Wish-List Based Shopping Path Discovery and Profitable Path Recommendations

Retail customers find shopping in huge retail malls stressful due to various reasons such as being unable to locate the items, overcrowded stalls and long queues. In this paper, we present a solution to determine optimal shopping paths to locate the items based on the wish-list of a customer. We developed a graph theory based approach to discover shopping paths based on the shelf-item layout and customer's purchase patterns. We also propose an efficient approach to recommend profitable shopping paths to cross-sell potential buy-in items close to base shopping path. Our approach also facilitates updating the item list and discovering the paths dynamically while shopping. The proposed solution provides enriched shopping experience to customers.