HOTSHOTS: Meet EasySize

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If you work in e-commerce, you are probably familiar with one of the major problems in fashion e-commerce: rate of items returned. Successful e-commerce websites understand how customer’s satisfaction is a major asset and they invest large quantities of cash to ensure the item replacement process goes seamless. Nevertheless, looking from a customer’s perspective, it may still be very disappointing to have to return your item to a company and have to wait for the right size to arrive, specially when you have a deadline. There is much anxiety in finding out if the company will be able to fulfill delivery in time.

With this in mind, Gulnaz and her team of “data geeks and fashion enthusiasts” joined forces to create Easysize: a plug&play algorithm for providing size guidance to customers during online purchases.

EasySize finds a customer’s best fit in seconds using existing data, without the need for physical or clothes measurements. It uses crowdsourced fashion data and advanced algorithms to ensure the 90%+ accuracy of the size prediction. For new customers without a shopping history, it predicts the best fit based on the customer’s sizing with other brands.

Easysize algorithm in action

Large brands in Denmark and abroad are currently using this solution with great success.

In this week’s video, we talked to CEO and Founder of Easysize,  Gulnaz Khusainova. She tells us a little more about her startup, her challenges as a foreigner entrepreneur in Denmark and her expectations to the future. I hope you enjoy our video and remember to share!

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Rafael Berti is an entrepreneur with long international experience in e-commerce sales and management. He is an aficionado for technology and loves assisting other businesses willing to step into Latin America, providing consulting services from his firm, Biassa.

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