Product Experience Wall: A Context-adaptive Outfit Recommender System

Abstract

This paper presents research in progress and describes the concept of the so called „Product Experience Wall“, an interactive and context-adaptive outfit recommendation system for retail fashion stores. The goal is to design an experiential system that serves both, functional and hedonic needs. Context adaption allows pro-actively approaching the user and recommending products based on the respective user context. Next to face detection algorithms, we use RFID sensors and interfaces to external data sources (e.g., weather information) to create a unique customer experience. This experience is furthermore supported by displaying product combinations on virtual, life-size avatars. The core functionality of the concept is based on the findings of 32 qualitative customer interviews.