This article comprehensively analyzes Amazon data scraping methods and their crucial role in product selection, discussing the advantages of data-driven product selection, key data metrics, and the risks of lacking data support. The article examines the challenges and difficulties in obtaining Amazon data, including platform limitations, technical challenges, and compliance issues, and details the main data scraping methods: self-built scrapers, third-party tools, and professional API services. It highlights Pangolin Scrape API as an ideal data acquisition solution and, through practical guides and code examples, demonstrates how to utilize API data for product selection analysis. Finally, the article emphasizes the importance of compliant data usage and provides a future outlook for data-driven product selection. For sellers aiming to succeed on the Amazon platform, this article offers comprehensive guidance on data scraping and product selection analysis.