Use interest data for personalized recommendations
Learn how to turn on interest capture, let Business Account build interest profiles, and use them to personalize feeds, community suggestions, and notifications.
Interest data lets Business Account recommend videos, communities, and notifications that match what each person cares about. Business Account builds and updates interest profiles automatically with AI from Supervised Intelligence. You decide where recommendations appear, and you track how they perform.
Personalized recommendations raise engagement, surface relevant videos and communities sooner, and keep people coming back. Targeted recommendations also improve clicks and actions, and the AI adapts them as behavior changes. Feed personalization is part of Control; see How Control works.
Turn on interest capture
- Turn on User Profile & Interests in your app.
- In your Business Account, go to Manage > Category.
Genuin then captures interest signals from two sources:
- Onboarding selections, the interests people choose explicitly
- User interactions: views, likes, shares, and watch time
Note
The more interaction data people generate, the more accurate the recommendations are.
Learn how to set up brand categories and topics.
In Manage > Category, you add, edit, and delete categories and the topics and keywords inside each. Your brand needs at least three categories at all times.
If people skip interest selection at sign-up, turn on Enable Interest selection popup in Settings > Guided Onboarding Controls. It asks them to pick interests after the number of swipes you set, from 1 to 5. Mobile and web use the same settings.
How interest profiles work
Once interest capture is on, Business Account creates dynamic user interest profiles automatically. Each profile updates continuously from:
- Content consumption patterns
- Community participation
- Engagement signals
AI models generate the recommendations dynamically, and profiles evolve in real time as behavior changes. Recommendations work across feeds, communities, and notifications.
Where recommendations appear
| Surface | What interest data does |
|---|---|
| Personalized feeds | Ranks and displays videos by user interests, and prioritizes high-affinity content categories |
| Community and group recommendations | Suggests relevant communities based on user preferences, which raises join rates through contextual discovery |
| Content suggestions | Recommends similar or related content after an interaction, for deeper engagement within a session |
| Notifications and re-engagement | Sends personalized alerts based on interests, and promotes trending or new content in preferred categories |
Configure where recommendations appear
You configure recommendations in your Business Account, mainly in Grow > On Site:
- Surfaces: homepage feeds, embedded widgets (Carousel, Feed, and Standard Wall), and in-app experiences.
- Filters: interest category, community relevance, and content type.
In Grow > On Site, a placement's Feed Type is Brand Feed, Community Feed, or Group Feed, in a Grid, Dynamic, Carousel, or Feed layout. An embed's Feed Display Preference sets how content appears in its feed: Default or Pinned Post First, starting on Default.
Learn how to get started with placements and generate embed codes.
Track recommendation performance
- In your Business Account, go to Report.
- Track CTR (click-through rate) on recommended content, engagement by interest category, and retention and session duration.
Use the results to refine interest mapping, improve content tagging, and adjust your recommendation strategy. For the interaction metrics in reports, see content interactions in reports.
Example: a media brand
A media brand wants more engagement across its video platform. Its users interact with tech, gaming, and finance content, and Business Account builds interest profiles from those interactions automatically.
Genuin then recommends similar videos, suggests relevant communities, and sends targeted notifications. The result is a higher CTR on recommended content, more watch time, and better user retention.
Limitations
- Recommendations need data. They require enough user interaction data, and interest signals must be enabled in your Business Account.
- New users get generic recommendations. Cold-start users might receive generic recommendations at first, until they interact with content.
- Tagging affects accuracy. Content must be tagged and classified. Misclassified content lowers recommendation accuracy, so review tags when recommendations miss.
- Personalization can narrow feeds. Over-personalization can limit content diversity unless you balance it.
