How the Music Industry is Getting Smarter

As I watched the Grammy Awards last month, I was taken in by the varied performances from the likes of Annie Lennox, Pharrell, Beyoncé, and newcomer Sam Smith. It occurred to me that while music is the tie that binds them all, Big Data—and Fast Data in particular—is what sets them apart. Fast Data has changed the music industry in incredible ways. How we discover music, listen to artists, and buy their music has changed immeasurably due to the real-time analysis of data. Here’s a look at how Fast Data is transforming the music industry.

Stay With Me

Do you remember the last time you were at a restaurant or bar and just could not remember the name of the song playing on the radio? Your friend pulls out his phone, turns on the app Shazam, waits a few seconds, and voila… “I knew that was Another Star by Stevie Wonder!” Except you didn’t—at least not until Shazam reminded you via its acoustic algorithm, which it then matched against a vast database of songs. While primarily known for its music identification capabilities, Shazam is much more than a fun party trick. It’s Fast Data.

With 100 million monthly users and more than 15 billion Shazams, the company has a wealth of information it can use to analyze music preference around the globe, in addition to narrowing down song plays by city and genre. The tool informs the music industry of the songs people find most interesting, which gives music executives and talent scouts a look into the future hits around the world.

For instance, at the end of 2013, Shazam released its predictions for top artists in 2014. One of the artists listed was Sam Smith, the crooner who swept away this year’s Grammys with four wins, including Record of the Year. If you heard Stay With Me on the radio and Shazamed the song, you’d be prompted to buy it through iTunes or Google Play. You could also take a look at charts in the app, mapping the top 10 songs in the U.S., worldwide, by genre, and future hits, determined by Shazams geotagged in your phone and recorded by the company. This information changes the way you listen to music, prompting you to—in real time—discover newly popular and famous artists.

Without Shazam’s Fast Data approach to music curation, it’s likely Beyoncé would have walked home with more Grammys, and we would never have heard of Sam Smith.

Because I’m Happy

If you ask anyone if they’ve heard the song Happy by Pharrell, the majority of the people will say an emphatic “yes,” whether it makes them happy or not. The song’s massive popularity (more than 550 million YouTube views and counting) was not always the case. When the song first came out with the soundtrack to Despicable Me 2, it wasn’t a hit and radio stations weren’t interested in the song. That’s when Pharrell’s team got innovative, disruptive even, and created the first-ever 24-hour music video to accompany the song.

Pharrell enlisted the help of Gupta Media (which also boasts Taylor Swift, Sam Smith, Jay-Z, Beyoncé, Lady Gaga, and Katy Perry as clients), a company that uses targeted advertisements in real time to encourage fans to listen to and purchase music on multiple channels by reaching millions of fans through search results, social media, and previous buying habits.

Say you heard about the new Happy video while browsing Twitter in November of 2013. You watched the video on YouTube, signed up for Pharrell’s newsletter and liked him on Facebook. A few months later, you watched him perform with Daft Punk at the 2014 Grammys (incidentally, this is when the Google search “Pharrell Happy” had the highest number of searches) and got a targeted alert on Facebook that Pharrell won four Grammys, including a link for you to buy Get Lucky. When Happy was set to be re-released on his new album, G I R L, you received an email with a special pre-order offer.

In all of those actions, and in anticipation of these events, Gupta Media was ready with a deeply researched digital media campaign for fans who have showed intent (i.e., website visits, newsletter subscriptions, previous purchases, YouTube shares, comments and likes, as well as follows on Twitter and likes on Facebook). With so many fans, this targeted and real-time advertising facilitates higher odds of discovery (and purchase) of an artist’s music.

Case in point: after the creation of the 24-hour video, sales of Happy went from 100,000 copies sold to more than 11 million worldwide. As of this past summer, the song became only the fourth single to go triple platinum in the UK in the past 20 years. His album, G I R L, won the Grammy award for Best Urban Music Album. Combining the YouTube views with views on 24hoursofhappy.com, Happy has seen at least one billion views. The accolades go on. But, without the mechanisms of Fast Data at play with advertising, sales would never have looked like this and Happy wouldn’t have been the top of the Billboard 100 for 10 weeks straight.

Teenage Dream

Big Data has also led to the success of music streaming companies like Spotify, Songza, MusicMetric, and Rhythm. Without it, these companies wouldn’t exist. Spotify, in particular, has paved its way to the top of the list via a Fast Data approach that delivers unique insights into its customers, songs, and artists. Being active in more than 58 countries, boasting over six million paying subscribers, offering 1.5 billion playlists, and more than 20 million songs, Spotify produces an estimated 1.5 terabytes of compressed data daily. It also has one of the largest Hadoop clusters in Europe, with close to 700 heterogeneous nodes running approximately 7,000 jobs per day.

How Spotify uses Hadoop is really the key piece to its success. Beyond predicting this year’s Grammy winners with 67 percent accuracy, and explaining the shooting popularity of Aerosmith’s I Don’t Want to Miss a Thing from the Armageddon soundtrack because an actual comet came close to Earth, Spotify helps executives make future business decisions.

Let’s take Katy Perry, for example. Her concert promoter is scheduling her world tour and it has to be a bigger, better success than ever before. She’ll look into which cities stream Perry’s songs the most, in addition to information from other companies looking at thousands of data signals (from tweets, Facebook shares, Instagram likes, etc.) to decide that (hypothetically) São Paulo is a better choice than Buenos Aires, translating into higher revenue and more satisfied fans.

The decision to choose Katy Perry to headline the halftime show at the XLIX Super Bowl this year was certainly made with data indicating her visibility and popularity in the world—such as her 65 million followers on Twitter. In fact, this year Pepsi and ShopTV sent out tweets with links to buy merchandise related to the halftime show, giving customers the option to buy directly from connected TVs, social media, and mobile apps, allowing these sponsoring companies to also take advantage of an in-the-moment opportunity, aka Fast Data.

Fast Data has brought real-time insight into listener and fan data to the benefit of consumers, artists, and music industry executives. Without these tools, we wouldn’t have discovered artists like Sam Smith or rediscovered artists like Pharrell. So, the next time you’re skipping along to the song Happy, give a little nod of thanks to Fast Data.