Research On Personalized Pricing Of Commoditiesin Environment Of Electronic Commerce

As consumer’s demands differentiation increasingly, we entered the era of personalization, analysis and study consumer’s personal information,we can provide products and services to consumers which more consistent with consumer’s preferences.Especially in the e-commerce environment, this service is more convenient and received by consumers favor. E-commerce personalized products, personalized service, personalized recommendations developed rapidly, but now,marketing research in personalized e-commerce, most tend to study personalized recommendations of products and services, and rarely involve personalization prices and promotions, do not make the corresponding development of personalized pricing.On the other hand, in recent years, as long as people’s pursuit of personalized and the development of e-commerce personalized service, as an important component of personalized service, personalized pricing attracts more and more people’s attention, coupled with data mining technology daily maturing, the industry respond optimistic to personalized pricing application prospect under e-commerce environment.In this thesis, from the consumer individual behavior, e-commerce product pricing environment and other aspects, analyzes the main steps of personalized pricing. Cotrapose the main three steps of personalized pricing:measure the willingness to pay, search the target customers, implement the personalized pricing plan, based on the mainstream method of measurement of willingness to pay, combined with the customer survey method and level of correlation coefficient of joint analysis method, using clustering to measure willingness to pay (WTP) for each customer; Based on consumers’ willingness to pay, built the personalized pricing model about the product cost, inventory, consumer decision factors, and introduced genetic algorithm, constructed optimization search algorithm to maximize the enterprise profit, to determine the plan for each customer;finally, studied the concrete scheme to implement personalized pricing.The main contents of this thesis are:First, introduced the concept and target of pricing, summed up the traditional pricing methods, analyzed the origin, type and social welfare of personalized pricing. Focus on analysis the steps of personalized pricing and pointed out the challenge and opportunities of personalized pricing in the e-commerce environment.Second, study the methods and techniques to measurement consumers’willingness to pay, and combine the correlation coefficient of level of joint analysis and customer survey thought’s put forward the to measure customer’s willingness to pay (WTP),which is suitable for the research content of this thesis. According to consumers’ demographic information and historical consumption data, using data mining algorithm to calculate the degree of each individual belonging to each group, regard the degree as a coefficient that each consumer associated with the various groups’ willingness to pay,the cumulative sum of the coefficient product the corresponding customer’s willingness to pay is the final WTP for each consumer. Collecting the historical data of consumers shopping data, using the model build in this thesis to measure the willingness to pay, take the direct inquiry value for comparative analysis.Third, study the principles of genetic algorithms, describes the reasons that this thesis select genetic algorithm. Based on consumers’ willingness to pay, built the personalized pricing model about the product cost, inventory, consumer decision factors, and introduced genetic algorithm. Studied the principle of genetic algorithm, the reasons for selecting the genetic algorithm in this thesis, and constructed the optimization method for personalized pricing. According to the willingness to pay get of the experiment,using the genetic algorithm to optimize the model, through a large number of experiments to determine the parameters of genetic algorithm, and analyzed the search results of model.Fourth, studied the concrete scheme to implement personalized pricing, points out that setting the "threshold" is the best choice in personalized pricing, and pointed out that in the implementation of personalized pricing to customers, to mark the prices of the goods at beginning, after analysis through the "threshold" of customer information, or take the initiative to the customer arrive to issue the corresponding discount vouchers to customers.