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|Title||How much is a Customer Worth? Exploring Techniques to Improve the CLV Prediction in Retailing Industry|
|Institution||University of Zurich|
|Faculty||Faculty of Business, Economics and Informatics|
|Number of Pages||42|
|Abstract Text||With customer lifetime value (CLV) playing a great role for firms to evaluate marketing decisions, this bachelor thesis aims at giving an overview of how accurate the estimation of individual CLV is by analyzing the purchase history of multiple retailers. In a first step, findings from previous studies are summarized and different dataset characteristics are discussed. In a second step, the results of customer behavior prediction with a hiatus heuristic and with an advanced analytics are compared. Moreover, it will compare the impact of variations of the prediction period over multiple cohorts by analyzing real-world data from multiple retailers. The results of the customer base analysis indicate that the predictive performance strongly depends on the dataset characteristics and the length of the prediction period. Keywords: customer lifetime value, Pareto/NBD, hiatus heuristic, forecasting, cohort comparison, customer base analysis|