Being present on a platform is not the same as being visible on it. Recommendation systems decide which artists get surfaced, to whom, and how far their music travels, and the logic behind those decisions stays largely opaque to the people whose careers depend on it.

In 2024, APEM brought a deliberately simple question to Music Tomorrow: does Spotify treat French-language repertoire the same way in France as it does in Canada and Québec? Answering it meant building comparable, defensible indicators of algorithmic positioning and visibility, measured in the same week, on the same charts, with the same model, in both markets.

This case study walks through the method, the four repertoire groups compared, and what the results say about how local music circulates inside a recommendation system. It was written for cultural institutions, publishers and policy teams who need evidence rather than assumptions.

Download the full study for the market-by-market results and the complete methodology.