AI Music Platform for Independent Artist Distribution, Spotify Pitch, and Metadata

Independent artists typically do not enjoy the same support as traditional major record labels in the music industry or have the same resources as those labels. One of the most important opportunities the client identified was developing accurate and engaging music metadata. Metadata that can identify the mood, genre, sub-genre, and lyrical theme can prove to be critical in cataloging your music and being discovered by the right listeners. Artists have always defined this information on their own, which takes time and has the potential to be misleading to the audience on a service like Spotify. 

Additionally, artists need to provide a Spotify pitch, which is an engaging summary of the song, in order for that song to be considered for music discovery playlists when uploading songs on Spotify. For independent artists, creating Spotify pitches to go along with their songs can be overwhelming without the pre-existing knowledge that can come from a background in marketing and using effective music marketing tools.

The client envisioned a solution that would:

• Scrape song lyrics automatically and do some analysis on them through AI lyrics transcription.
• Create structured music metadata such as title, mood, theme, genre, and sub-genre through heuristic processing.
• Create a premium and engaging Spotify pitch. 
• Create AI-developed cover images or singles through artful image prompts.
• Use analytics to provide artists with insight into song performance and trends to help them make better, data-informed decisions, supporting AI music promotion.

Seaflux collaborated with the client to design and implement an AI-powered music application that automates metadata creation and enhances the music distribution process, helping independent artists with AI music promotion and turbo music features.

1. Lyrics Extraction
   • The solution integrated Whisper AI by OpenAI, a powerful speech-to-text model, to transcribe the song lyrics accurately from the uploaded audio file using AI lyrics transcription technology.
     
      
2. Metadata Generation with GPT-4 Turbo
   • Once the lyrics were extracted, they were processed through GPT-4 Turbo, which generated a comprehensive set of metadata, including:
      
     • Suggested song title
     • Mood and emotional tone
     • Theme and context of the lyrics
     • Primary genre and related sub-genre
       
        
3. Spotify Pitch Creation
   • The service utilized GPT-4 Turbo to generate a professional, concise, and engaging Spotify pitch for the song. 
   • Artists had the option also to edit or revise prompts for titles and pitches to meet their creative intent, providing guidance on how to write a Spotify pitch that resonates with listeners and playlist curators. 
     
      
4. AI-Generated Album Covers
   • Using DALL-E, the platform supplied four distinct cover images for each song.
   • Artists could choose from these AI-generated covers or supply their own prompts in order to generate visuals that more accurately illustrate their work.
     
      
5. Analytics Dashboard
   • To empower data-driven growth, the application provided detailed insights on:
      
     • Music metadata distribution
     • Audience trends and engagement
     • Content performance over time
        
   • These analytics allowed artists to understand their listener base, optimize releases, and strategize future music projects, further supporting AI music promotion efforts and independent artist distribution.

The impact of the platform was evident shortly after its launch:

• 30,000+ Sign-Ups in the First Quarter: This platform was met with almost instant success, with over 30,000 sign-ups in just the first quarter of launching. This shows that there is demand for AI music solutions that lessen all of the work/"release" processes for indie artists.
• 10,000+ Artists Served: The platform assisted in creating metadata, pitching songs to Spotify, and cover art for songs for well over 10,000 artists. The platform provided artists the ability to present this work, professionally done, and at a fraction of the previous cost, while offering valuable music marketing tools.
• More Singles and Albums on Spotify: This platform assisted the ability to create music metadata, pitch songs, and cover art for songs, which ultimately led to more singles and albums on Spotify and all related platforms for exploring for indie artists, leveraging turbo music processing and integrated music distribution software.
• Actionable Data-Driven Insights: The analytics dashboard engine provided artists with the ability to track how songs were performing and when the audience was engaging. Also, by providing a labels engine (data), there will be the ability to compare the data for actionable data-driven decision making pertaining to any releases or promotion and distribution for indie artists, further enhancing music artist analytics capabilities.