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SDOS took real commercial music data from Chartmetric, aggregating sources such as Spotify, Instagram and Tiktok, on 37 artists, yielding 19,462 data points.
The baseline, of all 37 artists in the sample, showed a 0.11% increase in the number of listeners on Spotify over a 30-day period.
Using its Refinery, SDOS identified five key artists that it predicted to outperform the baseline.
As SDOS predicted, these showed a significant increase in the number of listeners on Spotify over a 30-day period – by a striking 2.59%. This was 2.48 percentage points more than the 0.11% baseline figure, equivalent to 2.9m listeners for the five artists.
This knowledge enables enterprises to tailor advertising strategies to emerging music trends. It shows that the SDOS Refinery can transform music data into predictive commercial intelligence that can improve companies’ profitability.
For example, if SDOS detects that a particular sound or artist cluster is becoming more popular among 18–25-year-olds, a shoe manufacturer could combine SDOS intelligence with its own proprietary information on customers. The additional intelligence layer provided by SDOS supplements the shoe manufacturer’s own dataset and allows it to refine its commercial strategy further with actionable recommendations.
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