Original article published on VentureBeat (03/26/18) by Enrique Cadena Marin

The music industry is using artificial intelligence (AI) to transform its marketing model by applying it to consumer data sorted via machine learning, offering improved insights to harmonize artists with the industry and fans while keeping profits to a maximum. One area of AI development is audience engagement metrics that gauge how audiences respond to new music genres, trends, artists, and songs. Industry professionals can use this data to increase visibility for their signed artists and reach more fans. Music labels also can target audiences and track patterns to inform business decisions and stimulate revenue. Furthermore, data filtering can be a marketing advantage that spurs subscriber growth and better design of outreach initiatives and content to fuel competition. Meanwhile, YouTube and recommendation engines are bettering matches between listeners and artists, with industry professionals leveraging the underlying AI to promote artists through raw engagement data from streaming platforms. In addition, AI algorithms can help industry professionals rate the competition by analyzing the social and streaming patterns of artists and rival labels, while applying the same analysis to listeners' behavior patterns can enable identification of consistently profitable superfans.

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