This paper adopts the combination of fusion features and data clustering analysis, using fusion features and the FasterRCNN algorithm to process the data of artisanal skill cultivation and industrial synergistic development in the context of vocational education and derive relevant features. The features are fused and categorized by means of anchor frame extraction, and the processed data form a feature model. Then, the current development of vocational education in 31 provinces in China was analyzed using data clustering analysis, and Jiangsu Province, which has the best development, was selected for data collection. Six hundred and fourteen pieces of graduate information were selected for cluster analysis, and it was concluded that the cultivation of artisanal skill talents in the context of vocational education has a positive impact on the synergistic development of the industry.