Recommendation Engine

Boost engagement with recommendations that your users will love

We all have songs we know and love, but who doesn’t love discovering a new favourite? When looking to build out your music streaming platform, creating ways for your users to discover new music, audio and video content is a sure way to boost engagement and retention.

Tuned Global enhances the music experience by giving users music suggestions that are relevant and targeted to their preferences.


Music DNA – A multi-territory music intelligence solution

Good music and content recommendations are an essential element of any highly successful streaming platform – but they’re usually heavily reliant on available data. In metadata-poor markets such as South East Asia, it can be hard to find and make use of that data in an accurate way. This is how we came to build Music DNA, our own music recommendation system.

Our music intelligence system works equally well for Asian, European and US based artists – ensuring that you have a platform that can operate where your listeners are, the way they want to engage with your platform.


A white labelled music recommendation algorithm

The team at Tuned Global has developed a B2B music recommendation system using machine learning that fuses music analytics, tags, human input, Wilson Scores and Jaccard Indexes.  This enables us to provide not only similar products but provide greater relevance in what people are search and listening to right now.

This content suggestion algorithm is available with our white label streaming app or can be accessed via our Streaming Service APIs.
  • INTELLIGENCE - Use cutting-edge algorithms to generate intelligent recommendations
  • DISCOVERY - Help your users discover their new favourite music, audio and video content
  • LEARNING - Engage users by creating a platform that learns from their inputs
  • ENGAGEMENT - Generate engagement across your catalogue by directing user traffic
  • SCALABLE - Create a platform that is equipped to scale even in metadata poor environments
Learn more about our recommendation engine and other features designed to engage users
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