Music is intrinsic to human culture. And so, many of our commercial musical decisions are rooted in emotion and instinct. Yet only a few possess the uncanny insight and experience to make good decisions with these tools alone.
For most of us, making broad assumptions without data to back them up can result in devastatingly poor choices.
This is a thought experiment and early-stage model of a rational decision-making tool for independent artists, labels, and promoters. You should read on if you feel you might profit from a deeper understanding of the markets you wish to enter and dominate.
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How to interpret the match scores:
The match scores have a theoretical maximum of "1.0", but in order to get that, a song must display every single tag and preference that shows up for a country, but that is impossible. In general, a match score above 0.4 is notable, above 0.5 is great, and above 0.6/0.7 is extremely high.
"Serendipity" by Lewloh feat. Julia Gartha
Serendipity has a high country match score (53%) with Thailand. It scored highly in a range of tag categories including Genre, Mood, Influences, Energy, and Key.
Though it received a 134BPM Tempo tag, Serendipity is clearly in "half-time". This gives it an actual pulse of 67BPM, which is well within the preferred range in Thailand.
Its "Sounds Like Female" tag despite having both male and female vocals may be due to the heavy presence of male falsetto and head voice.
For more insights, including all tag/country data, which song from Thailand's Viral Top 20 it sounds most like, and how Serendipity can get an even higher match score with Thailand, download the white paper for free!
"Let You Down" by Gareth Fernandez
Let You Down demonstrates a fairly high 0.47 combined match score with Indonesia. The strongest tags are Genre, Influences, Mood, and Vocal.
The "Sounds Like Male and Female" tag despite having only male vocals was possibly due to the heavy presence of high falsetto in addition to low chest voice.
For more insights, including all tag/country data, which song from Indonesia's Viral Top 20 it sounds most like, and how Let You Down can get an even higher match score with Indonesia, download the white paper for free!
"i'm fine, no" by Shye
The last song we are analyzing has yet to be released by the label, so it will not be available for listening. But feel free to refer back to the white paper when the song is released to see if we hit the mark!
This song matches best with Vietnam, with a 0.47 combined match score. Next is Malaysia, following closely at 0.42.
For more insights, including all tag/country data, which songs from Vietnam and Malaysia's respective Viral Top 20 charts it sounds most like, and why Malaysia is a better bet even though it scored lower than Vietnam, download the white paper for free!
Applying the metadata and tags in this manner of analysis is the future. Beyond being adopted by A&R professionals, I see this methodology being especially useful to publishing houses, or even music export offices. A perfect example of how we can utilise music tech to better our craft.
David Siow, President of SGMUSO
When you’re running an indie label, we’re close to the ground but also constrained by our reach. This kind of information can give us a preliminary gauge as to how we should approach a new market, or grow an artist’s existing audience in a particular country.
Tan Peng Sing, Owner of the music label "Where Are The Fruits"
Let's be clear: human beings make these calls.
It is extremely difficult to replace years of experience, artistic sensibility, and all the other skills that go into accurately selecting artists and music for release in specific markets.
The most experienced and successful A&R executives from established and independent record labels are already formidable curators. Independent artists, by necessity, are incredible at making strategic decisions to make use of their limited resources.
Just imagine what they could do if they had help.