Study on inventory control model based on the B2C mode in big data environment

摘要

The current inventory problem has become the key issue in the enterprise survival and development. In this paper, we take “Taobao” as an example to conduct a detailed study of the inventory of the high conversion rate based on data mining. First, by using a funnel model to predict the conversion of the commodities on the critical path, we capture the factors influencing the consumer decision-making on each key point, and propose corresponding solutions of improving the conversion rate; Second, we use BP neural network algorithm to predict the goods traffic, and then obtain the corresponding weights by the relation analysis and the output of the goods traffic by the input of large data sample goods; Third, we can predict the inventory in accordance with the commodity conversion rate and flow prediction, and amend the predicted results to get accurate and real-time inventory forecast, avoiding the economic loss due to the inaccurate inventory.