Grammy performances yield 480% sales gain for artists

Songs performed at Saturday’s 61st Grammy Awards by Lady Gaga, Kacey Musgraves, Bradi Carlile, H.E.R. and others, collectively contributed to a 480% increase in digital download sales, according to Nielsen Music.

The songs performed at the awards ceremony, including H.E.R.’s ‘Hard Place’ (up 102,000%), Kacey Musgraves’ ‘Rainbow’ (up 9,430%), Brandi Carlile’s ‘The Joke’ (up 2,771%) and Lady Gaga and Bradley Cooper’s ‘Shallow’ (up 229%), collectively sold 71,000 downloads on the day of the show, 12,000 more than on the day before the awards.

‘Shallow’, winner of best pop duo/ group performance, was the biggest seller of all Grammy-performed songs, selling 14,000 downloads on the day of the awards. The song lost out to Childish Gambino’s ‘This is America’ in the record of the year category, a win predicted by artificial intelligence platform, DataRobot.

Musgraves’ Golden Hour, winner of album of the year and best country album at the Grammys, also saw a vast increase in sales, selling over 3,000 copies on Saturday, up from less than 1,000.

Songs performed at the awards ceremony collectively sold 71,000 downloads on the day of the show, 12,000 more than the day before

Songs featuring in a Dolly Parton tribute performed by Musgraves, Katy Perry, Miley Cyrus and Parton herself, among others, also registered sales increases. The original Parton versions of the five songs performed in the medley sold 6,000 downloads collectively, up 718% in comparison to the previous day’s 1,000 downloads.

The sum includes Parton’s renditions of ‘Here You Come Again’, ‘Jolene’, ‘Red Shoes’ and ‘9 to 5’, along with her version of Neil Young’s ‘After the Gold Rush’.

This year’s Grammy Awards, held at Staples Center in Los Angeles, saw other notable performances from awards host Alicia Keys, Janelle Monae, Shawn Mendes, Cardi B, and St Vincent and Dua Lipa, winner of best new artist.

See the full list of winners at the Recording Academy website.

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AI correctly predicts Grammys 2019 song of the year

American data scientists correctly predicted Childish Gambino’s song of the year win at the 61st Grammy Awards, held at Staples Center in Los Angeles last night (10 February).

Using its machine learning platform, Boston, Massachusetts-based DataRobot analysed all Grammy song of the year winners since 1959, identifying common traits – including the genre of the song, amount of profanity, general sentiment, total word count and various audio features derived from Spotify, such as tempo, time signature, key and duration – to determine this year’s most likely victor.

After six minutes, during which the artificial intelligence (AI) generated 140 data models, DataRobot’s Taylor Larkins established the best model, which “performed about 44% better than randomly guessing during my testing period [from 2012–2018],” he explains.

“Machine learning … can have applications well beyond the traditional ones we are used to seeing in fields such as banking or insurance”

This model correctly predicted Gambino’s ‘This is America’ as most likely song of the year candidate, with Lady Gaga and Bradley Cooper’s ‘Shallow’, from A Star is Born, as a close runner-up (screenshot courtesy of DataRobot):

“With this experiment, we’re demonstrating that machine learning cannot only be fun but can also have applications well beyond the traditional ones we are used to seeing in fields such as banking or insurance,” explains Larkin.

“The music industry could tap into its potential, studying what makes a song successful and understanding why people listen to the songs that they do. With the volume of great music being produced, having quick insights into song popularity could be another tool to help musicians and music producers to refine their expertise.”

Kacey Musgraves won the Grammy for album of the year, for Golden Hour, with Dua Lipa taking home the prize for best new artist. Gaga and Cooper’s ‘Shallow’, meanwhile, won best pop duo/group performance.

See the full list of winners at the Recording Academy website.

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