Predicting Sales of Cross-chain Discrete Manufacturing Products Based on LSTM

In the mass customization product value chain, the sales forecast in the marketing chain is important. Traditional forecasting methods only consider the previous sales volume, which is a single value chain factor. In fact, with the rapid development of online media, the factors affecting the sales of manufacturing products have become increasingly complex. For example, the attention and evaluation of online social media is an important influence on sales forecasts. In addition, other influencing factors such as stocks also have a certain impact on product sales. Therefore, it is possible to integrate cross-domain information to improve the accuracy of prediction results.In this paper, we propose an LSTM model with the portal's attention index, and involve factors from multiple domains, such as the network media, market environment and original product sales volume. Experiment results show that using the proposed cross-domain approach obtains more accurate prediction results than other mainstream models.