The topic of innovation appears again and again in the government work report. The state and enterprises also pay more and more attention to product optimization and the output of innovative products, and more innovative and technological content has emerged from the products. At the same time, China’s foreign trade is transitioning from the traditional big country of foreign trade to the modern foreign trade power. In this paper, we combine natural language understanding and interactive image command mapping networks to improve the command optimization of digital products. The improved Graph-LSTM model is utilized to process the natural language instruction vectors, and the ICF network is utilized to take the environment image and user instructions as inputs to construct a fusion network in which the environment image and the natural language instructions can complement each other to complete the instruction mapping and to generate the location heat map for the execution of the instructions. Using principal component analysis, panel regression modeling, and other methods, we extracted and screened indicators of the influencing factors of export trade performance evaluation and constructed the performance evaluation index system. The synergistic enhancement of product instruction optimization and export trade performance is analyzed through empirical analysis and enhancement effect evaluation. The regression results of the selection equation are analyzed, and in the second column of the model, the coefficients of marketing cost and financial cost are 35.254 and -2.568, respectively, and the P-value is greater than 0.1, which can be analyzed in the next stage. In terms of the level of economic development, the difference between the comprehensive performance of export trade between Guangdong and Heilongjiang is 55.11, which is a large gap, and the optimization of product instructions has a greater impact on the performance of export trade in the eastern region.