Abstract: Our work outlines an innovative solution for optimizing retail product placement using demand sensing techniques. It addresses the challenge of stockouts and product accessibility by integrating real-time analytics with planograms, data visualization, and sales projections. Employing an LSTM model on extensive sales data, the solution achieved industry-leading accuracy in sales predictions. The interactive dashboard provides detailed insights from category to product level, enhancing strategic decision-making and the customer shopping experience. Initially deployed in the grocery section, the solution is set for expansion across other categories and store locations, showcasing significant advancements in retail analytics.
Student team: Hummarah Shahzad ( / hummarahshahzad )
Ifrah Bilal ( / ifrah-bilal )
Momina Khan ( / momina-khan- )Piyush Kakde ( / piyush25kakde )
Priyanka Shinde ( / priyashi45 )
Mentor:
Shoaib Khan ( / shoaib-a-khan )
Mathew Lanham ( / mattlanham )
MS BAIM Program: business.purdue.edu/masters/p...
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