This is great if you want to save on mobile data or don’t always have your laptop or phone connected to the internet while you work. One of the best features of the premium account is that you can download tracks for offline listening in both the mobile and desktop apps. Basically, you can listen to whatever music you want without any limitations in either the desktop or mobile apps. You can also listen to any track, album, artist, or playlist you like at any time in any order with unlimited skips. You can listen to as much music as you want and you’ll never get interrupted by an ad. The main thing you get with any Premium plan is an entirely ad free experience. Student: One account for $4.99 per month (must prove you attend an accredited higher education institution).Family: Up to six accounts for $15.99 per month.Duo: Two accounts for $12.99 per month.Individual: One account for $9.99 per month.Spotify Premium consists of four different plans (pricing as of August 2022): RELATED: How to Subscribe to Podcasts on Spotify What You Get With Spotify Premium That includes the ability to download them for offline listening. You can’t select a specific track to play and you are also limited to skipping six tracks per hour.įree users also get the same access to Spotify podcasts as Premium subscribers. Outside of the “Made for You” personalized playlists chosen by Spotify, you can only listen to playlists, albums, or artists on shuffle.
Spotify’s curated playlists like RapCaviar (the hottest rap and hip hop tracks) and Ultimate Indie (the best new and upcoming indie tracks).Release Radar (new tracks from artists you listen to or Spotify thinks you’ll like).Daily Mix (a mix of your favorite tracks and ones you haven’t heard that Spotify thinks you’ll like).Discover Weekly (a weekly selection of tracks Spotify thinks you’ll like).When using the mobile app with a free account, you can listen to any songs in any order with unlimited track skips as long as it appears on one of the personalized playlists made for you by Spotify’s machine learning algorithms.
0 kommentar(er)
