Blend
Music is emotion. Find your match.
Blend
MUSIC · EMOTION · MATCH
Project Specs
Why this product should exist.
The Problem
Dating and social platforms rely heavily on photos, short bios and generic interests. They rarely use one of the clearest expressions of identity and emotion—music taste—as the primary basis for connection.
The Idea
Build a social discovery experience where shared listening patterns reveal compatibility before a conversation begins.
The Solution
Blend uses Spotify authentication and top listening data to compare artist, track and genre overlap. Potential connections are ordered by a music-similarity score and filtered by location and gender preference, with mutual matches able to chat in the app.
Target Users
Music lovers who want to meet romantic interests or new people through shared artists, genres, listening patterns and live-music culture.
What the product does.
Spotify Authentication
Spotify provides account access and the listening data used to create each user's music profile.
Music Profile
Top artists, tracks and genre patterns are transformed into a clear representation of the user's taste.
Similarity Algorithm
A composite comparison of artist, track and genre overlap produces a visible compatibility percentage.
Swipe-Based Discovery
Users browse potential connections in a familiar card interface ordered around music compatibility.
Distance & Preference Filters
Location radius and gender preferences narrow discovery to relevant potential matches.
In-App Chat
Mutual matches can begin a private conversation after both people express interest.
How the product creates value.
This is a strategic product map—not a fabricated interface. It shows the core modules currently defining the experience while real product media is still being prepared.
System Architecture
Blend core product logic
Spotify Authentication
Spotify provides account access and the listening data used to create each user's music profile.
Music Profile
Top artists, tracks and genre patterns are transformed into a clear representation of the user's taste.
Similarity Algorithm
A composite comparison of artist, track and genre overlap produces a visible compatibility percentage.
Swipe-Based Discovery
Users browse potential connections in a familiar card interface ordered around music compatibility.
Distance & Preference Filters
Location radius and gender preferences narrow discovery to relevant potential matches.
In-App Chat
Mutual matches can begin a private conversation after both people express interest.
Where the product stands now.
IncubatorProduct direction, feature scope and early systems are being shaped before focused development.
Validate the initial city or music-community launch strategy Prototype and test the similarity model Confirm Spotify API constraints Design the pre-launch waitlist experience