Sales Micro-Patterns: ML-driven detection of deviant Store/SKU sales patterns

For almost a century, Canadian Tire has been offering products and services to help Canadians with the jobs and joys of life in Canada. Today, with a network of over 1,700 retail locations, Canadian Tire is dedicated to improving products and services offered to the community they serve. With this project, the company aims to examine the patterns of sales among its stores to identify anomalous product sales patterns. The objective is to design and develop a system capable of generating high-confidence automated notification to the stores. Sales patterns will be investigated to identify products deviating from normal patterns. The stores would be notified of the results and incentivized to investigate the flagged Stock Keeping Units (SKUs) for in-store issues, such as missing inventory or tags.

Faculty Supervisor:

Katarina Grolinger

Student:

Partner:

Canadian Tire Corporation

Discipline:

Engineering

Sector:

Retail trade

University:

The University of Western Ontario

Program: