FashionHunt

We are a team of four with a shared ambition to radically improve how people are discovering products in e-commerce using smartphones. We do this by developing state of the art algorithms for visual search where we use image pixel data to find similar looking products.

Our technology has its foundations in computer vision and artificial intelligence. It makes it possible to automatically search similar images based solely on pixel information in a given query image. This means that no manual labor or hands-on text tagging needs to be applied in order to take advantage of the technology. Our technology mimics the human perception system and aims at serving a user with the same level of accuracy and understanding as a real human sales person in an offline store.

Our target clients are in a highly competitive market and as a result a primary need of theirs is to improve their competitive advantage. We have identified three common objectives among our clients that aim to fulfill this need.
• Improving conversion rate.
The rate of visitors to a store that convert into paying customers is one of the key performance indicators for an online retailer. It is driven by several factors, one of them being the user interface of the shop. An increase in the rate of conversion due to interface improvements has a significant effect on the shops bottom line profit.
• Increase rate of returning customers.
An increase in the rate of customers who are returning to the site after visiting improves the profitability of marketing efforts.
• Strengthen returns on marketing budgets.
A large part of an online retailers cost base is marketing and having a higher return on marketing activities provides a powerful advantage.