Understanding customer behavior using indoor location analysis and visualization

摘要

Understanding customer behavior in brick-and-mortar stores and other physical indoor venues is essential for any business aiming to provide a more personal and compelling shopping experience, optimize store layout, and improve store operations. Achieving these goals ultimately leads to improved user experience, conversion rates, and increased revenue. Today's mobile-based location technologies provide information about the user's location that can be used in advanced analytics and visualizations. This means retailers and enterprises can gain insight into customer behavior patterns and understand, for example, how much time customers spend in different areas of the store, what routes they take, how well they are serviced, and more. In this paper, we present a solution approach for better understanding customer behavior based on mobile indoor location data as well as the technologies developed by IBM Research for realizing this solution. We describe significant challenges considering collection, curation, analysis, and visualization of indoor location-based data and illustrate the use of the approach for smarter commerce in a real-world use case.