Clustering Analysis for Shoppers’Trajectory in Store Using String Similarity

The huge collection of movement data is significant and precious information in various application domains. Many different studies have been done towards interpreting this data to get some hidden information on it. For this purpose, grouping certain shoppers based on their behaviors is one of important strategies in grocery store business. Shoppers’trajectory presents how the behavior of shoppers is. For the marketing side, shoppers movement trajectories are valuable to be analyzed in order to have better understanding of their behaviors in a store. To have proper and meaningful groups of shopper, business intelligence strategy based on clustering and string similarity analysis is performed. And in the experimental results this approach has performed better than traditional approach. Then hopefully, this valuable information will help store managers to manage store and leads to increase sales accordingly.