Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
    data driven insights
    How Data-Driven Insights Are Addressing Gaps in Patient Communication and Equity
    8 Min Read
    pexels pavel danilyuk 8112119
    Data Analytics Is Revolutionizing Medical Credentialing
    8 Min Read
    data and seo
    Maximize SEO Success with Powerful Data Analytics Insights
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Music App Predicting the 2014 Top Artists with Big Data
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Mining > Music App Predicting the 2014 Top Artists with Big Data
Data MiningModelingSocial DataSocial Media Analytics

Music App Predicting the 2014 Top Artists with Big Data

Todd Nevins
Todd Nevins
4 Min Read
Image
SHARE

Image15 million song identifications per day on the song finding app, Shazam, has provided the Big Data needed to predict who will hit and who will miss in the music scene for 2014.

Image15 million song identifications per day on the song finding app, Shazam, has provided the Big Data needed to predict who will hit and who will miss in the music scene for 2014.

Users activate the mobile music app for a few seconds while a song is being played on the radio, TV or even the shopping mall and the app immediately identifies the song and artist. Once the song is identified, the user can tweet or share the results socially, listen to it for free, watch YouTube videos of the performer, check out other songs by the artist and of course, purchase the song on iTunes. Now Shazam is using this data to predict which artists are expected to hit it big next year.

Shazam’s list of “Artists to Watch” and the Big Data behind it successfully predicted Lana del Ray in 2012 and French Montana for 2013. So what is the big deal behind the big data and how does it work? The first variable used is how frequently a song is identified using the app and combining this information with how frequently it was shared socially, emailed, purchased and if users watched YouTube videos of the performer or checked out other songs by the artist. This data is combined with critics’ reviews and added to this is the location data that the app is compiling to not only predict which artists have the best chance of ‘making it’ next year but also what countries, cities or regions it will happen in.

More Read

Image
Where in the World Does All this ESRI World Data Come from?
Can Real-Time Social Analytics Provide Early Indications of Business Results
San Diego Forum on Analytics — review
Electronic Substitution in the New Economy
Predictive Analytic Strategies to Out-Predict the Competition

Adding social data, location data mobile data and consumer behavior data with positive and negative criticism from the heavyweight industry critics has allowed Shazam to compile the latest list of who to watch out for next year.

The list of who is gaining traction via Shazam’s Big Data:

  • Action Bronson – released first album in 2011 and gained traction through mix tapes in 2013.
  • August Alsina – one of the most Shazamed rap songs of 2013.
  • Banks – released an acclaimed EP in 2013.
  • Jhené Aiko – collaborations with Drake and Big Sean in 2013 is launching her career.
  • Kid Ink – set to release his first major label album next year.
  • Lucy Hale – set to be the next country star after her role in ABC Family series, Pretty Little Liars.
  • Martin Garrix – a Dutch DJ and youngest person to top the Beatport charts.
  • Rich Homie Quan – named by the New York Times as one of “Atlanta’s rising generation of rappers.”
  • Sam Smith – soul artist born in London with contributions to two hits in 2013.
  • Vancy Joy – already achieving success in his home country of Australia, set to hit globally in 2014.

Check out the top Shazamed Songs of 2013.

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

image fx (2)
Monitoring Data Without Turning into Big Brother
Big Data Exclusive
image fx (71)
The Power of AI for Personalization in Email
Artificial Intelligence Exclusive Marketing
image fx (67)
Improving LinkedIn Ad Strategies with Data Analytics
Analytics Big Data Exclusive Software
big data and remote work
Data Helps Speech-Language Pathologists Deliver Better Results
Analytics Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Image
Big DataBusiness IntelligenceCRMSocial Data

Big Data’s Athletic Moment: Turning Sporting Arenas into Preferred Business Venues

6 Min Read

SmartData Collective

2 Min Read

R: From zero to Web 2.0 in six weeks

3 Min Read

Keep Off My Big Data

4 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?