When firms are able to recognize their previous customers, they may be able to use their information about the consumers’ past purchases to offer different prices and/or products to consumers with different purchase histories. This article surveys the literature on this “behavior-based price discrimination.” *Forthcoming in the Handbook on Economics and Information Systems, Elsevier. We thank M...

Aggressive marketing campaigns to attract new customers only covers customer churn, resulting in neither growth nor profitability. Retaining current customers, increasing their lifetime value, and reducing customer churn rates, thereby allowing greater efforts and resources to be dedicated to capturing new customers are the goals of a commercial director. But how can that loss be detected in ti...

Web usage mining techniques are increasingly used today to understand e-customers’ within-site behavior. We propose a data mining model that considers e-customers’ activities as a discrete-time semi-Markov process and explains their behavior. An algorithm is proposed to compute transition probability matrix and holding time mass functions from the site navigation data. Finally, the model is use...

The customer relationship management (CRM) is a business methodology used to build long term profitable customers by analyzing customer needs and behaviors. The customer behavior is analyzed by choosing important attributes in the customer database. The customers are then segmented into groups according to their attribute values. The rules are generated using rule induction algorithms to descri...

Online brand communities, enabled by social media technology, are being utilized by companies to improve marketing and sales. However, little is known about how to encourage customer interactions in an online brand community and whether the interactions can affect purchase behavior. To address these research questions, we explore factors that influence the formation of social interactions in an...

The calculation of customer value without regard to marketing policy is problematic because the value of managerial flexibility and the impact of consumer learning are neglected. This article develops a structural dynamic programming model of consumer demand that includes marketing variables and consumer expectations of promotions. The author uses the estimated parameters to conduct policy expe...

Predicting customer purchase behavior in the e-commerce activities is an important task. However, this effort requires fulfillment of a lot of problems. Recommendation systems have become a common way how to help peo-ple when they have to decide in complex selections. But they are not able to perform predictive tasks in this context satisfactorily. In this paper, we deal with a design of a pred...

A seller in showroom does not know that what goes in mind of consumer when the consumer enters the shop to buy TV. Seller has to rely on trial and error basis this research will tell what factor consumer considers so that he comes to a particular shop. Thus he can convert maximum of potential customer into buyers if he knows what exactly triggers the customer decision. The research discloses th...

The last few years have seen an increased interest in incorporating context within recommender systems. However, little empirical evidence has emerged to support the premise that context can actually improve recommendation accuracy. Indeed little agreement exists as to what represents the context of a user or indeed how such context should be used within a recommendation strategy. In this paper...