Future Demand featured on Deutschlandfunk Kultur
TLDR
In an interview during the "Konzert im Deutschlandfunk Kultur" with the Rundfunk-Sinfonieorchester at the Berlin Philharmonie, editor Stefan Lang spoke with Hannes Tronsberg, CEO of Future Demand, about the future of the classical music industry.
In the "Konzert im Deutschlandfunk Kultur" on March 13, 2022, Pablo Heras-Casado conducted the Rundfunk-Sinfonieorchester Berlin in the Berlin Philharmonie. The program included works by Claude Debussy, Manuel de Falla and Béla Bartók.
After the concert, editor Stefan Lang spoke with Hannes Tronsberg, founder & CEO of Future Demand, about the Future Demand software, its functionality and applications, and how it helps cultural institutions attract a wider audience to their events.
Stefan Lang: And we add at this point a conversation under the heading >>Future Demand<<. Hannes Tronsberg and Christian Reichart are my interlocutors. Future Demand, a platform that should help to promote shows, concerts, or games. Software that allows you to plan months in advance, in effect. Hannes Tronsberg is the founder, Christian Reichert the dramaturge in the venture, which also advises the RSB, which played our evening concert. Is "advise" actually the right word? You can say, Mr. Tronsberg, how concerts are sold out. Is that about right?
Hannes Tronsberg: That absolutely sums it up. We can help figure out who is interested in what event and why. And then also help orchestras and theaters find, reach, and convince more of that audience.
Stefan Lang: That's where we're in the middle of this. Hannes Tronsberg, CEO of Future Demand. We want to explore the question, how can you succeed in bringing targeted audiences to shows or, in our case, to concerts? How can I pursue a targeted audience policy with digital means? Can I use a clever audience survey (we'll see how this should be done in a moment) to say with a fair degree of certainty, not just for the next week, but 24 months in advance, up to which quota an event is fully booked?
Hannes Tronsberg: That's exactly one of our big challenges and also at the same time one of the use cases of our platform and the software. Today, we can predict the occupancy of a concert up to 24 months in advance with 90% to 95% accuracy. That's all based on very many data points and machine learning. And with that, we can actually also help institutions to know well in advance where are perhaps priorities to be set in advertising as well.
Stefan Lang: You need to explain that a little bit more. Where do you get the data? How do you collect the data? Is it targeted surveys? How do you go about doing that?
Hannes Tronsberg: No, we don't rely on audience surveys at all, but we want to find out why an audience or individuals are interested in certain topics. Today, our software can describe a concert with over 1,000 characteristics fully automatically. In the context of a classical symphony concert, this can go as far as the tonality of each piece played or the instrumentation size. And with machine learning, we can then read from this which parameters or which characteristics of a concert have which demand. The amalgamation of that then leads to the fact that afterwards we can give these forecasts so accurately and so far in advance. No keywording of concerts or audience survey is necessary to make this possible. To get all these data points, we access over a hundred external data sources. These can be things like Spotify, but also Google Trends, Wikipedia and special music databases. Or we also collect and describe individual works ourselves, for example.
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The full interview can be listened up here (german only):
