Expert-Driven Validation of Rule-Based User Models in Personalization Applications
Data Mining and Knowledge Discovery
A Mental Cognitive Model of Web Semantic for e-Customer Profile
DEXA '02 Proceedings of the 13th International Workshop on Database and Expert Systems Applications
Design of a shopbot and recommender system for bundle purchases
Decision Support Systems
A Logit Model of Brand Choice Calibrated on Scanner Data
Marketing Science
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Spurred by rapid development of computers and Internet technology, online shopping is gradually overtaking in-store shopping, because of advantages such as convenience, more choice of products or services etc. Online stores must devote a great deal of time and resources to locating and attracting new customers. Growing a customer base requires first understanding customers and then providing the products or services they need, thus encouraging customers to purchase more. This paper develops a system to analyse customers’ purchasing behaviour and track shifts in their interests. Customers’ purchasing behaviour is measured using proposed standard product loyalty status and standard brand loyalty status. Using these metrics, together with the preference map established for each customer, a marketing specialist can easily locate potential customers to target when a company launches a new product. The new-product-launch strategy proposed in this paper can be used to create a list of potential customers for a product being launched under a variety of conditions. A prototype system has been built to test the feasibility of the proposed new-product-launch strategy. The result shows almost 40% of potential customers respond to the recommendation positively. © 2012 Wiley Periodicals, Inc.