Revolutionizing the fAshIon industry

Artificial intelligence is now playing an important role in terms of changing the shopping experiences by using machine learning algorithms to analyze, track and satisfy consumer-specific needs. Imagine a user taking a picture of someone wearing a dress that he has liked, or something as abstract as a painting, and the image-recognition search engine searching the huge database of products that can be bought to make available the desired or similar items.?

AI can serve as a communication platform to update customers on collection releases and product availability. It can provide interactive storytelling and unique digital experiences with the help of creative algorithms. Also, it can strengthen e-commerce by tracking users’ preferences and give them a customized shopping experience.

Let us see an example from the Guangdong province of China, where a group of shoppers experienced smart clothing recommendations integrated with an intelligent fitting room in stores of Jack & Jones and VeroModa. With the help of facial recognition technology, a magic mirror system allows customers to view the clothes selected. To further enhance the consumer experience, the technology considers gender, age, climate and other predilections and offers recommendations to swap clothes and eliminates the need to constantly shuttle between clothing racks and changing rooms.?

An AI machine will crunch fashion data related to millennial, current color and silhouette trends, trend forecasts for the next season, what movie stars are wearing and such similar information, and suggest in a matter of seconds several options to choose from. In comparison, a fashion designing team working manually will take many days to come up with such suggestions. In fact, some experts feel that artificial intelligence systems have now reached a stage where they could well replace the human fashion stylists!

AI can help retailers to leverage massive amounts of unstructured data to improve and personalize the online shopping experience. At present, fashion brands and retailers are dependent on a limited amount of data to forecast the products to order and then the products to discount or replenish towards the end of the season. A wrong prediction results in revenue loss due to mark-downs, wastage and discounted selling of items. AI can help a retailer to align product stocks with demand, and also display products for maximum sales generation by analyzing large amounts of data—for example, browsing and shopping history of customers.

Fashion is an art form similar to music and painting and creating AI models to assist different types of works done by fashion practitioners, including sellers, stylists, designers and buyers, so as to empower the current industry by upgrading its structure while elevating the economy can be a bit challenging. DesiCrew offers a machine learning application that recommends fashion looks by learning user preferences through the Multilayer Perceptron model along with computer vision. To know more contact us on [email protected]