Storefronts play a crucial role in shaping consumer perceptions and driving foot traffic for small businesses, yet many owners struggle to create visually appealing designs due to limited resources and expertise. This study introduces an innovative methodology that integrates neuromarketing techniques with AI-driven style transfer to enhance storefront design evaluation and optimization. By utilizing tools such as InstantStyle for realistic style translation and Neurons AI for generating attention heatmaps, we analyze the visual attention distribution and aesthetic quality of various storefront designs. The research evaluates the effectiveness of neuromarketing-based attention functions in mitigating biases and producing more balanced and diverse visual appeal rankings compared to traditional prior-based approaches. Additionally, it provides actionable design recommendations to help small business owners optimize their storefronts effectively. The findings demonstrate that combining AI-driven aesthetic evaluation with neuromarketing insights offers a scalable, data-driven approach to improving storefront designs, ultimately enhancing brand visibility and consumer engagement.