2014-01-27

The results are in, and if you watched the live telecast of the 56th Annual GRAMMY awards last night, you already know who the winners are. But here’s a recap just in case:



Record of the Year: Get Lucky – Daft Punk featuring Pharrell Williams and Nile Rodgers

Album of the Year: Random Access Memories -Daft Punk

Song of the Year: Royals – Joel Little and Ella Yelich O’Connor, songwriters – Lorde

Best New Artist: Macklemore and Ryan Lewis

Best Pop Solo Performance: Royals – Lorde

Best Pop Duo/Group Performance: Get Lucky – Daft Punk featuring Pharrell Williams and Nile Rodgers

Best Rock Album: Celebration Day – Led Zeppelin

Best Rap Album: The Heist – Macklemore and Ryan Lewis

Best Country Album: Same Trailer Different Park – Kacey Musgraves

Check out the full list of winners here.

Did Big Data make the right calls?

 

Last week, SiliconANGLE published some predictions made by different parties, based on advanced analytics that incorporated data from previous years and current social media trends.  So who called the winners last night?

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Spotify

The music service used its streaming data to predict Grammy winners, speculating that Imagine Dragons’ Radioactive will win Record of the Year, Macklemore and Ryan Lewis’ The Heist would win Album of the Year and Best New Artist, Lorde’s Royals as Best Pop Solo Performance. Spotify also predicted that Daft Punk featuring Pharrell Williams and Nile Rodgers; Get Lucky, would win the Best Pop Duo/Group Performance.

Based on the actual winners, Spotify got three right, Best New Artist, Best Pop Solo Performance, and Best Pop Duo/Group Performance.  Last year, Spotify correctly predicted Gotye’s “Somebody That I Used to Know” for ‘Record of the Year’, and Mumford & Sons’ “Babel” for the ‘Album of the Year.’  It seems Spotify listeners are the best source for predicting Grammy winners.

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Bing

Bing looked to its search activity from 2013 to predict that Record of the Year would go to Blurred Lines, and that either Katy Perry or Justin Timberlake would win Best Pop Solo Performance. Microsoft’s search tool also guessed that Taylor Swift would bag this year’s Best Album of the Year award, Macklemore and Ryan Lewis would win Best New Artist this year.  Bing only got one prediction right.

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Shazam

The mobile phone-based music identification service used listeners’ habits to predict that Blurred Lines would be named Record of the Year, The Heist as Album of the Year, Just Give Me a Reason by Pink as Song of the Year, and Macklemore and Ryan Lewis will be named as Best New Artist.  Just like Bing, it only got one of its predictions correct.

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CivicScience and AXS TV

For the first time, CivicScience, creator of iQpoll, and AXS TV aired their Grammy predictions. CivicScience used a proprietary method for predicting the winners, by analyzing results from surveys conducted online among a mix of music enthusiasts and general consumers.

The team predicted the following: Macklemore and Ryan Lewis would win Best New Artist, Blurred Lines – Robin Thicke feat. T.I. and Pharrell for Best Pop Duo/Group Performance, Mechanical Bull – Kings of Leon as Best Rock Album, Royals – Joel Little and Ella Yelich O’Connor, songwriters – Lorde as Song of the Year, The Heist – Macklemore and Ryan Lewis for Best Rap Album and Album of the Year, Red – Taylor Swift as Best Country Album, and Royals – Lorde for Record of the Year.  CivicScience correctly predicted the Song of the Year, Best New Artist, and Best Rap Album.

Analytics methods are not created equal

 

So what did the predictions tell us? Predictions, despite the use of advanced analytics, is not 100 percent accurate.  There are many factors to consider and they don’t necessarily follow the masses. Different consumer groups and web activity are strong indicators of who will win big at the Grammys, but that doesn’t go for all user activity across search and radio streaming.

Nevertheless, it’s fun to see how well or badly these parties did based on their early predictions.  I wonder who will win next year?  Will other parties be inspired to give their predictions using Big Data tactics?  Guess we’ll just have to wait and see.

photo credit: Stephen Sloggett Photography via photopin cc

photo credit: NRK P3 via photopin cc

photo credit: Redfishingboat (Mick O) via photopin cc

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