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Lauren Blumberger

Indoor Positioning Technology: Exploring Analytical Methods of Understanding Visitor Behaviour in a Retail Environment ©2016

Understanding visitor behavior in indoor spaces is essential for any business aiming to improve customer experience and ultimately increase revenue. This is particularly applicable in the retail industry, which has evolved immensely over the past decade. Changes have primarily emanated from an explosion in the number of shoppers purchasing online and, in response, to the adoption of location technologies by brick-and-mortar venues. While individual stores have been leveraging the ability to track objects, employees and customers for some time, shopping centre owners have just begun deploying positioning systems in the past few years. Today's crowded vendor space for positioning technologies provides clients with information about visitor location that can be used in advanced analytics and visualizations. This means shopping centre owners can gain insight into customer behavior patterns and understand, for example, how much time customers spend in different zones, what entrance they arrive from, what routes they take, and how well they are serviced. This paper focuses in on the shopping centre as a space to explore potential solutions for better understanding customer behavior, using indoor location data produced from a Wi-Fi mesh sensor network. The methods presented blend sales, social media, floor plan, and sensor data, while working through significant challenges related to the collection, analysis, and visualization of this data. The results of this multimethod approach are combined on interactive dashboards to illustrate how property owners can implement positioning technology and location analytics for smarter commerce.