How Many Music Streams Does it Take to Earn a Dollar? - Visual Capitalist
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How Many Music Streams Does it Take to Earn a Dollar?

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Music Streams to Earn a Dollar

How Many Music Streams Does it Take to Earn a Dollar?

A decade ago, the music industry was headed for a protracted fade-out.

The disruptive effects of peer-to-peer file sharing had slashed music revenues in half, casting serious doubts over the future of the industry.

Ringtones provided a brief earnings bump, but it was the growing popularity of premium streaming services that proved to be the savior of record labels and artists. For the first time since the mid-90s, the music industry saw back-to-back years of growth, and revenues grew a brisk 12% in 2018 – nearly reaching $10 billion. In short, people showed they were still willing to pay for music.

Although most forecasts show streaming services like Spotify and Apple Music contributing an increasingly large share of revenue going forward, recent data from The Trichordist reveals that these services pay out wildly different rates per stream.

Note: Due to the lack of publicly available data, calculating payouts from streaming services is not an exact science. This data set is based on revenue from an indie label with a ~150 album catalogue generating over 115 million streams.

Full Stream Ahead

One would expect streaming services to have fairly similar payout rates every time a track is played, but this is not the case. In reality, the streaming rates of major players in the market – which have very similar catalogs – are all over the map. Below is a full breakdown of how many streams it takes to earn a dollar on various platforms:

Streaming serviceAvg. payout per stream# of streams to earn one dollar# of streams to earn minimum wage*
Napster$0.0195377,474
Tidal$0.012580117,760
Apple Music$0.00735136200,272
Google Play Music$0.00676147217,751
Deezer$0.0064156230,000
Spotify$0.00437229336,842
Amazon$0.00402249366,169
Pandora**$0.001337521,106,767
YouTube$0.000691,4492,133,333

*U.S. monthly minimum wage of $1,472 **Premium tier

Napster, once public enemy number one in the music business, has some of the most generous streaming rates in the industry. On the downside, the brand currently has a market share of less than 1%, so getting a high volume of plays on an album isn’t likely to happen for most artists.

On the flip side of the equation, YouTube has the highest number of plays per song, but the lowest payout per stream by far. It takes almost 1,500 plays to earn a single dollar on the Google-owned video platform.

Spotify, which is now the biggest player in the streaming market, is on the mid-to-low end of the compensation spectrum.

The Payment Pipeline

How do companies like Spotify calculate the amount paid out to license holders? Here’s a look at their payout process:

artist spotify streaming payouts

As this chart reveals, dollars earned from streaming still don’t tell the full story of how much artists receive at the end of the line. This amount is influenced by whether or not the performer has a record deal, and if other contributors have a stake in the recorded work.

The Pressure is Heating Up

When Spotify was a scrappy startup providing a much needed revenue stream to the music industry, labels were temporarily willing to accept lower streaming rates.

But now that Spotify is a public company, and tech giants like Apple and Amazon are in the picture, a growing chorus of industry players will likely dial up the pressure to increase compensation rates.

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Infographic: Generative AI Explained by AI

What exactly is generative AI and how does it work? This infographic, created using generative AI tools such as Midjourney and ChatGPT, explains it all.

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Generative AI Explained by AI

After years of research, it appears that artificial intelligence (AI) is reaching a sort of tipping point, capturing the imaginations of everyone from students saving time on their essay writing to leaders at the world’s largest tech companies. Excitement is building around the possibilities that AI tools unlock, but what exactly these tools are capable of and how they work is still not widely understood.

We could write about this in detail, but given how advanced tools like ChatGPT have become, it only seems right to see what generative AI has to say about itself.

Everything in the infographic above – from illustrations and icons to the text descriptions⁠—was created using generative AI tools such as Midjourney. Everything that follows in this article was generated using ChatGPT based on specific prompts.

Without further ado, generative AI as explained by generative AI.

Generative AI: An Introduction

Generative AI refers to a category of artificial intelligence (AI) algorithms that generate new outputs based on the data they have been trained on. Unlike traditional AI systems that are designed to recognize patterns and make predictions, generative AI creates new content in the form of images, text, audio, and more.

Generative AI uses a type of deep learning called generative adversarial networks (GANs) to create new content. A GAN consists of two neural networks: a generator that creates new data and a discriminator that evaluates the data. The generator and discriminator work together, with the generator improving its outputs based on the feedback it receives from the discriminator until it generates content that is indistinguishable from real data.

Generative AI has a wide range of applications, including:

  • Images: Generative AI can create new images based on existing ones, such as creating a new portrait based on a person’s face or a new landscape based on existing scenery
  • Text: Generative AI can be used to write news articles, poetry, and even scripts. It can also be used to translate text from one language to another
  • Audio: Generative AI can generate new music tracks, sound effects, and even voice acting

Disrupting Industries

People have concerns that generative AI and automation will lead to job displacement and unemployment, as machines become capable of performing tasks that were previously done by humans. They worry that the increasing use of AI will lead to a shrinking job market, particularly in industries such as manufacturing, customer service, and data entry.

Generative AI has the potential to disrupt several industries, including:

  • Advertising: Generative AI can create new advertisements based on existing ones, making it easier for companies to reach new audiences
  • Art and Design: Generative AI can help artists and designers create new works by generating new ideas and concepts
  • Entertainment: Generative AI can create new video games, movies, and TV shows, making it easier for content creators to reach new audiences

Overall, while there are valid concerns about the impact of AI on the job market, there are also many potential benefits that could positively impact workers and the economy.

In the short term, generative AI tools can have positive impacts on the job market as well. For example, AI can automate repetitive and time-consuming tasks, and help humans make faster and more informed decisions by processing and analyzing large amounts of data. AI tools can free up time for humans to focus on more creative and value-adding work.

How This Article Was Created

This article was created using a language model AI trained by OpenAI. The AI was trained on a large dataset of text and was able to generate a new article based on the prompt given. In simple terms, the AI was fed information about what to write about and then generated the article based on that information.

In conclusion, generative AI is a powerful tool that has the potential to revolutionize several industries. With its ability to create new content based on existing data, generative AI has the potential to change the way we create and consume content in the future.

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