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In our work, we often come in contact with radio stations that think they have to maintain excessively large music libraries in order to battle the perception that they repeat the same song too often, and/or think having a giant music library is what’s necessary to convey a better sense of variety.  Our experience in conducting countless auditorium music tests and OMTs vividly shows that these approaches do not actually yield this desired outcome. 

 

It’s consequently encouraging for us to see this finding, and so many great others, reflected in The Economist’s recent special report on mass entertainment:

 

http://www.economist.com/news/special-report/21716467-technology-has-given-billions-people-access-vast-range-entertainment-gady?frsc=dg%7Ca

 

Many of us have read (or at least like to pretend that we’ve read) Chris Anderson’s 2006 classic The Long Tail, and we agree with the author that “the long tail is always there for people with eclectic tastes.”  Nonetheless, as this article points out “it turns out that everyone wants hits.”  Even though the consumer has access to more choices than s/he has ever had before, choices that are specialized to some extremely unique tastes, “people still crave experiences that they can share with others.  What they want most is what everyone else wants.”

 

Music streaming services like Spotify and Pandora are seeing this trend quite vividly as they continue to add more and more users.  The following metrics were particularly interesting to us: “In 2015 the top 1,000 songs were streamed 57bn times in America, accounting for 18.8% of the total volume of streams, according to BuzzAngle Music; last year the top 1,000 songs accounted for 92bn streams, or 23% of the total.”

 

For these music streaming services, suggestion algorithms, which use market research data or what a customer has been known previously to like, have been especially effective in moving a customer out of her/his comfort zone and nudging them toward a particular song or genre.  These tactics are increasingly important in boosting appeal for new music and should be embraced more by the radio industry, in our opinion.  The data is there (we can help you find it) and should be better utilized in creating something akin to Spotify’s “Discover Weekly Playlist,” a playlist of 30 songs (it could be a podcast available on a station’s website or app) that gets refreshed and delivered every Monday.  Spotify has learned that these algorithms help to move people slightly away from hits and expand their horizons.  For those of us in the radio industry, it’s a great way for us to start to “warm up” these new songs in the hope that they will become one of the hits that the masses still crave.