Reported impact
Business outcome
Yuyi Technology helped the brand move from passive service response to proactive customer understanding. The program lifted service-management efficiency by 51.7%, improved first-line customer-service conversion by 30.8%, raised risk-insight efficiency by 80%, pushed store satisfaction to 95.5%, and increased online conversion by 32.7% by turning AI analysis into a repeatable user-feedback-to-action loop.
- Customer Experience
- Productivity Improvement
- Revenue Growth
- Risk Reduction
Solution
Yuyi Technology combined its NeoSight 5.0 platform with Alibaba Cloud's Qwen large model to build an end-to-end customer-service and voice- of-customer analysis stack for a maternal-and-infant commerce scenario. Real-time conversations are analyzed for user intent, automatically labeled, and routed into standard-answer guidance so frontline service teams can respond faster and more consistently. NeoTrainer AI then simulates high-frequency consultation scenarios to improve agent preparedness, while VOC analysis over comments and feedback extracts structured defect or demand tags such as color mismatch or material sensitivity and links them back to specific SKUs. LabelPaas extends the same data model into refund and return analysis so the brand can identify recurring causes such as fulfillment delay or description mismatch. The result is a closed loop in which AI parses user signals, business teams act on them, and service, product, and supply-chain processes are updated continuously.
Data flow
Customer-service dialogs, reviews, and feedback are sent through NeoSight and Qwen for intent recognition, tagging, and VOC analysis. Structured results then flow to service guidance, product and R&D teams, and refund-root-cause workflows in LabelPaas, where recurring issues can be linked to specific SKUs and turned into product, service, or supply-chain improvements.
