Practical Applications of Signal Processing and Machine Learning in a Dynamic Retail Environment

Abstract

The retail industry is the midst of rapid change due to intensifying competition from fragmented and non-traditional sources, expansion of assortment breadth and product availability, and more transparent pricing. Evolving consumer expectations have applied stress to traditional retailing approaches and existing networks. To adapt, the application of analytical methods has become pervasive across a wide range of retailing functions including marketing, merchandising, logistics, and pricing. In this talk, we will discuss methods to overcome emerging supply chain constraints, how cross-channel demand information can be used to inform localized assortment decisions, and the use of customer insights and visual learning to enable personalized shopping experiences.