The key question of this study is: How long should the length of customer event history be for customer churn prediction? While most studies in predictive churn modeling aim to improve models by data augmentation or algorithm improvement, this study focuses on a another dimension: time window...

The purpose of this paper is to evaluate whether pictorial data can improve customer churn prediction and, if so, which pictures are most important. We use Random Forest and five times twofold cross-validation to analyze how much pictorial stimulus-choice data increase the AUC and top decile...

Since customer relationship management (CRM) plays an increasingly important role in a company’s marketing strategy, the database of the company can be considered as a valuable asset to compete with others. Consequently, companies constantly try to augment their database through data...

Several supervised learning algorithms are suited to classify instances into a multiclass value space. MultiNomial Logit (MNL) is recognized as a robust classifier and is commonly applied within the CRM (Customer Relationship Management) domain. Unfortunately, to date, it is unable to handle...

Since it is generally recognized that models evaluated on the data that was used for constructing them are overly optimistic, in predictive modeling practice, the assessment of a model’s predictive performance frequently relies on a one-shot train-and-test split between observations used for...

In this research we use the framework of market-basket analysis and techniques from modern multivariate time-series analysis to measure and explain the dynamic impact of a price promotion on the sales of a complementary product. The large scale of this research enables us to derive empirical...

Undoubtedly, Customer Relationship Management (CRM) has gained its importance through the statement that acquiring a new customer is several times more costly than retaining and selling additional products to existing customers. Consequently, marketing practitioners are currently often focusing...

In an era of strong customer relationship management (CRM) emphasis, firms strive to build valuable relationships with their existing customer base. In this study we attempt to better understand three important measures of customer outcome: next buy, partial defection and customers’...

In this study, we propose a customer-oriented conceptual model of segmentation variables for mail-order repeat buying behavior. We investigate (1) from a theoretical perspective what customer-related variables should be included in response models for modeling repeat purchasing, and (2)...

Although most data mining (DM) models are complex and general in nature, the implementation of such models in specific environments us often subject to practical constraints (e.g. budget constraints) or thresholds (e.g. only mail to customers with an expected profit higher than the investment...