In my first Medium story I want to share my experience so far working with music, design and technology. I was impressed by the lack of information and enterprise solutions available for the industry — this showed an area for design impact — and motivated me to join a multidisciplinary team building an ecosystem for the music space.
My role — with an analytics app — focused on contributing with human-centered methods & design thinking as to bring the users needs to the core of the creation and development process, while using new technologies to enable access, consumption tracking, transparency and more.
The music industry landscape has been slowly shifting towards new technologies like deep data analysis, Ai, decentralized databases and machine learning with the vision of improving an industry – that has largely been unchanged in the bigger picture.
Today the use of machine intelligence and the possibilities of analyzing and interpreting large sets of data is a practice that most companies are embracing and exploring; in order to deliver better products and more personal and unique user experiences.
The digital- and tech-space surrounding the music industry is constantly changing and impacting every stakeholder in the value chain – from artists to fans. Tons of data and disperse information are being generated daily by social media and streaming services which represents a need for new tools and apps that can make sense out of all of it.
“If I’m going to pay one tech company to make sense of the mess created by another tech company, I need real results.”
— Jeff Bacon. Artist, Manager & Industry Expert
Each social media platform and DSP has unique features, methods of measurement, interaction and data collection. For instance, Facebook and Youtube are completely different platforms with different features and purposes. However studying the possibilities of the data collected from each platform, and showing cause and effect between platforms could draw new and valuable insights for users and also businesses.
With the right information and know-how’s, these tools can be very powerful and used in synergy to maximize efforts and resource allocation for touring, merchandise, marketing and many other possibilities. Visualizing an artist performance in a central hub is needed in order to guide users through complex systems and information overload.
Currently artist are in the position to spend valuable time learning how each one of these tools work and how their music is being consumed and tracked – all while losing time for what they do best, creating music.
Streaming services are increasingly generating more revenue and relevance in the music industry, so how does this change the economical landscape for musicians? What if some users are less tech-savvy than others? How does social media impact DSP performance, and ultimately revenue streams?
“There’s a learning curve with each major DSP’s “artist marketing” platform and their individual features are continually evolving. So if you’re an artist managing your own digital marketing and fan engagement campaigns and strategy, you will be spending a lot of time teaching yourself how each artist platform works. These are basically the back end of a consumer facing DSP”.
Machine intelligence and artificial intelligence can gather large amounts of data and interpret crucial data points to draw conclusions; considering specific roles(composer, songwriter, performer, manager, etc); royalty splits; inform touring; licenses; brand association and more. Most importantly though, open channels for artist-to-fan communication, enabling end to end benefits from artists and creators to fans and everyone else involved in the value chain.
From a designer’s point of view this represents a huge opportunity to have an impact applying design thinking methods and user centric design to humanize new technologies and new products.