Abstract
In this era, shopping has become an essential part of our daily life. Going for shopping consumes a lot of time. This research studies the possibility of applying recommendation techniques on traditional shopping to offer the only interesting items to clients and make the products more personalized. It adopts approaches of recommendation system that collects, classifies and analyzes the traditional shopping shoppers interests by using membership card (e.g., Iktissab from Abdullah Al Othaim Markets) and other factors by applying collaborative approaches on traditional shopping to provide an accurate personalized shopping list for traditional shopping customers.