The eBay Interests Feature Provides Product Recommendations
References: itunes.apple & digitaltrends
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.
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 Themes
1. Hyper-personalization - Advanced algorithmic knowledge and personalized touch can provide hyper-personalized product recommendations for online retailers.
2. User Questionnaires - User questionnaires can help online retailers gain insights about user interests and preferences to provide better recommendations.
3. Data-driven Recommendations - Data-driven recommendations can help online retailers upsell and cross-sell products to increase revenue and customer loyalty.
Industry Implications
1. E-commerce - Hyper-personalized product recommendations can improve user engagement, retention, and revenue in e-commerce platforms.
2. Market Research - User questionnaires can help market research companies collect valuable data about user interests and preferences for different products and services.
3. Data Analytics - Data analytics can help companies make data-driven decisions to optimize product recommendations, user experiences, and sales in different industries.
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