I been noticed? Are people talking about me? This is also measured with tools, and I'm currently pulling their data into our platform. I'm already very excited about the statistical correlations... we will then be able to see in my dashboard what has brought how much effect.
Finally, back to your grandma - what is special about your work, what gives you pleasure?
For me personally, the nice thing is that I have a lot to do with people in the communications field. They are very nice people. Exchanging ideas with them just puts you in a good mood and the topics are always super interesting.
Thank you for the interview!