KakaoTalk’s gift-giving feature recently incorporated artificial intelligence technology that accounts for 9 percent of total transactions, according to Yang Ho-cheol, Co-CEO of Kakao Commerce CIC. Yang shared this information through the web magazine ‘Tech Ethics,’ dedicated to introducing Kakao’s AI technology and policies.

The KakaoTalk gift-giving feature’s advantage lies in its convenience, leveraging the widely used messenger to send gifts easily even without knowing the recipient’s address or phone number. The service also provides recommendation features based on satisfaction and similarity to help users quickly find items that the recipient might like.

Taking things a step further, Kakao introduced the ‘AI Gift Exploration’ service in September 2023, using AI technology to alleviate user concerns about gift selection and enhance the recipient’s satisfaction.

For example, by selecting criteria such as ‘female,’ ‘30s,’ and ‘romantic,’ users receive a list of recommended gifts along with the phrase, ‘Romantic recommendations that a woman in her 30s would like.’

The service generates a list of potential gifts based on the recipient’s service usage logs, including the recipient’s publicly shared wish list and the history of exchanged gifts. Kakao explains that the information reflects the recipient’s preferences, increasing the likelihood of high satisfaction with the received item.

The service also expands the list of recommended products by considering gifts exchanged and similar items. Even if there is a similar list of recommended products, the order in which items are presented varies for each user based on selected recipient conditions (gender, age, etc.), gift type (luxury, healthy, holiday, etc.), and service usage specifications.

To assist users in making the final selection, personalized recommendations come with reasons for each suggested product. Kakao emphasizes its commitment to expanding the application of personalized AI recommendations in the gift-giving service from the user’s perspective, ensuring thorough discussion and review processes before using collected user information for recommendations.

By Pulse

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