Traktomizer was created by me, Music Producer and Software Engineer, Steven (Lipschitz) Freedom. The project has been in constant development since early 2014.
I had read that my playlist was being influenced by a robot, which seemed rather vulgar! On deeper investigation my final understanding is that in the absence of music recommendation algorithms (I call Recommendabots), less than 5% of available online music is actually visible, let alone played.
As a music-maker I had to know how Recommendabots were making choices and why [they] would or would not choose to promote the songs I publish, whether independently or via the record label to which I am signed. The result of that question is Traktomizer Audio Analyser, which took around 18 months to program, including 6 months of researching the technologies in use by platforms like Spotify, Deezer, Rdio, Apple Music, Google Music, Pandora, etc. (You can view much of my research here https://traktomizer.com/learning-resources and pinned here http://pinterest.com/traktomizer).
I was an early adopter and evangelist of SEO and ranked #11 on SEOmoz.org back in 2008 (with my profile: ‘Klikhir‘). Passionate about music (since forever), I studied violin, guitar, bass-guitar and piano from the age of 7 and finished formal studies with Jazz and African Musicology at the University of Cape Town. During a superlative 4 year music tour I started back in 2009, playing mostly in Berlin, Paris, Stockholm, Sydney, Delhi and Cape Town, I had also became frustrated hearing my musician and DJ friends unending complaints about the new perils of making a living in music – and I wondered how I might use my software development skills to help!
Eventually I set everything aside to create Traktomizer, the only program that leverages music subscription platform recommendation algorithm calibrations for the benefit of the artists – offering them powerful audio analytics and suggestions about improving the audio features of any song, which is achieved with reference to and in consideration of the very methodologies, standards and lessons invented by and learned from The EchoNest, the Labrosa Million Song Dataset, the top music information retrieval APIs and music aggregators such as Spotify, Billboard and Next Big Sound, hundreds of white papers and articles and 50 years of research conducted by some 30 000+ Ph.D’s, music institutes, practitioners, learning and education centres and enthusiasts.
Traktomizer takes a look at music through the subscription music platform lens in order to inform artists about how their imminent publication is likely going to be indexed, auto-promoted and or shelved, thus securing its place in professional music production studios by providing accurate insights into how song-suggesting algorithms (employed by services like Spotify to auto-generate and auto-update millions of playlists) are likely to deal with their publications.
With these insights artists are able to optimise critical audio features in advance of publishing, thereby rendering their published works with a predisposition for maximum choice-worthiness and auto-playlist-selection and play-suggestions, which is tantamount to implementing Search Engine Optimisations (SEO) to achieve the highest possible organic search result rankings. Optimisations are implemented by and at the discretion of the artist and may be achieved without impinging on artistic freedoms.
Steve Freedom was ranked No.1 in Electronica on Reverbnation.com Berlin during 2011. From 2008-2010 Steve made the No.1 spot on the Soundclick.com charts nine times. Currently he spends most of his time working on and improving Traktomizer.
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