By: Patrick Keenaghan, Media Analytics Executive
The growth of streaming platforms has completely transformed how media consumers interact with their content. In fact, audiences have greater autonomy now than ever before.
Think back to the pre-internet age. Media consumers used to be limited to the shows or movies broadcasted on TV and the songs played on the radio; they did not have a choice in their media.
Contrastingly, now, audiences decide on every piece of media they consume. Whatever you want, you can have. At face value, this independence seems perfect. However, at a certain point, too many options can be overwhelming.
In this world of absolutely infinite content, media consumers need some way of weaving through the limitless possibilities at their fingertips. Recommendation engines have been incorporated on social media and streaming platforms as a way to guide consumers through the jungle of content.
Recommendation systems usually take the form of suggested playlists of what is currently popular. The idea is that if other people like it, then you probably will.
This concept is the reason behind Netflix’s “Top 10 in the U.S.” or Spotify’s “Today’s Top Hits.” Even on apps like Instagram and TikTok, specific content is pushed onto users’ screens. Indeed, algorithms are becoming increasingly more influential in deciding what is shared and talked about.
These suggested playlists greatly help consumers navigate their abundant options. However, what about content producers? How can niche producers get the exposure necessary to grow?
A study done by University of Pennsylvania researchers found that since recommendation systems favor what is already popular, they are unable to surface any truly novel content.
This becomes extremely problematic. Producers may look at what is popular and try to replicate it, thinking that is their route to success. Here, a paradox begins.. If multiple producers are all generating similar content, is there really “infinite” content for consumers? Content will continuously get more and more identical.
The only way to break out of this cycle would be to create distinct niche content. However, with that course, producers run the risk of getting left behind by the algorithm.
As you can see, content producers are caught between a rock and a hard place in this new media age. Content consumers are not too much better off. They are unaware that their media consumption is not as personalized as they think.
In conclusion, recommendation systems are necessary in helping consumers navigate the content world which sees new items generated rapidly. However, suggested content can be unfair to certain producers who do not receive the same recognition as others. Lastly, in the fight over consumers’ attention, producers may create similar content which ultimately leads to a smaller and limited field of content.