What Taylor Swift Means to Big Data
A recent article in Forbes explored the connection between Big Data and changes in the music industry…
Common knowledge just a few short years ago is that the Internet was slowly strangling the music industry. The more access users had to different music, the less control the music industry could exert. This mindset led to the slow evolution of the music industry to changing technology.
Most in the industry reacted to streaming, online sales and digital downloads with the same sort of militant horror peasants employed in response to Frankenstein’s monster. They feared losing cash and losing control. They feared the devolution of a control-based economy they loved.
But consumers were not having it. They simply pirated the music. Music piracy online became so pervasive, some bands even encouraged the practice. Finally, the industry bent enough to allow iTunes to soar. Other competitors entered the digital download arena, and all was right with the world.
Then streaming dropped a bomb on the entire industry. While music companies saw the potential to make more money and regain some lost control, artists saw shrinking revenue streams. As the new technology evolved, and with the incidental help of megastars such as Taylor Swift, both the music industry and music makers found a way to coexist in the new digital age … and to cash in on it.
But how did Big Data make that possible? Think about how streaming works. When a consumer chooses a specific artist or genre to stream, data engines begin assembling a custom playlist build around specific criteria established by Big Data algorithms informed by that user’s personal choices.
Big Data also helps the music industry understand what consumers want … and which ones want what music. In the olden golden days, music was purchased and consumed. Success was judged by units sold, but music executives didn’t know who was buying what records, or why. They just knew what was being sold and how often.
With Big Data, though, everyone can know who is buying what, when and how often. Individual tastes and demographic trends can be closely monitored, and sellers adjust accordingly. When a user is in the mood for a certain kind of music, Big Data engines make it possible for music producers to introduce that user to new artists in that genre. Suddenly, the consumer has more potential choices, and might have a new favorite band, while retailers sell more, bands connect to new fans without their direct input.
Think about it. In the old days, if you wanted to learn about a new band, you either had to hear about it from a friend or hear them in concert. Now, you can meet them through whatever means you use to stream the music you already love. Thanks to Big Data, you may never miss out on Your Next Favorite Band again. Better still, you can shut the stuff you hate out of your life forever.
Gennady Barsky is a real estate mogul from NYC.