Enhancing Product Quality in Cross-Border E-Commerce with AI and Big Data
With the rapid development of cross-border e-commerce in China, more and more Chinese enterprises have joined the CBEC business. Therefore, the product quality is crucial for CBEC enterprises to reduce return rate and economic losses. By using AI technology and quality management tools in each link of supply chain, efficiency can be increased and defects can be reduced. Use BDA to analyze trends in international customers demand and satisfaction, it can help to detect and identify problems in advance. Then, CBEC enterprise can solve these deficiencies and feed them back to suppliers. This can form a cycle closed loop to improve the product quality.
Nowadays, people’s shopping behavior is not only limited to local physical stores, but also relies on online shopping, especially cross-border e-commerce shopping. With the opening up of global trade and cultural exchanges, people also like to live abroad. They often cannot buy anything unique to their ethnic group in local stores. Therefore, they prefer to purchase these things from cross-border e-commerce platforms. In addition, they can also buy many cheap and high-quality products on cross-border e-commerce platforms. As we all know, famous cross-border e-commerce platforms include Amazon, eBay, TikTok, Temu, Shein, AliExpress, Wish, Lazada, Shopee, Alibaba, etc.
With the fierce competition among cross-border e-commerce platforms, people pay more attention to product quality and services. Therefore, CBEC companies are more focused on satisfying customer needs. In order to win customer loyalty and trust, these companies will serve as important bridges between the supply chain and customers. CBEC companies use big data analysis technology to collect international customers’ reflections on product quality. They then feed these quality issues back to the supply chain. The supply chain continues to improve these products by leveraging AI technology and quality management tools. The entire process is shown in Figure 1 below.
Figure 1: The core processes (Qiu, 2024)
Regarding how to improve product quality, this article mainly answers the following three questions around five elements (AI, QMT, CBEC, BDA and customers’ need).
How can AI technology and quality management tools optimize supply chain management and better improve product quality?
Supply chain management involves supplier production management, procurement inventory management, logistics warehouse transportation management, risk awareness management, etc. AI technology can be used in these managements to improve production efficiency and management efficiency.
Manufacturers can use AI technology to build smart factories and establish simulated diagnostic production processes. Manufacturers combined with quality management tools, such as 6sigma tools, can ensure uniform product quality and zero defects. Procurement departments can use AI technology ERP systems for efficient supplier management, information management and warehouse management. The Lean tool among quality management tools can also very well help the purchasing department improve work efficiency, with zero manual error rate and accurate stocking rate. The logistics and transportation department can use AI technology to fully automatically pack goods, accurately plan routes, ensure zero damage to goods and improve transportation efficiency. Sustainable management concepts in quality management tools can also optimize logistics packaging materials and reduce the burden on the environment during transportation. In addition, the entire supply chain can use AI technology and quality management tools to prevent and control risk awareness, identify risks early, and intervene early to reduce or mitigate risks.
Through the above methods, each link in the supply chain can use AI technology and quality management tools according to the company’s financial status, so as to better optimize the supply chain and improve product quality.
How to analyze customer satisfaction trends through big data analytics and identify problems in advance to improve product quality and service issues?
CBEC company downloads customer evaluation information in the backend of CBEC platform, or can send customer satisfaction survey forms to customer email. After company operators extract, clean and organize this information, they can conduct big data analytics. Use the random forest model used in my thesis to analyze satisfaction trends. In this way, customer dissatisfaction can be discovered early and improvements can be made in advance. For example, the company can make internal adjustments for internal application problems such as unclear platform web page descriptions, lack of videos, and lack of services. For quality issues reported by customers, the company can provide feedback to suppliers for improvement. In short, use BDA to discover problems in advance, intervene early, avoid errors, and improve customer satisfaction.
Will products developed using big data and AI software be more likely to have good sales and increase revenue for the company, under the context that CBEC platforms are in a stage of rapid development?
After my thesis analysis, the answer is yes. Because big data software will accurately help companies analyze key information on the CBEC platform, such as providing currently hot-selling products, keywords, best selling prices, product potential analysis, etc. Companies can develop new hot-selling products based on the precise information captured. The company then combines and innovates the selling points of these products, then most of the products will sell well and the company will be profitable.
Conclusion
In the context of the country’s encouragement of Silk Road e-commerce, CBEC companies need to continuously improve product quality and services. The process model formed through the five core elements mentioned above can provide CBEC with a reference for improving quality and reducing return rates. In this way, both the company and international customers can achieve a win-win situation. The company can increase sales and gain profits. International customers can get products that meet their expectations. Only in such a benign e-commerce environment can the company’s development be sustainable and profitable.
Reference
Lloyd, S. (2018). Insight e-commerce can make trade more inclusive, but greater coordination is needed. Moni. https://www.monigroup.com/article/e-commerce-can-make-trade-more-inclusive-greater-coordination-needed