Content recommendations

Recommendations help you keep the next item served to viewers relevant. In a sports app, that might mean what everyone is watching right now, what this viewer tends to open, or a mix across surfaces. Experiences gives you different tools for those cases.

flowchart TD
  R[Recommendations]
  R --> T[Trending]
  R --> P[Personalization]
  P --> E[Explicit]
  P --> I["Implicit: For you"]

Trending: a shared ranking from aggregated engagement. Covered on this page. To fetch that ranking server-side, see Recommendations.
Explicit personalization: you map declared preferences to labels or ranked content IDs. See Explicit personalization.
Implicit personalization: the service ranks from viewer behavior and returns For you. See Implicit personalization.

Trending (global recommendations)

Trending ranks content from aggregated engagement signals (with time decay), not per viewer. Point a widget or player source at the Recommendations data source with the Trending type. Viewers see what is broadly popular without your app sending viewer preference signals for that ranking.

Use Trending for a shared feed (for example, a home-screen highlights rail) or when tracking limits mean you can't use For you. See Viewer privacy considerations and privacy compliance.

You can also fetch the trending ranking server-side, outside the SDK, with the Recommendations endpoint. Use that when your backend needs the trending set itself: to build a custom feed, to check whether a piece of content is currently trending, or to drive push notifications.

Personalization (viewer-specific)

Personalization is content tailored to a viewer. It breaks into explicit (declared preferences you map to labels or ranked IDs) and implicit (the service ranks from behavior: For you).

	Explicit	Implicit (available for Moments and Stories only)
What it is	Viewers explicitly select what they want. Who to follow What tab to view	The recommendations service learns what the viewer likes from the viewer's behavior.
Example	The viewer selects the favorite team	The viewer watches a series of goals
Implementation	You map the viewer selections to labels and optionally to content IDs in the app backend. The SDK serves the content based on the label and the content ID list. To use content IDs, you need to ingest the content catalog using the Blazefeed API and search for content that matches the viewer’s preferences.	The Experiences AI-driven recommendation engine provides a ranked content list that the SDK uses to serve content. The recommendations engine does the mapping for you.

SDK API reference

SDK type names are not the Concepts terms on this page. Use the following table to find the matching SDK parts.

Concepts	SDK	API reference
Trending and For you	Recommendations data source: `BlazeRecommendationsType`, Web `recommendations`	iOS \| Android \| Web \| React Native
Explicit personalization (labels and content IDs)	`BlazeDataSourceType`: `labels()` and `ids()`	iOS \| Android \| Web
Optional ID or label filters on a data source	`BlazeDataSourcePersonalizedType`. Web: `personalized` on `labels()`. This is not Concepts Personalization.	iOS \| Android \| Web

See Recommendations data source for how to configure For you and Trending.

Also see Viewer ID and Viewer privacy considerations and privacy compliance. For follows in the player, see Follow button for Moments.