# Hyper-Personalized Ecommerce Features The eBay Interests Feature Provides Product Recommendations By Joey Haar | Published 2018-05-17 | Business Source: Trend Hunter, https://www.trendhunter.com/trends/ebay-interests References: [digitaltrends](https://www.digitaltrends.com/mobile/ebay-launches-interests-feature-on-mobile-app/?utm_source=feedly&utm_medium=webfeeds#/9) & [itunes.apple](https://itunes.apple.com/us/app/ebay-home-fashion-shopping/id282614216?mt=8&ign-mpt=uo%3D8) Online shopping has shifted from being an occasional necessity to the way that many people look for the majority of their purchases, and the new eBay Interests feature is a way to connect people with the things that they might want in the future. The new recommendations section of the popular online marketplace uses a combination of advanced algorithmic knowledge and a personal touch to find the best items on the site for any given user. The eBay Interests feature is a step above the "similar items" or "other people also purchased" sections of online retailers. Rather than making guesses based purely on purchase history, the Interests feature takes users through a quick questionnaire to figure out precisely the styles, lifestyles, and products they're most into. ## Trend Insights (Trend Hunter) - Score: 3.3/10 - Popularity: 43% | Activity: 49% | Freshness: 8% - Audience gender: 50% men, 50% women - Primary generations: Millennial, Gen X - Top markets: North America ## Categories [Trend Hunter](https://www.trendhunter.com/trends) > [Business](https://www.trendhunter.com/business) > [Retail](https://www.trendhunter.com/retail) ## Key Themes ### What Makes This Trend Stand Out - **Hyper-personalization:** Advanced algorithmic knowledge and personalized touch can provide hyper-personalized product recommendations for online retailers. - **User Questionnaires:** User questionnaires can help online retailers gain insights about user interests and preferences to provide better recommendations. - **Data-driven Recommendations:** Data-driven recommendations can help online retailers upsell and cross-sell products to increase revenue and customer loyalty. ### Sectors Adopting This - **E-commerce:** Hyper-personalized product recommendations can improve user engagement, retention, and revenue in e-commerce platforms. - **Market Research:** User questionnaires can help market research companies collect valuable data about user interests and preferences for different products and services. - **Data Analytics:** Data analytics can help companies make data-driven decisions to optimize product recommendations, user experiences, and sales in different industries. ## Related on Trend Hunter - [AI-Powered Outfit Shopping Features](https://www.trendhunter.com/trends/ebay-shop-the-look.md) - [Personalized Ecommerce Updates](https://www.trendhunter.com/trends/google-shopping-1.md) - [Personalized Streaming Merch Features](https://www.trendhunter.com/trends/spotify-merch-hub.md) - [Social Media-Inspired eCommerce Features](https://www.trendhunter.com/trends/amazon-inspire.md) - [AI-Powered Personal Shoppers](https://www.trendhunter.com/trends/perplexity-shopping-experience.md) - [AI-Powered Search Features](https://www.trendhunter.com/trends/shop-premium-outlets.md) - [AI Commerce Platforms](https://www.trendhunter.com/trends/imerchai.md) - [Article Product Suggestions](https://www.trendhunter.com/trends/shopsense-ai.md) - [Agentic Commerce Recommendation Platforms](https://www.trendhunter.com/trends/agentic-commerce-recommendation.md)