Exploitation Mode uses statistical modeling and machine learning to predict what music listeners will enjoy. It allows you to heart and skips tracks, creating a personal profile based on your ratings and listening behavior. It also analyzes your past behavior and suggests new artists for you to listen to — sometimes even before they become popular. In other words, it considers what you like and what other users who share similar taste in music do, then tries to find music that you might like based on that information.
In exploration mode, users are given random music recommendations based on their tastes. This mode is excellent for helping you discover new genres or artists that you might have overlooked before. If you're planning to check out a specific festival, for example, BaRT will help ensure that your set-list will be full of unfamiliar tunes that go along with that genre or vibe. Exploration mode provides variety and exposure to new music—while considering things like artist similarity—so it can boost both your long-term listening pleasure and short-term satisfaction. It gives you just enough exposure to ensure that you'll try something new without overwhelming your sense of discovery and personal taste.
BaRT is a system that manages and predicts our interests and influences our experience with music. I t depends on two basic parameters: The first one is time because listening habits can change from one day to another. In other words, yesterday I was a big fan of electronic music, but today I'm listening to hip-hop more than anything else. The second parameter is artist because if I have liked a lot a band, it doesn't mean that I will continue liking them forever. Today's artists can become tomorrow's never heard again, just as by other artists who could be a real treasure for us. BaRT predicts these future changes according to what we've done in the past. You could love Dua Lipa today and decide to stop listening to her in a few weeks. That’s why tracking what is happening with your audience on music streaming platforms is crucial today.