Ecommerce sites have definitely made our lives easier by making the process of shopping easier and even addictive for some. But, as we are spoiled by the plethora of options available, the excitement turns to greed and finally confusion takes over. As the online fashion market gears up to grow to $35 Bn by 2020, so have the fashion discovery apps.
Fabence, the personalized fashion discovery engine and shopping assistant founded in January 2014, is growing up and adapting fast as well. It’s currently growing up at 30% month-on-month and is coming up with some innovative new features in the coming months. It’s also about to launch its new enhanced website in the next two months.
Anshul Gupta, founder of Fabence, also fell prey to this ecommerce induced confusion, while attempting to buy a t-shirt online. While contemplating the situation, he realized that personalization and smart discovery are key in solving the fashion discovery problem. He met Manish Kumar, cofounder and CTO of Fabence, at a startup networking event. “We both realized that fashion discovery was going to become a huge problem and that scalable technology, personalization and smart discovery would be solution. That’s when we got together and focused on Fabence,” said Anshul.
Anshul believes that there is immense potential in this space as currently, there are just 2-3 players operating in the market and there is room for multiple players to grow together. Apart from end consumers, the concept also appeals to entrepreneurs because the business is very light touch (no inventory, logistics or warehousing costs) and the scalability factor is quite high.
Discovering Personalized Fashion
Fabence offers a variety of features such as shopping with friends, 24/7 in-build personal stylist, personalized shopping feed, and even a virtual closet. Users can either sign in with their Facebook accounts or email ids. Signing in with one’s Facebook account allows the user to explore various features such as ‘shop with friends’ and ‘Your closet’. Facebook friends can be invited during live shopping session to search, assort and shop along with the user. This is a very useful feature for users who hate shopping alone and always second guess their choices.
Its in-built fashion stylist is powered by an intelligence-based algorithm that suggests various fashion ensembles that suits the users, based on their physical attributes. The user provides their physical attributes while signing up.