Justus, Mr. Communication Strategy at .companion, has been a management consultant with us for 6 years. Together with the Data Driven Teams of his clients, he analyzes the ongoing content marketing of Bosch, Merck or Covestro, among others. Nevertheless, he had time for a short conversation.
in the digital business since 1997. He has held senior marketing and media positions at Jägermeister, Bertelsmann, Warsteiner, Eckes Granini, among others.
There are countless analysis tools. Which cardinal problems of customers can .companion solve?
Most don't know what to do to make the mountains of data and analytics deliver real value. Data must lead to decisions, and getting that done in an organization is the main problem.
We solve this by looking at the opportunities where data should be used and then bringing order to the digital data chaos. We radically simplify KPIs and enforce these conventions across the business. That's not so easy, You have to consistently practice interpretation with client teams, it's really fun. What is not so nice are the constant objections from "experts" who miss their good old special KPI. But we don't even have them. They are part of the special analyses for individual silos that hardly anyone needs, just as they used to be.
Why is simplicity important, metrics are complicated either way, right?
No, they are not. There are just far too many and far too specific key figures. No one understands them without a master's degree in secret sciences. But this complexity is completely superfluous. You can turn any KPI jungle into a fertile plantation - you just have to want to garden with us.
The difficulty is that the data on the success of digital marketing communications is completely incomprehensible to most. We, on the other hand, make success visible in such a simple way that everyone in a company immediately understands the results - regardless of which department they work in. We use the same data as all these experts in agencies and companies, but turn it into just three KPIs, always the same success indicators that everyone knows:
- Reach
- Engagement
- Conversion
We apply these three KPIs in a totally uniform way to every media service. This makes everything and anything in digital media comparable, which is fascinating. There is a lot of data processing behind it. This is done in our engine room. It then sends the analyses back to me via a dashboard or directly to the company. You look at it and in the discussion it happens: channels, KPIs and technology disappear and are no longer an issue. Instead, it's all about content, media formats, goals and efficiency. This is a real leap in quality. Customers can evaluate and control communication with pinpoint accuracy, whether entire campaigns or a single post. We moderate, interpret and help them to help themselves.
Large companies in particular are already complaining about too many analyses and measurement procedures, so why aren't they enough?
Because each department (marketing, PR, IR, ...) and each area of responsibility (web, social, campaigns, ...) has its own key figures, analysis tools and goals. You can't play the fragmented media landscape with these contradictory silo systems. They are pure ends in themselves and outdated. Companies and tool manufacturers know this. That's why they're all tinkering with additional integration platforms.
But they don't go beyond a platform for editorial processes, such as Sprinklr or Percolate, or a Tableau dashboard. But that's not enough. To manage a digital campaign, I need to integrate all the content, its media performance in all channels, and the money flows for digital ads from the agencies. We can do that - who else?
Let's take an example: Around an international industrial trade fair, a company wants to communicate its new positioning via digital channels in addition to the usual trade fair communication and invests heavily in media for this purpose. Corp Comm, Branding, Event and Product Marketing are involved. Together with the team, we define the communication goals, very specifically, on the basis of a mix of goals consisting of
- Awareness
- Involvement
- Target Actions
We link these goals to our 3 KPIs, which are agreed upon by all parties involved, and evaluate success only on the basis of the set mix of goals. The evaluation is cross-channel and shows success and failure based on formats and content - independent of departments.
Senior management gets clear statements on campaign performance, departments get pointers on optimization potential for their individual measures, and the editor for his next video post. Everyone has worked towards common goals and checked them at the end - something like this unites people. Teamwork changes sensationally through shared data.
What are the KPIs that, in your experience, are the most important to customers?
- The number that looks best - if my boss asks me.
- The number that shows whether a content excites the target audience - if I'm an editor.
- The number that illustrates whether the strategy is being implemented - when I need to steer.
In short: the number that proves that a target has been met. However, this is only possible if a consensus on the goal and KPI is reached among all participants beforehand. This cannot be imposed, it has to be practiced. We support and moderate this process. This goes far beyond the mere analysis of data. The "social work", the discussion of the data science results with the teams, that is the exciting part of our work.
Communication is gut feeling plus crystal ball. At which points did customers name a very concrete benefit? Not "they now know a lot more about their communication channels", but: where have you at least saved lives?
Okay, so saving lives isn't really what we do. But we do help marketers save money and communicate better digitally. For example, we optimized a campaign media plan through modeling based on performance data in such a way that the campaign performance was increased by 65% with unchanged purchase prices and budget.
Another example: the 1-year retrospective data analysis of a content audit, showed that 30% - 50% of digitally published content is "peanuts", as we call it when a piece of content, i.e. a web page or a video ad, whatever, produces less than 1,000 views. But in creation, peanuts sometimes cost the same as other content. Producing content costs real money. And what good is content that no one views? Satisfied author egos, perhaps, but nothing else. In this case, there was no budget available to promote and grow his content with agencies, so the client scaled down his content production and reduced editorial costs massively - but without losing communication power! He was able to focus on his strengths and practice content promotion step by step. All good.
What relevance do the press and "classic media" still have for customers - is it all about social media buzz?
The time of the classical press, or other classical media, as the star soloist of communication is long gone. But as a sounding board in the orchestra and as a driver of "buzz," they are still necessary. "Buzz", i.e. the size of the echo, is not a value in itself, however. It depends on which melody is sung. You can see that in the engagement. So, the orchestra has to integrate new instruments, it has to practice much more often than before, learning how to play familiar melodies in new instrumentation. Social buzz is the volume that arrives, engagement is the melody. A Capella is pretty, but only the big orchestra has the right sound.
Honestly: What can still be improved and what needs to be improved?
Targeted meetings - we call them "learning sessions" - need to be worked on all the time. Teams have their human dynamics. You often have to argue, but you can't lose anyone from the team in the process, otherwise the data won't be transformed into meaningful action. That is our mission today. The next will be to get responsible people to make data-based decisions who have never seen a dashboard or chart, and don't want to. Few have an appetite for data, but everyone wants to get better. There's a huge gap there, and that's where automated interpretation plays a big role. Robotic interpretation, that's where we're at right now.
Thank you for the interview!
P.S. How are data treasures lifted and can one actually already get interpretations as automated text summaries - that's what the next "Datafy" our newslet is about.soon in a completely new design. Watch Out, here is the registration.