The effectiveness of e-commerce in empowering rural revitalization is often influenced by multiple factors, and there are complex nonlinear relationships between these factors, making it difficult to capture data characteristics and affecting the reliability of evaluation results. Therefore, in order to clarify the effectiveness of e-commerce in empowering rural revitalization and improve evaluation reliability, convolutional neural networks are introduced to conduct research on the evaluation method of e-commerce in empowering rural revitalization. Selecting evaluation indicators for the effectiveness of e-commerce in rural revitalization, and combining them with convolutional neural networks to construct an evaluation model. Based on its powerful nonlinear mapping ability, it automatically learns the nonlinear features in the data to more accurately evaluate the effectiveness of e-commerce in rural revitalization, and accurately obtain the coordinated development of rural e-commerce, farmers’ income increase, and rural revitalization in a certain city. The study’s findings reveal that this methodology not only aids in the transformation of agricultural production in Jiyuan City and the modernization of rural primary, secondary, and tertiary industries, but also catalyzes the transformation and enhancement of agricultural production and the integration of urban and rural development. Additionally, it contributes to narrowing the gaps between urban and rural areas in income, environment, and institutional frameworks, thereby promoting the achievement of rural revitalization in Jiyuan City. At the same time, it can also provide effective references for other regions of China in terms of working modes and methods to consolidate the victory of farmers in poverty alleviation and income generation and to realize the rapid revitalization of the countryside.