Accurate estimations of fashion trends are important in the modern fashion retail industry. They facilitate effective inventory management, reduce markdowns due to overstocking and thereby increase profits. Estimating production quantity in terms of colour, even of the same design, carries risks for inventory and sales.
Traditionally, buyers, designers and merchandisers have made decisions about colour based on their own experience and fashion sense. However, this project poses a question: is it possible to replace intuition with IT-based evidence to guide retailers when ordering designs in different colours?
Although annual professional reports on colour trends are available, a systematic and fast-response tool for analyzing such trends in fast fashion does not presently exist. This project has developed a reliable real-time estimation of fashion colour trends by using the actual sales records over two years from a multinational fashion retailer and big data from social media. A colour prediction model has been developed which integrates sales, pricing and branding to best meet operational needs such as product planning and inventory management.
The model makes use of a database comprising millions of posts from Facebook and Weibo, two of the most popular social media sites in the Greater-China region. Posts in both English and Chinese are used in the model. Authentic fashion posts that relate to colour are identified through Natural Language Processing (NLP). The model also applies advanced machine-learning methods to improve the accuracy of fashion colour prediction.
The project studied the transmission pattern of fashion colour information in social media and generated equations based on posts from fashion brands, magazines, designers and key opinion leaders.
The model can be customised for different users, based on their market positions and production lag time. In other words, the tool can be modified to match appropriately each user’s particular features and needs.
Upgrading traditional experience-based decision-making with analysis of current big data and machine learning modeling techniques, this project has great potential to generate fashion trend estimations in terms of colour range, style, fitting, and may even function to help drive a form of “new retail”, both on- and off-line.
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|A special prize from National Research Council of Thailand in the 46th International Exhibition of Inventions of Geneva|
|Gold Medal in the 46th International Exhibition of Inventions of Geneva (2018)|
|Related ITF project|
|Research Start Date||2016-09-15|