Spotify's growth loop is bloody brilliant. It's also cloneable.

First of all, if you didn't know, Spotify breaks their entire catalog of over 100 million songs into over 6,000 genres (Some of their genres are downright goofy like "Bedroom Pop," "Escape Room," and "Yacht Rock"), but these genres are the keys to Spotify's growth loop.

Here's how it works:

Every time you listen to a song on Spotify, you're doing a few different things —

1. Obviously, you're showing Spotify what you like to listen to, and the finer Spotify can understand your preferences (through these more specific genres), the better they can recommend you songs, events, content, and even ads that you'll enjoy. ("Rock" could mean anything from The Eagles to Vanessa Carlton...that's why these 'microgenres' are necessary.)

2. Secondly, your listening is informing Spotify on larger trends. Broadly speaking, you're teaching Spotify that "people who like X, also tend to like Y," but you're also teaching Spotify sequences —

   • For example, "People who listened to genres A, B, and C tended to listen to genre D next."

   • ...or things like "people who generally listen to genre X and Y during the week tend to listen to genre Z on the weekends."

   • ...or even things like "Genre B only tends to be popular for X number of weeks."

Once you have the genres...or the *tags* as they're commonly called... your opportunities for learning are virtually limitless. That's how Spotify is able to consistently nail the user experience for each individual user.

So, how do you implement this in your own product?

1. Tag everything you can (messages, products, etc.) as specifically as you can. The dress isn't just "blue". It's "blue, formal, strapless, evening gown, silk, cocktail party, flirty, light, sporty,..." As many meaningful tags as you can apply.

2. Use an agentic system that's able to dynamically update your product and user experience at the individual level based on the interactions users have with their content.

Spotify's data growth loop is smart, but you don't need a massive data science/marketing team to implement it for yourself. We're implementing this for apps every day with Aampe.