listingrelated

Listingrelated is a feature in digital marketplaces and listing platforms that presents a curated set of listings related to the item a user is viewing. The goal is to improve item discovery, engagement, and conversion by surfacing alternatives the user may find relevant.

Implementation typically relies on two classes of signals: content-based signals derived from listing metadata such as category, attributes, price range, brand, and location; and user-behavior signals derived from past interactions, such as views, saves, add-to-cart, and purchases. Hybrid approaches combine both. Candidate listings are retrieved from the catalog using category and attribute filters, then ranked by a learned model that scores relevance, novelty, and similarity.

Data sources include listing metadata, taxonomies, and historical interaction data. Systems may also include session context or user profiles to personalize results. The user interface often labels these as Related listings, Similar items, or You may also like, displayed in a carousel or a list.

Evaluation focuses on offline metrics such as precision/recall, MAP, and NDCG, and online metrics like click-through rate and conversion rate. Trade-offs include freshness vs. caching, cold start for new listings, and potential bias or redundancy.

Limitations and considerations: accuracy depends on data quality; privacy and consent must be respected when using user data; systems should mitigate spam, manipulation, or over-representation of popular items.

See also: recommendations, similar items, cross-selling.