Retail is the sale of goods and services from a brick-and-mortar business to a consumer for their own use. E-commerce refers to the sale of goods and services via commercial transactions made electronically over the internet. Omnichannel retailing integrates both brick-and-mortar and e-commerce sales channels to provide consumers a flexible retail shopping experience. Global retail sales were US$18.84 trillion of which e-commerce sales accounted for US$ 2.86 trillion representing 15.2% web penetration. Similar to other industries, there has been a growing interest in leveraging data science and related techniques in retail and e-commerce (Retail E-com) to provide a more efficient, convenient and personalized shopping experiences to increase customer foot traffic and spend. With the democratization of machine learning and artificial intelligence, there is a great opportunity to bring awareness of Retail E-com to more experts in the SDM community and tackle problems which can have a wide impact in this multi trillion-dollar industry. There are plenty of opportunities to apply data science in the customer retail journey ranging from pre-interaction marketing, product search and recommendations and inventory management, to warehouse operations automation, delivery prediction and customer aftercare.
We expect our workshop will not only expose current researchers in SDM community to unexplored high impact problems in e-commerce, but also help grow the community by attracting researchers from the broader retail and e-commerce space.
Home Depot
Department of Computer Science at Indiana University Purdue University Indianapolis
Department of Computer Science at Virginia Tech
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