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FOR PLAYLIST CURATORS

Find tracks that fit your playlist. Objectively.

SongScore's acoustic matching helps curators evaluate whether a submitted track truly fits their playlist's mood, energy, and genre profile — beyond gut feeling.

Analyse a TrackSee a Demo Report

SOUND FAMILIAR?

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Receiving 50+ weekly submissions for a chill lo-fi playlist and half of them being energetic pop tracks

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Having no objective way to explain to an artist why their track doesn't fit — "it just doesn't feel right" is hard to defend

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Accidentally adding a track that breaks the mood of a playlist because it was marketed as one genre but sounds like another

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Not having a systematic way to compare two similar tracks to decide which one fits better

HOW SONGSCORE HELPS

01

Verify acoustic fit instantly.

Run a submitted track through SongScore to see its Sonic DNA, Mood Analysis, and Genre Detection data. Compare these against the audio profile of your playlist. If the moods and energy levels don't align, you have the data to explain why.

02

Reduce time spent on obvious mismatches.

A track submitted to a "Dark Ambient" playlist that scores 85% Happy and 75% Energetic is an obvious mismatch. SongScore surfaces this in seconds, before you spend time listening.

03

Give artists useful rejection feedback.

Share your acoustic fit criteria with submitting artists. When you reject a track, the SongScore data gives them actionable information: "Your track's energy profile doesn't match our playlist's 0.2–0.4 energy range" is more useful than no response.

FEATURES YOU'LL USE MOST

Mood Analysis (31 dimensions)
Genre Detection
Sonic DNA Radar
Energy, Valence & Arousal scores
Playlist Matches database
Single Report (pay-per-track) — no subscription required

ALSO BUILT FOR

Independent ArtistsMusic ProducersA&R and Labels

KEY TERMS

Sonic DNA
SongScore's proprietary six-dimension acoustic fingerprint radar: Energy, Valence, Arousal, Danceability, Acousticness, and Instrumentalness.
Mood Analysis
SongScore's detection and scoring of 31 emotional mood dimensions present in a track, from Happy and Energetic to Melancholic and Dark.
Genre Detection
Automatic classification of a track's primary genre, subgenres, and free genre tags from audio analysis.
Platform Fit Score
A score measuring how well a track matches the algorithmic and cultural preferences of a specific streaming platform.

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