Custom Voice Training → A/B Test Songs → Analyze Performance Data

Train 2-3 different voice models using the Voices feature - one with clean studio vocals, one with raw recordings, and one with your natural speaking voice. Use Custom Models to create genre-specific variations for each voice type.

Create the same song concept using different voice models and the My Taste feature to vary musical styles. Generate at least 3 versions of each song to test which combination of voice and style performs best.

Upload the different versions to streaming platforms through DistroKid with slightly different titles or as separate singles. Use consistent artwork and release timing to ensure fair testing conditions.

Monitor streaming data, skip rates, playlist additions, and listener demographics for each version. Compare performance metrics after 2-4 weeks to identify which voice and style combinations resonate most with your audience.

Create a dashboard that pulls data from Spotify for Artists and other streaming analytics. Track metrics like completion rate, saves, and shares to determine your most effective AI voice and musical style combinations for future releases.