Traditional product packaging design mainly relies on the designer's personal experience and intuition, but there are problems such as uncontrollable content and lack of knowledge and guidance in the field of product design. With the development of big data technology, product packaging design in the era of big data is carried out under the support of a large amount of real data, which has high predictability, success rate, and short development cycle. Compared with structured data, unstructured data such as text, images, and audio has a higher value. Among them, text big data and image big data have good application prospects in the field of product packaging design due to their easy data acquisition, mature processing technology, and simple operation. This paper proposes a combination of big data technology and neural style transfer model and proposes an innovative design method for product packaging that can generate high-quality images and controllable content. First, the perceptual engineering theory is used to obtain user needs, to build a mapping model between product modeling elements and product semantics, and to guide the selection of product semantics and style maps; second, use neural style transfer models to reconstruct and combine the color features of style maps. After the integration, it migrated to product packaging design, based on big data product packaging innovation design methods, and developed a product innovation design auxiliary prototype system based on actual needs to improve the company’s R&D and innovation capabilities, shorten product development cycles, and reduce R&D costs. Improve product success rate and user satisfaction.