CrossBorderEcommerce

The 90% Selection Framework: How This Amazon Refined-Selection Operator Achieves Consistent Success

When operators talk about Amazon product selection, they usually hedge. “It depends.” “You need feel.” “Every market is different.” Huang—the founder behind a refined-selection operation running across multiple Amazon marketplaces—has a different answer. “Success rate: 90% plus. Not 90% occasionally. Consistently.” I’ve spent the last two weeks reverse-engineering the methodology behind that claim. The source is a nearly five-minute video (281 seconds of ASR transcript) from a Douyin creator known in Chinese cross-border circles as “蟹老板” (Crab Boss). The content is dense—eight distinct dimensions, each with hard numbers attached. What follows is a structured breakdown of every dimension, the exact thresholds, and what they mean in practice for a refined-selection operation. ...

From 170 Employees to 50: How This Cross-Border E-commerce Founder Built a 300M RMB Business with RPA and AI

The warehouse looked nothing like what you’d expect from a 300 million RMB business. It was modest—a few rows of shelves, a handful of people clicking through browser tabs. But what those people were doing with their time told a different story. “Before RPA, we had 170 people doing maybe 100 million RMB in revenue,” Huang Xufeng told me over a video call from his office in Shenzhen. “Today we have 50 people and we’re doing 300 million.” ...