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From mom and pop shops selling garments to stores, mega stores, exclusive stores, and e-commerce, the fashion industry has come a long way. Just when one thought the industry couldn’t get any better, it is now on the road to become smarter. Fashion houses took to AI with a mixed sense of eagerness to innovate and measured reluctance. This has, however, changed with time. AI is increasingly changing the Modus Operandi of the fashion industry. Here’s how!
Design and manufacturing
Earlier retailers would estimate their sales for the current year on the basis of data from the year gone by. But this data may not be quite accurate as sales are driven by a variety of factors that are not factored in. AI can make demand projections quite accurately and save a lot of effort and manufacturer’s money or fashion brands. Post-designing too, AI helps in determining defects, if any, in fabrics, and also better streamlines the quality assurance process with the aid of computer vision tech.
Sales and promotion
As with all consumer goods, the fashion industry too is always exploring new ways to reach more people by creating brand awareness and consequently, demand. AI and ML help in bringing the customers closer to the brands by way of interactive chat systems or chat bots in e-commerce which speak to the customers and answer questions or concerns, and also gather data which aids the business of fashion. Burberry, for example, started using chatbots during London Fashion Week 2016 to provide behind-the-scenes insights to customers. The brand is now using the Facebook Messenger to notify customers of new product launches, pre-order invitations etc. Not only do chat bots aid the customer in getting what they want they gather valuable data for the brand which can be implemented to drive sales.
AI helps consumers get near-precise to precise results of what they are looking for thus boosting sales. In one of our engagements for a fashion giant, if a consumer keys in the words ‘glittery teal stilettos’ on an e-commerce portal, the search engine tries to match these words with that of the product description to display on their screen the desired results. In case, there is no match for those words in the product description they get ‘No Results’ on the screen. The descriptions that a search engine has are called vectors, and each product has 10-12 vectors. Our proprietary tool, sherlock.Ai is changing this by providing another layer between the search engine and the product description. In this new layer, the search engine additionally searches its knowledge base such as dictionary, Wikipedia, and even metadata of product images to increase the previous 10-12 vectors to about a 100. To a customer this would translate to greater chances of finding what they are looking for and lesser chances of getting a ‘No Results’ display on their screens.
Counterfeit detection
Like the luxury watch industry, luxury fashion brands too face the issue of counterfeits. Exact looking but inferior quality products leave a negative influence for the brand in the customer’s eyes and AI is here to help. Drawing from big datasets and pictures of online marketplaces, AI is used to detect goods that may be counterfeit. Furthermore Machine Learning enables computer vision to detect counterfeit or fake products which was the job of human experts earlier. AI can constantly track fake products and such tech is increasingly put to use by customs officers.
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