Precise Target is a clothing recommendation service that brings machine learning to the fashion world. The company wanted to build a mobile platform and engaged in Intrepid’s five-day design sprint process to map out a concept. Shortly afterwards, our design and development team built out Precise Target’s iOS app, Cobrain.
Bringing Machine Learning to Retail
Client: Percise Target Date: 2016 Site: http://www.precisetarget.com/
Intrepid create a mobile app that serves up suggestions based on preference history and location. Users can further personalize their feed by using filters that only show products sold at local shops and malls.
Like many online shopping experiences, users can uses categories and filters to narrow down results. However, Cobrain also incorporates the user’s tastes and product preferences, so that they can choose to see only the recommended results that suit their style.
Intrepid incorporated findings from user testing to to design a means for encouraging users to rate products—feedback that allowed the app to provide smarter recommendations that more closely fit the style and taste of the user.