The Korea Herald


ShinWon spurs fashion tech innovation with AI, big data

By Kim Jun-hong

Published : June 21, 2024 - 14:50

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ShinWon uses AI and big data to analyze fashion trends and build their product strategy. (ShinWon Corporation) ShinWon uses AI and big data to analyze fashion trends and build their product strategy. (ShinWon Corporation)

Korean fashion company ShinWon Corporation said Friday that it is increasingly adopting artificial intelligence and big data to lead tech innovation in fashion.

By predicting future trends through extensive data analysis, ShinWon said it adapts swiftly to market changes, incorporating these insights into product planning and production.

To understand market conditions and patterns, ShinWon employs online market sales data analysis, trend analysis and social media analysis. By examining actual sales data by market and category, the company identifies preferred colors and designs to offer future trend predictions through machine learning and deep learning technologies.

ShinWon's AI-driven data analysis covers sales status, inventory trends, retail price trends, colors and designs. In 2023, 20 percent of its market intelligence data was built using AI data analysis, with plans for wider adoption.

The company also pursues design innovation with technologies like 2D and 3D styling and virtual reality stores. Its 3D virtual studio visualizes designs on virtual mannequins, featuring interactive functions like 360-degree zoom. This enhances customer experience through realistic fitting scenarios.

Virtual avatars are also used for visual merchandising, allowing customers to select various outfits online.

"We use AI technology to analyze vast amounts of data and predict trends scientifically. Our designers curate final design insights based on our brand DNA and market trend awareness. We value the designer's role as a curator and will keep enhancing trust among our clients through advanced technology and data curation," said Sue Lee, vice president of design and R&D at ShinWon.