01914nas a2200145   4500008004100000245005100041210005100092260001600143520143700159100002301596700002001619700002001639700002401659856008501683       2015                        eng d00aBehavioral Entropy and Profitability in Retail0 aBehavioral Entropy and Profitability in Retail  aParisbIEEE3 aHuman behavior is predictable in principle: people are systematic in their everyday choices. This predictability can be used to plan events and infrastructure, both for the public good and for private gains. In this paper we investigate the largely unexplored relationship between the systematic behavior of a customer and its profitability for a retail company. We estimate a customer’s behavioral entropy over two dimensions: the basket entropy is the variety of what customers buy, and the spatio-temporal entropy is the spatial and temporal variety of their shopping sessions. To estimate the basket and the spatiotemporal entropy we use data mining and information theoretic techniques. We find that predictable systematic customers are more profitable for a supermarket: their average per capita expenditures are higher than non systematic customers and they visit the shops more often. However, this higher individual profitability is masked by its overall level. The highly systematic customers are a minority of the customer set. As a consequence, the total amount of revenues they generate is small. We suggest that favoring a systematic behavior in their customers might be a good strategy for supermarkets to increase revenue. These results are based on data coming from a large Italian supermarket chain, including more than 50 thousand customers visiting 23 shops to purchase more than 80 thousand distinct products.1 aGuidotti, Riccardo1 aCoscia, Michele1 aPedreschi, Dino1 aPennacchioli, Diego  uhttps://kdd.isti.cnr.it/publications/behavioral-entropy-and-profitability-retail