In text books as well as in the business literature, market basket analysis is often promoted as a means to obtain product associations to base a retailer’s promotion strategy on. They argue that associated products with a high lift/interest can be promoted effectively by only discounting just...

In the first part of this paper we present an overview of e-commerce and Internet characteristics. We explain why data mining plays a central role among the digital marketing technique: it is the tool to achieve customer knowledge, the key of success in the wide but highly competitive world of...

There are two main research traditions for analyzing market basket data that exist more or less independently from each other, namely exploratory and explanatory model types. Exploratory approaches are restricted to the task of discovering cross-category interrelationships and provide marketing...

Our research examines the hypothesis that products chosen on a shopping trip to a supermarket indicate the preference interdependencies of consumers between different products or brands. The bundle chosen on the trip can be regarded as an indicator of a global utility function. This function...

Based on market basket data, multicategory purchase incidence models analyze demand interdependencies between product categories. We propose a finite mixture multivariate logit model to derive segment-specific intercategory effects of market basket purchase. Under the assumption that only a...

Modern statistical data analysis is predominantly model-driven, seeking to decompose an observed data distribution in terms of major underlying descriptive features modified by some stochastic variation. A large part of data mining is also concerned with this exercise. However, another...

The following research is guided by the hypothesis, that products chosen on a shopping trip in a supermarket are an indicator of the preference interdependencies between different products or brands. The bundle chosen on the trip can be regarded as an indicator of a global utility function. More...

Data Mining is used to describe the totality of techniques which aim to find the unexplored patterns in a set of data. The purpose of data mining is to create models of decision-making devoted to estimations of future behavior based on analysis of past activities. In this study the shopping data...