Shein employs machine learning and AI to optimize its on-demand fashion model. Here’s how they do it:

1. Activity Analysis: Shein uses machine learning and AI to monitor and analyze user activity on their website. This allows them to predict demand accurately. For example, the system can determine the anticipated demand for specific items, such as tie-dye tops, in the next 24 hours 00:29:01 - 00:29:16.

2. Production Planning: The technology quickly decides which factories should produce the required items and in what quantities. This ensures that production is aligned with the predicted demand 00:29:19 - 00:29:24.

3. Supply Chain Coordination: Once the production plan is set, the system communicates with the transportation infrastructure to ensure timely delivery of the products. This integrated approach helps avoid the need for physical stores or warehouses 00:29:25 - 00:29:29.

4. Cost Efficiency: By leveraging this technology, Shein can deliver apparel at significantly lower costs (40-60% less) compared to competitors like Zara or H&M. This is particularly appealing to young consumers who are budget-conscious but still want to express their individuality 00:29:37 - 00:29:52.

5. Minimized Waste: Shein's approach results in minimal returns and waste. Because the demand is perfectly calibrated, they avoid overproduction and the associated waste that plagues traditional fashion models 00:30:13 - 00:30:28.

By using these advanced technologies, Shein has positioned itself to become a major player in the apparel industry, surpassing even Amazon and Walmart in the near future 00:29:52 - 00:29:57.