AI-enabled Personalized Product Recommendation System

Online shopping has been growing rapidly in the last decade, especially since the COVID pandemic when citizens tend to stay home to avoid crowded areas, e.g., shopping mall. ShopHopper is on a mission to modernize local shopping by making it as easy to shop locally as it is to shop on Amazon. We are building a local shopping marketplace that will give the same tools and technology to local retailers, making it easier for consumers to support them. What retailers really need is a solution for retailers to get their products in front of more shoppers, who care about their brand and products. This is why we’re building an AI driven personalized shopping assistant. With this tool, we can automatically match products from local retailers to the preferences of local shoppers (and even global clients) making it convenient for shoppers to find perfectly matched outfits from local retailers. We know that greater personalization equals greater engagement. This proposed project will give local retailers the growth marketing sales channel they need to scale their e-Commerce business, compete with big e-Com/big box stores, and sustain themselves as independent retailers.

Faculty Supervisor:

Irene Cheng

Student:

Partner:

Shop Hopper

Discipline:

Computer science

Sector:

Retail trade

University:

University of Alberta

Program: