Electronic Commerce encompasses all electronically conducted business activities, operations, and transaction processing. With the development of electronic commerce in the Internet, companies have changed the way they connect to and deal with their customers and partners. Businesses now could overcome the space and time barriers and are capable of serving customers electronically and intelligently. However. it is quite a great challenge to attract and retain the customers over Internet due to the low barrier of entrance and severe competition. Personalization, a special form of differentiation, when applied in market fragmentation can transform a standard product or service into a specialized solution for an individual. In this research, an on-line personalized sales promotion decision support system is proposed. The proposed system consists of three modules: (I) marketing strategies, (2) promotion patterns model, and (3) personalized promotion products. The marketing strategies contain sales promotion strategies and pricing strategies. Promotion patterns are generated according to various sales promotion strategies, and the promoted prices for the promotion products are generated by considering both the current stages of business life cycle and product life cycle. In the promotion patterns model, by segmenting the market, customer behaviors of three categories can be analyzed by utilizing data mining techniques and statistical analysis to generate personalized candidate promotion products. Finally. multiple evaluation indicators are used and adjusted to rank and obtain the final personalized promotion products. With the promotion products based on customers past frequent purchase patterns, it has the potential to increase the success rate of promotion, customer satisfaction. and loyalty. In this paper, a prototype system was developed to illustrate how the proposed on-line personalized promotion decision support system works in electronic commerce and a simplified case of performance analysis was conducted for evaluation. (C) 2003 Elsevier Ltd. All rights reserved.
