Using Context to Improve Predictive Modeling of Customers in Personalization Applications

The idea that context is important when predicting customer behavior has been maintained by scholars in marketing and data mining. However, no systematic study measuring how much the contextual information really matters in building customer models in personalization applications has been done before. In this paper, we study how important the contextual information is when predicting customer behavior and how to use it when building customer models. It is done by conducting an empirical study across a wide range of experimental conditions. The experimental results show that context does matter when modeling the behavior of individual customers and that it is possible to infer the context from the existing data with reasonable accuracy in certain cases. It is also shown that significant performance improvements can be achieved if the context is "cleverly" modeled, as described in this paper. These findings have significant implications for data miners and marketers. They show ...

• Type: Journal
• Year: 2008
• Where: TKDE
• Authors: Cosimo Palmisano, Alexander Tuzhilin, Michele Gorgoglione
• Keywords: Contextual Information, Customer Behavior, Customers, TKDE 2008