Search should help users find what they already know. Recommendations should help them keep going once they have started.
Tuned Global’s Metadata APIs support both parts of that journey, with enough breadth for universal discovery and enough depth for more advanced, product-specific experiences.
Overview
This guide explains how Tuned Global supports content discovery across music and audio products.
It shows how to build discovery experiences using Tuned Global's Search APIs and Recommendations APIs, from broad catalogue search through to more precise track retrieval and recommendation-driven continuation.
It should help you understand:
How users can search for tracks, artists, albums, playlists, stations, and other entities
How global search, advanced search, and recommendations work together
How search supports browse, editorial pages, carousels, tags, and recommendation modules
Which discovery patterns are best suited to different product types
How discovery supports engagement, retention, and stronger product experiences
Search in Tuned Global is not limited to a single keyword endpoint. The platform supports:
A broad global search layer for universal catalogue discovery
A deeper advanced song search layer for more precise track retrieval
Recommendation flows based on track relationships, tags, and seeded IDs
Similarity and matching utilities that help extend discovery and improve result quality
How search and recommendation fits into the product
In most products, search is the first step in a wider journey:
Search --> Get Results --> Playback / Add to Playlist / Get Recommendations
A strong implementation does more than return matches. It:
Supports different levels of search precision
Returns enough metadata to power the next UI step
Helps users move from known-item search into broader discovery
Connects naturally into playback, artist pages, album pages, playlists, stations, and recommendation modules
Tuned Global's discovery stack is designed to support full discovery journeys across a catalogue, from universal search and track-first retrieval through to browse-led discovery and deeper recommendation flows.
The strongest discovery experiences use these layers together. A practical pattern is:
This creates a discovery stack that supports both known-item search and deeper continuation once the user is engaged.
Global Search
Endpoint: GET /api/v2.4/search
Swagger: Metadata API — Search
Global Search is the best starting point when the product needs a universal search bar and the user may be looking for different kinds of content.
This endpoint provides the broadest response, while the other search endpoints are more specific. It searches across the available catalogue and reflects licensing and territory availability, including an available territory node in the response. That makes it well suited to real-world music products where availability matters as much as relevance.
Global Search returns results that can move directly into richer metadata retrieval, playback, browse surfaces, and downstream recommendation flows. It supports broad discovery while still respecting catalogue availability and territories, which makes it suitable for commercial implementations across multiple markets.
Advanced Song Search
Endpoint: GET /api/v2.4/search/songs/advanced
Swagger: Metadata API — Advanced Song Search
Advanced Song Search is the deeper track discovery layer. It moves beyond a basic keyword search and supports products that need greater precision, filtering, and richer query behaviour.
This endpoint returns highly structured song-level results with substantial metadata depth, including scoring and ranking fields, identifiers, artist data, label and owner fields, tags, countries, translations, plugin metadata, and release context. That makes it useful not only for retrieval, but also for ranking, filtering, merchandising, and more deliberate discovery workflows.
Advanced Song Search is built for implementation depth, giving teams more room to refine discovery, ranking, filtering, and merchandising.
Recommendations
Search helps the user find something they already want. Recommendations help the product continue the journey once that intent has been expressed.
Tuned Global exposes multiple recommendation patterns rather than a single generic recommendation endpoint. That gives teams flexibility to support different types of continuation across the same catalogue.
Similar artists
Endpoint: GET /api/v2.4/artists/{id}/similar
Swagger: Metadata API — Artist
Returns artists similar to a specified artist based on overlapping listening patterns and catalogue attributes. This is the primary similarity endpoint in the Metadata API and supports artist-led continuation when the user's intent is performer-led rather than track-led.
This is especially useful when you want:
Similar artists by tags
Endpoint: GET /api/v2.4/artists/{id}/similarbytags
Swagger: Metadata API — Artist
Returns artists similar to a specified artist based on tag overlap rather than behavioural data. Useful when you want tag-driven similarity without relying on listening patterns.
Similar stations
Endpoint: GET /api/v2.4/stations/{id}/similar
Swagger: Metadata API — Station
Returns stations that share the most tracks by the same artists. Useful for radio-style continuation and "more like this" station modules.
Similar podcasts
Endpoint: GET /api/v2.4/podcasts/{id}/similar
Swagger: Metadata API — Podcast
Returns similar podcasts based on matching channel tags.
Playlists by track
Endpoint: GET /api/v2.4/playlists/by-track
Swagger: Metadata API — Playlist
Returns playlists that contain a specific track. This is useful for track-led discovery — once a user selects or plays a song, you can surface playlists that feature it, creating a natural bridge from a single track into a broader listening experience.
Tag-driven recommendations
Endpoint: GET /api/v2.4/tags/artists?tag={tag}, GET /api/v2.4/tags/albums?tag={tag}, GET /api/v2.4/playlists/by-tags
Swagger: Metadata API — Tag / Playlist
Returns content filtered by tags associated to tracks, albums, or artists. This approach uses the tag system to determine similarity rather than behavioural data.
This is useful when you want:
TunedIQ — Personalised track recommendations
TunedIQ is Tuned Global's collaborative-filtering recommendation engine. It learns from real listening behaviour rather than static metadata, making it effective even for catalogues with limited or inconsistent tagging.
Once enabled, TunedIQ provides track-level recommendation capabilities including:
Seeded recommendations — recommended tracks based on up to 3 specified track IDs
Tag-driven related tracks — recommendations using tags associated to tracks or derived from albums and artists
Track similarity — related tracks with rich metadata including identifiers, ISRC, explicit flags, image fields, and linked release data
Daily Discovery Mixes — blends of familiar favourites and new tracks
Personalised Trending — trending tracks filtered by the user's taste profile
Continuous Play — automatically extends listening sessions from a seed track
These are useful when you want:
A "similar tracks" or "you might also like" module
Seeded recommendations from a small set of known tracks
Smarter continuation from a user's recent behaviour
Recommendation flows that feel more intentional than simple nearest-neighbour similarity
What's available without TunedIQ
The following similarity and discovery endpoints are available in the public Metadata API and do not require TunedIQ:
There is currently no track-level similarity endpoint (e.g. "similar songs") in the public Metadata API. Track-level recommendations require TunedIQ.
Summary
Tuned Global supports multiple recommendation models:
Tag-driven related content via tag discovery endpoints
Seeded track recommendations, track similarity, and personalised discovery via TunedIQ (requires activation)
This makes it easier to design recommendation experiences that fit the product.
Additional discovery tools that strengthen the stack
Beyond search and recommendations, Tuned Global also includes supporting discovery tools that help improve result quality, handle catalogue matching, and extend discovery into richer product experiences.
ISRC Matching
Endpoint: GET /api/v2.4/search/search-matching
Swagger: Metadata API — Song Matching
This endpoint returns tracks that share the same ISRC. It supports matching by ISRC, song name, artist name, and duration — useful for prioritising a single track per ISRC when multiple tracks exist.
This is useful for:
Display-Ready Similarity Responses
The similar content endpoints (GET /api/v2.4/artists/{id}/similar, GET /api/v2.4/artists/{id}/similarbytags, GET /api/v2.4/stations/{id}/similar, GET /api/v2.4/podcasts/{id}/similar) include not only identifiers, but also artist arrays, release objects, translations, image fields, and other display-ready data. Recommendation modules can therefore be wired directly into product experiences without needing a separate minimal similarity layer.
Supporting Discovery Surfaces
Search and recommendations become even more powerful when combined with supporting discovery surfaces such as:
Content pages
Carousels
Editorial modules
Browse-led collections
These surfaces help turn discovery into a broader product experience rather than a single search box.
Catalogue filtering and availability
Discovery quality depends on more than relevance alone. Tuned Global's search and recommendation stack can also reflect catalogue availability, licensing, territories, and richer metadata such as tags, genres, language, owner, label, and release context.
This makes it possible to build discovery experiences that are not only relevant, but also commercially usable in the markets and contexts where the product operates.
Getting started
A practical way to start implementing search and recommendation capabilities is:
When to use each endpoint
Why this is powerful
Tuned Global's discovery capability is strong because it is not built around only one search pattern. It combines:
Tag-driven browse and recommendation surfaces
Track-level personalised recommendations via TunedIQ (separately licensed)
Rich metadata responses that are already useful for downstream UI and playback flows
That gives technical teams more freedom to design discovery experiences around product intent, not just around whichever endpoint exists.
Swagger References:
Services API (v3) — Play history, personalised playlists, authenticated similar artists
