This article summarizes 20 common questions and solutions related to FBA labels, covering all aspects from product labeling to warehouse management. By detailing issues such as handling unlabeled items, account restrictions, choosing the right label types, and ensuring accurate labeling, it aims to enhance sellers' logistics efficiency and compliance, helping them to sell successfully on the Amazon platform.
The latest announcement indicates that starting from August 1, 2025, port fees will increase at the ports of Los Angeles and Long Beach, and customs inspections are expected to intensify. There is an urgent need to address entry restrictions at multiple warehouses and issues related to Amazon appointments, as difficulties in container retrieval in some areas are exacerbating.
Amazon Listing star ratings are influenced by four key factors: buyer account quality, review retention time, number of upvotes, and the content and format of the reviews. Sellers should prioritize buyer reviews, encourage high-quality Verified Purchase (VP) reviews, and optimize the review section's display through upvoting strategies. This ultimately improves listing conversion rates and sales.
Hai Xing Cheng in Suzhou is hiring a cross-border e-commerce Product Manager to focus on developing high-quality products for the European and American markets. This position requires skills in market research, product strategy, competitive analysis, product innovation, and project management. Candidates should possess a solid engineering background and experience in Amazon product development/operations.
Amazon's AI assistant, Rufus, deeply integrated with the search bar, is reshaping the cross-border e-commerce landscape. The era of keyword dominance is ending, giving way to intent-based search. Sellers need to shift towards scene descriptions, prioritize user reviews, and create high-quality visual content. By capitalizing on this AI-driven new traffic entry point, they can gain a competitive advantage and achieve rapid growth. This transformation requires adapting to how AI understands and responds to user intentions, rather than relying solely on traditional keyword optimization.
This article delves into a successful case study of a non-professional earning nearly $30,000 monthly on Spotify and YouTube using AI music. It details crucial steps like keyword selection, song title generation, music creation, cover design, and distribution. The article reveals the immense potential of AI music monetization and encourages readers to actively explore this emerging field. It showcases how accessible AI tools are empowering individuals to generate revenue through music, even without formal musical training, emphasizing the democratization of music creation and the opportunities for financial gain.
Vipshop has launched an intelligent delivery unmanned vehicle, breaking through traditional delivery methods. It features 20 express storage spaces, autonomous navigation, and obstacle avoidance, aimed at improving last-mile delivery efficiency. Meanwhile, Vipshop continues to innovate within the smart logistics industry chain, further optimizing logistics processes through smart AGV robots and efficient warehousing systems, ultimately providing consumers with a superior shopping experience.
According to a recent Gartner survey, only 23% of supply chain leaders have a formal AI strategy. Most businesses focus on short-term investments while neglecting long-term planning, which may hinder future development. To enhance competitiveness, companies should formulate a systematic strategy that balances short-term benefits with long-term goals.
Alibaba released its large language model "Tongyi Qianwen," marking its official entry into the competitive field of LLMs. The article reviews the historical roles of BAT (Baidu, Alibaba, Tencent) in China's internet development. It introduces Alibaba's progress in large model research and development, including its open-source initiatives. Finally, the abstract looks ahead to future development trends in the era of large language models.
This study evaluates the application of ERNIE Bot (Wenxin Yiyan) and Qwen (Tongyi Qianwen) in the field of education. Tests in subjects like high school English and junior high school mathematics reveal that both models possess strengths and weaknesses, indicating room for improvement. The assessment highlights the current capabilities and limitations of these large language models in supporting educational tasks and providing personalized learning experiences. Further research and development are needed to optimize their performance and ensure their effective integration into educational settings.
