Using data to reduce waste in fashion
Where did you get that jacket? You MUST tell me where you found that dress. Fashion rules – but behind the scenes is an ecological nightmare. Did you know about 20% of ALL fashion purchases are returned? Trucks filled with clothing, just moving from A to B to A again. Engines running, and carbon dioxide pouring into an atmosphere that isn’t getting any colder.
That’s the reality of an online fashion industry: people buying clothes on a whim, getting it delivered, and finding out it doesn’t quite fit – so they return it. Fair enough – but it’s not good for the environment, it’s not good for consumers, and it isn’t good for retailer’s bottom line, either. Easysize has made a way to make things better for everyone.
By applying machine learning algorithms to the problem, Easysize service can drastically reduce the return rate of online fashion stores.
Easysize’s engineers started their careers working within the online fashion industry. Here, they slowly gained a distinctive insight to the pains of running a large-scale online operation. They realized that keeping return costs low and customer satisfaction high can be contradictory. We all want free shipping, right?
And that’s where the thought of creating the world’s finest algorithm for real-time return monitoring all started. The idea was to combine data from all over the world to recognize patterns and predictability among customers. And, by adding machine learning capabilities, the algorithm grows stronger for every new client that joins Easysize.
KickAss Capital backs Easysize and their important ambition to make the fashion industry more sustainable. Our role includes advice on product development, market development, as well as technical support and communications support, apart from financing.
Founded
2014
Founders
Gulnaz Khusainova
Headquarters
Copenhagen, Denmark
Business model
Software-as-a-Service