Abstract-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 that contextual information does matter in personalization and companies have different opportunities to both make context valuable for improving predictive performance of customers' behavior and decreasing the costs of gathering contextual information.

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Purpose-This study proposes to model customer experience as a 'continuum', labelled Customer Experience Continuum (CEC). We adopt a customer experience quality construct and scale (EXQ) to determine the effect of customer experience on a bank's marketing outcomes. We discuss our study's theoretical and managerial implications, focusing on customer experience strategy design. Design/methodology/approach-We empirically test a scale to measure customer experience quality (EXQ) for a retail bank. We interview customers using a means-end-chain approach and soft-laddering to explore their customer experience perceptions with the bank. We classify their perceptions into the categories of 'brand experience' (pre-purchase), 'service experience' (during purchase), and 'post-purchase experience'. After a confirmatory factor analysis, we conduct a survey on a representative customer sample. We analyze the survey results with a statistical model based on the partial least squares method. We test three hypotheses: 1) Customers' perceptions of brand, service provider, and post-purchase experiences have a significant and positive effect on their experience quality (EXQ), 2) EXQ has a significant and positive effect on the marketing outcomes, namely share of wallet, satisfaction, and word-of-mouth, and 3) The overall effect of EXQ on marketing outcomes is greater than that of EXQ's individual dimensions. Practical implications-Banks should focus their customer experience (CE) strategies on the Customer Experience Continuum (CEC) and not on single encounters, tailoring marketing actions to specific stages in a customer's CE process. Different organisational units interacting with customers should be integrated into CE strategies, and marketing and communication budgets should be allocated according to CEC analysis. The model proposed in this paper enables the measurement of the quality of CE and its impact on marketing outcomes, thus enabling continuous improvement in customer experience. Findings-The results of the statistical analysis support the three hypotheses. Originality/value-The research proposes a different view of customer experience by modelling the interaction between company and customer as a continuum (CEC). It provides further empirical validation of the EXQ scale as a means of measuring customer experience. It also measures the impact of customer experience on a bank's marketing outcomes. It discusses the guidelines for designing an effective customer experience strategy in the banking industry.