استراتژی های قیمت گذاری و ارتقاء یک فروشگاه آنلاین بر اساس تقسیم بندی مشتری و تصمیم گیری چند هدفه

The advent of the Internet and web technologies has enabled the prosperity of virtual stores, which greatly reduce customers’ search costs and retailers’ overhead. However, the furious competition between online shops makes it difficult for them to generate profits. This study attempts to establish pricing and promotion strategies for online shops to enhance their profitability. The pricing decision is based on the concept of customer relationship management, where a greater margin of price concession is given to customers who are more valuable to the shop. The process of our approach is: clustering customers into different classes based on their RFM data, computing and presenting the list prices of products to customers according to their classes, allowing customers to bargain over the price and offering conceded prices which are computed based on customer classes and a multi-objective decision making model, and finally providing promotion options to customers to reinforce their purchase inclination. The proposed approach is implemented at an online shop of a computer peripherals retailer. Transaction data before and after the implementation are collected and compared to assess the performance of the proposed approach.

Business-to-consumer electronic commerce provides a new and effective channel for retailers and their consumers to perform online transactions through commercial Web sites. However, the furious competition between online shops makes it difficult for them to generate profits. The competition arises from the following combination: reduced barriers to product information, easier access to a great number of potential suppliers, and increased threat of substitutes (Wilson-Jeanselme & Reynolds, 2005). Furthermore, the Internet has reduced the differentiation among products and services and hence has switched the focus of customers to price discounting (Porter, 2001). Consequently, buyers generally surf through many shops and compare their list prices of the target product to look for the best offer on the Internet. Therefore, unless visitors of the online shop can be converted into buyers and be kept by creating value for them, online transactions will not be profitable (Wilson-Jeanselme & Reynolds, 2005). The list price of a product of an online shop is generally the first factor that determines if a visitor will stay and further seek a chance to get a bargain. The belief that price is a primary purchasing determinant for online buyers was reinforced by the objective of always offering the lowest prices of some online shops (Kung, Monroe, & Cox, 2002). Price promotions significantly affect consumers’ price perception (Folkes & Wheat, 1995). For example, offering a product with a rebate results in higher perceptions as measured by the most one would pay (Laroche, Pons, Zgolli, & Kim, 2001). Such a consumer behavior has been explained from a mental accounting perspective by Thaler (2008). The transaction utility theory of Thaler (2008) suggested to price a product according to its value perceived by customers, where the perceived value is the sum of the customer’s acquisition utility and transaction utility, in which the utility function involved three factors, namely the actual price, the reference price, and the reservation price (i.e. the maximum the individual would pay). Web-based pricing strategies differ with the merchant, the market, and the type of customer (Awad, 2004). In other words, different market strategies should be applied to different type of customer to enhance profitability and customer satisfaction. Personalization is a mean to achieve such a goal. When being applied in market segmentation, personalization can transform a standard product into a specialized solution for an individual. Businesses are able to know their customers’ buying behaviors and thus develop appropriate promotion actions to attract each customer of a specific type. Through personalization, the customer’s satisfaction and loyalty can be enhanced, and the increase of each customer’s visiting frequency can further create more transaction opportunities and hence benefit the online shop (Lee, Liu, & Lu, 2002). A number of web-based personalized systems have been developed, e.g. Borchers, Herlocker, Konstan, and Reidel (1998), and Changchien, Lee, and Hsu (2004). Personalization usually works by filtering a candidate set of items through some presentation of personal profile. For example, a prototype system of Changchien et al. (2004) for online personalized sales promotion consisted of three modules, namely marketing strategies, promotion patterns model, and personalized promotion products, to select promotion products based on the experiences analyzed and retrieved from historical transactions. The authors also used simulations to evaluate the performance of their prototype systems. To enhance the profitability of online shops, the present study also uses personalization to suggest different pricing and promotion strategies in the transaction process. In addition, the pricing and bargaining decisions are based on the concept of customer relationship management (CRM). In our pricing strategy, a lower list price will be presented to customers who are more valuable to the shop, and a greater margin of price concession will also be given to such customers in the further bargaining process. The proposed approach contains the following steps: • Clustering customers into different classes based on their RFM (recency, frequency, and monetary value) data. •Computing and presenting the list prices of products to customers according to their classes. •Allowing customers to bargain over the price and offering conceded prices which are also computed based on customer classes. • Providing promotion options to customers to reinforce their purchase inclination. The proposed approach is implemented on the online shop of a computer peripherals retailer in Taiwan. Transaction data before and after the implementation are collected and compared to assess the performance of the proposed approach.

This study has presented the effects of implementing pricing and promotion strategies at an online shop of a computer peripherals retailer. The pricing decision is based on the concept of customer relationship management, where a greater margin of price concession will give to customers who are more valuable to the retailer. The concessive magnitude was determined based on a multiple objective decision making model, and was solved by a max–min approach. Transaction data before and after the implementation of the proposed pricing and promotion strategies were collected and compared to assess the performance of the proposed approach. The findings from the empirical results include: (1) the sales performance after the implementation of pricing and promotion strategies is significantly greater than that before the implementation; (2) there is no significant evidence that customers of different classes prefer different promotion options, which implies that there is no need to differentiate the promotion options among different classes of customers; and (3) the profit rate after the implementation of pricing and promotion strategies is indifferent to that without such an implementation. The last finding encourages the use of pricing and promotion strategies at the online shop, because they are able to improve the total sales of the shop and at the same time they do not reduce the shop’s profit rate significantly.