A Study Of Pricing For New Product Marketing Test On Dual-channel System

A new product for an enterprise, which is a new project, it requires multiple choice, the companies need to allocate his resources, such as financial, human resources and so on. What factors are make products to marketing quickly, this is the choice of a business strategy, because the new product determines the future market image for that company. According to statistics, the company’s 50 percent sale is come from new product introduced in five years. So we need to balance the return of investment, the maintenance and development, as well as short-term and long-term new product plans.With the development of various online media, as well as maturity of the e-commerce, online shopping has entered people’s daily life, the emergence of large online retailer, such as Amazon and Alibaba, has make the shopping online into the household. So the big traditional retailers have set up their own network sales channels as well. With this new multi-kinds of sales channel system, how to price? How to make the maximum profit for their products? In particular, how is the pricing for the new product? What’s the relationship between those channels? Is the lower prices on online will impact of the store sales?With the new channel, it brings uncertainty and variability, new opportunities and competitor, multi-objective and multi-strategic considerations. How to make decisions? If we just rely on a simple meta-analysis, we are unable to finish this arduous task. Because pricing for a new product is dynamic, integrated management process. Therefore, the pricing for a new product on dual-channel has been born.This paper introduces the important of pricing for a new product and dual-channel sales based on the background. Comparing similarities and differences between the characteristics of the retail data, demonstrated the characteristics of different retail channels, systems, and solutions, and then draw on the results of the model analysis. After that, use the Markov matrix to quantify the new products sales and transfer probability, next, established the consumer decision tree, and then re-define the classification. Next step, use the logistic regression analysis of the new increment and transfer, to make up for the deficiency of Bass model can’t predict the fast consumer goods, based on the above analysis of the model to matching the price, to obtain the optimal results. Provide customers with pricing, promotions and other multi dimension, a series of solutions, to help enterprises achieve profitability, development planning and reasonable. Then use the operational data of several large retailers, analysis, targeted to retail oriented new product of multi-channel retail obtain results, verify the feasibility of our model.