# How does incorporating user background attributes such as skills or interests affect recommendation quality in domains with sparse interaction data? | FAQ

> Source: https://www.recombee.com/faq/how-does-incorporating-user-background-attributes-affect-recommendation-quality

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# How does incorporating user background attributes such as skills or interests affect recommendation quality in domains with sparse interaction data?

In domains where users interact infrequently - such as job platforms or professional networks - interaction history alone is insufficient to build a reliable preference model. **Background attributes like skills, interests, or professional bio provide a non-behavioral signal that compensates for sparse interaction data**, enabling relevant recommendations from a user's first session. This is especially consequential for new user retention: a platform that can deliver relevant results before a user has clicked or purchased is more likely to establish a habit. Organizations in low-frequency domains should prioritize collecting structured background attributes during onboarding rather than relying solely on behavioral data accumulation.

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