온라인 패션 리테일링의 사이즈 추천 기술 동향 (Trends of Size Recommendation Technology in Online Fashion Retailing)

서지정보

· 발행기관 : 한복문화학회
· 수록지 정보 : 한복문화 / 24권 / 1호 / 79 ~ 90페이지
· 저자명 : 김지은

초록

As the sales of the entire fashion industry are declining due to the Covid-19 pandemic fashion retailers introduce retailing technologies to enhance the shopping experience online. The Size Recommendation Technology(SRT) is one of the retailing technologies to support customers by recommending customers the right size by using data analysis. This study classifies the size recommendation technologies according to data types and finds the implications for online fashion retailers. 5 types of size recommendation technologies are as follows. First the size recommendation technology with virtual try-on using customer body size data, this model is meaningful as it helps customers imagine the fit and size of the product by using an avatar made with the customer's body shape. Second the recommendation technology with robotics using body type, this model helps customers to imagine how the product will be worn through various body types. Third size recommendation technology using customers’ detailed body size data, this model is meaningful in that it develops an app that can measure the detailed body size of consumers to increase the sense of reality. Fourth size recommendation technology using garments dimensions this model extends the scope of usage data beyond matching body size and product size. Lastly size recommendation technology through the conversion of consumers' body size and purchasing history this model uses previous purchase history to achieve a subjective fit of fashion items that previous models could not. This study suggests to the online retailers based on research as follows. First smooth interaction between the program and customers is necessary to enhance the online shopping experience. Second simple operation is essential for customers to complete their purchasing journey without forgetting their original purpose. Third it is necessary to develop new data hat describes purchasing habits and customer situations. SRT will be a stepping stone to improve and commercialize personalization services by helping online consumers to purchase the right size without experiencing the product in the future.

영어초록

As the sales of the entire fashion industry are declining due to the Covid-19 pandemic fashion retailers introduce retailing technologies to enhance the shopping experience online. The Size Recommendation Technology(SRT) is one of the retailing technologies to support customers by recommending customers the right size by using data analysis. This study classifies the size recommendation technologies according to data types and finds the implications for online fashion retailers. 5 types of size recommendation technologies are as follows. First the size recommendation technology with virtual try-on using customer body size data, this model is meaningful as it helps customers imagine the fit and size of the product by using an avatar made with the customer's body shape. Second the recommendation technology with robotics using body type, this model helps customers to imagine how the product will be worn through various body types. Third size recommendation technology using customers’ detailed body size data, this model is meaningful in that it develops an app that can measure the detailed body size of consumers to increase the sense of reality. Fourth size recommendation technology using garments dimensions this model extends the scope of usage data beyond matching body size and product size. Lastly size recommendation technology through the conversion of consumers' body size and purchasing history this model uses previous purchase history to achieve a subjective fit of fashion items that previous models could not. This study suggests to the online retailers based on research as follows. First smooth interaction between the program and customers is necessary to enhance the online shopping experience. Second simple operation is essential for customers to complete their purchasing journey without forgetting their original purpose. Third it is necessary to develop new data hat describes purchasing habits and customer situations. SRT will be a stepping stone to improve and commercialize personalization services by helping online consumers to purchase the right size without experiencing the product in the future.

참고자료

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