Research Of Data Mining On Railway Freight Product Marking

In recent years, as competition intensifies among different modes of transport, the market structure of Chinese cargo transport industry has been changed dramatically, and the market share of China’s railway freight transportation has been in decline year by year. But it can not only be ascribed to the full development of other modes of transport, the main reason is that railway transportation itself has many deficiencies. Thus in order to follow the trend of railway transport reformation and reverse the current passive situation, railway freight departments have to strengthen product marketing management and map out rational as well as effective marketing programs and strategies, in which utilizing the data mining technology to deeply analyze the mass freight data accumulated in information system will be an important research direction.After consulting and acquainting with many successful cases about data mining, this paper will illustrate the universality and reliability of data mining technology. Meanwhile, the paper works out a product marketing research program based on data mining in accordance with the speciality of China’s rail freight products and the status as well as problems of rail freight marketing. This program aims to take advantage of the mature data mining technology to make a further analysis on the large amount of historical data accumulated in transportation departments and to rely on applicable data mining model to find out the valuable rules hidden in the database, developing more railway freight markets and customers. Also, combined with modern marketing concepts, the paper, which builds up a rail freight product marketing system, chooses appreciate data mining technology according to the characteristics of investigating objects and respectively makes specific marketing analysis from three aspects:market segments, freight product & service association and customer value segmentation. First, after collecting large freight data, it predicts the orientation of railway freight transportation market and exploits a well-behaved market by using time-series pattern. Second, it will launch some suitable promotion service portfolios by resorting to the hidden relevance (which is explored through the association rules) between cargo service projects. Third, it uses cluster analysis to profile customers and makes different product marketing strategies according to customers’ features and needs.All in all, mainly based on the original data of shipping order, this paper analyzes the trend of market development and the spending patterns of customers in accordance with the freight product marketing process which is in view of data mining technology. It also proposes railway freight transport product marketing strategies which are scientifically valid and clearly targeted. It provides a new idea and a new direction for the future freight marketing development.