Data-Driven Models for Promoting Impulse Items in Supermarkets
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This research seeks to investigate whether systematically designing the layout of supermarkets can effectively influence customer shopping decisions. We argue that utilizing analytical models for optimally locating products within the store layout can increase the exposure of "impulse items", thus potentially inducing changes in the customer final shopping lists.Supermarkets have the potential to sway customers shopping list by promoting "impulse items" throughout the store. The customer is often submerged with various items during their shopping trip. For instance, strategically placing the diary department in the rear end of the market exposes customers to an array of promotional products that serve as external memory cues that simulate new needs or triggers forgotten needs. Supermarkets can use this power to promote healthy products to fight against obesity; since obesity is linked to more than 60 chronic diseases. According to the American Cancer Society, 572,000 Americans die of cancer each year where one-third of these cancer deaths are related to excess body weight, poor nutrition and/or physical inactivity.This project will investigate how a retail store layout can influence customers decisions by: (1) How to use historical purchase data in order to understand the customers shopping patterns, and identifying customers’ plan and unplanned purchases? (2)How to build a data driven model that finds the optimal layout of traditional retail store, by increasing the visibility of "impulse items"? (4) How to optimize the product placement of items in promotional areas? (5) Building a framework for a Recommender System for an Online Supermarket. It is imperative to collect customer data to accomplish the objectives for the sake of understanding customer shopping patterns in a retail store. The data will serve as inputs for the proposed models and validate models.