Naver's artificial intelligence (AI) shopping agent ended about four months of beta service and launched officially on the 25th of last month. Following the conversational search AI tab, the official release of an AI shopping agent specialized for shopping is expected to further expand the agentic experience that consolidates users' exploration into real actions across Naver's services.
The AI shopping agent is evolving beyond a shopping guide that finds and summarizes products into an execution-type agent that understands users' question intent and shopping context and even proposes next actions.
More than 70% of users of the AI shopping agent are entering concrete long-tail queries of 15 or more characters, and complex shopping requests that consider multiple conditions such as price and features are steadily increasing. Naver noted that users are growing accustomed to refining their shopping criteria through conversations with the agent and finding the optimal choices.
User changes are also evident in service growth metrics. In June, the AI shopping agent's daily users increased more than 50% compared with March, right after the beta launch, and the average number of daily returning users nearly tripled, indicating the service is taking hold among loyal users. The transaction amount through the AI shopping agent grew more than 2.7 times. As recommendation quality improves, it shows that product exploration through conversations with AI is naturally leading to actual purchases.
In the official version, answer performance was advanced to more broadly understand users' question intent and shopping context. For example, if a user asks, "What meal kit is good for a housewarming?," instead of merely listing products, it first proposes shopping criteria suited to the situation, such as "visually appealing main dishes," "party platters," and "simple soup dishes," and then recommends products that fit. Even for simple situational queries like "Recommend cat health care items," it presents shopping themes tailored to the purpose, such as gut health and joint/skin care, and guides the exploration direction more precisely. It also provides information on promotions and membership benefits so each user can receive the best possible benefits.
Ease of use for the agent was also improved. A "edit question" feature was added so users can modify questions already entered during a conversation, and a "feedback" feature was added to allow positive or negative ratings and other opinions on the agent's answers.
In addition, a "view sources at once" feature was added to let users see at a glance the UGC content the AI shopping agent referenced for its recommendations. The company said users can more easily check the latest content generated on blogs and cafes, and trust in the agent's generated answers is expected to improve.
Naver's Lee Jeong-tae, head of Shopping Search & AI, said, "The Naver AI shopping agent is rapidly evolving into an execution-type agent that, through a process of asking and answering with users, performs the complex steps of online shopping—such as searching, comparing, and exploring—on their behalf and even proposes actions that can lead to actual purchases," adding, "In the second half of this year, we will focus on advancing the technology to deliver a seamless, smart, agentic shopping experience from search to payment, including personalized membership benefit recommendations and enhanced cart and delivery information."