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Domains / Music, Podcasts

AI-Based Music Recommendations

Utilize insights into listeners’ preferences to offer a listening experience tailored to each user - just like Spotify!

Music, Podcasts

Use Cases

Fully Personalized Homepage

Automate and tailor all your homepage rows 1:1 for each user.

Similar Songs/Artists

Present new songs and podcasts based on the content the user is currently enjoying.

Playlists Made For You

Customize playlists by showing the most relevant songs or podcasts from a pre-selected list.

New Releases

Give listeners an overview of the week's new releases.

Recommended Artists For You

Inspire your users with work from artists they might enjoy based on their listening history.

Quick Search

Match search queries and tailor the music and podcast selection to individual preferences.

Why Recombee

Recommend Songs, Albums, Artists and Podcasts

Recombee automatically understands the links between songs, albums, and artists.

Uplift Revenues, Boost Playtime, Subscriptions and Retention Rates

Increase number of plays, active users, artist follows, ad revenues and other metrics.

Offer Great Personalized Recommendations for Music and Podcasts

Recommend music that fits the user using advanced collaborative filtering models.

Recommend Local and Niche Content

Allow listeners to discover unique content creators within a large catalog of songs and podcasts, including sensitivity to particular cultural regions.

Provide Real-Time Responses to Mood Changes

Recommend content selections based on different situations and time of the day.

Manage the Behavior of Recommendations

Control what content is being recommended, e.g., by filtering out explicit or unverified content while boosting content that is local to the user's country or area.

"Striving to be the ever limitless music sharing and discovery platform, we need to make sure the user experience of our listeners is smooth and sound. And one of the most critical aspects of achieving such a goal is content personalization tailored 1:1 in real-time. That's why we switched to Recombee. Thanks to their recommender engine, our monthly plays increased by 206% and weekly follows by 67%. Because the recommendations performed so well, we moved them from our Search page to the top of our main Discover tab. They are now the best-performing module within that tab, accounting for 46% of all plays."

Christopher Dalla Riva
Senior Product Manager at Audiomack

Increase the Number of Subscribers and Time Spent With Personalized Playlists and Podcasts

With more aspiring artists and easy access to music and podcasts, it is no easy task to stay competitive. We analyze consumed content, favorite artists, speakers, genres, or descriptions in multiple languages, to help your platform offer podcasts and music recommendations tailored to personal tastes.

Beyond basic data, Recombee’s recommendation engine works with information about which songs/podcasts were listened to till the end, which halfway or skipped completely. Utilize Recombee to offer recommendations of genres, artists, songs or playlists to keep the listener entertained and eager to revisit your platform.

Recombee’s robust recommendation engine analyzes item properties such as title, genre, author, language or tags and interactions like view, replay, like or rating. Autoplay is one of many features that Recombee offers to the listeners and enhances their time spent on the platform.

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Core Technology

Adapting to your data

Adapting to your data

A robust system that can utilize all data available to generate great recommendations for your users, including collaborative filtering and content-based models.

Dynamically Retrained Models

Dynamically Retrained Models

Real-time content personalization that adapts to the flourishing customer’s tastes and considers the newly added music or podcast content.

Specific Functionalities to Music Platforms

Specific Functionalities to Music Platforms

Recommendations taking into account the users’ listening time; which titles were listened to until the end, which were listened to halfway or skipped completely.

AI-powered A/B Testing

AI-powered A/B Testing

In-house AutoML AI applied to keep maximal KPIs and advance the deep learning algorithm functions.

Advanced Business Rules

Advanced Business Rules

Boosters or filters to push forward desired songs or genres and easy to manipulate, adjustable rules for additional optimization of your content.

Real AI Inside

Real AI Inside

Reinforcement learning and other algorithms designed to recognize the preferences of individual users and predict desired music or podcast with higher accuracy boosting user engagement.

"Working with Recombee to develop an affordable solution to provide our users with excellent music recommendations has exceeded our expectations in every way. They have been able to understand the relationships in the data of our industry and create effective models to use efficiently. We also appreciate the nuance and flexibility they offer when it comes to deciding the right solution based on quality, cost, complexity, speed, and other factors."

Ty Wangsness
Founder/CTO at Audiomack

Chosen Customers