Analytics, Advanced Digital Technologies and AI Initiative (AAAI) Guest Speaker: Felipe Caro

Problem definition

Omnichannel retailers interact with customers both online and offline. So far, they have used this richer information to optimize the sales process by designing the right channel and supply chain structures, and by personalizing offer, pricing and promotions. We advance an additional dimension of omnichannel value: retailers can use online clickstreams to better understand customer needs and optimize store layouts to maximize conversion. Methodology/results: We develop a model where in-store purchases depend on the customer’s shopping list, and the effort required to locate and reach the products within the store. Category location in the store thus drives conversion. We then apply our model to a large home improvement retailer and find that shoppers’ preferences are revealed by nearby online traffic, and hard-to-reach locations lead to lower conversion. Finally, we optimize category-location assignments using our demand model and find that putting higher-interest and higher-price items in the most effective locations can increase revenues by about 2% in comparison with models that ignore online clicks. Managerial implications: We show how using online clickstream information for optimizing offline operations can create significant value. More fundamentally, our results provide a word of caution that in some retail segments like home improvement, longer in-store paths might not necessarily be better.