Epidemic Sound, a subscription service that provides backing tracks for YouTube creators to orchestrate their videos, has launched a new tool to help make the song selection process a little bit more seamless.
The Stockholm-based firm unveiled today a machine learning-powered ‘Music Recommender’ that services song suggestions based on the content of a creator’s most recently-published videos. The Music Recommender furnishes five track recommendations at a time — which can be instantly refreshed by users — from the Epidemic Sound library comprising songs that have been used in other, similar videos, the company says, as determined by its machine learning tech.
Epidemic says that videos containing its songs are viewed 1.5 billion times on YouTube every day — and it is harnessing learnings from this vast pool of usership to help fuel suggestions. The suggestions will appear users’ landing pages, and will auto-refresh every 24 hours.
Subscribe for daily Tubefilter Top Stories
“We know what the internet sounds like,” Epidemic co-founder and CEO Oscar Höglund said in a statement. “We’re humbled to be in a position where there are millions of YouTube channels out there using Epidemic Sound music to power the emotion of their stories, and we want to use this insight to develop features that fuel creators with quick and easy ways to find the music they need.”
Epidemic offers a total of 32,000 royalty free tracks and 60,000 sound effects, with subscription prices starting at $15 per month or $144 per year. The company works with YouTube luminaries like PewDiePie, Peter McKinnon, Jack Black, and Mr. Kate.
Epidemic Sound posted net revenues of $42 million in 2019, per Music Business Worldwide. In May, the company laid off roughly 20% of its staff — 79 of its 419 employees — amid the coronavirus pandemic. Most of the layoffs occurred within its sales department, as subscription sales became increasingly digitally-driven, the company said.