How does Naver's product search algorithm prioritize product listings based on user search behavior within the Naver ecosystem?

Naver's product search algorithm, deeply integrated with the broader Naver ecosystem, prioritizes product listings based on several user behavior signals, with a strong emphasis on recency, relevance, and user engagement within Naver's platforms. Primarily, the algorithm considers click-through rate (CTR) and conversion rate (CVR) for each product listing. Listings with higher CTR and CVR for specific search queries are given preferential treatment. Naver also factors in purchase history and user reviews. Products frequently purchased by users searching for a particular keyword are ranked higher, as are products with positive reviews. Importantly, user activity within Naver's other services, such as Naver Blog, Naver Cafe, and Naver Shopping, influences product ranking. Mentions of a product in relevant blog posts or cafe discussions can boost its visibility in search results. Similarly, products with high ratings and positive comments within Naver Shopping are likely to rank higher. Recent trends in user searches also play a role. Products that are gaining popularity based on recent search activity and social media mentions are often given a temporary boost in ranking. Finally, the algorithm considers the completeness and accuracy of product information, including product titles, descriptions, and attributes. Listings with detailed and accurate information are favored over those with incomplete or misleading information. This holistic approach ensures that products that are most relevant, engaging, and well-received by Naver users are prioritized in search results.