Naver AI Shopping Recommendation Technology Increases Selection Rate of Less Popular Products by 6.2 Times

[Asia Economy Reporter Bu Aeri] Naver announced on the 13th that its artificial intelligence (AI) product recommendation technology has increased user selection of less popular products with fewer reviews.

According to the 'D-Commerce Report 2020' created by a research team led by Professor Geonwoong Lee of Korea University Business School, the user selection rate through Naver Shopping's AI product recommendation technology, 'AiTems,' was 6.2 times higher for less popular products with fewer reviews compared to popular products.

The user selection rate for new products was about 1.2 times higher than for non-new products.

Naver explained, "Since AiTems recommends products tailored to user preferences based on big data, it reduces the importance of recognition factors such as the number of reviews and product age, which were previously considered important in existing search services, thereby increasing the likelihood of selecting recommended products that match user tastes."

Additionally, AI technology was found to enhance the substitution effect of user experience. The selection rate in product categories where user experience is important, such as fashion apparel and sports & leisure, was 5.5 times higher than in categories like electronics and food products, where product value can be assessed through search alone.

The company stated that AI technology increases user selection rates by substituting user experience regarding product value before purchase and alleviating uncertainty.

Professor Lee said, "AiTems alleviates the so-called 'superstar' polarization phenomenon between products and stores, providing important socioeconomic implications for balanced growth through AI at a time when the importance of the Digital New Deal is being emphasized."

This content was produced with the assistance of AI translation services.